A method, system and device for automatic maintenance of ion trap for quantum computing

Abstract

The present invention discloses an automatic maintenance method, system and equipment for an ion trap used for quantum computing, and relates to the technical field of ion trap quantum computing. The method comprises: imaging ions in an ion trap used for quantum computing by an ion imaging device to obtain an initial image; processing the initial image to obtain the current state of at least one target ion; comparing the current state of all target ions with the standard state of all standard ions in the ion trap; when there are missing ions, controlling the ion filling-related instruments and equipment to fill ions into the space region to which the missing ions belong, and when there are ions exceeding the set deviation, correcting the position of the ions exceeding the set deviation by ion cooling-related instruments and equipment. The present invention can automatically maintain the ion trap, so that the ion trap quantum computing system can automatically maintain a state in which quantum computing can be performed without human maintenance.

Description

Background Art

[0002] Quantum computing was first proposed by Feynman in the 1980s. It is a method of processing information using the principles of quantum mechanics. Quantum computing has obvious advantages over classical computing in some cases, so quantum computing is considered a revolutionary technology.

[0003] As a physical implementation of quantum computing, ion traps have received extensive attention and research. The basic principle is to use electromagnetic fields to confine ions in a specific spatial region and to achieve quantum computing by precisely manipulating the quantum states of these ions. Ion traps have the advantages of high precision, long coherence time, scalability, and broad application prospects.

[0004] When using ion traps for quantum computing, the ions need to be confined in a specific spatial region. Due to the influence of various factors, the ions in the ion trap may break free from their confinement, making the ion trap unable to perform quantum computing. To deal with this situation, in existing solutions, experimental personnel are required to monitor the state of the ions in the ion trap through imaging equipment, take corresponding measures immediately when observing that the ions are unstable or lost, and manually operate the experimental equipment when necessary to keep the entire system in a state where quantum computing can be performed. This makes it difficult for ion trap quantum computing systems to operate unattended for a long time, greatly limiting the widespread application of ion trap quantum computing systems. Summary of the invention

[0005] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide an automatic maintenance method, system and device for an ion trap for quantum computing, as follows:

[0006] 1) In the first aspect, the present invention provides an automatic maintenance method for an ion trap used for quantum computing, and the specific technical solution is as follows:

[0007] Imaging ions in an ion trap used for quantum computing by an ion imaging device to obtain an initial image;

[0008] processing the initial image to obtain a current state of at least one target ion;

[0009] Compare the current states of all target ions with the standard states of all standard ions in the ion trap to determine whether there are missing ions in the ion trap, and determine whether there are ions in the ion trap that exceed a set deviation;

[0010] When there are missing ions, the ion filling related instruments and equipment are controlled to fill ions into the space area where the missing ions belong. When there are ions exceeding the set deviation, the position of the ions exceeding the set deviation is corrected through the ion cooling related instruments and equipment.

[0011] The beneficial effects of the automatic maintenance method of an ion trap for quantum computing provided by the present invention are as follows:

[0012] It can automatically monitor the status of ions in the ion trap. When there are missing ions, it controls the ion filling-related instruments and equipment to fill ions into the space area where the missing ions belong. When there are ions that exceed the set deviation, the position of the ions that exceed the set deviation is corrected through ion cooling-related instruments and equipment, so that the ion trap quantum computing system can automatically maintain a state where it can perform quantum computing without human maintenance.

[0013] Based on the above solution, the automatic maintenance method of an ion trap for quantum computing of the present invention can be further improved as follows.

[0014] Furthermore, the initial image is a two-dimensional grayscale image, and the initial image is processed to obtain the current state of the target ion, including:

[0015] Perform median filtering on the initial image to obtain a median filtered image;

[0016] Binarize the median filtered image to obtain a binary image;

[0017] The bright spots in the binary image are partitioned to obtain multiple bright areas. Bright spots refer to pixels with a gray value of 255. Each target bright area corresponds to a target ion.

[0018] Obtain the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion.

[0019] Further, determining whether there are missing ions in the ion trap includes:

[0020] According to the position of the center point, each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and it is determined whether each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and a pairing judgment result is obtained. When the pairing judgment result is yes, it is determined that there are no missing ions in the ion trap. If not, it is determined that there are missing ions in the ion trap.

