Quantum circuit and intention generation signal processing device

Abstract

[Problem] To provide a quantum circuit that performs arithmetic operations for changing propositions by making the flow of positive calculations reversible. [Solution] A quantum circuit used in a quantum computer, the quantum circuit being characterized in that an inverse-function space is generated with a function obtained from an intersection of an arbitrary string and a rev function as an axis, and the inverse-function space is used for calculation.

Description

Quantum circuits and intention-emergent signal processing devices

[0001] The present invention relates to a quantum circuit and an intention-emergent signal processing device using the same, and more particularly to a quantum circuit that performs operations in a space with functions as axes, and an intention-emergent signal processing device using the same.

[0002] The inventor previously created a unique quantum gate and reproduced an artificial neuron, which he presented at the SC held in the United States from 2020 to 2022. During this time, an unpredictable surprise occurred, generating new neurons spontaneously and reversibly inputting feedback functions as inputs. This phenomenon was mathematically extremely difficult to interpret, and previously uncontrollable. The inventor then utilized the extended Riemann model, the Möbius strip cut model, and the orthogonal model to make it possible to control it. He believed that this surprise was due to the irreversible computational vectors in gate control based on logic, even in digital computers and quantum computers. He created a new computer circuit using a geometric approach and a new mathematical model to appropriately explain the phenomenon. The inventor also invented devices based on these theories (e.g., Patent Documents 1 and 2).

[0003] <Introduction> The inventor made this possible using the "cut operation" and "dynamic operation" operations from his doctoral thesis published in 2006, the "multiplication operation" and "reverse operation" operations from papers written between 2019 and 2021, and the calculation methods and operators found in the White Hole existence on the inverse universe in 2023. This series of arithmetic was reproduced using artificial neurons that used quantum gates in the extended Riemann model using Bloch sphere quantum gates and anti-Riemann spheres, and at that time, a surprise occurred in which an unspecified "new neuron" was spontaneously generated and a function signal was reversibly fed back to the input side.

[0004] We came up with a mathematical model that can interpret this as follows. In mathematics and logic, a proposition is an unshakable starting condition, and the flow from there toward a solution to find a solution is called a calculation formula; this flow is considered a positive vector. A negative vector would then be the direction from the solution toward the proposition. Does this really hold up as arithmetic? At the very least, it is easy to see that there are an infinite number of combinations of propositions, making things uncertain. There is a problem with artificial intelligence built on logic and existing mathematics being able to pattern match. This is because it is not possible to doubt propositions and change them at will.

[0005] Patent No. 6977009 Patent No. 6851871

[0006] The present invention has been developed in response to the above-mentioned problems, and aims to provide a quantum circuit that performs arithmetic that changes propositions by making the flow of positive calculations reversible.

[0007] The inventor realized that arithmetic, which makes the flow of positive calculations reversible and modifies propositions, could explain a series of surprises.

[0008] The present invention resides in a quantum circuit used in a quantum computer, which is characterized in that a space having an axis defined by a function obtained from the intersection of an arbitrary chord and a rev function is generated, and the space is used for calculations.

[0009] The present invention resides in the quantum circuit described above, in which the string is an inv function of the quarks that make up the proton.

[0010] The present invention resides in the above-described quantum circuit in which a space is formed by a plurality of axes.

[0011] The present invention resides in the above-described quantum circuit, which operates polarity reversal, quantum overlap, or energy-mass conversion by overlapping spaces.

[0012] The present invention resides in an intention-emergent signal processing device that uses the quantum circuit described above, which performs an operation of overlapping spaces and causes the operation to emerge as intention.

[0013] The present invention may also be implemented by appropriately combining the above configurations.

[0014] Quantum circuits generate a space whose axis is a function obtained from the intersection of an arbitrary string and the rev function, and by using the space for calculations, it becomes possible to perform calculations in a space whose axis is a function.

[0015] Quantum circuits can easily generate multiple functions to use as axes because the string is an inv function of the quarks that make up the proton.

[0016] Quantum circuits have multiple axes that make up the space, making it possible to perform operations on multiple elements at once.

[0017] Quantum circuits operate by superimposing spaces to perform polarity reversals, quantum overlaps, or energy-mass conversions, making it possible to calculate phenomena that cannot be explained by arithmetic operations.

[0018] The intention-emergent signal processing device is an intention-emergent signal processing device that uses the quantum circuit described above, and performs calculations to overlap spaces.By making this calculation an emergence of intention, it becomes possible to artificially reproduce biological reactions.

