Method, device and equipment for detecting influence of single event effect on quantum chip

Abstract

The invention relates to a method, a device and equipment for detecting the influence of a single event effect on a quantum chip. The method comprises the following steps: acquiring a preset bombardment parameter of a to-be-measured sub-chip by a Acquiring a first chip reference parameter when the to-be-measured sub-chip is not subjected to single particle bombardment; according to the preset bombardment parameter, the first chip reference parameter and a pre-constructed quantum state evolution model, determining a first quantum state parameter after the to-be-measured sub-chip is subjected to single-particle bombardment; and according to the first chip reference parameter and the first quantum state parameter, determining the influence degree of the single event effect on the to-be-measured sub-chip. By adopting the method, the influence of the single event effect on the quantum chip can be detected, and the detection accuracy can be improved.

Description

Technical Field

[0001] This application relates to the field of quantum computing technology, and in particular to a method, apparatus, and device for detecting the effects of single-event effects on quantum chips. Background Technology

[0002] As the hardware carrier of quantum computers, the performance and reliability of quantum chips directly determine the computing power of the entire system. Quantum chips are extremely sensitive to their operating environment, especially to high-energy particles in the space radiation environment. When high-energy charged particles (such as protons, heavy ions, and alpha particles) bombard the sensitive areas of a quantum chip, they generate a large number of electron-hole pairs through ionization, thus triggering single-event effects. In traditional semiconductor devices, single-event effects mainly manifest as single-event flips, single-event transients, and single-event latch-up. In quantum chips, these effects exhibit unique and more complex influences.

[0003] Currently, the assessment of the impact of single-event effects on quantum chips mostly draws on the testing methods of traditional semiconductor chips, such as irradiating them under ground-based simulated radiation sources (such as lasers and ion accelerators) and assessing them by statistically analyzing the error rate after a large number of operating cycles. However, there is a lack of systematic methods for assessing the impact on quantum chips, which leads to inaccurate assessments.

[0004] Therefore, it is crucial to develop an effective method for detecting the impact of single-event effects on quantum chips. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, and device for detecting the influence of single-event effects on quantum chips that can improve detection accuracy, in order to address the aforementioned technical problems.

[0006] In a first aspect, this application provides a method for detecting the influence of single-event effects on quantum chips, comprising:

[0007] Obtain the preset bombardment parameters of a single particle on the sub-chip to be measured;

[0008] Obtain the first chip reference parameters of the sub-chip under test when it is not subjected to single-particle bombardment;

[0009] Based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle are determined.

[0010] Based on the first chip reference parameters and the first quantum state parameters, determine the degree of influence of single-event effects on the sub-chip to be measured;

[0011] The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and the influencing parameters of the quantum chip, including the bombardment parameters and the chip reference parameters.

[0012] In one embodiment, the first chip reference parameters include a first initial coherence time; determining the first quantum state parameters of the sub-chip under test after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and a pre-constructed quantum state evolution model, includes: inputting the first initial coherence time and the preset bombardment parameters into a pre-constructed coherence time evolution model to obtain the first coherence time of the sub-chip under test after being bombarded by a single particle.

[0013] In one embodiment, determining the degree of influence of the single-event effect on the sub-chip under test based on the first chip reference parameters and the first quantum state parameters includes: calculating the coherence time decay after single-event bombardment based on the first initial coherence time and the first coherence time; and determining the degree of influence of the single-event effect on the coherence time of the sub-chip under test based on the coherence time decay.

[0014] In one embodiment, the first chip reference parameters include a first initial fidelity; determining the first quantum state parameters of the sub-chip under test after being bombarded by a single particle based on the preset bombardment parameters, the first chip reference parameters, and a pre-constructed quantum state evolution model includes: inputting the first initial fidelity and the preset bombardment parameters into a pre-constructed fidelity evolution model to obtain the first fidelity of the sub-chip under test after being bombarded by a single particle.

[0015] In one embodiment, the first chip reference parameters further include a first initial pulse amplitude; determining the degree of influence of single-event effect on the sub-chip under test based on the first chip reference parameters and the first quantum state parameters includes: calculating the electrical signal amplitude after single-event bombardment based on the first initial pulse amplitude, the first fidelity, and the first initial fidelity; calculating the electrical signal distortion degree based on the first initial pulse amplitude and the electrical signal amplitude; and determining the degree of influence of single-event effect on the electrical signal of the sub-chip under test based on the electrical signal distortion degree.