[0021] Further, judging whether there are ions exceeding the set deviation in the ion trap includes:

[0022] When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: a preset position deviation ratio threshold and a preset radius deviation ratio threshold.

[0023] 2) In a second aspect, the present invention also provides an automatic maintenance system for an ion trap used for quantum computing, and the specific technical solution is as follows:

[0024] It includes an imaging module, an ion recognition module, a state comparison module and an automatic maintenance module;

[0025] The imaging module is used to: image the ions in the ion trap used for quantum computing through an ion imaging device to obtain an initial image;

[0026] The ion recognition module is used to: process the initial image to obtain the current state of at least one target ion;

[0027] The state comparison module is used to compare the current state of all target ions with the standard state of all standard ions in the ion trap, determine whether there are missing ions in the ion trap, and determine whether there are ions in the ion trap that exceed the set deviation;

[0028] The automatic maintenance module is used to: when there are missing ions, control the ion filling related instruments and equipment to fill ions into the space area where the missing ions belong; when there are ions exceeding the set deviation, correct the position of the ions exceeding the set deviation through ion cooling related instruments and equipment.

[0029] Based on the above solution, the automatic maintenance system of an ion trap for quantum computing of the present invention can also be improved as follows.

[0030] Furthermore, the initial image is a two-dimensional grayscale image, and the ion recognition module is specifically used for:

[0031] Perform median filtering on the initial image to obtain a median filtered image;

[0032] Binarize the median filtered image to obtain a binary image;

[0033] The bright spots in the binary image are partitioned to obtain multiple bright areas. Bright spots refer to pixels with a gray value of 255. Each target bright area corresponds to a target ion.

[0034] Obtain the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion.

[0035] Furthermore, the status comparison module is also specifically used for:

[0036] According to the position of the center point, each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and it is determined whether each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and a pairing judgment result is obtained. When the pairing judgment result is yes, it is determined that there are no missing ions in the ion trap. If not, it is determined that there are missing ions in the ion trap.

[0037] Furthermore, the status comparison module is also specifically used for:

[0038] When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: a preset position deviation ratio threshold and a preset radius deviation ratio threshold.

[0039] 3) In a third aspect, the present invention further provides a computer device, comprising a processor coupled to a memory, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor, so that the computer device implements any of the above-mentioned methods for automatic maintenance of an ion trap for quantum computing.

[0040] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned methods for automatic maintenance of ion traps for quantum computing.

[0041] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0043] Figure 1 This is one of the flow charts of an automatic maintenance method of an ion trap for quantum computing according to an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the structure of an ion trap quantum computing system;

[0045] Figure 3 This is an example of an image under normal conditions;

[0046] Figure 4 This is an example of an image when there are ion deletions;

[0047] Figure 5 This is an example of an image when the ion motion amplitude is large;

[0048] Figure 6 is a schematic diagram of a binary image;

[0049] Figure 7 Schematic diagram of the radius and center point position of the target bright area;

[0050] Figure 8 The second flowchart of an automatic maintenance method of an ion trap for quantum computing according to an embodiment of the present invention;

[0051] Fig. 9 A schematic diagram of the structure of an automatic maintenance system for an ion trap used for quantum computing according to an embodiment of the present invention;

[0052] Fig.10 The figure is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0054] like Figure 1 As shown, an automatic maintenance method of an ion trap for quantum computing according to an embodiment of the present invention comprises the following steps:

[0055] S1, imaging ions in an ion trap for quantum computing by an ion imaging device to obtain an initial image;

[0056] The ion trap used for quantum computing specifically refers to: the ion trap in the ion trap quantum computing system. The ion trap quantum computing system is a device that can bind ions in several specific spatial regions. At the same time, the ion trap quantum computing system can also perform ion filling and ion cooling operations, specifically including: ion trap, ion cooling module, ion filling module, quantum computing module and quantum imaging module, such as Figure 2 As shown, the details are as follows:

[0057] 1) An ion trap includes a vacuum chamber, and the ion trap can generate a specific electromagnetic field that can confine ions in several spatial regions within the vacuum chamber. Usually, in an ion trap used for quantum computing, each spatial region can only accommodate one ion. In S1, the ions in the ion trap refer to: ions in all spatial regions within the vacuum chamber.