[0019] [Correction based on Rule 91 23.04.2025] Figure 1 is an explanatory diagram showing the operations used in the present invention. Figure 2 is an explanatory diagram showing the relationship between the "cut" operation and the "move" and "connect" operations. Figure 3 is an explanatory diagram showing the relationship between the "cut" operation and the "move" and "connect" operations. Figure 4 is an explanatory diagram showing the relationship between the "cut" operation and the "move" and "connect" operations. Figure 5 is an explanatory diagram showing the relationship between the "cut" operation and the "move" and "connect" operations. Figure 6 is an explanatory diagram showing the "move" operation. Figure 7 is an explanatory diagram showing the "move" operation. Figure 8 is an explanatory diagram showing the "move" operation. Figure 9 is an explanatory diagram showing the "connect" operation. Figure 10 is an explanatory diagram showing the "connect" operation. Figure 11 is an explanatory diagram showing the "connect" operation. Figure 12 is an explanatory diagram showing the relationship between the "connect" operation and the "multiply" operation. Figure 13 is an explanatory diagram showing the relationship between the "connect" operation and the "multiply" operation. FIG. 14 is an explanatory diagram showing the relationship between the "connection" operation and the "multiplication" operation. FIG. 15 is an explanatory diagram showing the relationship between the "connection" operation and the "multiplication" operation. FIG. 16 is an explanatory diagram showing the relationship between the "connection" operation and the "multiplication" operation. FIG. 17 is an explanatory diagram showing the relationship between the "moving" operation and the "mixing" operation. FIG. 18 is an explanatory diagram showing the relationship between the "moving" operation and the "mixing" operation. FIG. 19 is an explanatory diagram showing the relationship between the "moving" operation and the "mixing" operation. FIG. 20 is an explanatory diagram showing the relationship between the "mixing" operation and the "multiplication" operation. FIG. 21 is an explanatory diagram showing an example of the "mixing" operation. FIG. 22 is an explanatory diagram showing the "multiplication" and "moving" operations. FIG. 23 is an explanatory diagram showing the "multiplication" and "moving" operations. FIG. 24 is an explanatory diagram showing the "multiplication", "moving" and "reverse" operations. FIG. 25 is an explanatory diagram showing the "multiplication", "moving" and "reverse" operations. FIG. 26 is an explanatory diagram showing "multiple calculation", "dynamic calculation", and "reverse calculation" operations. FIG. 27 is an explanatory diagram showing "multiple calculation", "dynamic calculation", and "reverse calculation" operations. FIG. 28 is an explanatory diagram showing an example of the "reverse calculation" operation. FIG. 29 is an explanatory diagram showing an example of the "reverse calculation" operation. FIG. 30 is an explanatory diagram showing an example of the "reverse calculation" operation. FIG. 31 is an explanatory diagram showing an example of the "reverse calculation" operation. FIG. 32 is an explanatory diagram showing an example of the "forging" operation. FIG. 33 is an explanatory diagram showing an example of the "forging" operation. FIG. 34 is an explanatory diagram showing an example of the "forging" operation. FIG. 35 is an explanatory diagram showing an example of the "forging" operation.FIG. 36 is an explanatory diagram showing an example of the "forging" operation. FIG. 37 is an explanatory diagram showing an example of the "forging" operation. FIG. 38 is an explanatory diagram showing an example of the "weaving" operation. FIG. 39 is an explanatory diagram showing an example of the "weaving" operation. FIG. 40 is an explanatory diagram showing an example of the "weaving" operation. FIG. 41 is an explanatory diagram showing an example of the "weaving" operation. FIG. 42 is an explanatory diagram showing an example of the "weaving" operation. FIG. 43 is an explanatory diagram showing a specific example of the "weaving" operation. FIG. 44 is an explanatory diagram showing a specific example of the "weaving" operation. FIG. 45 is an explanatory diagram showing a cut operation. FIG. 46 is an explanatory diagram showing the relationship between cut operation, moving operation, multiple operation, reverse operation, and weaving operation, and the algorithms resulting from these. FIG. 47 is an explanatory diagram showing the relationship between cut operation, moving operation, multiple operation, reverse operation, and weaving operation, and the algorithms resulting from these. FIG. 48 is an explanatory diagram showing the relationship between cut operation, moving operation, multiple operation, reverse operation, and weaving operation, and the algorithms resulting from these. Figure 49 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 50 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 51 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 52 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 53 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 54 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. Figure 55 is an explanatory diagram showing the relationship between cut calculations, moving calculations, multiple calculations, reverse calculations, and weaving calculations and the algorithms resulting from them. FIG. 56 is an explanatory diagram showing the relationship between cut calculation, moving calculation, multiple calculation, reverse calculation, and weaving calculation, and the algorithms resulting from these. FIG. 57 is an explanatory diagram showing the relationship between cut calculation, moving calculation, multiple calculation, reverse calculation, and weaving calculation, and the algorithms resulting from these. FIG. 58 is an explanatory diagram showing the relationship between cut calculation, moving calculation, multiple calculation, reverse calculation, and weaving calculation, and the algorithms resulting from these. FIG. 59 is an explanatory diagram showing cut calculation. FIG. 60 is an explanatory diagram showing cut calculation. FIG. 61 is an explanatory diagram showing cut calculation. FIG. 62 is an explanatory diagram showing cut calculation. FIG. 63 is an explanatory diagram showing moving calculation. FIG. 64 is an explanatory diagram showing multiple calculation and reverse calculation.FIG. 65 is an explanatory diagram showing the interpretation of a quantum state. FIG. 66 is an explanatory diagram showing a quantum state equivalent to superposition. FIG. 67 is an explanatory diagram showing the use of quantum superposition and superposition. FIG. 68 is an explanatory diagram showing a cut model of a Möbius strip. FIG. 69 is an explanatory diagram showing a multiplication axis. FIG. 70 is an explanatory diagram showing an imaginary number. FIG. 71 is an explanatory diagram showing a negative imaginary number. FIG. 72 is an explanatory diagram showing processing using the imaginary model. FIG. 73 is an explanatory diagram showing processing using the imaginary model. FIG. 74 is an explanatory diagram showing processing using the imaginary model. FIG. 75 is an explanatory diagram showing processing using the imaginary model. FIG. 76 is an explanatory diagram showing processing using the imaginary model. FIG. 77 is an explanatory diagram showing processing using the imaginary model. FIG. 78 is an explanatory diagram showing processing using the imaginary model. FIG. 79 is an explanatory diagram showing processing using the imaginary model. FIG. 80 is an explanatory diagram showing processing using the imaginary model. Fig. 81 is an explanatory diagram showing processing using the imaginary model. Fig. 82 is an explanatory diagram showing processing using the imaginary model. Fig. 83 is an explanatory diagram showing processing using the imaginary model. Fig. 84 is an explanatory diagram showing processing using the imaginary model. Fig. 85 is an explanatory diagram showing processing using the imaginary model. Fig. 86 is an explanatory diagram showing processing using the imaginary model. Fig. 87 is an explanatory diagram showing processing using the imaginary model. Fig. 88 is an explanatory diagram showing processing using the imaginary model. Fig. 89 is an explanatory diagram showing processing using the imaginary model. Fig. 90 is an explanatory diagram showing processing using the imaginary model. Fig. 91 is an explanatory diagram showing processing using the imaginary model. Fig. 92 is an explanatory diagram showing processing using the imaginary model. Fig. 93 is an explanatory diagram showing processing using the imaginary model. Fig. 94 is an explanatory diagram showing processing using the imaginary model. Fig. 95 is an explanatory diagram showing processing using the imaginary model. Fig. 96 is an explanatory diagram showing processing using an imaginary model. Fig. 97 is an explanatory diagram showing processing using an imaginary model. Fig. 98 is an explanatory diagram showing processing using an imaginary model. Fig. 99 is an explanatory diagram showing processing using an imaginary model. Fig. 100 is an explanatory diagram showing processing using an imaginary model.FIG. 101 is an explanatory diagram showing processing using an imaginary model. FIG. 102 is an explanatory diagram showing processing using an imaginary model. FIG. 103 is an explanatory diagram showing processing using an imaginary model. FIG. 104 is an explanatory diagram showing processing using an imaginary model. FIG. 105 is an explanatory diagram showing processing using an imaginary model. FIG. 106 is an explanatory diagram showing processing using an imaginary model. FIG. 107 is an explanatory diagram showing processing using an imaginary model. FIG. 108 is an explanatory diagram showing processing using an imaginary model. FIG. 109 is an explanatory diagram showing processing using an imaginary model. FIG. 110 is an explanatory diagram showing an inverse field transformation. FIG. 111 is an explanatory diagram showing the relationship between functions. FIG. 112 is an explanatory diagram showing the generation of a function. FIG. 113 is an explanatory diagram showing the generation of a function. FIG. 114 is an explanatory diagram showing the generation of a function. FIG. 115 is an explanatory diagram showing the generation of a function. FIG. 116 is an explanatory diagram showing the generation of a function. FIG. 117 is an explanatory diagram showing the generation of a function. FIG. 118 is an explanatory diagram showing the generation of a function. FIG. 119 is an explanatory diagram showing the generation of a function. FIG. 120 is an explanatory diagram showing the generation of a function. FIG. 121 is an explanatory diagram showing the generation of a function. FIG. 122 is an explanatory diagram showing the generation of a function. FIG. 123 is an explanatory diagram showing the generation of a function. FIG. 124 is an explanatory diagram showing the generation of a function. FIG. 125 is an explanatory diagram showing the generation of a function. FIG. 126 is an explanatory diagram showing the generation of a function. FIG. 127 is an explanatory diagram showing the generation of a function. FIG. 128 is an explanatory diagram showing an inverse function space. FIG. 129 is an explanatory diagram showing the generation of a function. FIG. 130 is an explanatory diagram showing the generation of a function. FIG. 131 is an explanatory diagram showing the generation of a function. FIG. 132 is an explanatory diagram showing the generation of a function. FIG. 133 is an explanatory diagram showing the emergence of function dimension from the proton back-calculation internal orthogonal separation quantity measurement method C. FIG. 134 is an explanatory diagram showing the overlap of inverse function spaces. Fig. 135 is an explanatory diagram showing an anti-boundary transformation. Fig. 136 is an explanatory diagram showing an anti-boundary derivative. Fig. 137 is an explanatory diagram showing an anti-boundary derivative. Fig. 138 is an explanatory diagram showing an anti-boundary derivative. Fig. 139 is an explanatory diagram showing an anti-boundary derivative. Fig. 140 is an explanatory diagram showing an anti-boundary derivative. Fig. 141 is an explanatory diagram showing an anti-boundary derivative. Fig. 142 is an explanatory diagram showing an anti-boundary derivative. Fig. 143 is an explanatory diagram showing an anti-boundary derivative.FIG. 144 is an explanatory diagram showing anti-boundary derivatives. FIG. 145 is an explanatory diagram showing an artificial nerve. FIG. 146 is an explanatory diagram showing an artificial nerve. FIG. 147 is an explanatory diagram showing an artificial nerve. FIG. 148 is an explanatory diagram showing an artificial nerve. FIG. 149 is an explanatory diagram showing an artificial nerve. FIG. 150 is an explanatory diagram showing an artificial nerve. FIG. 151 is an explanatory diagram showing an artificial nerve. FIG. 152 is an explanatory diagram showing an artificial nerve. FIG. 153 is an explanatory diagram showing an artificial nerve. FIG. 154 is an explanatory diagram showing an artificial nerve. FIG. 155 is an explanatory diagram showing an artificial nerve. FIG. 156 is an explanatory diagram explaining a mathematical formula. FIG. 157 is an explanatory diagram showing an artificial nerve. FIG. 158 is an explanatory diagram showing an artificial nerve. FIG. 159 is an explanatory diagram showing an artificial nerve. FIG. 160 is an explanatory diagram showing cutting and division. FIG. 161 is an explanatory diagram showing cutting and division. FIG. 162 is an explanatory diagram showing cutting and division. FIG. 163 is an explanatory diagram showing cutting and division. FIG. 164 is an explanatory diagram showing cutting and division. FIG. 165 is an explanatory diagram showing a reversible process. FIG. 166 is an explanatory diagram showing division. FIG. 167 is an explanatory diagram showing the concept of quantum orthogonal overlap interpretation. FIG. 168 is an explanatory diagram showing orthogonal transformation. FIG. 169 is an explanatory diagram showing overlap perspectives and continuous quantity axes. FIG. 170 is an explanatory diagram of a consciousness signal processing algorithm. FIG. 171 is a flowchart showing conversion to "overlap perspectives and continuous quantity axes". FIG. 172 is an explanatory diagram showing input. FIG. 173 is an explanatory diagram showing geometric transformations used in control. FIG. 174 is an explanatory diagram showing geometric transformations used in control. FIG. 175 is an explanatory diagram showing geometric transformations used in control. FIG. 176 is an explanatory diagram showing geometric transformations used in control. FIG. 177 is an explanatory diagram showing geometric transformations used in control. FIG. 178 is an explanatory diagram showing geometric transformations used in control. Fig. 179 is an explanatory diagram showing the geometric transformation used in the control. Fig. 180 is an explanatory diagram showing the geometric transformation used in the control. Fig. 181 is an explanatory diagram showing the geometric transformation used in the control. Fig. 182 is an explanatory diagram showing the geometric transformation used in the control. Fig. 183 is an explanatory diagram showing the geometric transformation used in the control.FIG. 184 is an explanatory diagram showing a geometric transformation used in control. FIG. 185 is an explanatory diagram showing a geometric transformation used in control. FIG. 186 is an explanatory diagram showing a geometric transformation used in control. FIG. 187 is an explanatory diagram showing a geometric transformation used in control. FIG. 188 is an explanatory diagram showing a quantum in a function basis. FIG. 189 is an explanatory diagram showing a biological design diagram in a function basis. FIG. 190 is an explanatory diagram showing division. FIG. 191 is an explanatory diagram showing division. FIG. 192 is an explanatory diagram showing division. FIG. 193 is an explanatory diagram showing division. FIG. 194 is an explanatory diagram showing division. FIG. 195 is an explanatory diagram showing division. FIG. 196 is an explanatory diagram showing division. FIG. 197 is an explanatory diagram showing division. FIG. 198 is an explanatory diagram showing division. FIG. 199 is an explanatory diagram showing division. FIG. 200 is an explanatory diagram showing division. FIG. 201 is an explanatory diagram showing division. FIG. 202 is an explanatory diagram showing division. FIG. 203 is an explanatory diagram showing division. FIG. 204 is an explanatory diagram showing division. FIG. 205 is an explanatory diagram showing forging. FIG. 206 is an explanatory diagram showing forging. FIG. 207 is an explanatory diagram showing forging. FIG. 208 is an explanatory diagram showing forging. FIG. 209 is an explanatory diagram showing forging. FIG. 210 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 211 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 212 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 213 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 214 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 215 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 216 is an explanatory diagram showing the relationship between function axes and a viewpoint. FIG. 217 is an explanatory diagram showing the relationship between a vector function and a Möbius strip. Fig. 218 is an explanatory diagram showing the basis coordinates of positive and negative imaginary numbers. Fig. 219 is an explanatory diagram showing the basis coordinates of the empty set and the anti-empty set. Fig. 220 is an explanatory diagram showing a Möbius cut. Fig. 221 is an explanatory diagram showing a Möbius cut. Fig. 222 is an explanatory diagram showing the function axes of a Möbius strip. Fig. 223 is an explanatory diagram showing the function axes of a Möbius strip. Fig. 224 is an explanatory diagram showing the function axes of a Möbius strip. Fig. 225 is an explanatory diagram showing the function axes of a Möbius strip. Fig. 226 is an explanatory diagram showing the function axes of a Möbius strip.Figure 227 is an explanatory diagram showing the function axes of a Möbius strip. Figure 228 is an explanatory diagram of quantum gravity theory and the extended Riemann model. Figure 229 is an explanatory diagram of calculations in an Einstein field. Figure 230 is an explanatory diagram of calculations in an Einstein field. Figure 231 is an explanatory diagram of calculations in an Einstein field. Figure 232 is an explanatory diagram of calculations in an Einstein field. Figure 233 is an explanatory diagram of calculations in an Einstein field. Figure 234 is an explanatory diagram of calculations in an Einstein field. Figure 235 is an explanatory diagram of calculations in a geometric imaginary field. Figure 236 is an explanatory diagram of calculations in a geometric imaginary field. Figure 237 is an explanatory diagram of calculations in a geometric imaginary field. Figure 238 is an explanatory diagram of calculations in a geometric imaginary field. Figure 239 is an explanatory diagram of calculations in a geometric imaginary field. Figure 240 is an explanatory diagram of calculations in a geometric imaginary field. Figure 241 is an explanatory diagram of calculations in a geometric imaginary field. FIG. 242 is an explanatory diagram of the speed of light. FIG. 243 is a diagram illustrating the number (32). FIG. 244 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 245 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 246 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 247 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 248 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 249 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 250 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 251 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 252 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 253 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 254 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 255 is an explanatory diagram showing the boundary between convergence and divergence. FIG. 256 is an explanatory diagram showing the boundary between convergence and divergence. Fig. 257 is an explanatory diagram showing the boundary between convergence and divergence. Fig. 258 is an explanatory diagram showing a field energy gate. Fig. 259 is an explanatory diagram showing a field energy gate. Fig. 260 is an explanatory diagram showing a field energy gate. Fig. 261 is an explanatory diagram showing a field energy gate. Fig. 262 is an explanatory diagram showing a field energy gate. Fig. 263 is an explanatory diagram showing a field energy gate. Fig. 264 is an explanatory diagram showing a field energy gate.Fig. 265 is an explanatory diagram showing a field energy gate. Fig. 266 is an explanatory diagram showing a field energy gate. Fig. 267 is an explanatory diagram showing the division of the speed of light. Fig. 268 is an explanatory diagram showing the division of the speed of light. Fig. 269 is an explanatory diagram showing the division of the speed of light. Fig. 270 is an explanatory diagram showing the division of the speed of light. Fig. 271 is an explanatory diagram showing the division of the speed of light. Fig. 272 ​​is an explanatory diagram showing the division of the speed of light. Fig. 273 is an explanatory diagram showing the division of the speed of light. Fig. 274 is an explanatory diagram showing the division of the speed of light. Fig. 275 is an explanatory diagram showing the division of the speed of light.