[0016] In one embodiment, the method further includes: acquiring a second chip reference parameter set, a second bombardment parameter set, and a second quantum state parameter set corresponding to the experimental quantum chip; using the second chip reference parameter set and the second bombardment parameter set as inputs, and performing parameter training on an initial quantum state evolution model based on the second quantum state parameter set to obtain preset model parameters, wherein the model parameters of the initial quantum state evolution model are initial values; replacing the initial values ​​of the model parameters of the initial quantum state evolution model with the preset model parameters to obtain a pre-constructed quantum state evolution model.

[0017] Secondly, this application also provides a device for detecting the effect of single-event effects on quantum chips, comprising:

[0018] The first acquisition module is used to acquire the preset bombardment parameters of a single particle on the sub-chip to be measured;

[0019] The second acquisition module is used to acquire the first chip reference parameters of the sub-chip to be measured when it is not bombarded by a single particle.

[0020] The first determining module is used to determine the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model.

[0021] The second determining module is used to determine the degree of influence of single-event effects on the sub-chip to be measured based on the first chip reference parameters and the first quantum state parameters.

[0022] The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and the influencing parameters of the quantum chip, including the bombardment parameters and the chip reference parameters.

[0023] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method for detecting the influence of single-event effects on quantum chips proposed in the first aspect of this application.

[0024] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for detecting the influence of single-event effects on quantum chips proposed in the first aspect of this application.

[0025] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method for detecting the influence of single-event effects on quantum chips proposed in the first aspect of this application.

[0026] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for detecting the impact of single-event effects on quantum chips acquire preset bombardment parameters of the quantum chip under test by a single particle; acquire first chip reference parameters of the quantum chip under test when it is not bombarded by a single particle; determine the first quantum state parameters of the quantum chip under test after being bombarded by a single particle based on the preset bombardment parameters, the first chip reference parameters, and a pre-constructed quantum state evolution model; and determine the degree of influence of the single-event effect on the quantum chip under test based on the first chip reference parameters and the first quantum state parameters. This application not only achieves the detection of the impact of single-event effects on quantum chips, overcoming the lack of detection methods specifically for quantum chips in traditional methods, but also determines the quantum state parameters of the quantum chip after being bombarded by a single particle based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, and determines the degree of influence of the single-event effect on the quantum chip based on the quantum state parameters and the chip reference parameters, focusing on the quantum state parameters under the single-event effect, thereby achieving the detection of the degree of influence and overcoming the limitation of traditional methods that only focus on logic state flips, providing comprehensive detection. Therefore, the embodiments of this application can effectively detect the impact of single-event effects on quantum chips, thereby improving detection accuracy. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is an application environment diagram of a method for detecting the impact of single-event effects on quantum chips in one embodiment;

[0029] Figure 2 This is a flowchart illustrating a method for detecting the impact of single-event effects on a quantum chip in one embodiment.

[0030] Figure 3 In one embodiment Figure 2 A flowchart illustrating step 203;

[0031] Figure 4 In one embodiment Figure 2 A flowchart illustrating step 204 in the middle section;

[0032] Figure 5 In another embodiment Figure 2 A flowchart illustrating step 203;

[0033] Figure 6In another embodiment Figure 2 A flowchart illustrating step 204 in the middle section;

[0034] Figure 7 This is a schematic diagram illustrating the process of constructing a quantum state evolution model in one embodiment;

[0035] Figure 8 This is a flowchart illustrating a specific example of a method for detecting the impact of single-event effects on a quantum chip.

[0036] Figure 9 This is a structural block diagram of a device for detecting the effect of single-event effects on a quantum chip in one embodiment;

[0037] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0039] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0040] Compared to traditional semiconductor devices, single-event effects exhibit unique and more complex influences in quantum chips:

[0041] Bit flip error: Similar to single event upsets (SEU) in classical computing, bombardment by high-energy particles can cause the state of a qubit to flip from 0 to 1, or vice versa;

[0042] Phase flip error: An error unique to qubits. High-energy particle bombardment may not change the probability amplitude of the bit state, but it will flip its relative phase.

[0043] Increased energy relaxation (relaxation time decay): Particle bombardment may disrupt the energy level structure of qubits, causing their excited state energy to relax to the ground state more quickly, i.e., significantly reducing the relaxation time T1;

[0044] Shortened coherence time (coherence time decay): Particle bombardment may introduce additional decoherence channels, destroy the quantum superposition state, and cause phase information to be lost rapidly, that is, significantly reduce the coherence time T2;

[0045] Control / readout circuit failure: Single event transient (SET) or SEU caused by bombarding the classical control circuits (such as DAC, ADC, amplifier) ​​around the quantum chip will manifest as glitches or distortions in the control signal, indirectly affecting the performance of the quantum bit, and even leading to erroneous readouts;

[0046] Permanent damage: High-energy heavy ions may cause lattice damage, leading to permanent drift or even complete failure of quantum bit parameters (such as frequency and coupling strength).

