Multi-harmonic quantum voltage synthesis device based on optimal phase plane

Abstract

The invention discloses a multi-harmonic quantum voltage synthesis device based on an optimal phase plane, which comprises a signal generation module, a delta-sigma modulator, a pulse code pattern driving module and a Josephson junction array, and is characterized in that the signal generation module is sequentially connected with the delta-sigma modulator, the pulse code pattern driving module and the Josephson junction array; according to the invention, through phase plane optimization, signals are more uniformly distributed in a phase plane, and excellent performance in the aspects of test efficiency and coverage rate is shown; the multi-harmonic design based on R can maximize the ADC test coverage rate and better describe analog-to-digital conversion error distribution, and the optimized signal generates a predetermined multi-harmonic quantum voltage signal through an ACJVS system; the ACJVS is a very ideal waveform generator, the problems of high distortion and high background noise of a conventional synthesis mode do not exist, quantum accuracy of synthesized voltage signals can be guaranteed, and therefore ADC testing and work in other measurement fields can be better carried out.

Description

Technical Field

[0001] The invention relates to a multi-harmonic quantum voltage synthesis device based on an optimal phase plane. Background Art

[0002] An analog-to-digital converter (ADC) is an electronic device that converts analog signals into digital signals. In ADC testing, a known analog signal is applied to the input of the ADC, and then its digital output is measured. By comparing the difference between the input signal and the output signal, it can be determined whether the performance and accuracy of the ADC meet the requirements. Traditional ADC testing usually uses a single sine wave or multiple sine signals for testing. Although the single sine wave test method is simple and effective, it cannot truly reflect the various signal conditions encountered by the ADC in actual applications, and cannot simulate the combination of different amplitudes and change rates of multiple signals; and the test efficiency is low: only a single frequency is used for testing, and the frequency response of the ADC cannot be fully characterized. Especially in large-scale production, this method is time-consuming and cannot find defects in production. In addition, in the currently used multiple sine signal ADC test, the frequency components of the multiple sine signals are not optimized, and the phase selection method is generally random or simply distributed, resulting in the signal being concentrated in certain areas on the phase plane, resulting in the phenomenon of local over-dense spectrum, affecting the test signal quality and system performance; due to the uneven selection of frequency components, the signal spectrum is not fully covered, and the dynamic performance and frequency response cannot be fully tested. Some frequency areas will be omitted, resulting in incomplete testing. Summary of the invention

[0003] The object of the present invention is to provide a multi-harmonic quantum voltage synthesis device based on an optimal phase plane, which generates a multi-harmonic quantum voltage signal with low distortion, low noise, quantum accuracy, high flexibility and long-term stability for ADC testing through the combination of optimal phase plane design and a pulse-driven quantum voltage system (ACJVS).

[0004] In order to achieve the above object, the scheme of the present invention is:

[0005] A multi-harmonic quantum voltage synthesis device based on an optimal phase plane comprises a signal generation module, a delta-sigma modulator, a pulse code pattern driving module and a Josephson array, wherein the signal generator is sequentially connected to the delta-sigma modulator, the pulse code pattern driving module and the Josephson array, wherein: the signal generation module is used to generate a multi-harmonic initial signal, and performs optimal phase plane processing on the multi-harmonic initial signal to form an optimized multi-harmonic signal, the signal generation module inputs the optimized multi-harmonic signal into the delta-sigma modulator, the delta-sigma modulator modulates the optimized multi-harmonic signal to form a multi-harmonic digital signal, the delta-sigma modulator inputs the multi-harmonic digital signal into the pulse code pattern driving module, the pulse code pattern driving module processes the received multi-harmonic digital signal to generate a current pulse of a corresponding waveform, the pulse code pattern driving module outputs a current pulse driving signal to the Josephson array, and the Josephson array outputs a multi-harmonic quantum voltage signal according to the current pulse driving signal.