[0058] 2) Ion cooling module:

[0059] Ideally, the trapped ions in the ion trap remain stationary at a specific position in the space region (called the equilibrium point). In the process of performing quantum computing, the trapped ions will gradually accumulate kinetic energy and move back and forth near the equilibrium point due to various factors. If the movement amplitude is too large, the ions will break free. The kinetic energy of the ions can be reduced (laser cooling) with the help of lasers of a specific wavelength to prevent the ions from breaking free due to excessive movement amplitude.

[0060] Ion cooling will affect the quantum state of ions and interfere with quantum computing, so ion cooling should be carried out in a planned manner.

[0061] In the present invention, the ion cooling module refers to: instruments and equipment related to ion cooling.

[0062] 3) Ion filling module:

[0063] In the initial state, there are no ions in the space region in the vacuum chamber of the ion trap that can bind ions. It is necessary to release specific types of ions from the ion source into the vacuum chamber. At the same time, with the help of laser cooling, the ions entering the space region that binds the ions are gradually stabilized near the equilibrium point.

[0064] Usually, quantum computing can only be performed when each bound ion space is filled with an ion. However, in the process of performing quantum computing, some ions may break free and leave the space where they were originally located, which will cause the ion trap to be unable to continue to perform quantum computing. Therefore, the above operation needs to be performed when it is found that an ion has broken free.

[0065] Since the process of releasing and cooling ions is random, the above operation may not be able to fill all the spatial regions of bound ions with ions, that is, there is a certain probability of failure in the operation.

[0066] Ion filling will destroy the quantum state of the ions and interfere with quantum computing, so ion cooling should be carried out in a planned manner.

[0067] Compared with ion cooling, ion filling takes longer, so ion cooling should be used first to prevent ions from breaking free, rather than waiting for the ions to break free and then perform ion filling.

[0068] In the present invention, the ion filling module refers to: instruments and equipment related to ion cooling such as lasers and ion sources.

[0069] 4) Quantum computing module:

[0070] The quantum computing module is used to perform quantum computing. Specifically, quantum computing can be achieved by precisely manipulating the quantum state of ions trapped in an ion trap.

[0071] The quantum computing module can receive and execute a quantum computing program and return the result after the execution is completed. During the execution of the quantum computing program, the quantum computing module can also receive an interrupt instruction, and immediately interrupt the executing quantum computing program after receiving the interrupt instruction. Then, according to the program settings, it can immediately return an error message as a result, or wait for a recovery signal and resume the execution of the quantum computing program.

[0072] There are many implementation schemes for the quantum computing module, which are not limited in the present invention.

[0073] 5) Ion imaging module:

[0074] Ion imaging module refers to a device that can image ions in an ion trap, usually composed of devices such as cameras and lasers.

[0075] The laser emits a laser of a specific wavelength to the spatial region where the ions are bound in the ion trap, which causes the ions to produce fluorescence. At the same time, the camera is also aimed at the spatial region where the ions are located, and the fluorescence produced by the ions is received for imaging to obtain a two-dimensional grayscale image (unlike common cameras, the grayscale image output by laboratory cameras is not necessarily the common 256-level color scale). Due to various factors, there will be some random noise in the image.

[0076] By observing whether there are bright spots in the image, we can determine whether there are bound ions in the corresponding spatial area, and we can also obtain the state information of the ions based on the shape of the bright spots. Figure 3 This shows an image with five ions in the ion trap. Figure 3 The bright spot in the image is the image of the ion. Figure 4 The image shows an ion freed from its confinement, with a bright spot missing. Figure 5The image shows what happens when the ions are moving too much, with one bright spot being noticeably larger.

[0077] S2, processing the initial image to obtain the current state of at least one target ion;

[0078] S3, comparing the current states of all target ions with the standard states of all standard ions in the ion trap, determining whether there are missing ions in the ion trap, and determining whether there are ions in the ion trap that exceed a set deviation;

[0079] S4. When there are missing ions, the ion filling-related instruments and equipment are controlled to fill ions into the space area to which the missing ions belong. When there are ions exceeding the set deviation, the positions of the ions exceeding the set deviation are corrected through the ion cooling-related instruments and equipment.

[0080] The present invention provides an automatic maintenance method for an ion trap used for quantum computing, which can automatically monitor the state of ions in the ion trap. When there are missing ions, the ion filling-related instruments and equipment are controlled to fill ions into the space region to which the missing ions belong. When there are ions exceeding the set deviation, the positions of the ions exceeding the set deviation are corrected through ion cooling-related instruments and equipment, so that the ion trap quantum computing system can automatically maintain a state in which quantum computing can be performed without human maintenance.