[0047] Currently, the assessment of the radiation resistance of quantum chips largely draws on testing methods used in traditional integrated circuits, such as irradiation under simulated ground-based radiation sources (e.g., lasers, ion accelerators) and evaluation by statistically analyzing the error rate after a large number of operating cycles. These methods have significant shortcomings: existing research mainly focuses on the effects of single-event effects (SEE) in traditional complementary metal-oxide-semiconductor (CMOS) circuits, but lacks a systematic approach to modeling and detecting the effects on quantum chips. This leads to incomplete detection (current technologies primarily focus on logic state transitions at the electrical signal level, only coarsely observing quantum state parameters without systematically collecting and analyzing them as core detection indicators, failing to capture subtle perturbations of the quantum state caused by single-event bombardment (such as local decoherence), resulting in incomplete detection), insufficient accuracy, and low efficiency. Therefore, proposing an effective single-event effect detection method is crucial for improving the reliability of quantum computing systems.

[0048] This application aims to provide a precise, efficient, and comprehensive method for detecting the impact of single-event effects on quantum chips. By constructing an integrated detection system, collecting quantum state parameters, and combining this with a quantum state evolution model, the precise detection of the impact of single-event effects can be achieved.

[0049] The method for detecting the impact of single-event effects on quantum chips provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0050] In one exemplary embodiment, such as Figure 2 As shown, a method for detecting the influence of single-event effects on quantum chips is provided, and this method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 201 to 204. Wherein:

[0051] Step 201: Obtain the preset bombardment parameters of the single particle to be measured sub-chip.

[0052] The bombardment parameters may include at least one of the following: single-particle type, flux, energy, and bombardment time. Preset bombardment parameters refer to known bombardment parameters used to detect the influence of single-particle effects on the target sub-chip. Single-particle types may include protons, neutrons, electrons, heavy ions, etc. Single-particle flux refers to the number of single particles bombarding the target sub-chip per unit time. The energy of a single particle can be adjusted by an accelerator or energy regulator. The bombardment time refers to the time interval between the incoming gas single-particle beam and the relative beam.

[0053] For example, when it is necessary to detect the effect of a single particle with known preset bombardment parameters on the sub-chip to be measured, the preset bombardment parameters are obtained. These preset bombardment parameters can be arbitrarily input or determined according to manually input detection requirements.

[0054] Step 202: Obtain the first chip reference parameters of the sub-chip to be measured when it is not bombarded by a single particle.

[0055] The first chip reference parameters refer to the initial quantum state parameters and initial electrical signal parameters of the sub-chip under test when it is not bombarded by a single particle. The first chip reference parameters include at least one of the first initial coherence time, the first initial fidelity, and the first initial pulse amplitude.

[0056] For example, the chip to be measured undergoes preprocessing, including chip cleaning, pin soldering, and initial calibration of performance parameters. Through actual measurements, the first initial coherence time, first initial fidelity, and / or first initial pulse amplitude of the chip under test when not subjected to single-particle bombardment are obtained as reference data for subsequent detection.

[0057] Step 203: Determine the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model.

[0058] The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and influence parameters of the quantum chip. Influence parameters include bombardment parameters and chip baseline parameters, while quantum state parameters are predicted values ​​of the quantum state parameters of the quantum chip after being bombarded by a single particle. The pre-constructed quantum state evolution model can accurately describe the influence of single-particle effects on the quantum chip. Optionally, the pre-constructed quantum state evolution model is at least one mathematical expression representing the mathematical relationship between the quantum state parameters and influence parameters. Based on this expression, the quantum state parameters corresponding to the influence parameters can be calculated. Optionally, the pre-constructed quantum state evolution model is a machine learning or deep learning model, with influence parameters as input and quantum state parameters as output. Influence parameters can be input into this model to obtain the corresponding quantum state parameters.

[0059] For example, the preset bombardment parameters and the first chip reference parameters are substituted into the pre-constructed quantum state evolution model for calculation to obtain the preset bombardment parameters and the first chip reference parameters. The corresponding quantum state parameters are referred to as the first quantum state parameters. The first quantum state parameters include: the first coherence time, or the first coherence time and the first fidelity.

[0060] Step 204: Determine the degree of influence of single-event effects on the sub-chip to be measured based on the first chip reference parameters and the first quantum state parameters.