[0006] The solution further comprises: an ADC test module is connected to the output end of the Josephson array, and the multi-harmonic signal is a multi-harmonic signal represented by a waveform expression, and the waveform expression is:

[0007]

[0008] in:

[0009] Parameter vector A h and are the amplitude and phase of the hth sinusoidal component, N is the number of multi-harmonic components, T is the total data acquisition time, t is the data acquisition time, f is the frequency, and f h is the hth component frequency;

[0010] The optimal phase plane processing is to uniformly distribute the phase plane waveform point set of the multi-harmonic signal in a set limited area. The processing process of uniformly distributing the phase plane waveform point set of the multi-harmonic signal is:

[0011] Step 1: Determine the waveform expression parameter vector Projecting the multiharmonic signal with a determined parameter vector onto the plane coordinates of a limited area and forming a phase plane point set image by selecting a number of points for imaging;

[0012] The second step is to calculate the point set uniformity quality R value of the phase plane point set image by the R value calculation formula, and determine an optimal point set uniformity quality R best value;

[0013] Step 3: Compare R value and R best Comparison of values:

[0014] If the R value is less than R best value, execute step 4;

[0015] If the R value is greater than or equal to R best value, the current R value replaces R best value, becoming the new R best value, execute step 4;

[0016] Step 4: Use the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal generating a new multiharmonic signal using the adjusted parameter vector;

[0017] Step 5: Determine whether the output multi-harmonic signal meets the preset requirements. If not, return to step 4. If yes, continue to step 6.

[0018] Step 6: Use the SQP algorithm to optimize the new multi-harmonic signal to generate a new multi-harmonic signal;

[0019] Step 7: Project the new multi-harmonic signal onto the plane coordinates to form a phase plane point set image;

[0020] Step 8, calculating the uniformity quality R value of the phase plane point set image point set in step 7 by using the R value calculation formula;

[0021] Step 9: Compare the R value calculated in step 8 with R best The values ​​are compared, where:

[0022] When the R value is less than R best value, return to step 4;

[0023] When the R value is greater than R best value, replace R with the current R value best The value becomes the new R best value, return to step 4 until the R value reaches convergence or reaches the set maximum number of iterations, and the optimal phase plane processing ends;

[0024] The R value calculation formula is:

[0025]

[0026] in:

[0027] R is the uniformity quality of the point set, which represents the average distance between each point and its m nearest neighboring points;

[0028] M represents the total number of image points in the phase plane point set;

[0029] m represents the number of nearest neighboring points of each point;

[0030] R ij =1-PE ij , expressed as a uniformity quality measure;

[0031] It is expressed as the uniformity of the distribution of the point set in the Euclidean space;

[0032] r ij represents the Euclidean distance between the i-th point and the j-th point;

[0033] α is represented as an arbitrary constant;

[0034] The total number M of the image points in the phase plane point set, the number m of the nearest neighboring points of each point, and the arbitrary constant α are predetermined before calculation.

[0035] The scheme is further as follows: the arbitrary constant α is given by the formula Sure.

[0036] The solution further includes: the preset requirement is: under the set ADC measurement constraint conditions, the output multi-harmonic quantum signal is used as an excitation signal to test whether the ADC has potential overshoot.

[0037] The solution is further as follows: the use of the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal is to jointly determine the next moving direction and speed of the particle through the inertia weight, self-cognition parameter and social cognition parameter in the PSO algorithm, thereby determining the optimal solution for each parameter vector.

[0038] The scheme further includes: the pulse pattern driving module includes a PPG series pulse pattern generator and a radio frequency microwave amplifier, the PPG series pulse pattern generator processes the received multi-harmonic digital signal to generate a current pulse output with a corresponding waveform, and the output current pulse is amplified by the radio frequency microwave amplifier to form a current pulse driving signal to the Josephson array;

[0039] The Josephson array is a 1V JAWS Josephson array chip of model SRI6011a, which contains 51240 Josephson junctions and can generate a quantum precision waveform of up to 1V and frequency components of a voltage waveform of 4Hz to 1MHz.

[0040] The scheme is further as follows: the Josephson array is connected to a low-frequency driving module and an IV waveform measuring module, the low-frequency driving module is connected to the adjustment port of the Josephson array, the IV waveform measuring module is connected to the voltage output port of the Josephson array, the IV waveform measuring module is used to measure the output signal of the Josephson array, and the low-frequency driving module adjusts the Josephson array according to the IV curve diagram of the observed output waveform, so that the output signal of the Josephson array is in a quantum state.