[0081] Optionally, the initial image is a two-dimensional grayscale image. In S2, the initial image is processed to obtain the current state of the target ion, including: median filtering the initial image to obtain a median filtered image; binarizing the median filtered image to obtain a binary image; partitioning the bright spots in the binary image to obtain multiple bright areas, where the bright spots refer to: pixels with a grayscale value of 255, and each target bright area corresponds to a target ion; obtaining the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion.

[0082] S20, performing median filtering on the initial image to obtain an image after median filtering, which can effectively reduce noise in the image;

[0083] S21, binarize the image after median filtering to obtain a binary image. Specifically, the image after median filtering is binarized using a bimodal method, which can simplify the image content. The binary image is as follows: Figure 6 As shown, there is only a bright spot near the image of the ion, and other locations are completely dark.

[0084] S22, partitioning the bright spots in the binary image to obtain multiple bright areas, where the bright spots refer to pixels with a gray value of 255, and each target bright area corresponds to a target ion. The specific implementation process is as follows:

[0085] S220, searching all bright pixels, i.e., bright spots, in the two-dimensional image, and ignoring dark pixels, where dark pixels refer to pixels with a gray value of 0;

[0086] S221, marking all bright spots as “ungrouped”;

[0087] S222, randomly select an ungrouped bright spot p0, create a new group G, and mark the selected bright spot p0 as "group G";

[0088] S223. For each bright spot in group G (there is only one pixel in the initial state), search for all ungrouped bright spots whose distance to each bright spot in group G is less than l, and mark them as "group G", where l represents a preset distance threshold, which can be set according to actual conditions.

[0089] S224, repeat S223 until no new bright spots are added to group G;

[0090] S225, jump to S222, until all bright spots are grouped;

[0091] After executing the above process, each group contains multiple bright pixels with similar distances, namely bright spots, which are called "bright areas". Ideally, each bright area should correspond to an ion.

[0092] S23, obtaining the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of the target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion, specifically:

[0093] S230, counting the number of bright spots contained in each bright area, and determining the bright area whose number of bright spots is within a preset range of pixel points as the first bright area;

[0094] S231, mapping the binary image into a two-dimensional coordinate system, respectively calculating the average of the x-coordinate and the y-coordinate of all bright spots in each first bright area, and obtaining the coordinates of the center point of each first bright area;

[0095] S232, calculating the radius of each first bright area, specifically: calculating the distance between all bright spots in any bright area and the center point of the first bright area, specifically calculated by coordinate operation, and taking the maximum value of the distance as the radius of the first bright area, until the radius of each first bright area is calculated;

[0096] S233: taking the first bright area with a radius within a preset radius as the target bright area. It can be understood that the center point position of the target bright area is specifically represented by the center point coordinates.

[0097] For example, when Figure 6 When all bright areas in are target bright areas, the center point coordinates of the first target bright area 1 are: (24.1, 46.8), and the radius r is 3.6; the center point coordinates of the second target bright area 2 are: (45.5, 54.4), and the radius r is 4.2; the center point coordinates of the third target bright area 3 are: (66.8, 59.9), and the radius r is 3.8; the center point coordinates of the fourth target bright area 4 are: (88.2, 66.8), and the radius r is 3.87; the center point coordinates of the fifth target bright area 5 are: (110.1, 72.5), and the radius r is 4.2. Figure 7 As shown, Figure 7 The plots in are drawn at the corresponding radii.

[0098] It can be understood that the target bright area is a bright area that has been screened by a preset pixel point number range and a preset radius range. When the number of bright spots in all bright areas is within the preset pixel point number range and the radius of all target bright areas is within the preset radius range, then all bright areas are target bright areas.

[0099] Optionally, in S3, determining whether there are missing ions in the ion trap includes:

[0100] S30. Pair each target bright area with each standard target bright area in the standard state of all standard ions in the ion trap according to the position of the center point, determine whether each target bright area with each standard target bright area in the standard state of all standard ions in the ion trap is matched one by one, and obtain a pairing judgment result. When the pairing judgment result is yes, determine that there are no missing ions in the ion trap. If not, determine that there are missing ions in the ion trap.