[0061] For example, relevant calculations are performed on the first chip reference parameters and the first quantum state parameters. The change in the first quantum state parameters relative to the first chip reference parameters is calculated. The degree of influence of the single-event effect on the measured sub-chip is determined based on the change. Specifically, the degree of influence can be determined based on the relationship between the change and at least one preset change. For example, if the change is greater than the preset change, the degree of influence is determined to be large; if the change is less than or equal to the preset change, the degree of influence is determined to be small.

[0062] In the aforementioned method for detecting the impact of single-event effects on quantum chips, preset bombardment parameters of the single particle on the quantum chip under test are obtained; first chip reference parameters of the quantum chip under test when it is not bombarded by a single particle are obtained; based on the preset bombardment parameters, the first chip reference parameters, and a pre-constructed quantum state evolution model, the first quantum state parameters of the quantum chip under test after being bombarded by a single particle are determined; and the degree of influence of the single-event effect on the quantum chip under test is determined based on the first chip reference parameters and the first quantum state parameters. This application not only achieves the detection of the impact of single-event effects on quantum chips, overcoming the lack of a specific detection method for quantum chip effects in traditional methods, but also determines the quantum state parameters of the quantum chip after being bombarded by a single particle based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, and determines the degree of influence of the single-event effect on the quantum chip based on the quantum state parameters and the chip reference parameters, focusing on the quantum state parameters under the single-event effect, thereby achieving the detection of the degree of influence. This overcomes the limitation of traditional methods that only focus on logic state flips, providing comprehensive detection. Therefore, this application embodiment can effectively detect the impact of single-event effects on quantum chips and improve detection accuracy.

[0063] In an exemplary embodiment, where the pre-built quantum state evolution model includes at least a pre-built coherent time evolution model, and the first chip reference parameters include a first initial coherence time, such as... Figure 3 As shown, step 203 includes step 301. Wherein:

[0064] Step 301: Input the first initial coherence time and preset bombardment parameters into the pre-constructed coherence time evolution model to obtain the first coherence time of the sub-chip to be measured after being bombarded by a single particle.

[0065] The pre-built coherence time evolution model is used to characterize the relationship between coherence time and initial coherence time and bombardment parameters. The preset bombardment parameters include preset single-particle flux, energy, and bombardment time.

[0066] For example, the pre-constructed coherence time evolution model is a mathematical equation whose input parameters are the first initial coherence time and preset single-particle flux, energy, and bombardment time. The output parameter is the first coherence time of the sub-chip under test after being bombarded by a single particle. Therefore, by inputting the first initial coherence time, single-particle flux, energy, and bombardment time into this equation, the first coherence time can be obtained. Optionally, the equation is:

[0067] T2=T20 / (1+α×Φ×E×t+γ×(Φ×t) 2 ).

[0068] Where T2 is the first coherence time, T20 is the first initial coherence time, α and γ are preset model parameters, which can be known parameters obtained from historical experience, experimental testing, etc., α: material ionization-decoherence coefficient, γ: cumulative damage amplification factor, and Φ, E, and t are preset single-particle flux, energy, and bombardment time, respectively. By inputting T20, Φ, E, and t into the above equation, T2 can be calculated.

[0069] Therefore, in this embodiment, the first initial coherence time and preset bombardment parameters are input into a pre-constructed coherence time evolution model to obtain the first coherence time of the quantum chip under test after being bombarded by a single particle. This not only realizes the prediction of the coherence time of quantum state parameters under the single-particle effect, but also achieves this through the coherence time evolution model. This model can accurately characterize the influence law of the single-particle effect on the coherence time of the quantum chip, thus improving the accuracy of the predicted coherence time value, i.e., the first coherence time.

[0070] Furthermore, based on step 301, such as Figure 4 As shown, step 204 includes steps 401 and 402. Wherein:

[0071] Step 401: Calculate the coherence time decay after single-particle bombardment based on the first initial coherence time and the first coherence time.

[0072] For example, the ratio of the difference between the first coherence time and the first initial coherence time to the first initial coherence time is calculated to obtain the coherence time decay of the sub-chip under test after being bombarded by a single particle. Optionally, the coherence time decay is calculated using the following formula:

[0073] S1=(T20-T2) / T20×100%.

[0074] S1 is the coherence time decay rate, T2 is the first coherence time, and T20 is the first initial coherence time.

[0075] Step 402: Determine the degree of influence of single-event effect on the coherence time of the sub-chip under test based on the coherence time decay.

[0076] Specifically, this step includes: when the coherence time decay is less than or equal to a first preset decay, determining that the impact of single-event effect on the coherence time of the chip under test is slight; when the coherence time decay is greater than the first preset decay and less than a second preset decay, determining that the impact of single-event effect on the coherence time of the chip under test is moderate; and when the coherence time decay is greater than or equal to the second preset decay, determining that the impact of single-event effect on the coherence time of the chip under test is severe.