[0020] Preferred embodiments of the present invention will be described in detail below, with reference to the drawings as necessary. In the drawings, identical elements are designated by the same reference numerals, and duplicate explanations will be omitted. Furthermore, unless otherwise specified, positional relationships such as up, down, left, and right are based on the positional relationships shown in the drawings. Furthermore, the dimensional ratios of the drawings are not limited to those shown.

[0021] <Novelty> The novelty of this invention lies in the following points: 1. Detailed explanation of the new computer circuit 2. A new function generation method using orthogonal functions with the new computer circuit 3. A method of controlling electrons, protons, field energy, etc. with a quantum circuit in an orthogonal model of the real and imaginary planes using a new mechanism of imaginary numbers and negative imaginary numbers

[0022] First, we will explain the "cut" and "dynamic" operations. Next, we will give a geometric explanation of the "baseless phenomenon" that uses the gaps in a Möbius strip, which can explain the "multiplication" and "reverse" operations, and imaginary coordinates. We will explain the surprise through these series of calculations. After that, we will explain signal processing and applications.

[0023]

[0024] Figures 6 to 8 are explanatory diagrams showing the "moving operation." Figures 9 to 11 are explanatory diagrams showing the "connecting operation." In the connecting operation, the results of cut operations are connected, so in the example shown in Figures 9 to 11, a function calculation is involved to generate two periodic circles. Figures 12 to 16 are explanatory diagrams showing the relationship between the "connecting operation" and the "multiplication" operation. The set with these two periodic features f1 and f2 becomes the function axis and is brought into the overlapping operation. This converts the two periods into two straight lines. At this time, there may be another cut operation, but this is omitted from the diagram.

[0025] Figures 17 to 19 are explanatory diagrams showing the relationship between "mixing" operations and "mixing" operations. Next, suppose there are red and blue 3Ds on either side of a break in the moving operation. When this is brought into mixing, mix 2 becomes a gradation. Figure 20 is an explanatory diagram showing the relationship between "mixing" operations and "multiplication" operations. When this gradation is brought into multiplication, it becomes as shown in Figure 20. Figure 21 is an explanatory diagram showing an example of a "mixing" operation. Also, in the case of mix 1, it becomes as shown in Figure 21.

[0026] Figures 22 and 23 are explanatory diagrams showing the "multiplication" and "movement" operations. As shown in Figure 22, 3D red and blue are placed as another function in the multiplication. When the rev lever (reverse) moves to the left, as shown in Figure 23, the gradient moves simultaneously, exerting pressure on the blue. At this point, a forging operation occurs, but in this case, the pressure breaks through the limits of the thresholds (complex plane) on both sides of the gradient, transcending the complex plane concepts of right and left, appearing three-dimensional.

[0027] Figures 24 to 27 are explanatory diagrams showing "multiplication," "movement," and "reverse calculation" operations. The same thing happens in reverse, in the red part. When the red and blue bars that appear on both sides are brought into reverse calculation, the two-color functions initially defined in the dynamic calculation are output from both sides of the gradient function axis, which creates logic gates used in computer processors and logic such as "If A, then B (Then)."

[0028]

[0029] 29 to 31 are explanatory diagrams showing examples of "reverse calculation" operations. At the same time, it is recognized as inv and output as reverse calculation. Then, the gradation function that has the movement of rev is output as the constitutive rev of reverse calculation.

[0030] Figures 32 to 36 are explanatory diagrams showing examples of the "forging" operation. Here, if a circular circle of 1 is converted into a cylinder and then infinitely forged and stretched, the cross section becomes infinitesimal. Figure 37 is an explanatory diagram showing an example of the "forging" operation. If it is infinitely forged and shrunk, the cross section becomes infinitely large. This relationship between infinity and infinitesimal is called a quality transformation.

[0031] Figures 38 to 42 are explanatory diagrams showing examples of the "weaving" operation. Here, if we interpret the four arithmetic operations, which are functions that perform independent calculations, as warp threads, and the rev function created by multiplication as a weft thread, and extend it using forging, it can be woven together, and the intersection points of the warp and weft threads become equations that can be connected by mixing and multiplication. Figures 43 and 44 are explanatory diagrams showing specific examples of the "weaving" operation. In the case of weaving, for example, if the first "circulated 1" with periodicity is considered to be a clock, the various hour, minute, and second hands have inv functions with different periodicities.

[0032] Figure 45 is an explanatory diagram showing an example of a "cutting" operation. When a cyclical existence is "cut," a beginning and an end are created.

[0033]

[0034] In this description, two x-direction gradients overlap, one in the y direction, as shown in Figure 51. In this case, when the operator moves to the right, as shown in Figure 52, it outputs a function called f1, which later becomes inv1. Also, when the operator moves to the left, it outputs a function called f2, which later becomes inv2. In this way, we have shown the appearance of an operator that outputs at least two functions, and an operator that overlaps this dynamic operator with a bar is called a superposition (multiplication). Since the basic condition of an operator is to output a function, this operator that dynamically outputs a function is called a Mitsuyoshi operator.

[0035]

[0036] Figure 56 illustrates how "independent arithmetic"—the arithmetic that ignores the 0.5 in the shaded area during division—results in an existing universe model similar to existing Riemann sphere calculations. On the other hand, if we focus on the 0.5 in the shaded area and consider it, and call the arithmetic system "simultaneous arithmetic," then Figure 57 shows a universe model in that domain. In this universe model, the interior of the existing model and its inverse model can be calculated by reverse calculation, creating a set of simultaneous calculations using a series of Mitsuyoshi operators. This series of calculation processes explains the invented algorithm for the computer processor leading up to the weaving algorithm. This weaving algorithm creates equations between orthogonal functions through later orthogonal calculations, which existing computers cannot generate. However, this weaving processor makes it possible to derive equations. As shown in Figure 58, this is a process algorithm in which a computer uses will as a vector to make decisions in the form of equations.

[0037] <2. New Function Generation Method Using Orthogonal Functions with New Computer Circuits> <2.1 "Cut" Operation and "Dynamic Operation" Operation> Figures 59 to 62 are explanatory diagrams showing cut operations. Cut operations were introduced by the inventor in 2006 as an arithmetic that existed before the arithmetic of division. Here, basic arithmetic is explained. As shown in Figure 1, when considering a circle, the function to find a means to cut a circle so that it becomes 1 is written as 1 cut operation 1. This means cutting a part of the circle only once, and at this time, it can be interpreted that the circle becomes the same as a line with a beginning and an end, called 1.

[0038] Similarly, the method for cutting a circle into 2 parts is written as 1, division, 2, and so on, 3, 4, 5, etc. The function of describing only one of the divided pieces after dividing into equal parts can also be interpreted as ÷ (divide). The basis for describing one piece is generally explained using folding, but since 1 divided by 2 is divided equally into 0.5, for example, the other piece is not described. If ÷ (divide) were to be written as only one half of a fold, it would be impossible to explain when a remainder is produced by dividing by ÷ (divide). Furthermore, with division, unequal divisions that are not equal in nature can also be described by using the additive operator or & as an intermediary, such as 0.3 and 0.7 or 0.4 and 0.6.

[0039]

[0040]

[0041] <2. New Function Generation Methods Using Orthogonal Functions with New Computer Circuits> <2.1 "Dividing" and "Dynamic" Operations> Figure 64 is an explanatory diagram showing multiplication and reverse calculations. Figure 65 is an explanatory diagram showing the interpretation of quantum states. Consider a clock, as shown in Figure 63, where the hour, minute, and second hands coexist on a single disk and move independently. A dynamic calculation function exists to represent the independent movements of the three hands. Based on the standard that the hour hand rotates twice a day at 2 r / day, the minute hand rotates once per hour at 1 r / h, which is a sexagesimal function that divides 1 hour into 60 equal parts. The second hand rotates 60 times per hour at 60 r / h, which is a sexagesimal function that divides 1 hour into 3600 equal parts. In this case, it cannot be described as hour hand + minute hand + second hand, nor can it be described as hour hand x minute hand x second hand. Therefore, the overlapping state of the hour, minute, and second hands is called "overlap." By outputting the common qualities of the hour, minute, and second hands, we can calculate the regularities of the duodecimal, sexagesimal, and 360° circumference systems that have existed since Babylonian times. This is called recursive calculation. The unique functions 2r / day, 1r / h, and 60r / h of the hour, minute, and second hands, respectively, are called intrinsic substances (inv), and the shared qualities obtained by recursive calculation are called contribs (rev). Outputting the difference between these qualities is called "reverse calculation." As shown in Figure 64, when the series of arithmetic operations of the Mitsuyoshi operator are combined into a function, it is clear that tense is eliminated, and at the same time, it is possible to create a reversible calculation vector from this. This arithmetic, as shown in Figure 65, has been simplified to simplify quantum computation, which is particularly prone to high uncertainty, making it easier to calculate.