[0101] It should be noted that the process of obtaining the standard state of all standard ions includes:

[0102] After the experimenter calibrates the ion trap quantum computing system, ion imaging is performed to obtain a standard initial image, which is also a two-dimensional grayscale image. S2 is used to obtain a standard binary image corresponding to the standard initial image, and then the standard state of all standard ions in the ion trap is obtained. For ease of distinction, the target bright area obtained based on the standard initial image is recorded as the standard target bright area, and the ion corresponding to the standard target bright area is recorded as the standard ion. The standard state of any standard ion in the ion trap specifically includes: the radius and center point position of the standard target bright area corresponding to the standard ion.

[0103] The pairing process is as follows:

[0104] S300, randomly select a target bright area, and select a standard target bright area closest to the target bright area from among all standard target bright areas to pair with the randomly selected target bright area, until all target bright areas are paired, and the specific implementation method is as follows:

[0105] A two-dimensional image obtained based on the initial image and a binary image obtained as a standard based on the initial image as a standard are completely overlapped and placed on the same canvas to obtain a fused image, which is mapped in a two-dimensional coordinate system, and the distance between an arbitrarily selected target bright area and each standard target bright area is obtained by coordinate calculation, and then the standard target bright area closest to the target bright area is determined.

[0106] S301, judging whether each target bright area and each standard target bright area in the standard state of all standard ions in the ion trap are matched one by one. Specifically, if at least one of the following conditions is met, the matching judgment result is no, and the matching is regarded as failed. If none of the following conditions are met, the matching judgment result is yes, and the matching is regarded as successful:

[0107] 1) The first situation: there is a standard target bright area that is not paired with any target bright area;

[0108] 2) The second situation: the same standard target bright area is paired with multiple target bright areas respectively.

[0109] Optionally, in S3, determining whether there are ions in the ion trap that exceed a set deviation includes:

[0110] S31. When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: a preset position deviation ratio threshold and a preset radius deviation ratio threshold.

[0111] For the paired target bright area and the standard target bright area, the target bright area is recorded as: a = (x a ,y a ,r a ), x a Indicates the x-coordinate and y-coordinate of the center point of the target bright area. a Indicates the y coordinate of the center point of the target bright area, r arepresents the radius of the target bright area, and the standard target bright area is recorded as: b = (x b ,y b ,r b ), x b The x-coordinate and y-coordinate of the center point of the standard target bright area b The y coordinate of the center point of the standard target bright area, r b Indicates the radius of the standard target bright area and the position deviation ratio d l The calculation formula is: Calculation formula for radius deviation ratio d r for: When the position deviation ratio between any pair of target bright area and the standard target bright area is less than the preset position deviation ratio threshold, and the radius deviation ratio between the paired target bright area and the standard target bright area is less than the preset radius deviation ratio threshold, it is determined that the ions corresponding to the target bright area exceed the set deviation; otherwise, it is determined that the ions corresponding to the target bright area do not exceed the set deviation.

[0112] Optionally, when there are missing ions and / or when there are ions that exceed the set deviation, a signal is sent to control the quantum computing module to interrupt the quantum computing. When the relevant instruments and equipment for ion filling are controlled to fill ions into the space region to which the missing ions belong, and the positions of ions that exceed the set deviation are corrected through the relevant instruments and equipment for ion cooling, a signal is sent to control the quantum computing module to continue the quantum computing.

[0113] The specific implementation process of the above S2 is called an ion recognition algorithm, and the specific implementation process of the above S3 is called an ion state comparison algorithm.

[0114] The present invention is further described by the following embodiment. Figure 8 As shown, specifically:

[0115] S1001, Initialization and calibration:

[0116] Before starting, the experimenter needs to fill the ions and adjust the parameters of the camera, laser, ion trap and other related equipment so that the imaging system, i.e. the ion imaging module, can obtain a clear image. The experimenter also needs to manually calibrate and confirm that there are no abnormalities in the ions in the current ion trap, i.e. there are no missing ions and no ions with large position deviations. Then, ion imaging is performed, and the ion recognition algorithm is called to obtain the current state of each ion. The current state of each ion is used as the standard state, which is the standard ion mentioned above.

[0117] This step involves multiple devices and needs to be completed manually to ensure imaging quality. For the same set of equipment, this step does not need to be repeated without significantly changing the relevant parameters.