[0077] The first and second preset attenuation rates can be obtained based on historical experience and experimental tests. For example, the first and second preset attenuation rates can be 10% and 30%, respectively. That is, if S1 ≤ 10%, the impact is slight; if 10% < S1 < 30%, the impact is moderate; and if S1 ≥ 30%, the impact is severe. The greater the coherence time attenuation rate, the more severe the impact of single-event effects on the coherence time of the sub-chip to be measured.

[0078] Therefore, this example calculates the coherence time decay after a single-event bombardment based on the first initial coherence time and the first coherence time, and then determines the degree of influence of the single-event effect on the coherence time of the quantum chip under test based on the coherence time decay. This ability to determine the impact of the single-event effect on the quantum chip under test based on the coherence time solves the problem of insufficient comprehensiveness and accuracy caused by focusing only on logic state flips, thus improving the accuracy of detecting the impact of the single-event effect on quantum chips.

[0079] In another exemplary embodiment, where the pre-built quantum state evolution model includes at least a pre-built fidelity evolution model, and the first chip reference parameters include a first initial fidelity, such as Figure 5 As shown, step 203 includes step 501. Wherein:

[0080] Step 501: Input the first initial fidelity and preset bombardment parameters into the pre-constructed fidelity evolution model to obtain the first fidelity of the sub-chip to be measured after being bombarded by a single particle.

[0081] The pre-built fidelity evolution model is used to characterize the fidelity and its relationship with the initial fidelity and bombardment parameters. The preset bombardment parameters include preset single-particle flux, energy, and bombardment time.

[0082] For example, the pre-constructed fidelity evolution model is a mathematical equation whose input parameters are a first initial fidelity and preset single-particle flux, energy, and bombardment time. The output parameter is the first fidelity of the sub-chip under test after being bombarded by a single particle. Therefore, by inputting the first initial fidelity, single-particle flux, energy, and bombardment time into this equation, the first fidelity can be obtained. Optionally, the equation is:

[0083] F = F0 × exp(-β × Φ × E × t).

[0084] Where F represents the first fidelity, F0 represents the first initial fidelity, β represents the preset model parameters, which can be known parameters obtained from historical experience, experimental testing, etc., β: energy deposition-fidelity attenuation coefficient, and Φ, E, and t represent the preset single-particle flux, energy, and bombardment time, respectively. By inputting F0, Φ, E, and t into the above equation, F can be calculated.

[0085] Therefore, in this embodiment, the first initial fidelity and preset bombardment parameters are input into a pre-constructed fidelity evolution model to obtain the first fidelity of the quantum chip under test after being bombarded by a single particle. This not only realizes the prediction of the fidelity of quantum state parameters under the single-particle effect, but also achieves this through the fidelity evolution model. This model can accurately characterize the influence law of the single-particle effect on the fidelity of the quantum chip, thus improving the accuracy of the fidelity prediction value, i.e., the first fidelity.

[0086] Furthermore, based on step 501, the first chip reference parameters also include the first initial pulse amplitude, such as... Figure 6 As shown, step 204 includes steps 601 to 603. Wherein:

[0087] Step 601: Calculate the electrical signal amplitude after single-particle bombardment based on the first initial pulse amplitude, the first fidelity, and the first initial fidelity.

[0088] For example, based on the inherent linear correlation between quantum states and electrical signals (pulse amplitude and fidelity are positively correlated), the product of the first initial pulse amplitude and the first fidelity is calculated, and the ratio of this product to the first initial fidelity is calculated to obtain the electrical signal amplitude of the sub-chip under test after being bombarded by a single particle. The calculation formula is as follows:

[0089] V = V0 × F / F0.

[0090] Where V is the amplitude of the electrical signal, V0 is the amplitude of the first initial pulse, F is the first fidelity, and F0 is the first initial fidelity.

[0091] Step 602: Calculate the electrical signal distortion degree based on the first initial pulse amplitude and the electrical signal amplitude.

[0092] The calculation formula is:

[0093] ΔV=(V0-V) / V0×100%.

[0094] Where ΔV represents the electrical signal distortion degree.

[0095] Step 603: Determine the degree of influence of single-event effect on the electrical signal of the chip under test based on the electrical signal distortion.

[0096] Specifically, this step includes: when the electrical signal distortion is less than or equal to a first preset distortion, determining that the impact of single-event effect on the fidelity of the sub-chip under test is slight; when the electrical signal distortion is greater than the first preset distortion but less than a second preset distortion, determining that the impact of single-event effect on the fidelity of the sub-chip under test is moderate; and when the electrical signal distortion is greater than or equal to the second preset distortion, determining that the impact of single-event effect on the fidelity of the sub-chip under test is severe.