[0042] Figure 66 is an explanatory diagram in which a quantum state is equivalent to superposition. The quantum world is not irreversible, but exists in a superposition state, and in order to describe this, it was necessary to create a mathematical model of dynamic equilibrium. Therefore, using the animation model currently expressed at MIT, this dynamic equilibrium model was replaced with superposition, resulting in Figure 66.

[0043] Figure 67 is an explanatory diagram showing how to use quantum superposition and superposition. The important thing here is the calculation function that converts four quarks into functions and superposes them like the hands of a clock. Also, even if a new quark is discovered, it can be handled infinitely simply by adding a superposition bar. As shown in Figure 67, f1 is xg, f2 is xS, and f3 is xu v , f4 is xd v In this case, different gradients = different functions, and different functions = different curves. As shown in Figure 67, this can be made into a function as the individual quality of each quark, using inv. Then, the change in shutter speed becomes the shared quality.

[0044] <2.2 Möbius strip cut model using "reverse calculation" and "cut calculation" operations that enable imaginary number explanations> Figure 68 is an explanatory diagram showing a Möbius strip cut model. When we consider the flow of calculation in terms of time, and search for the structure that creates reversible calculation vectors using the WH irradiation mechanism formula (Equation (1)), we can see that the Möbius strip cut model, as shown in Figure 68, is appropriate. The reason for this lies in the essence of cut calculation, which involves cutting a circulating circle. This requires the unique concept of two sides of the same coin. A circulating circle has neither a "beginning" nor an "end." Furthermore, in the front-back circulation that is the greatest feature of a Möbius strip, if the front side is colored blue and the back side is colored red, a seam between the blue and red colors will appear.

[0045]

[0046] Therefore, when a cut, a characteristic of kiri-san, is inserted into the seam, a circular model that can be said to be the emergence of a beginning and an end is created as a geometric structure in a situation where they are two sides of the same coin. At this cut, red and blue face each other, reversed inside out. Furthermore, between the "beginning" and the "end" there is a gap where the base has been cut off, and if we were to try to put this into words, the only way to describe it would be as a "phenomenon without a base."

[0047] Figure 69 is an explanatory diagram showing the multiplication axis. When blue is at the front of the Möbius strips on both sides of this "baseless phenomenon," red is on the backside. This is created by the cutting operation that creates the "beginning" of the blue on the front side. This corresponds to the Möbius strip cutting operation 1. Looking at Figure 69, we can see that the "blue 0 (beginning)" is at the edge of the break at the "beginning" of the blue on the front side. And the "blue 1 (end)" exists on the backside of the strip on the opposite side. At the same time, we can see that the "red 0 (beginning)" is at the edge of the break at the "beginning" of the red on the front side. And the "red 1 (end)" exists on the backside of the strip on the opposite side. If we consider this a swap of color "qualities," then we can see that in both strips, the colors coexist in a state where the 0 (beginning) and 1 (end) of red and blue are swapped.

[0048] In this case, the bases of x and y, which are the bands of numbers, are cut between these gaps, so a new base "based on multiplication" different from the axis of numbers is assumed here. Figure 70 is an explanatory diagram showing imaginary numbers. Looking at the gap on both sides of the Möbius strip, it is possible to imagine that the red and blue, which were two sides of the same coin, exist at the very limit as negative (red) x positive (blue) or positive x negative. In this case, as shown in Figure 70, both multiplications are always negative, so an imaginary base can exist in this space.

[0049] Figure 71 is an explanatory diagram showing negative imaginary numbers. Simultaneously, if we eliminate the swaps within this space, the combinations converge to red 01 and blue 01, as shown in Figure 70. If we consider this combination to be a negative imaginary vector and a positive imaginary vector, as shown in Figure 71, it is naturally possible to explain that the plane of positive and negative imaginary numbers exists perpendicular to the plane of the band. Furthermore, since this imaginary plane is also a complex plane, it is easy to imagine the existence of a Möbius strip in another dimension, and it is clear that positive and negative combinations are freely possible. This makes sense if we consider that new bases are created in baseless phenomena. This not only makes it possible to neatly explain imaginary numbers using a basis obtained by dividing a Möbius strip, but also negative imaginary numbers, and it appears that a structure in which positive and negative numbers can be freely reversed is also possible. The WH mathematical formula predicts the existence of a Riemann sphere without a complex plane, in which the interiors of both positive and negative Riemann spheres are condensed into this baseless phenomenon space.

[0050] This leads us to realize that the origin of the imaginary of beginnings and endings can be found mechanically in the gaps of a Möbius strip, which is a space of "baseless phenomena" as a geometry. If we interpret this vector as the flow of time, then as explained in the explanation of negative imaginary numbers, we can freely combine calculation vectors and procedures in reverse, and a structure that mechanically creates reversible calculation vectors, as shown in Figure 71.

[0051] Figures 72 through 110 are explanatory diagrams showing processing using the imaginary model. Now, let's look at an example of how this new imaginary model can be applied to both space models and tactical mathematical processors. Even in the imaginary model used by Leonhard Euler (1707-1783) to explain geometry, a 1 / 2 twist of a Möbius strip synchronizes with the rotation of the axis of Euler's imaginary transformation. This is shown in Figure 72. When this Euler imaginary transformation model is treated using simultaneous arithmetic, the quaternion is compressed. As shown in Figure 73, if we first interpret the vertical axis in Euler's model as a 1 / 4 twist of a Möbius strip, then further twisting it by the same 1 / 4 rotation results in a 1 / 2 twist.

[0052] As a result, as shown in Figure 74, it can be seen that the imaginary axis overlaps with the number axis, and the quaternions are grouped together to form the imaginary part. The imaginary part on this number axis determines the relative real part, so real and imaginary parts are generated on the number axis, as shown in Figure 75. Furthermore, if this axis shown in Figure 76 is rotated by a quarter turn, an additional vertical axis is created, as shown in Figure 77, and this vertical axis generates a real part domain surface, as shown in Figure 78. At the same time, an imaginary part domain surface is also generated, as shown in Figure 79, and further below, a reverse domain (the plane perpendicular to the positive plane is considered reverse) is developed, as shown in Figure 80.

[0053] By performing "overlap calculations" and "inside-out calculations" in this antithesis domain, it becomes a strategic mathematical processor. First, imagine a team of two, and consider the aspects of each team's attacks as aggression and defense, as shown in Figure 81. If we then incorporate the second law of thermodynamics, we have entropy and inverse entropy, and by considering the inverse and inverse of the Riemann sphere, the invented processor can calculate inverse entropy and anti-entropy, as shown in Figure 82.

[0054] Using this to solve the classic problem of territorial control in war (border disputes), the invented processor first performs a cut operation, and if the cut is taken as the point of conflict, it moves using a dynamic operation, as shown in Figure 83. Naturally, the offense and defense are reversed, resulting in the situation shown in Figure 84. This is how war involves a switch in offense and defense, and in this case, a color charge reversal (color charge transformation) occurs, as shown in Figure 85. Therefore, if the calculation proceeds from the calculation area calculated by the processor up to this dynamic operation to the area below, it will have the effect of a simultaneous calculation from an overlapping operation to an inside-out operation, and a mixing operation like "mixing into two (mix2)" will be produced, and a gradation function will be output, as shown in Figure 86.

[0055] When this gradation is calculated dynamically, as shown in Figure 87, by simultaneously operating a 1 / 4 rotation on the axis and a further 1 / 4 and 1 / 2 rotation, the gradation phase is calculated to calculate the "function that does not create resentment" and the "equation that returns war to diplomacy." This results in a processor that can output strategic mathematics and strategic mathematics doctrine as shown in Figure 88. In Figure 89, the "function that does not create resentment" of military power mathematics becomes f on the right shoulder of the dynamic calculation, and strategic mathematics becomes a cumulative calculation. At the same time, by making this f a shared function and rev, the strategic mathematics doctrine becomes a cumulative calculation, as shown in Figure 90.

[0056] Now, let's return to the cut model of the Möbius strip. The limit of the speed of light and infinite mass can be used as the basis for the coordinate system as the limit region of the real field. This is E=mc 2 If we consider the Einstein field as follows, we need to calculate the speed of light and mass in the imaginary field, anti-imaginary field, and anti-real field. Also, in the cut model of a Möbius strip, the following specific processor calculation model is as shown in Figure 91.

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[0059]

[0060] An electron, whose phase inverts at 360° and becomes (-) when the quantum is swapped, returns to its original state at 720°. In the spinor wave function, a (-) appears on the wave function; swapping two wave functions, or the wave functions of two particles, inverts the phase, so swapping two electrons also adds a (-) to the wave function. Is this the i-characteristic between the imaginary field and fermions? In this case, 720° returns to its original state in two rotations. The processor of this invention is also effective in reproducing this mysterious quantum phenomenon on a computer.

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[0063] Figure 110 is an explanatory diagram showing antifield transformation. In this case, the WH calculation predicts that functions (f1, f2, f3, f4) will be transformed into masses (m1, m2, m3, m4) in the antifield, and this matrix-like transformation is called antifield transformation. A case where a reversible process is performed by superposition and reverse calculation using this quality transformation will be explained in paragraph <2.4> as a surprise that occurred in our artificial neural network.

[0064] Fig. 111 is an explanatory diagram showing the relationship between functions. Here, the signal processing for determining rev is constructed as shown in Fig. 111.

[0065] <2.3 Function generator from the mechanical structure of an arithmetic summation device and signal processing technology> The multiplication and inverse operations of arithmetic summation, which cannot be reproduced using arithmetic operations alone, are reproduced using the overlapping state of protons in a violin model. For example, the strings become the inv functions of each quark, and theoretically an infinite number of strings can be set up. Arranging these to create a rev function that acts as a bow and creating a violin structure is called overlapping, and this is the basic structure of overlapping. Continuous quantities become like a song, and become the rev shared function of all quarks. The amount of separation is found at the intersection of the shutter speed setting. A vector function is generated from this combination.

[0066] Figure 112 is an explanatory diagram showing the generation of a function. First, let's say the curve that appears on the vertical axis of shutter control is rev-f. This is done by connecting the intersections of f1, f2, f3, and f4 to create a curve, which is then orthogonalized and output to the left. At this time, an equation is generated at each intersection and output simultaneously.