[0118] S1002: After initialization and calibration, regular inspection is performed according to preset rules. During the inspection, ion imaging is performed once, the ion recognition algorithm is called to obtain the current state of all target ions, and then the ion state comparison algorithm is called to compare the current state of all target ions with the standard state of all standard ions in the ion trap.

[0119] When there are missing ions, it means that some ions have escaped the constraints of the ion trap. At this time, a specific signal is sent to interrupt the quantum computing program being executed and perform the ion filling operation. The specific implementation process is: ions are emitted into the ion trap to fill the space area where the missing ions belong, and then ion identification is performed again. If the ion filling operation is successful, the execution of the quantum computing program can be resumed. If the ion filling operation fails, the above steps are repeated until the ion state matches the standard state.

[0120] Optionally, based on actual needs, an upper limit on the number of repeated attempts can be set. If multiple refills fail to meet the standard status, the attempt is stopped and a prompt signal for manual inspection is sent.

[0121] If there is no ion missing, but the current state of the ion deviates greatly from the standard state, that is, there are ions that exceed the set deviation, it means that the ion movement amplitude is too large. At this time, a specific signal is sent to interrupt the quantum computing program being executed, and the ion cooling operation is performed, that is, the position of the ion that exceeds the set deviation is corrected through ion cooling related instruments and equipment.

[0122] If the current state of all ions is consistent with the standard state, there is no need to interrupt the quantum computing program being executed, and the quantum computing program continues to be executed until the next check. In other words, when there are no missing ions in the ion trap and no ions that exceed the set deviation, there is no need to interrupt the quantum computing program being executed. The quantum computing program continues to be executed until the next check.

[0123] Among them, the ion recognition algorithm can also be understood as follows:

[0124] The ion identification algorithm can identify the position and radius of the images of multiple ions in the image obtained by ion imaging, and provide structured data for checking the ion state. The ion identification algorithm includes the following steps:

[0125] 1) Preprocessing:

[0126] The purpose of this step is to simply process the image, optimize the image quality, and convert the data format to make it suitable for subsequent calculation steps. The preprocessing includes the following processes:

[0127] ①Perform median filtering on the two-dimensional grayscale image to obtain the median filtered image. This operation can effectively reduce the noise in the image.

[0128] ② Use the bimodal method to binarize the two-dimensional grayscale image after median filtering to obtain a binary image. This operation can simplify the image content. The binary image is as follows: Figure 6 As shown, there is only a bright spot near the image of the ion, and other locations are completely dark.

[0129] 2) Split the bright area:

[0130] The purpose of this step is to divide the bright spots corresponding to each ion into multiple groups.

[0131] Preset parameters: distance threshold l;

[0132] The specific implementation process of this step is S220 to S225 in the above text, which will not be repeated here.

[0133] 3) Post-processing:

[0134] The purpose of this step is to process the data of each bright area to obtain data such as the center point coordinates and radius.

[0135] Preset parameters: The range of the number of bright spots in the bright area is the preset range of the number of pixels, and the range of the radius of the bright area is the preset radius range;

[0136] The specific implementation process of this step is as follows:

[0137] ① Count the number of bright spots in each bright area. According to the preset parameters, keep the bright areas with the number of pixels within the preset range and discard the bright areas with too many or too few pixels.

[0138] ② Calculate the coordinates of the center point of each bright area: Calculate the average value of the x coordinates (y coordinates) of all pixels in the bright area as the x coordinate (y coordinate) of the center point.

[0139] ③ Calculate the radius of each bright area: calculate the distance from all pixels in the bright area to the center point, and take the maximum value of the distance of all pixels as the radius of the bright area.

[0140] ④ According to the preset parameters, the bright areas with a radius within the preset range are retained, and the bright areas with a radius that is too large or too small are discarded.

[0141] Thus, the target bright area, the center point coordinates and the radius of the target bright area are determined, the number of bright spots in each target bright area is within the preset pixel number range, and the radius of each target bright area is within the preset radius range.

[0142] Through the ion recognition algorithm, the center point coordinates and radius of multiple target bright areas are output as ion states.