[0097] The first and second preset distortion degrees can be obtained based on historical experience and experimental tests. For example, the first and second preset distortion degrees can be 10% and 30%, respectively. That is, if ΔV ≤ 10%, the impact is slight; if 10% < ΔV < 30%, the impact is moderate; and if ΔV ≥ 30%, the impact is severe. The greater the electrical signal distortion, the more severe the impact of single-event effects on the fidelity of the chip under test.

[0098] It should be noted that, when the first quantum state parameters include the first coherence time and the first fidelity, the influence mechanism can be analyzed based on the α and β contribution ratios of the pre-constructed coherence time evolution model and fidelity evolution model. If α is dominant, it is charge deposition; if β is dominant, it is energy deposition.

[0099] After obtaining the extent of the impact of single-event effects on the target sub-chip, a preset standard can be matched to resist single-event effects.

[0100] Therefore, this example calculates the electrical signal distortion degree after single-event bombardment based on the first initial pulse amplitude, the first initial fidelity, and the first fidelity, and then determines the degree of influence of the single-event effect on the electrical signal of the quantum chip under test based on the electrical signal distortion degree. This method, which determines the impact of the single-event effect on the quantum chip under test based on fidelity, solves the problem that focusing solely on logic state flips leads to insufficient comprehensiveness and accuracy of the impact, thus improving the accuracy of detecting the influence of the single-event effect on the quantum chip.

[0101] The above describes the detection of influences (single-particle effects on quantum chips) based on a pre-built quantum state evolution model. The following describes the construction process of the quantum state evolution model.

[0102] In one exemplary embodiment, such as Figure 7 As shown, the method for detecting the impact of single-event effects on quantum chips further includes steps 701 to 703. Wherein:

[0103] Step 701: Obtain the second chip reference parameter set, the second bombardment parameter set, and the second quantum state parameter set corresponding to the experimental quantum chip.

[0104] The second chip reference parameters include a second initial coherence time and a second initial fidelity, and the second quantum state parameters include a second coherence time and a second fidelity.

[0105] Here, the experimental quantum chip refers to the quantum chip used to obtain a pre-constructed model of quantum state evolution. The second chip reference parameter set, the second bombardment parameter set, and the second quantum state parameter set refer to the chip reference parameter values, bombardment parameter set, and quantum state parameter set of the experimental quantum chip, respectively.

[0106] For example, the first step is to construct a detection system for the impact of single-event effects on a quantum chip. This system includes a single-event source module, a quantum chip testing fixture, environmental control equipment, a signal acquisition and analysis module, and a data preprocessing module, forming a software and hardware co-operating system. The single-event source module, quantum chip testing fixture, and environmental control equipment (such as a cryostat) constitute the hardware; the signal acquisition and analysis module and data preprocessing module constitute the software. Together, they achieve the detection function of the experimental quantum chip. Based on this detection system, the second chip reference parameter set, the second bombardment parameter set, and the second quantum state parameters of the experimental quantum chip are obtained through experiments.

[0107] The single-particle source module generates single particles of different types, energies, and fluxes, and can utilize sources such as radioactive isotopes or accelerator ion sources. The quantum chip testing fixture holds the experimental quantum chip and provides the bias voltage and control signals required for its normal operation. The signal acquisition and analysis module acquires the second quantum state parameters of the quantum chip under single-particle bombardment (such as the coherence time and fidelity of the qubits) and analyzes the acquired data. Environmental control equipment controls environmental parameters during the detection process, such as temperature, humidity, air pressure, and electromagnetic shielding, ensuring the stability of the detection environment. For example, temperature is controlled by a thermostat with a high-precision temperature control unit for high accuracy; humidity / air pressure is equipped with a dehumidifier (humidity ≤30%) and an air pressure stabilization system (maintaining standard atmospheric pressure), which monitors and dynamically adjusts in real time.

[0108] The specific operating steps during the experiment are as follows:

[0109] The first step involves preprocessing the experimental quantum chip, including cleaning the chip, soldering the pins, and initial calibration of performance parameters. Initial measurements are then taken to obtain the chip's baseline parameters (second initial coherence time and second initial fidelity) before single-particle bombardment, which serve as reference data for subsequent detection.

[0110] Step 2: According to the test requirements, set the second bombardment parameters of the single particle through the single particle source module, including the type of single particle (such as proton, neutron, electron, heavy ion, etc.), energy (which can be adjusted by the accelerator or energy regulator), flux (the number of single particles bombarding the quantum chip per unit time) and bombardment time (the time period from turning on the beam to turning off the beam).