[0067] Figures 113 to 116 are explanatory diagrams showing the generation of functions. If the next rev-f axis is slid to the left, another intersection point connection like that shown in Figure 113 will be generated. By repeating this process, three functions will be obtained, for example, as shown in Figure 114. Functions can be generated infinitely. Each of the three functions obtained will be called an inv-f(a, b, c) function (see Figure 115). This function will be output (see Figure 116).

[0068] Figures 117 to 120 are explanatory diagrams showing the generation of functions. Considering Inv-f(a), we can imagine a circle that encloses the tense as a function of the periodicity of the cut operation (see Figure 117). In this case, when the cut operation is commanded to inv-(a) cut operation 1 (see Figure 118), the arithmetic function of the cut operation will simply output the function curve inv-(a) (see Figures 119 and 120).

[0069] Figures 121 to 127 are explanatory diagrams showing the generation of functions. Here, we will perform new signal processing. This is a groundbreaking method equivalent to the emergence of the series transform in the Fourier transform, performed geometrically and algebraically. First, create a straw with the inv-(a) circle as its cross section (see Figure 121).

[0070] At this time, it is important that the periodicity of the cross section becomes a function. This can be said to be similar to the state of only the concept of the empty set (see Figure 122). On the other hand, consider the length of a straw (see Figures 123 and 124). In this case, the circle containing only the circulating function is taken as the one-dimensional length that serves as the basis for a new function axis called inv-f(α) (see Figure 125).

[0071] Performing this process three times, for example, generates a three-dimensional basis for the function axis inv-(α,β,γ), as shown in Figures 126 and 127. For example, if we consider this periodic circle inv-f(a) to be a clock, we can see that the various hour, minute, and second hands have functions with different periodicities, and have "vector functions" that form a spring-like structure within the function axis. By outputting the differences between these hands, we can generate three new inv function axes. The rule for this clock is called rev (common substance). The function axes of the three hands rotate over time within the function axis, and how they wind in a spiral structure determines how many revolutions the clock face makes; one revolution creates a division that corresponds to "1" on that hand's scale. Using this as a basis like a number axis makes it easier to understand the periodicity of the function axis and the cross section.

[0072] Figure 128 is an explanatory diagram showing an inverse function space. We imagine a space with the function axis generated by the above method. The existence that fills the space formed within the three-dimensional basis of the function axis inv-(α,β,γ) is called an inverse function. This is a completely new function, different from a generalized function. Figures 129-132 are explanatory diagrams showing the generation of functions. As shown in Figures 129-132, this time we perform the same process as before, but you will notice that by moving the rev-f function up and down, we can generate a completely new function in the same way. Performing this process three times generates a new function axis inv-f(δ,ε,ζ). Until now, humanity has lacked the mathematics for generating functions, so arithmetic using a series of rev functions is a groundbreaking way to generate signals. This is called recursion, and the arithmetic for finding rev and inv is reverse-arithmetic.

[0073] FIG. 133 is an explanatory diagram showing the generation of a function dimension from the proton back-calculation intrinsic orthogonal separation measurement method C (C represents the illustrated orthogonal calculation). By means of re-calculation and back-calculation, coordinates based on a function as the axis (basis), different from the number axis, can be created (see FIG. 133). When a weaving calculation is installed in the inverse function box in the figure and the equations of the function intersections are connected, functions that change according to each function axis are generated. That change is recognized as a moving character, and humans can visualize and understand the inverse function. If the discrete points of the weaving calculation become the peak vertices of the function, it will be in a state of mix2 or more of the mixed calculation. By orthogonalizing the change patterns generated from this gradation, the vector of the function is obtained. Then, a changing function is created by using the function of generating a function from the deviation from the orthogonal. The smaller this deviation is, the more it generates an extremely large field energy density. It is exactly the mechanism by which characters, words, and the meaning content are generated from the phenomenon without a basis. That is, it is the same as taking a part of a circle, which is a cycle, as a function and creating the consciousness of the beginning and the end. The existence of a basis surrounded by the function axis means a cycle system. Therefore, it can be said that consciousness is generated by cutting the cycle system and performing dynamic calculation. So, when using the peak of the function at the timing of starting the cutting calculation, it becomes DSP (Digital Signal Processing). Here, if mix1 of the mixed calculation is adopted, it can create consensus formation as negotiation, so it becomes a function of summarizing and proposing opinions. Also, when the frequency change from sound is made into a function and input to the function axis of this inverse function box, it can also be used for things such as signal processing of words and viewing the signal state of consciousness. When the functions of various quarks are input here, it becomes a quantum mechanics and also a visualization device. By inputting an arbitrary function to this function axis, it becomes possible to generate dynamic characters. FIG. 134 is an explanatory diagram showing the re-calculation of the inverse function space. The re-calculation of the coordinates using this function axis is as shown in FIG. 83. This state corresponds to a calculation in the anti-boundary (anti-Riemann sphere) model in the extended Riemann.

[0074] Figure 135 is an explanatory diagram showing an inverse transformation. The transformation using this model for signal processing is the inverse transformation shown in Figure 84. Functions f1, f2, f3, and f4 are transformed into m1, m2, m3, and m4, respectively. For example, if the functions are transformed into mass, f1 becomes m4, f2 becomes m3, f3 becomes m2, and f4 becomes m1, a cross calculation similar to a matrix cross calculation. This is called a quality transformation. This quality transformation causes polar inversions such as SN, plus / minus, and 01.

[0075] Figure 136 is an explanatory diagram showing antiboundary derivatives. If we compare this to the Mitsuyoshi formula and the extended Riemann equation, we get the antiboundary derivative af-D, or number (3). This is the normal derivative number (4) with the numerator and denominator reversed, and in signal processing, the smaller the deviation, the closer to infinity the energy produced. This is a prediction function found in the extended Riemann model, derived from the formula for white hole radiation due to the geometric structure of the reverse Riemann and the Riemann sphere, which does not have a complex plane and is a "basisless phenomenon." The mathematical application of this is the antiboundary derivative.

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[0078] Figures 137-143 are explanatory diagrams showing anti-field derivatives. If we call this baseless phenomenon a Mitsuyoshi sphere (see Figure 137), it is a state where functions are infinitely packed together. Because there is no definition, it cannot be labeled. It is called an anti-empty set, which means "it cannot be defined or explained by its contents alone (it does not have a complex plane)." It is predicted to exist within the Schwarzschild radius, which is believed to be the limit of a black hole. When an infinite number of inv functions are emitted from the Mitsuyoshi sphere toward the Schwarzschild radius (see Figure 138), the rev function, which is an orthogonal function from the sphere, is output in a wave-like form, as shown in Figure 139. This is because it is an undefined field (see Figure 140). If we cut a slit in the Möbius strip at the limit of the Schwarzschild radius (see Figure 141), a function axis basis coordinate consisting of inv and rev appears as the field's energy. For example, to reproduce this, in a device that irradiates a sphere with a laser and outputs a function, if this coordinate is defined as equivalent to matter (see Figure 142), then a reversal effect that projects the shadow of the sphere through a feedback effect occurs on the input side, projecting a wave from the function onto the quantum basis coordinate. This can be structured with the cuts in a Möbius strip cut model (see Figure 143).

[0079] Figure 144 is an explanatory diagram of anti-boundary derivatives. Measurement devices using this technology could be expected to convert antimatter into a function relative to matter, measuring quantum waves—the shadow of matter in the anti-boundary—as anti-waves. It could also be used as a mathematical formula calculator that changes propositions through a "feedback effect"—a method of solving and visualizing invisible entities and unimaginable problems—or as a means of generating new, unknown entities like field energy. The reason why anti-boundary derivatives "produce infinite energy, or mass, the more slight the deviation" is because quantum derivatives in the actual world "dissipate like clouds when differentiated and refined." This can be considered a state immediately before a baseless phenomenon that is "unthinkable" in the steady-state actual world. This dissipating, wave-like shadow is converted into anti-boundary derivative energy. Therefore, in the steady-state anti-boundary world, which is before anti-boundary derivatives (or, from our perspective, the appearance of the anti-boundary world after anti-boundary derivatives), the quantum world may dissipate like clouds when differentiated and refined. If this is the case, then what we call limit quantum waves is nothing more than the shadow of the anti-boundary world. From the perspective of this steady-state world, when an infinite light source is shone on a basisless phenomenon (what Kyoto University calls a Mitsuyoshi sphere), a shadow appears as a wave. Isn't it simply a case of particles being superimposed on this? As a specific experiment, when an infinite light source is shone on a basisless phenomenon, a shadow appears as a wave. Isn't it simply a case of particles being superimposed on this? When a light source is pointed at a Mitsuyoshi sphere, a shadow, the wave projected by the sphere, is projected in the opposite direction from the light source. Isn't this shadow created by the transformation of quality in the Mitsuyoshi sphere? What if we could discover a break in Klein's bottle when all sides of the Mitsuyoshi sphere are illuminated? What would happen in a laser experiment? This raises the question of whether an anti-wave would emerge from this break, and the inventor believes that there is a way to measure this with this invention.

[0080] <2.4 Analytical Signal Processing: Finding Invisible Waveforms> Inputting inv(f1-f4) not only outputs inv(a-d), but also produces continuous function changes from the combination of A and B. By inputting the vibration characteristics and amplitude fluctuations of inv(f1-f4), the shared generalized function rev can be found. Conversely, factorization can be performed by inputting the rev function, predicting a different function curve to find the original inv(f1-f4) from the combination of the internal properties of A and B, making it possible to use this as a new type of signal processing. Furthermore, signal processing can be envisioned that makes it possible to predict the distribution of waveforms of various element invs from the commonality between inv(a-g) and inv(f1-f4). This can also be used as a quantum computing model without using quantum circuits or probability. It has been shown that the generation and feedback of this new neuron can be explained using a series of arithmetic and the Riemann sphere.

[0081] Figures 145-151 are explanatory diagrams of an artificial neuron. First, let me explain the original artificial neuron. This artificial neuron is constructed using an extended Riemann model. Figure 145 shows the input to the neuron. The Riemann sphere does not diverge at infinity at the north pole, but converges to a single point. A wave function is generated along the way. However, as shown in Figure 146, it disappears upon reaching the north pole, and no wave function is generated. Up to this point, this is expected, since it is a normal Riemann surface. The problem is that the function that disappeared after the north pole selection generated a completely new, continuous function in a completely different space (see Figure 147). This was unexpected. After that, new neural pathways were automatically generated, extending the stimulation circuit (see Figures 148 and 149). At this point, a feedback function was returned to the input neural circuit (see Figures 150 and 151). Researchers at the University of Tokyo Faculty of Medicine and Tottori University Faculty of Medicine measured this, which is the same as a typical biological response in reinforcement learning, and even a sigmoid function. This raised the question of whether the a priori bio-neural model was replicated.