[0143] Among them, the ion state comparison algorithm can also be understood as follows:

[0144] The ion state comparison algorithm is used to compare the given ion state with the standard ion state to determine whether the given ion state is consistent with the standard state. For the case where the ion state does not match the standard state, it can also distinguish between "ion missing" and "ion state deviation is too large". The specific implementation process is as follows:

[0145] 1) Pairing is performed according to the position. The specific implementation process is S300 to S301 in the above text, which will not be repeated here. If the pairing fails, the result of "ion missing" is directly output. If the pairing is successful, the step of "checking the degree of deviation" is executed.

[0146] 2) Check the degree of deviation. The specific implementation process is as explained in the above S3, which will not be repeated here. When the position deviation ratio and radius deviation ratio between all target bright areas and the standard target bright areas paired with the target bright areas are less than the corresponding preset thresholds, the output is "compliant", otherwise, the output is "ion state deviation is too large".

[0147] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0148] like Fig. 9 As shown, an automatic maintenance system 200 of an ion trap for quantum computing according to an embodiment of the present invention comprises an imaging module 201, an ion identification module 202, a state comparison module 203 and an automatic maintenance module 204;

[0149] The imaging module 201 is used to: image the ions in the ion trap used for quantum computing through an ion imaging device to obtain an initial image;

[0150] The ion identification module 202 is used to: process the initial image to obtain the current state of at least one target ion;

[0151] The state comparison module 203 is used to compare the current state of all target ions with the standard state of all standard ions in the ion trap, determine whether there are missing ions in the ion trap, and determine whether there are ions in the ion trap that exceed the set deviation;

[0152] The automatic maintenance module 204 is used to: when there are missing ions, control the ion filling related instruments and equipment to fill ions into the space area where the missing ions belong; when there are ions exceeding the set deviation, correct the position of the ions exceeding the set deviation through ion cooling related instruments and equipment.

[0153] Optionally, in the above technical solution, the initial image is a two-dimensional grayscale image, and the ion recognition module 202 is specifically used for:

[0154] Perform median filtering on the initial image to obtain a median filtered image;

[0155] Binarize the median filtered image to obtain a binary image;

[0156] The bright spots in the binary image are partitioned to obtain multiple bright areas. Bright spots refer to pixels with a gray value of 255. Each target bright area corresponds to a target ion.

[0157] Obtain the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion.

[0158] Optionally, in the above technical solution, the state comparison module 203 is further specifically used for:

[0159] According to the position of the center point, each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and it is determined whether each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and a pairing judgment result is obtained. When the pairing judgment result is yes, it is determined that there are no missing ions in the ion trap. If not, it is determined that there are missing ions in the ion trap.

[0160] Optionally, in the above technical solution, the state comparison module 203 is further specifically used for:

[0161] When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: a preset position deviation ratio threshold and a preset radius deviation ratio threshold.

[0162] Optionally, the ion identification module 202 is also used to: when there are missing ions and / or when there are ions that exceed the set deviation, send a signal to control the quantum computing module to interrupt the quantum computing; when controlling the ion filling-related instruments and equipment to fill ions into the space region to which the missing ions belong, and after correcting the position of ions that exceed the set deviation through the ion cooling-related instruments and equipment, send a signal to control the quantum computing module to continue the quantum computing.

[0163] It should be noted that the beneficial effects of the automatic maintenance system 200 for an ion trap for quantum computing provided in the above embodiment are the same as the beneficial effects of the automatic maintenance method for an ion trap for quantum computing provided in the above embodiment, which will not be described in detail here. In addition, when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described in detail here.

[0164] like Fig.10 As shown, a computer device 300 according to an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the computer device 300 implements any of the above-mentioned automatic maintenance methods of an ion trap for quantum computing, specifically:

[0165] The computer device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein at least one computer program 330 is stored in the one or more memories 310, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the computer device 300 implements any one of the automatic maintenance methods for ion traps for quantum computing provided in the above embodiments. Of course, the computer device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the computer device 300 may also include other components for implementing device functions, which will not be described in detail here.

[0166] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements any of the above-mentioned automatic maintenance methods for an ion trap for quantum computing.

[0167] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0168] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes any of the above-mentioned methods for automatic maintenance of an ion trap for quantum computing.