[0111] Step 3: Under stable environmental parameters controlled by environmental control equipment, the single-particle source module is activated, causing a single particle to bombard the experimental quantum chip in the quantum chip test fixture according to the second bombardment parameters. Simultaneously, the signal acquisition and analysis module is activated to acquire the quantum state parameters of the experimental quantum chip in real time during the single-particle bombardment process, namely the second quantum state parameters (second coherence time and second fidelity), and record the corresponding bombardment parameters as the second bombardment parameters corresponding to the second quantum state parameters.

[0112] Specifically, a standard chip of the same type and process as the quantum chip to be measured was selected as the experimental quantum chip, and three sets of gradient bombardment experiments were designed: a fixed bombardment time of 1 hour, and different particle energies (e.g., 4 MeV, 5.5 MeV, 6 MeV) and fluxes (e.g., 50, 100, 150, in units of particles / cm²) were set. 2 By simultaneously collecting bombardment parameters (Φ, E, and t) and measured quantum state parameters (T2, F) data from each group, the second bombardment parameter set and the second quantum state parameter set can be obtained.

[0113] Through the above steps, the second chip reference parameter set, the second quantum state parameters, and the second bombardment parameter set of the experimental quantum chip are obtained.

[0114] Step 702: The second chip reference parameter set and the second bombardment parameter set are used as inputs, and the initial quantum state evolution model is conditioned based on the second quantum state parameter set to obtain the preset model parameters.

[0115] The initial quantum state evolution model uses initial values ​​α0, β0, and γ0 as its model parameters. For the second chip reference parameter set and the second bombardment parameter set, these sets are input into the initial quantum state evolution model, which outputs the calculated quantum state parameters. The model parameters are iteratively adjusted using simple linear regression to minimize the error between the calculated and measured values ​​(second quantum state parameters), thus obtaining the preset model parameters. Optionally, the initial values ​​can be general reference values ​​for similar materials, and the parameters are iteratively adjusted to ensure an error ≤3%.

[0116] For example, an initial quantum state evolution model (equation) is established. Based on the decoherence theory of open quantum systems, it focuses on the core physical mechanism of single-particle effect (decoherence caused by charge deposition and quantum state decay caused by energy deposition), abandons complex operator operations, and constructs a direct correlation model of "macroscopic bombardment parameters - core quantum state parameters", achieving accurate mapping through three key parameters.

[0117] That is, a direct evolution model of quantum state core parameters is adopted, and the most representative coherence time T2 and fidelity F are selected as core outputs. The initial model form is as follows:

[0118] Initial coherent time evolution model: T2 = T20 / (1 + α0 × Φ × E × t + γ0 × (Φ × t)) 2 );

[0119] Initial fidelity evolution model: F = F0 × exp(-β0 × Φ × E × t);

[0120] Where α0, β0, and γ0 are the initial values ​​of the model parameters.

[0121] The second initial coherent time set and the second bombardment parameter set (single particle flux, energy, bombardment time) are input into the initial coherent time evolution model to obtain the coherent time output by the model. With the goal of the error between the coherent time output by the model and the second coherent time in the second coherent time set being ≤3%, the model parameters α0 and γ0 of the initial coherent time evolution model are conditioned to obtain the preset model parameters α and γ.

[0122] The second initial fidelity set and the second bombardment parameter set (single particle flux, energy, bombardment time) are input into the initial fidelity evolution model to obtain the model output fidelity. With the goal of the error between the model output fidelity and the second fidelity in the second fidelity set being ≤3%, the model parameter β0 of the initial fidelity evolution model is conditioned to obtain the preset model parameter β.

[0123] To ensure the accuracy and reliability of the preset model parameters α, β, and γ, a single verification experiment can be conducted using a set of typical bombardment parameters (covering commonly used particle energies and fluxes). Measured T2 and F values ​​are collected and compared with the model predictions. If the error is ≤5%, a test report containing the predicted data, the degree of impact, the mechanism, and the capability level is output. If the error is >5%, the verification experiment data is added to the domestication sample, and the α, β, and γ parameters are fine-tuned (adjustment range ≤10% of the initial value) before re-predicting until the error meets the standard.

[0124] Step 703: Replace the initial values ​​of the model parameters of the initial quantum state evolution model with preset model parameters to obtain the pre-constructed quantum state evolution model.

[0125] Specifically, the pre-defined model parameters α and γ are fixed to form a pre-constructed coherent time evolution model. The pre-defined model parameter β is also fixed to form a pre-constructed fidelity evolution model.