[0041] The solution is further that: the limited area is to normalize the multi-harmonic signal to a coordinate range of [-1, 1].

[0042] The beneficial effects of the present invention are as follows: the multi-harmonic designed by the present invention shows good performance in terms of convergence and efficiency through phase plane optimization; the multi-sine design based on R can maximize the ADC test coverage and better describe the analog-to-digital conversion error distribution; the advantages include:

[0043] 1. Improved the uniformity of waveform signal point distribution: ensure that the sampling points are more evenly distributed on the phase plane, improve the utilization of the spectrum, and avoid frequency overlap.

[0044] 2. Enhanced test coverage and effectiveness: The optimized signal ensures the extensiveness of multi-frequency components, enabling more comprehensive coverage of the test signal, and is more beneficial for ADC testing, and can better characterize the dynamic performance of the ADC.

[0045] 3. Improved signal robustness: By selecting different m values, it has better robustness to abnormal distribution values, which is suitable for complex test scenarios

[0046] The present invention utilizes the quantum effect generated by the Josephson array in the superconducting state and controls the synthesis of frequency signals through microwaves. The advantages include:

[0047] 1. Quantum accuracy: The present invention is based on the principle of the Josephson effect. The final voltage signal can be traced back to its source, thereby ensuring that the synthesized voltage signal can be fully predicted, thus avoiding the quantization error in traditional DAC devices.

[0048] 2. Low distortion: The signal synthesized by the present invention is basically close to the ideal signal, thereby avoiding the harmonic interference generated in traditional DAC devices.

[0049] 3. Low noise: Since the device generates voltage in a superconducting environment, the thermal noise and background noise of the present invention are extremely low, thereby ensuring the purity of the signal.

[0050] 4. High flexibility: The present invention can generate a variety of waveforms and supports the generation of complex waveforms.

[0051] 5. High long-term stability: The voltage generated by the present invention uses the physical properties of the superconducting Josephson junction, thereby avoiding the drift and distortion in traditional oscillators.

[0052] The present invention is described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a schematic diagram of the structure of the present invention;

[0054] Figure 2It is the optimal phase plane processing flow chart of the present invention;

[0055] Figure 3 1 is the image before optimization and the schematic diagram of R value of the present invention;

[0056] Figure 4 It is a schematic diagram of the optimized image and R value of the present invention. DETAILED DESCRIPTION

[0057] A multi-harmonic quantum voltage synthesis device based on an optimal phase plane, such as Figure 1 As shown, the device includes a signal generating module 1, a Δ-Σ modulator 2, a pulse pattern driving module 3 and a Josephson array 4. The signal generating module 1 is sequentially connected to the Δ-Σ modulator 2, the pulse pattern driving module 4 and the Josephson array 4. The pulse pattern driving module 3 and the Josephson array 4 constitute a pulse driven quantum voltage system (ACJVS).

[0058] The signal generating module 1 is used to generate a multi-harmonic initial signal, and perform optimal phase plane processing on the multi-harmonic initial signal to form an optimized multi-harmonic signal; the signal generating module 1 includes a signal generator 101 and a signal processing module 102, the signal generator 101 outputs the multi-harmonic initial signal, the signal processing module 102 performs optimal phase plane processing on the multi-harmonic initial signal to form an optimized multi-harmonic signal, and the work of the signal generator 101 and the signal processing module 102 can be completed by a computer; the optimized multi-harmonic signal is input into a Δ-Σ modulator 2, and the Δ-Σ modulator 2 modulates the input optimized multi-harmonic signal to form a multi-harmonic digital signal; the Δ-Σ modulator 2 It can be an independent device, or it can be used as a module in the computer to complete its work by calling the Δ-Σ modulator toolbox in matlab. The Δ-Σ modulator 2 inputs the multi-harmonic digital signal into the pulse code driving module 3. The pulse code driving module 3 processes the received multi-harmonic digital signal to generate a current pulse corresponding to the digital signal waveform. The pulse code driving module 3 outputs a current pulse driving signal to the Josephson junction array 4. The Josephson junction array 4 outputs a multi-harmonic quantum voltage signal according to the current pulse driving signal. A terminal resistor 5 is arranged at the output end of the Josephson junction array. The terminal resistor 5 is used to match the impedance of the microwave, and a resistor of about 22.4Ω is selected.