[0082] Figures 152 to 155 are explanatory diagrams showing artificial nerves. Figure 156 is an explanatory diagram explaining the mathematical formula. Now, we will explain the signal processing to control this phenomenon. First, as shown in Figure 152, let's make a proposition between A (nerve) and B (the new nerve generated). Then we will make this into the formula (5).

[0083]

[0084] When this "relationship is division," it becomes the number (6), and it is not a case of neural transmission or neural generation but a disconnection. The vertical ÷ symbol in Figure 152 is the symbol equivalent to division.

[0085] Then, neural transmission is not a function of A or B, but a function between A and B. This can be expressed as equation (7).

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[0088] First, let the number of overlaps be (8).

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[0090] Let the internal inv of A and the internal inv of B be functions f1 and f2 (see equation (9)), respectively.

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[0092] In this case, if the combination shown in FIG. 156 is performed on the multiplication axis, the result is the number (10).

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[0094] In this case, if we write the function f3 common to A and B as number (11), we can see that rev, the common property of A and B, becomes -1 when multiplied.

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[0096] In this case, if A's reverse calculation B is placed into the imaginary world, which is the space of "baseless phenomena," the number (12) is obtained through a free combination of functions, and the number 1, which represents creation, appears.

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[0101] <2.5 Discussion> This surprise phenomenon suggests the possibility of its occurrence through cutting. This can be explained by the principle that cutting a circulating circle creates a "beginning" and an "end." In other words, the artificial neuron surprised us by showing that the emergence of new neurons occurs through cutting the circulatory system. Because the extended Riemann model, which is the same formula for the emergence of the anti-universe predicted in another WH paper, is used in this work, a future challenge will be whether this prediction can be reproduced. The artificial neuron model's reproduction of the extended Riemann effect and the Möbius strip cut model is the same as the patented quantum gates created using the same method. There is a large difference in scale between quantum theory and living organisms. Therefore, we plan to begin by confirming the reproduction using a molecular model of actual living neurons. Furthermore, we will need a way to clarify where, when, and what circulatory system the artificial neuron cut. This is because it is still unclear whether this is due to the internal structure of the computer processor or the reversibility of mathematical instructions.

[0102] <2.6 Application Example> Figures 161 to 164 are explanatory diagrams showing division and reversal. This qualitative transformation allows a reversible process to be performed using multiplication and reversal in a diplomatic negotiation. The greatest feature of division is its bold transformation of mathematical equality. In mathematics, the answer (solution) is determined to be one, but division creates infinite combinations. This function can be used to generate infinite proposals toward the desired goal (solution) from infinite combinations. This property can be used for consensus building using the function axes mentioned above, and for diplomatic negotiations using this. First, as shown in Figure 161, let's create a diplomatic proposition between two countries, A and B. This will be expressed as equation (13).

[0103]

[0104] If this "relationship is division," it becomes the number (14), and it becomes war rather than diplomacy. The vertical ÷ symbol in Figure 161 is the symbol equivalent to division.

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[0106] Then, diplomacy is not a function of A or B, but a function between A and B. This can be expressed as an equation (15).

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[0109] Figure 165 is an explanatory diagram showing a reversible process. To avoid this conflict of division, multiplication is effective. The reason is that the PPT changes due to reversible calculation.

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[0113] In this case, if the function f3 common to A and B is written as number (18), this becomes rev as the common property of A and B.

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[0115] If AB is placed in the imaginary world, a space of "baseless phenomena," a free combination of functions generates f3. If this f3 is shared by both countries, and if it is calculated as the goal of negotiations, a solution can be found using the reverse calculation as a normal vector. However, there may be cases where f3 simply cannot be calculated. In such cases, if a surprise or accident occurs, f3 is generated, resulting in a functional rewrite of f1 and f2. Even if f3 has already been calculated, a rewrite of the PPT definition occurs as a result of a quality transformation, resulting in a polarity reversal of f1 and f2. When this surprise or accident occurs through a quality transformation in the imaginary world, a "baseless phenomenon," the WH paper suggests that it can be calculated as an influence from the anti-Riemannian world. This calculation is impossible to perform using logic, which can only analyze arthropods, and the pattern matching generated by differentiation (culture) and division (differentiation) using the principles of existing AI and quantum computers. However, experiments are being conducted to see if this is possible by using the anti-world transformation in the WH generation formula, along with division, dynamic, multiple, and reverse calculations. Cheating is not permitted in race car competitions. Furthermore, because life is at risk, both racers and engineers push themselves to their limits. Therefore, the chances of accidents and surprises are high. Therefore, all formula cars are equipped with the above calculation system, and experiments are being conducted under actual racing conditions. The artificial ego (AE) used in the experiments is equipped with a system that inputs digital information from the car, converts it into human hormones, and generates simulated emotions and drives for the car.

[0116] <2.7 Signal Processing of Will> Mathematics deals purely with "numbers." Philosophical mathematics attempts to make will mathematically treatable by properly separating and treating "consciousness," "action," "separable numbers," and "continuous quantities." A new arithmetic method used is geometric algebra using "addition of the four arithmetic operations."

[0117] <2.7.1 Calculation Method for Perspective and Intention> Figure 166 is an explanatory diagram illustrating division. In division, only a scaled-down portion is calculated. Therefore, as shown in Figure 166, the "quotient" is viewed in the four arithmetic operations of summation as a surface cut out into the complex plane. Therefore, the empty set in the extended Riemann model corresponds to this complex plane. This can be categorized as a function as a concept in consciousness. In the case of division, the perspective can only see this complex plane, so in this case, the circle becomes an infinitesimal differential. This is the case when dividing infinitely by 1 / 2 is considered an action. In this case, the action itself becomes an infinite number of times equivalent to an infinite ∫, resulting in the infinite red length shown in the diagram. This model is depicted as a straw with infinitesimal thickness and infinite length. Figure 167 is an explanatory diagram illustrating the concept of quantum orthogonal superposition interpretation. If the perspective of this straw model is set to the circle in front of the straw, it appears to disappear because of its infinitesimal thickness (see Figure 167). The inventor believes this demonstrates the concept of quantum orthogonal superposition interpretation. Figure 168 is an explanatory diagram showing an orthogonal transformation. The left side of Figure 168 shows the state where infinite length and infinitesimal thickness overlap. Separately, when infinity and infinitesimal become linear, a straw appears. Therefore, the orthogonal transformation of the straw is shown in Figure 168. Figure 169 is an explanatory diagram showing the overlapping perspective and continuous quantity axes. This orthogonal transformation allows the quantum state to be based on the orthogonal relationship between infinity and infinitesimal. This field is used as the overlapping perspective, creating a conscious space. Furthermore, the straw itself forms a differential axis from division, corresponding to the function axis of "Function dimension emergence from proton back-calculation internal orthogonal separation quantity measurement method C" (see Figure 169).

[0118] <2.8 Implementation Example> Figure 170 is an explanatory diagram showing the consciousness signal processing algorithm. Figure 171 is a flowchart showing the conversion to "overlapped perspective and continuous quantity axis." Input 1 is the user's or subject's actions, behavior, and judgment information. To convert this into the "overlapped perspective and continuous quantity axis" (function coordinates), an orthogonal transformation is performed based on the quantum orthogonal overlap interpretation concept. Through this transformation, the overlapped perspective creates consciousness space 3. This consists of the horizontal axis, where tense is generated by continuous quantity axis 4 and continuous quantities are functionalized, and the vertical axis, where the differential axis is conceptual axis 5, which is the empty set. This is consciousness space 3, generated using a method similar to "Function dimension emergence from proton's reverse-calculated internal orthogonal separation quantity measurement method C," based on the function axis. At this point, a means of measurement is obtained by outputting the intention from the basis coordinates, using the constitutive function as rev and the internal function as inv, and then back-calculating the input and output.

[0119] <2.8.1 Applications of Mathematics> In physics, as a deductive proposal, proving the assumed multiplication axis through physical experiments could conceivably create a means of creating field energy. Field energy is the permanent energy that forms a field; it exists to prevent that field from collapsing. For electrons, it is the field of their spin activity, the field that hydrogen maintains as hydrogen, and magnetic fields. For photons, it is the characteristic field of photons. When dealing with this in the present invention, it becomes rev. In the social sciences, computational methods have been established, but philosophical work is required to turn this into logical formulas and logic. If baseless phenomena are considered "something that cannot be visualized," their existence can only be discussed through philosophy. Furthermore, if "baseless phenomena" are defined through this work, this reversible arithmetic will provide society with new possibilities as philosophical mathematics. In this case, a new quantum logic model will be born, with existing propositions considered absolute and logic with the law of the excluded middle considered classical.

[0120] <2.8.2 Engineering Applications> Figure 172 is an explanatory diagram showing input. Quantums are entangled and cannot be controlled. This can be controlled using mixing and multiplication, which are the principles of gradation, and a function basis with an orthogonal transformation function. The input is a circle (see Figure 172). This can be easily input using a device that freely cuts and inputs functions. Figures 173 to 187 are explanatory diagrams showing geometric transformations used in control. Figures 173 to 176 show geometric transformations using mixing and multiplication, Figures 178 to 183 show geometric transformations using concatenation, and Figures 184 to 187 show dynamic equilibrium using concatenation. This command is geometrically transformed as shown in the figure, and controlled using rev, inv, and the orthogonal transformations in the dynamic equilibrium model (Figures 130 to 133).

[0121] Figure 188 is an explanatory diagram showing a quantum in a function basis. Inverse differentials are the inverse transformation principle shown in Figure 188, which transforms matter and functions in a function basis, like the dynamic function dimension of a quantum. In this case, the rev function, "input into a circle" orthogonal to inv, serves as the control. In this case, a model can be created in which a material transformation unit exists, like an electronic block in the function basis, and is controlled in dynamic equilibrium by the rev function. Placing a quantum in this cage makes it possible to control a quantum computer using the basis of the function axis, and to intentionally control quantum entanglement using various function axes. Figure 189 is an explanatory diagram showing a biological blueprint in a function basis. Placing a biological unit or biochemical circuit in this basis cage can recreate the homeostasis of an artificial life form, or, in the case of a machine, enable electromagnetic control to be controlled in dynamic equilibrium. The function that performs this orthogonal transformation and absolute control is rev. If you replace this cage unit with an object, connect it with a function bypass, and freely draw a pattern with curves and other shapes, it will become a blueprint, but with a single device that can cut a circle from anywhere (allowing various functions to be input), the circuit can be freely and intentionally transformed into an orthogonal matrix. By replacing genes with vector functions, this also becomes a blueprint for the emergence of intentions and wills through the matrix vectors of biological mechanisms. At the same time, since this circuit itself can evolve and transform, it can also be used as a learning model.