[0169] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0170] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0171] Any combination of one or more computer-readable media can be used. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0172] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for automatic maintenance of an ion trap for quantum computing, characterized in that: include: Imaging ions in an ion trap used for quantum computing by an ion imaging device to obtain an initial image; Processing the initial image to obtain a current state of at least one target ion; Comparing the current states of all target ions with the standard states of all standard ions in the ion trap to determine whether there are missing ions in the ion trap, and to determine whether there are ions in the ion trap that exceed a set deviation; When there are missing ions, the ion filling related instruments and equipment are controlled to fill ions into the space region to which the missing ions belong. When there are ions exceeding the set deviation, the positions of the ions exceeding the set deviation are corrected through the ion cooling related instruments and equipment; The initial image is a two-dimensional grayscale image, and the initial image is processed to obtain the current state of the target ion, including: Performing median filtering on the initial image to obtain an image after median filtering; Binarize the median filtered image to obtain a binary image; Partition the bright spots in the binary image to obtain a plurality of bright areas, where the bright spots refer to pixels with a gray value of 255, and each target bright area corresponds to a target ion; Obtaining the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion; Determining whether there are missing ions in the ion trap includes: According to the position of the center point, each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and it is determined whether each target bright area and each standard target bright area in the standard state of all standard ions in the ion trap are paired one by one to obtain a pairing judgment result. When the pairing judgment result is yes, it is determined that there are no missing ions in the ion trap. If not, it is determined that there are missing ions in the ion trap.

2. The automatic maintenance method of an ion trap for quantum computing according to claim 1, characterized in that: Determining whether there are ions exceeding a set deviation in the ion trap includes: When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: the preset position deviation ratio threshold and the preset radius deviation ratio threshold.

3. An automatic maintenance system for an ion trap used for quantum computing, characterized in that: It includes an imaging module, an ion recognition module, a state comparison module and an automatic maintenance module; The imaging module is used to: image the ions in the ion trap used for quantum computing through an ion imaging device to obtain an initial image; The ion identification module is used to: process the initial image to obtain the current state of at least one target ion; The state comparison module is used to compare the current state of all target ions with the standard state of all standard ions in the ion trap, determine whether there are missing ions in the ion trap, and determine whether there are ions in the ion trap that exceed a set deviation; The automatic maintenance module is used to: when there are missing ions, control the ion filling related instruments and equipment to fill ions into the space area to which the missing ions belong; when there are ions exceeding the set deviation, correct the position of the ions exceeding the set deviation through ion cooling related instruments and equipment; The initial image is a two-dimensional grayscale image, and the ion recognition module is specifically used for: Performing median filtering on the initial image to obtain an image after median filtering; Binarize the median filtered image to obtain a binary image; Partition the bright spots in the binary image to obtain a plurality of bright areas, where the bright spots refer to pixels with a gray value of 255, and each target bright area corresponds to a target ion; Obtaining the radius and center point position of each target bright area, wherein the number of bright spots in each target bright area is within a preset pixel number range, and the radius of each target bright area is within a preset radius range, and the current state of any target ion includes: the radius and center point position of the target bright area corresponding to the target ion; The state comparison module is also specifically used for: According to the position of the center point, each target bright area is paired with each standard target bright area in the standard state of all standard ions in the ion trap, and it is determined whether each target bright area and each standard target bright area in the standard state of all standard ions in the ion trap are paired one by one to obtain a pairing judgment result. When the pairing judgment result is yes, it is determined that there are no missing ions in the ion trap. If not, it is determined that there are missing ions in the ion trap.

4. The automatic maintenance system of an ion trap for quantum computing according to claim 3, characterized in that: The state comparison module is also specifically used for: When the pairing judgment result is yes, calculate and judge whether the position deviation ratio and radius deviation ratio between any target bright area and the standard target bright area paired with the target bright area are both less than the corresponding preset thresholds. If so, judge that the ions corresponding to the target bright area do not exceed the set deviation. If so, judge that the ions corresponding to the target bright area exceed the set deviation. The preset threshold corresponding to the position deviation ratio is the preset position deviation ratio threshold, and the preset threshold corresponding to the radius deviation ratio is the preset radius deviation ratio threshold. The set deviation includes: the preset position deviation ratio threshold and the preset radius deviation ratio threshold.

5. A computer device, characterized in that: The computer device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the computer device implements an automatic maintenance method for an ion trap for quantum computing as described in any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements an automatic maintenance method for an ion trap for quantum computing as claimed in any one of claims 1 to 2.

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