[0059] Wherein: the pulse pattern driving module 3 includes a PPG series pulse pattern generator 301 and a radio frequency microwave amplifier 302. In this embodiment, the PPG series pulse pattern generator 301 adopts an ABG2 pulse pattern generator made in the United States, which is used to process the multi-harmonic digital signal received from the Δ-Σ modulator to generate a current pulse output with a waveform corresponding to the digital signal. The high-speed current pulse output by the PPG series pulse pattern generator is amplified by the radio frequency microwave amplifier 302 to form a microwave current pulse driving signal and sent to the Josephson array 4.

[0060] The Josephson junction array 4 described in this embodiment adopts the 1VJAWS Josephson junction array chip of model SRI6011a from the US NIST. The chip contains 51240 Josephson junctions, which can generate a quantum voltage precision waveform of up to 1Vrms, a minimum current range of 1.0mA, and a frequency component capable of generating a voltage waveform of 4Hz to 1MHz; the Josephson junction array works in a 4.2k environment, and the pulse code driving module 3 and the Josephson junction array 4 constitute a pulse-driven quantum voltage system (ACJVS).

[0061] The device is also provided with an ADC test module 6, an IV waveform measurement module 7 and a rubidium atomic clock 8. The ADC test module 6 and the IV waveform measurement module 7 are connected to the output end of the Josephson junction array. The IV waveform measurement module 7 is used to measure the output signal of the Josephson junction array. The ADC test module 6 includes an ADC signal collector and a logic analyzer of model PXI-5922. The IV waveform measurement module 7 is an analog oscilloscope of model Tektronix 7603. The rubidium atomic clock 8 provides a high-precision and accurate clock for the pulse code generator 3 and the PXI-5922 logic analyzer in the ADC test module 6. The IV waveform image can be directly viewed through the Tektronix 7603 analog oscilloscope of the IV waveform measurement module 7, and the IV characteristics of the Josephson junction array can be observed. The quantum voltage output collected by the PXI-5922 logic analyzer of the ADC test module 6 can directly observe the time domain and frequency domain images of the output voltage waveform, analyze and evaluate the quantum voltage output signal, and thus test the effect on the ADC.

[0062] In the embodiment: the output end of the Josephson array is connected to an ADC test module, the purpose of which is to use the ADC collector to collect the output multi-harmonic quantum signal to test the performance of the ADC under test, and evaluate the quantum voltage signal through the PXI-5922 logic analyzer; the multi-harmonic signal is a multi-harmonic signal represented by a waveform expression, and the waveform expression is:

[0063]

[0064] in:

[0065] Parameter vector A h and are the amplitude and phase of the hth sinusoidal component, N is the number of multi-harmonic components, T is the total data acquisition time, t is the data acquisition time, f is the frequency, and f h is the hth component frequency (the frequency is set to f s is the sampling frequency, K is the number of samples, f h is an integer multiple of f0);

[0066] like Figure 2 As shown, the optimal phase plane processing is to uniformly distribute the phase plane waveform point set of the multi-harmonic signal in a set limited area, and the processing process of uniformly distributing the phase plane waveform point set of the multi-harmonic signal is:

[0067] Step 1: Determine the waveform expression parameter vector Projecting the multiharmonic signal with a determined parameter vector onto the plane coordinates of a limited area and forming a phase plane point set image by selecting a number of points for imaging;

[0068] The second step is to calculate the point set uniformity quality R value of the phase plane point set image by the R value calculation formula, and determine an optimal point set uniformity quality R best value;

[0069] Step 3: Compare R value and R best Comparison of values:

[0070] If the R value is less than R best value, execute step 4;

[0071] If the R value is greater than or equal to R best value, the current R value replaces R best value, becoming the new R best value, execute step 4;

[0072] Step 4: Use the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal Generate a new multiharmonic signal using the adjusted parameter vector; (that is, use the PSO algorithm to continuously update the position of the particles, thereby changing the parameter vector To find the global optimal solution, a new multi-harmonic signal is generated with the adjusted parameter vector);

[0073] Step 5: Determine whether the output multi-harmonic signal meets the preset requirements. If not, return to step 4. If yes, continue to step 6.