[0122] Figure 190 is an explanatory diagram showing division. One way to translate this function into a program is through weaving. First, consider the geometry of a solid as division. Figure 190 corresponds to 1 divided by 2. This can be interpreted as follows. Figure 191 is an explanatory diagram showing division. In mathematical group theory, division by 2 is folded in half to become 1 / 2 (0.5). When considered geometrically, this becomes Figure 191. Figure 192 is an explanatory diagram showing division. However, if this is changed to 0.5, it becomes Figure 192. In other words, this 0.5 can be interpreted as a plane (complex plane). Figures 193 to 195 are explanatory diagrams showing division. Now, let's move the 1 in the 3D behind it as shown in Figures 193 to 195. Figure 196 is an explanatory diagram showing division. We will notice that this solid is actually the same 1 as the solid above. 1 divided by 2 can then be interpreted as shown in Figure 196. However, in Figure 196, the plane cannot be interpreted as a division as shown below in order to satisfy the definition in group theory. Figures 197 and 198 are explanatory diagrams showing division. Here, you will notice that in Figure 197, the answer is different for the same 1 divided by 2. If you repeat this, you will get Figure 198.

[0123] 199 and 200 are explanatory diagrams showing division. This is because division and differentiation that repeats forever are infinitesimal (number (19)), that is, they correspond to differentiation, so the results are as shown in Figures 199 and 200.

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[0125] If we replace the relationship between the complex plane, in this case 0.125, and the 3D solid 1 behind it with a cylinder, the cross section of the circle becomes 0.125. This is actually just a concept. In that case, a concept is just a flag that exists only as a name or language and has no substance, so it is an empty set.

[0126] Figures 201 and 202 are explanatory diagrams showing division. Let's try calculating as shown in Figures 201 and 202. When this cylinder is differentiated by dividing by infinity, it will continue to stretch, and it is easy to see that the cross section becomes an infinitesimal differential (number (19)). 0.125 continues forever as 0.0000000000...

[0127] Figure 203 is an explanatory diagram showing division. If we think of division as the act of stretching a straw made of an infinitesimal material, it will look like Figure 203. Figures 204 to 207 are explanatory diagrams showing forging. This has been made into a calculation function that treats it as an act of stretching and contracting as follows. When a straight line 1 with a beginning and end is stretched (see Figure 204), it becomes the same 1 and retains its representative element (see Figure 205). However, when it is stretched twice as long, it becomes thinner and twice as long (see Figure 206). If we replace this with the straw model of division, we get Figure 207. Because this process is a function that stretches and contracts numbers and changes them, it resembles the act of forging iron, so it is called "forging" (see Figures 208 and 209).

[0128] <3. Control Method of Electron, Proton, Field Energy, etc. Using Quantum Circuits in an Orthogonal Model of the Real and Imaginary Planes Using New Imaginary and Negative Imaginary Number Mechanisms> <Control and Use of Physical Energy> Figures 210-216 are explanatory diagrams showing the relationship between function axes and viewpoints. Referring to Figure 210, we can see that there is a "vector function" with a spring-like structure within the function axis. By outputting the difference in these hands, three new inv function axes can be generated. The rule that can be thought of as a clock in this case is called rev (common substance). The function axes of the three hands rotate over time within the function axis, and the way they wind in the spiral structure that occurs within the function axis determines the number of rotations of the clock face, with one rotation creating a division that corresponds to the "1" mark on that hand. Using this as a basis like a number axis makes it easier to understand the periodicity of the function axes and cross sections (see Figures 210-215). This shows that the function axes are created by vector functions and complex plane matrices. When the upper chord of a vector function is cut by the imaginary plane, the complex plane is created with a base of consciousness that is the empty set and a base of existence that is the anti-empty set. Furthermore, positive and negative imaginary numbers exist as bases that are orthogonal to this base. Figure 217 is an explanatory diagram showing the relationship between vector functions and Möbius strips. Figure 217 makes the vector functions and Möbius strip functions easier to understand. Figure 218 is an explanatory diagram showing the base perspectives of positive and negative imaginary numbers. Figure 218 shows the base perspectives of positive and negative imaginary numbers. It can be seen that positive and negative are distinguished by the function axis. Figure 219 is an explanatory diagram showing the base perspectives of the empty set and the anti-empty set. Figure 219 shows the base perspectives of the empty set and the anti-empty set. Similarly, it can be seen that they are distinguished by the function axis.

[0129] Figures 220-221 are explanatory diagrams showing Möbius cuts. As shown in Figures 220-221, when the axes of the empty set and antiempty set and the axes of positive imaginary numbers and negative imaginary numbers are orthogonalized, a Möbius cut is created. The inside of this Möbius strip is generally empty, like the inside of a Schwarzschild radius, but the basis of the antiempty set is created here, giving rise to existence. Since the antiempty set has the inverse quality of the empty set, there is no set basis, and only the contents exist. Figures 222-225 are explanatory diagrams showing the function axes of a Möbius strip. Then, when the function axes of a Möbius strip are found, they look like Figure 222. Because the imaginary surface is cut at a single vertex of the periodicity, there is a break at the top of the imaginary axis (see Figures 223 and 224). When the imaginary plane deviates from this gap (or even if it does not), there is a mechanism whereby a baseless entity (an anti-empty set) emerges from the gap within the function axis (see Figure 225). Figure 226 is an explanatory diagram showing the energy of the field. This entity is called "field energy" as it is energy born from the basis (coordinates / field). Controlling this field energy with another function axis follows the same principle as controlling a proton. Figure 227 is an explanatory diagram showing the control of field energy. Figure 227 is the control of field energy. As mentioned above, it is controlled by performing operations in anti-function space.

[0130] Figure 228 is an explanatory diagram of quantum gravity theory and the extended Riemann model. To explain this field control in concrete terms using mathematical formulas, quantum gravity theory at the Planck length and the extended Riemann model are optimal. The following diagram is a simplified version. Current physics is divided into two major theories: superstring theory and loop quantum gravity theory, and the two theories are in absolute contradiction from a physical perspective. This invention realizes this as a computer approach to the principle of the constancy of the speed of light through the engineering control of field energy, as follows. Figure 228 shows the number of mechanisms (20) for WH irradiation, a calculation formula derived from the processor principle invented between the two absolutely contradictory physical laws.

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[0132] Figure 229 is an explanatory diagram of calculation in Einstein field. This is E=mc 2 , and the quantum mechanical physical model in (21) is geometrically integrated with the Möbius strip cut model to perform the calculation. Figure 230 is an explanatory diagram in which a representative quantum calculation model is added to the calculation in the Einstein field.

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[0134] Figures 231 and 232 are explanatory diagrams of calculations in Einstein fields. We note that the quantum model always requires an imaginary number (i). When (i sinθ) in Figure 290 is introduced into (sinα) in equation (21), θ ｉ is inserted between E / 2c and sinα as shown in Figure 232.

[0135] Figures 233 and 234 are explanatory diagrams of calculations in Einstein fields. Then, as shown in Figure 233, (v / c) and sinα disappear. Then, E=mc 2 E / c 2 (c 2 ) exponent disappears, and it becomes as shown in Figure 234, and E=mc 2 Since E=mc, (c 2 ) would result in the disappearance of energy equivalent to the square of the speed of light, making it mathematically possible to even neutralize nuclear weapons.

[0136] Figures 235 to 241 are explanatory diagrams of calculations in a geometric imaginary field. Now, in order to realize this calculation, an imaginary engineering mechanism was invented as a processor. When this is calculated, first, E=mc 2 Assuming that this is a physical principle limited to the universe where the natural constants in the visualization basis hold, when energy becomes a particle with mass, its spin is reversed and a particle and an antiparticle with opposite charges are born, as shown in Figure 235. In the geometric imaginary field, when a particle and an antiparticle come as close as possible to each other, as shown in Figure 236, imaginary numbers are generated on both sides of the edge.

[0137] At this time, if you look at the i axis from above (see Figure 237), the i on both sides is the same number (22), so i 2 =-1, but the momentum operator from quantum uncertainty There is an eigenvalue acting on the state, which is the number (23). This is the number (24), that is, due to this quantum uncertainty, swapping the order of multiplication results in a different answer, but at the same time, it also makes it possible to multiply matrices crosswise. As a result, the polarity returns to the original after two rotations, but the polarity is reversed after one rotation, which changes the quality. These two phenomena are called quality transformations (inversions), and by maintaining consistency in an Einstein field while corresponding to the breaking of parity symmetry, it is possible to realize calculations that make it possible to engineer the energy of the speed of light squared.

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[0141] In this case, the imaginary number i (number (22)) is θ i (See Figure 238) and E=mc 2 E / c ２ Located in ( ) by eliminating the exponent (see Figure 239).

[0142] In this case, if θ is rotation, it becomes rotation (spin) on the complex plane (see Figure 240), and if Einstein's space-time is a causal (prison) based on pi (see Figure 241), then the relationship between cosθ and sinθ is guaranteed on the Riemann sphere. Then, depending on whether sin(x) faces the real axis or the imaginary axis, in the extended Riemann sphere, it is not i on the extended complex plane at the south pole, but -i on the extended complex plane at the north pole (θ i ) 2 = 0. Here, if we consider a circle generated from an anti-Einstein field, the formula for the circle is cos 2 (x)+sin 2 We consider (x)=1 to be a representation of the positive Riemann sphere in two-dimensional real numbers (R2). It is important to note that the complex number C is expressed as R2 By considering it as such, we can express the Riemann sphere without using an imaginary number only once. From the formula for zero-fold angle, cos(0)=exp(iθ)・exp(-iθ), but this i is orthogonal to the positive Riemann sphere. It is not the imaginary unit of the extended complex plane corresponding to the positive Riemann sphere, but is orthogonal to that extended complex plane. This is because here we are using the positive Riemann sphere as R 2 This is because we had decided to express it as . This means that the "numbers" of the geometric imaginary field, which is at a higher level than the extended complex plane of the positive Riemann sphere, determine the positive Riemann sphere. For example, if we look at the formula for the zero-fold angle as cosh(Φ) = cos(iΦ) = exp(iθ)・exp(-iθ), we can interpret this as a projection (from complex to real) that causes a "number" with an angle of θ in the geometric imaginary field to appear as 0 degrees through the norm, and normalize it to 0 degrees. In the geometric imaginary field, the universe we live in actually has an angle, but we perceive it as 0 degrees. This also means that we currently only have a representation of the right-hand side where the left-hand side is always 0.