[0074] Step 6: Use the SQP algorithm to optimize the new multi-harmonic signal to generate a new multi-harmonic signal;

[0075] Step 7: Project the new multi-harmonic signal onto the plane coordinates to form a phase plane point set image;

[0076] Step 8, calculating the uniformity quality R value of the phase plane point set image point set in step 7 by using the R value calculation formula;

[0077] Step 9: Compare the R value calculated in step 8 with R best The values ​​are compared, where:

[0078] When the R value is less than R best value, return to step 4,

[0079] When the R value is greater than R best value, replace R with the current R value best The value becomes the new R best value, return to step 4 until the R value reaches convergence or reaches the set maximum (return) iteration number, and the optimal phase plane processing ends;

[0080] The R value calculation formula is:

[0081]

[0082] in:

[0083] R is the uniformity quality of the point set, which represents the average distance between each point and its m nearest neighboring points;

[0084] M represents the total number of image points in the phase plane point set;

[0085] m represents the number of nearest neighboring points of each point;

[0086] R ij =1-PE ij , expressed as a uniformity quality measure;

[0087] It is expressed as the uniformity of the distribution of the point set in the Euclidean space;

[0088] r ij represents the Euclidean distance between the i-th point and the j-th point;

[0089] α is an arbitrary constant. In order to make R reach the best sensitivity, the formula Determine, thus preventing numerical singularities;

[0090] The total number M of the image points in the phase plane point set, the number m of the nearest neighboring points of each point, and the arbitrary constant α are predetermined before calculation.

[0091] Wherein: the determined waveform expression parameter vector is the initial parameter vector data: where A h Initially, it is divided equally into 1 / N (N is the number of single sine waves that make up the multi-harmonic signal). Initially, the "Schroeder phase" is initialized. The Schroeder phase initialization formula is: θ p refers to the pth component of the Schroeder phase, i.e., θ p and The purpose of Schroeder phase initialization is to provide an initial value for the phase component of a multi-sinusoidal signal, thereby improving the uniformity of the signal in the phase space. "Schroeder phase" is used in signal processing and multi-harmonic signals to describe a design method that minimizes the signal peak through a specific phase configuration. This phase design is widely used in signal testing, acoustics, communications and other fields to improve the phase uniformity and energy distribution of the signal.

[0092] The PSO algorithm and the SQP algorithm are well-known technologies, and the two are combined in this embodiment. Among them: the PSO algorithm (particle swarm optimization algorithm) finds potential solutions by continuously updating the amplitude and phase of the vector. Although the PSO algorithm can effectively avoid falling into the local optimum, its local tuning ability is weak and the convergence speed is relatively slow. The PSO algorithm plays a role of global search in the optimal phase plane, which is used to escape the local minimum. After the PSO algorithm finds the optimal solution, the SQP (sequential quadratic rule) algorithm is used to locally refine the solution. SQP is an optimization algorithm based on Newton's method with a faster convergence speed; therefore, SQP is used to refine the optimal solution found by the PSO algorithm, thereby quickly approaching the global optimal solution.

[0093] Through this hybrid optimization, the amplitude and phase of the signal are optimized, making the point distribution on the phase plane more uniform, thereby maximizing the phase plane coverage of the multi-harmonic signal. This uniform coverage helps to better characterize the nonlinear distortion behavior of the ADC, provide a more accurate conversion error distribution, and ultimately improve the accuracy and coverage of ADC performance testing.

[0094] In order to improve the signal spectrum coverage, this embodiment performs optimal phase plane processing on the generated multi-harmonic signal and introduces R value evaluation. As mentioned above, the multi-harmonic signal is first projected to the plane coordinates and imaged by selecting the number of points M to form a phase plane point set image. Then, the R value is evaluated to form a multi-harmonic signal with optimal signal spectrum coverage, and then a pulse-driven quantum voltage system is used to generate a multi-frequency quantum voltage signal with low distortion, low noise and quantum accuracy.

[0095] In the calculation of the R value, the total number of image points M of the phase plane point set, the number of nearest neighboring points of each point m and the arbitrary constant α: a smaller m makes R more sensitive to changes in the nearest point; a larger m can improve the robustness of the algorithm to outliers, and is therefore more suitable for measuring the overall uniformity of the point set. By properly selecting the parameters m and α, the R value can more accurately reflect the uniformity of the point distribution. The value range of R is [0,1]. The larger the R value, the more uniform the distribution. The arbitrary constant α is given by the formula OK, the purpose of choosing an arbitrary constant is to prevent r ij =0 when the numerical singularity problem.

[0096] Figure 3 and Figure 4 M is 256 points, m is 4, and the maximum amplitude is V max 1V, minimum amplitude V min The maximum slew rate is ±1.5V·s. -1 , the point set distribution diagram after 100 iterations, where Figure 3 It is the point set distribution image and R value before optimization. Figure 4 It is the point set distribution image and R value after optimization; from the comparison of the two point set distribution images, it can be seen that the multi-harmonic signal optimized by the algorithm has a larger R value and better phase plane coverage, which can prove the superiority of the algorithm.

[0097] Wherein: the limited area is to normalize the multi-harmonic signal to the coordinate range of [-1, 1], which is the area within which the upper vertex and the lower vertex of the multi-harmonic signal waveform are allowed to extend outward to the maximum extent. Figure 3 and Figure 4 As shown, the limited area is within the horizontal axis -1.0 to 1.0, the purpose of which is to better compare the phase plane coverage before and after the optimization of the observation algorithm.

[0098] The preset requirement is that under the set ADC measurement constraint conditions (which can be found in the ADC measurement manual), the output multi-harmonic quantum voltage signal is used as the excitation signal to test whether the ADC has potential overshoot. The potential overshoot refers to: by changing the parameter vector The adjustment amount of the output multi-harmonic quantum voltage signal range is adjusted to have the adjustment capability beyond the standard output, thereby avoiding the test ADC input exceeding its allowed range, thereby preventing nonlinear distortion and the like from occurring.

[0099] in:

[0100] The use of the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal is to jointly determine the next moving direction and speed of the particle through the inertia weight, self-cognition parameter and social cognition parameter in the PSO algorithm, thereby determining the optimal solution for each parameter vector.

[0101] In this embodiment, the image points of the phase plane point set are regarded as particles, and the adjustment of the image points of the phase plane point set is regarded as the adjustment of the particles; the particle velocity calculation formula and the particle position calculation formula of the PSO algorithm are used to update the adjustment parameter vector;

[0102] The particle velocity calculation formula is:

[0103] v i (t+1)=w*v i (t)+c1*r1*(p besti -x i (t))+c2*r2*(g besti -x i (t))

[0104] in:

[0105] v i (t+1): is the updated velocity of particle i;

[0106] v i (t): is the velocity of particle i before the update;

[0107] x i (t): is the position of particle i before updating;

[0108] p besti : is the current individual best position of particle i;

[0109] g besti : is the current global optimal position of particle i;

[0110] c1 and c2: are random factors;

[0111] (r1): is the self-perception parameter;

[0112] (r2): is the social cognitive parameter

[0113] (w): is the inertia weight;

[0114] The particle position calculation formula is:

[0115] x i (t+1)=x i (t)+v i (t+1)

[0116] x i(t+1): is the updated position of particle i,

[0117] In the PSO algorithm, the initial position of the particle is first set based on the parameters initialized by Schroeder. Then, the latest particle position and speed are continuously adjusted based on the feedback of the objective function (R value). In addition, the particle position update process includes constraint checks, such as checking whether the amplitude of the signal exceeds the preset maximum value (Vmax and Vmin), and the slew rate (SLmax) of the signal.

[0118] The PSO algorithm parameter design:

[0119] Initial value setting: The initial velocity of the particle is set to any value between (Vmax and Vmin), and the initial position of the particle is set to the position after Schroeder initialization.