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[0145] As a prerequisite, the formula for 0-fold angle is cos(0) = exp(iθ) · exp(-iθ), so when a complex number is z = exp(iθ) and its conjugate is z* = exp(-iθ), z · z* = |z|, so it means norm. This is natural because it is a circle, but with the following ingenuity, i will no longer have its usual meaning. First, the formula for a circle, cos 2 (x)+sin 2 (x) = 1 is a positive Riemann sphere with two-dimensional real numbers (R 2 ) It is important to note that the complex number C is expressed as R 2 By thinking in terms of cos, we can express the Riemann sphere without using imaginary numbers only once. 2 (x)+sin 2If we look at (x) = cos(2Φ) = 1, it disappears at Φ = 0, but the geometric imaginary field Φ is such that one revolution in the geometric imaginary field corresponds to two revolutions in the Bloch sphere. We need to check the correspondence between the Bloch sphere and the Riemann sphere, but in other words, two revolutions return to the original (one revolution).

[0146] The phrase "one revolution" is likely a term used within the prison of π, and the prison seems to have a perspective. For example, the hyperbolic cosine cosh(x) = cos(ix), which is important when orthogonally orthogonalizing axes in a geometric imaginary field, does not evoke the idea of ​​a revolution. While quantum mechanics simply refers to spin, in a geometric imaginary field, spin is a property of the projected Riemann sphere, known as "field spin (dark energy?)." Treating photons as imaginary numbers from a quantum perspective simply means that their velocity is conserved in a world of vision only due to the quantum communication effect. This raises the question: Is it because θ = -iθ? In other words, if i is the θ (mass) of consciousness, does -i equal the θ (anti-mass) of anti-consciousness? Furthermore, isn't the square root of energy fixed from the beginning? Are there limits to the science of visual matter (mass)? Various questions arise from the calculation results.

[0147] Figure 242 is an explanatory diagram of the speed of light. This is because, in the first place, E=mc 2 Since this is a mathematically distinct domain, a model that is perpendicular to the principle of the constancy of the speed of light is created. Figure 242 explains how the speed of light is 300,000 km per second. If we can say that this function curve has a fixed square root of energy from the beginning, then it could be number (27).

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[0149] Why do photons have energy even though they have no mass? It is clear from BH that the energy of photons is affected by gravity. Also, why do other objects have mass? It is said that mass is created by the Higgs field, an "invisible" energy field that permeates the entire universe, and it is thought that when matter interacts with this field, it is affected by the resistance of water and acquires mass.

[0150] Considering an exponential curve in energy, the tetration result of (28) may not be infinity. In other words, (29) and (30) may have different solutions.

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[0154] Normally, we would think that it would become infinitely large, as in number (31).

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[0156] However, when we actually calculate it, we get an interesting result, as shown in number (32).

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[0158] Figure 243 is a diagram of the number (32). If you arrange 100 (or one trillion) square roots (√2) in a tetration and make the 101st (or one trillionth) square root a 2, the result will be 2, so it is clear that an infinite diagonal stack of square roots (√2) cannot exceed 2. 0 0 = 0. If we illustrate this, we get Figure 243, which closely resembles the function curve of the constant speed of light.

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[0160] In equation (33), F ∞ = infinity, so 0+1+1+2+3+5+8…=∞F n The sum of reciprocals (number (34)) converges between 3.3 and 3.4. This raises the question: does the speed of light limit of 300,000 km / s oscillate with an amplitude that expands between 3.3 and 3.4 for negative numbers?

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[0162] The sequence of the reciprocal (1 / n) of a natural number (n) converges to zero, but the Fn of the number (35) diverges to positive infinity, and the number (36) oscillates. In mathematical theory, the values ​​oscillate at the point where the upper and lower parts split, and do not converge, so it is outside the domain of the function. However, as a mathematical experiment, x=n 1 / nWhen it is, it seems to converge to n, so if we assume that the reason it takes on an infinite value is because the function can be expressed implicitly rather than explicitly, then the exponential function of i seems interesting.

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[0165] Figures 244 to 257 are explanatory diagrams showing the boundary between convergence and divergence. Now, from Figure 244, it seems that there is a boundary between numbers (37) and (38).

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[0168] Furthermore, if we go into more detail as in Figure 245, we can see that there seems to be a boundary between convergence and divergence around 1000 x's. If we graph this, it will look like Figure 246 when there are about 9 x's, and when there are about 30 x's, the points will fall off the graph as in Figure 247. And, if the number of x's is y, it will look like Figure 248 that the boundary of the divergence value is between 1.44 and 1.45. This boundary is y=x y (See Figure 249) and calculate y=x y When the equation is differentiated by x with respect to y, the result is as shown in FIG.

[0169] To make the calculation easier to understand, if we swap x and y, we get (39). Taking the logarithm of both sides and differentiating y with respect to x, we get (40). In (41), the y coordinate is y=1 / x. 2 Substituting x = e into the equation gives number (42), so by restoring x and y, point P becomes number (43) (see Figure 251).

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[0175] [Correction based on Rule 91 23.04.2025] Number (44) is substituted into number (45) to obtain number (46), and y = e?.

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[0179] If we graph the exponential function of x, we get something like Figures 252 and 253. If we repeat this process, interesting oscillations will occur between even and odd numbers, as shown in Figures 254 and 255.

[0180] So, by summarizing these phenomena, we can see that the conversion point is the number (47) (see 256).

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[0182] Furthermore, by summarizing, it can be normalized as shown in Figure 257. Figures 258 to 266 are explanatory diagrams showing field energy gates. Therefore, by assuming antiphotons (particles perpendicular to photons) and performing the calculations (see Figure 258), and by cutting the Möbius strip horizontally into two rows (see Figure 259), it can be diagrammed as shown in Figure 260. Using the characteristic of the Möbius strip that the causal chains form a chain, the state in which a photon is considered to have no mass can be interpreted as a state in which a gate has occurred, as shown in Figure 261. By introducing this into the WH equation, it can be summarized neatly and simply as shown in Figure 262.

[0183] This allows us to see gates that extract field energy by varying the way a Möbius strip is cut, as shown in Figure 263. For example, if we cut it vertically as in Figure 264, we can calculate energy that exceeds the speed of light (see Figure 265). Imaginary mass is generally called a "tachyon particle" (see Figure 266).

[0184] Figures 267 to 275 are explanatory diagrams showing the conversion of the speed of light. Well, now that we have calculated up to this point, let's try dividing by the speed of light (see Figure 267). Taking the logarithm of both sides gives number (48). When we multiply the denominator and numerator on the right side by 2 to get number (49), we obtain number (50). Therefore, in this region, we calculate the possibility that the speed of light jumps to 2 times or 4 times.

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[0188] Well, when we graph these two equations, three intersection points are obtained (see Figures 268 and 269). Since this is squared, for the intersection of y = x and number (51), negative values do not appear. Should we consider it a non-existent root? Or is it the acquisition of a perspective of imaginary numbers? When it is 2, let the number when n are arranged side by side be An, which is number (52). Thus, since An < 2 and √2 > 1, An is monotonically increasing, so it can be shown that An converges within the range of √2 < An < 2. But what else is needed to show that it converges to 2? This question arises.

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[0191] So, looking at Euler's transformation, it is as shown in Figure 270. When we perform this using the optical transformation with the invented processor, the graph becomes as shown in Figure 271. When we rotate the imaginary axis by 1 / 4 turn (see Figure 272), we can handle the relationship between the quantum field and the quantum in terms of the real part and the imaginary part. At this time, it can be seen that inverse Entropy occurs (see Figure 273). Also, Entropy occurs in this direction, and it can be seen that when this imaginary number 0.7666469… becomes 2 times the speed-of-light breakthrough, it is a certain value (see Figure 274). Then, assuming the region where the anti-boundary differential axis exists in space-time, it can be seen that the Energy calculation of the field is three-dimensional with the number (53) axis on the plane of mass × speed (see Figure 275).

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[0193] The quantum circuit of the present invention and the intention-emergent signal processing device using the same are quantum circuits that perform the above-mentioned operations. As mentioned above, these operations can reproduce nerves, and these operations can be said to be intention-emergent signal processing.

[0194] Quantum circuits generate an inverse function space whose axis is a function obtained from the intersection of an arbitrary string and the rev function, and by using the inverse function space for calculations, it becomes possible to perform calculations on the inverse function space whose axis is a function.

[0195] Quantum circuits can easily generate multiple functions to use as axes because the string is an inv function of the quarks that make up the proton.

[0196] Quantum circuits have multiple axes that make up the inverse function space, making it possible to perform operations on multiple elements at once.

[0197] Quantum circuits operate by superimposing inverse function spaces to perform polar inversion, quantum overlap, or energy-mass conversion, making it possible to calculate phenomena that cannot be explained by arithmetic operations.

[0198] The intention-emergent signal processing device is an intention-emergent signal processing device that uses the quantum circuit described above, and performs an operation to overlap inverse function spaces.By making this operation the emergence of intention, it becomes possible to artificially reproduce biological reactions.

[0199] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to the above embodiments.

[0200] In this embodiment, the string is an inv function or an imaginary function of the quarks that make up the proton, but is not limited to this.

[0201] By using the quantum circuit of the present invention, it becomes possible to perform calculations such as quantum overlap, overlap between imaginary and real numbers, conversion between matter and energy, reconciliation of conflicting interests, neural behavior, etc. Furthermore, by calculating neural behavior, it becomes possible to create an intention emergence signal processing device that artificially generates intention.

[0202] 1. Input 3. Consciousness space 4. Continuous quantity axis 5. Concept axis 6. Intention output

Claims

1. A quantum circuit used in a quantum computer, which generates a space whose axis is a function obtained from the intersection of an arbitrary string and a rev function, and uses the space for calculations.

2. A quantum circuit according to claim 1, wherein the string is an inv function of the quarks that make up the proton.

3. The quantum circuit according to claim 1, wherein the space is made up of a plurality of axes.

4. The quantum circuit according to claim 1, which performs polarity reversal, quantum overlap, or energy-mass conversion by overlapping the spaces.

5. An intention-emergent signal processing device using the quantum circuit of claim 4, which performs an operation to overlap the spaces, and which causes the operation to emerge as intention.

Images