[0120] Particle number: The number of particles in the particle swarm. The purpose is that the number of particles determines the coverage of the search space. Too few particles will lead to insufficient retrieval, and too many particles will lead to too long retrieval time. Generally, it is selected between 30-100.

[0121] Inertia weight (w): Indicates the ability of a particle to maintain its current state of motion. It controls the degree of influence of the particle's current speed on the next step. The closer it is to 1, the larger the search space is. It is suitable for global search. The value is generally selected between 0.4-0.9.

[0122] Self-cognition parameter (r1) and social cognition parameter (r2): A larger self-cognition parameter value will enhance the local search ability, and a larger social cognition parameter will enhance the global search ability. Generally, the self-cognition parameter is selected between 1.5-2.0, and the social cognition parameter is selected between 2.0-2.5.

[0123] Random factors (c1, c2): Two random numbers in the range of (0, 1) that increase the randomness of the algorithm. The purpose is to weight the movement of particles to the individual optimal position and the global optimal position. Through randomness, the PSO algorithm can jump out of the local optimal solution and prevent premature convergence.

[0124] The Josephson array is also connected to a low-frequency driving module 9, which is connected to the adjustment port of the Josephson array. The low-frequency driving module adjusts the Josephson array according to the IV curve of the observed output waveform so that the output signal of the Josephson array is in a quantum state.

[0125] Specifically, the low-frequency driving module 9 is an IV scanning current source (a known technology), which generally includes a triangle wave generator and a current driving module. By observing the IV characteristic curve of the Josephson junction array 4, if a deviation occurs, the triangle wave generator and the current driving module are adjusted according to the deviation to adjust the Josephson junction array, so that the output signal of the Josephson junction array is in a quantum state.

[0126] The multi-harmonic quantum voltage synthesis device based on the optimal phase plane of the above embodiment can be used to test ADC. Through the optimized multi-harmonic signal, it shows good performance in terms of coverage and efficiency. And the multi-harmonic signal designed based on the R value can better improve the test coverage of the ADC test and better describe the potential conversion error. The optimized signal generates a predetermined multi-harmonic quantum voltage signal through the ACJVS system. ACJVS is a very ideal waveform generator. There is no high distortion and high background noise problem of the conventional synthesis method, and the quantum accuracy of the synthesized signal can be guaranteed. The multi-frequency signal synthesized by it combines a series of advantages such as low distortion, low noise, quantum accuracy and strong flexibility. It is the best choice for precision electromagnetic measurement. Compared with the traditional multi-frequency signal synthesis method, it has many advantages such as low distortion, low noise, quantum accuracy, high flexibility, long-term stability, etc., so that it can better test ADC and test work in other measurement fields.

Claims

1. A multi-harmonic quantum voltage synthesis device based on an optimal phase plane, comprising a signal generation module, a delta-sigma modulator, a pulse code driving module and a Josephson array, characterized in that: The signal generating module is sequentially connected to a Δ-Σ modulator, a pulse code driving module and a Josephson array, wherein: the signal generating module is used to generate a multi-harmonic initial signal, and performs optimal phase plane processing on the multi-harmonic initial signal to form an optimized multi-harmonic signal; the signal generating module inputs the optimized multi-harmonic signal into the Δ-Σ modulator, the Δ-Σ modulator modulates the optimized multi-harmonic signal to form a multi-harmonic digital signal, the Δ-Σ modulator inputs the multi-harmonic digital signal into the pulse code driving module, the pulse code driving module processes the received multi-harmonic digital signal to generate a current pulse of a corresponding waveform, the pulse code driving module outputs a current pulse driving signal to the Josephson array, and the Josephson array outputs a multi-harmonic quantum voltage signal according to the current pulse driving signal.

2. The device according to claim 1, characterized in that An ADC test module is connected to the output end of the Josephson array, and the multi-harmonic signal is a multi-harmonic signal represented by a waveform expression, and the waveform expression is: in: Parameter vector A h and are the amplitude and phase of the hth sinusoidal component, N is the number of multi-harmonic components, T is the total data acquisition time, t is the data acquisition time, f is the frequency, and f h is the hth component frequency; The optimal phase plane processing is to uniformly distribute the phase plane waveform point set of the multi-harmonic signal in a set limited area. The processing process of uniformly distributing the phase plane waveform point set of the multi-harmonic signal is: The first step is to determine the waveform expression parameter vector A h and Projecting the multiharmonic signal with a determined parameter vector onto the plane coordinates of a limited area and forming a phase plane point set image by selecting a number of points for imaging; The second step is to calculate the point set uniformity quality R value of the phase plane point set image by the R value calculation formula, and determine an optimal point set uniformity quality R best value; Step 3: Compare R value and R best Comparison of values: If the R value is less than R best value, execute step 4; If the R value is greater than or equal to R best value, the current R value replaces R best The value becomes the new R best value, execute step 4; Step 4: Use the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal, and use the adjusted parameter vector to generate a new multi-harmonic signal; Step 5: Determine whether the output multi-harmonic signal meets the preset requirements. If not, return to step 4. If yes, continue to step 6. Step 6: Use the SQP algorithm to optimize the new multi-harmonic signal to generate a new multi-harmonic signal; Step 7: Project the new multi-harmonic signal onto the plane coordinates to form a phase plane point set image; Step 8, calculating the uniformity quality R value of the phase plane point set image point set in step 7 by using the R value calculation formula; Step 9: Compare the R value calculated in step 8 with R best The values ​​are compared, where: When the R value is less than R best value, return to step 4; When the R value is greater than R best value, replace R with the current R value best The value becomes the new R best value, return to step 4 until the R value reaches convergence or reaches the set maximum number of iterations, and the optimal phase plane processing ends; The R value calculation formula is: in: R is the uniformity quality of the point set, which represents the average distance between each point and its m nearest neighboring points; M represents the total number of image points in the phase plane point set; m represents the number of nearest neighboring points of each point; R ij =1-PE ij , expressed as a uniformity quality measure; It is expressed as the uniformity of the distribution of the point set in the Euclidean space; r ij represents the Euclidean distance between the i-th point and the j-th point; α is represented as an arbitrary constant; The total number M of the image points in the phase plane point set, the number m of the nearest neighboring points of each point, and the arbitrary constant α are predetermined before calculation.

3. The device according to claim 2, characterized in that The arbitrary constant α is given by the formula Sure.

4. The device according to claim 2, characterized in that The preset requirement is that under the set ADC measurement constraint conditions, the output multi-harmonic quantum signal is used as an excitation signal to test whether the ADC has potential overshoot.

5. The device according to claim 2, characterized in that The use of the PSO algorithm to update and adjust the parameter vector of the multi-harmonic signal is to jointly determine the next moving direction and speed of the particle through the inertia weight, self-cognition parameter and social cognition parameter in the PSO algorithm, thereby determining the optimal solution for each parameter vector.

6. The method according to claim 1, characterized in that The pulse pattern driving module includes a PPG series pulse pattern generator and a radio frequency microwave amplifier. The PPG series pulse pattern generator processes the received multi-harmonic digital signal to generate a current pulse output with a corresponding waveform. The output current pulse is amplified by the radio frequency microwave amplifier to form a current pulse driving signal to the Josephson array. The Josephson array is a 1V JAWS Josephson array chip of model SRI6011a, which contains 51240 Josephson junctions and can generate a quantum precision waveform of up to 1V and frequency components of a voltage waveform of 4Hz to 1MHz.

7. The method according to claim 1 or 6, characterized in that: The Josephson array is connected to a low-frequency driving module and an IV waveform measuring module. The low-frequency driving module is connected to the adjustment port of the Josephson array, and the IV waveform measuring module is connected to the voltage output port of the Josephson array. The IV waveform measuring module is used to measure the output signal of the Josephson array. The low-frequency driving module adjusts the Josephson array according to the IV curve diagram of the observed output waveform, so that the output signal of the Josephson array is in a quantum state.

8. The method according to claim 1, characterized in that: The limited area is a coordinate range of [-1, 1] where the multi-harmonic signal is normalized.

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