[0126] Therefore, this example constructs a detection system to synchronously collect quantum state parameters and, combined with an initial quantum state evolution model, obtains a pre-constructed quantum state evolution model, ensuring the model's accuracy. Based on this, it achieves precise identification, mechanism analysis, and trend prediction of the impact of single-event effects. This provides a scientific basis for optimizing the design and improving the reliability of quantum chips to resist single-event effects, promotes the secure application of quantum chips in key fields such as aerospace and finance, and accelerates the industrialization of quantum computing technology.

[0127] The detection method of this application embodiment is described below with an example.

[0128] In a specific example, such as Figure 8 As shown, the method for detecting the impact of single-event effects on quantum chips includes the following steps:

[0129] Step 801: Obtain the preset flux, energy, and bombardment time of a single particle on the target sub-chip;

[0130] Step 802: Obtain the first initial coherence time, first initial fidelity, and first initial pulse amplitude of the sub-chip to be measured when it is not bombarded by a single particle;

[0131] Step 803: Obtain the first initial coherence time, first initial fidelity, and first initial pulse amplitude of the sub-chip to be measured when it is not bombarded by a single particle;

[0132] Step 804: Input the first initial coherence time and the preset flux, energy and bombardment time into the pre-constructed coherence time evolution model to obtain the first coherence time of the sub-chip to be measured after being bombarded by a single particle.

[0133] Step 805: Input the first initial fidelity and the preset flux, energy and bombardment time into the pre-constructed fidelity evolution model to obtain the first fidelity of the sub-chip to be measured after being bombarded by a single particle.

[0134] Step 806: Calculate the coherence time decay rate after single-particle bombardment based on the first initial coherence time and the first coherence time.

[0135] Step 807: Determine the degree of influence of single-event effect on the coherence time of the sub-chip under test based on the coherence time decay rate;

[0136] Step 808: Calculate the electrical signal amplitude after single-particle bombardment based on the first initial pulse amplitude, the first fidelity, and the first initial fidelity.

[0137] Step 809: Calculate the electrical signal distortion degree based on the first initial pulse amplitude and the electrical signal amplitude, and determine the degree of influence of single-event effect on the electrical signal of the sub-chip to be measured based on the electrical signal distortion degree.

[0138] The specific implementation methods for steps 801 to 809 above are described above and will not be repeated here to avoid redundancy.

[0139] In summary, the embodiments of this application, by constructing a quantum state evolution model to analyze data, can accurately identify abnormal states of quantum chips caused by single-event effects, precisely describe the impact of single-event effects on quantum chips, and focus on collecting quantum state parameters, thus comprehensively reflecting the impact of single-event effects on quantum chips. This overcomes the limitations of traditional methods that only focus on logic state flips. It can provide detailed detection data and evaluation results for the design of quantum chips to resist single-event effects, helping researchers to specifically improve the structure and process of quantum chips, enhance their reliability and lifespan, and has high practical value.

[0140] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0141] Based on the same inventive concept, this application also provides a device for detecting the influence of single-event effects on quantum chips, which is used to implement the method for detecting the influence of single-event effects on quantum chips described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the device for detecting the influence of single-event effects on quantum chips provided below can be found in the limitations of the method for detecting the influence of single-event effects on quantum chips described above, and will not be repeated here.

[0142] In one exemplary embodiment, such as Figure 9 As shown, a device for detecting the effect of single-event effects on a quantum chip is provided, comprising: a first acquisition module 901, a second acquisition module 902, a first determination module 903, and a second determination module 904, wherein:

[0143] The first acquisition module 901 is used to acquire the preset bombardment parameters of a single particle on the sub-chip to be measured.

[0144] The second acquisition module 902 is used to acquire the first chip reference parameters of the sub-chip to be measured when it is not bombarded by a single particle.

[0145] The first determining module 903 is used to determine the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model.

[0146] The second determining module 904 is used to determine the degree of influence of single-event effects on the sub-chip to be measured based on the first chip reference parameters and the first quantum state parameters.

[0147] The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and the influencing parameters of the quantum chip, including the bombardment parameters and the chip reference parameters.

[0148] In one embodiment, the first chip reference parameters include a first initial coherence time; the first determining module 903 includes: a first input unit, used to input the first initial coherence time and the preset bombardment parameters into a pre-constructed coherence time evolution model to obtain the first coherence time of the sub-chip to be measured after being bombarded by a single particle.

[0149] Furthermore, the second determining module 904 includes a first calculation unit and a second determining unit, wherein:

[0150] The first calculation unit is used to calculate the coherence time decay rate after single-particle bombardment based on the first initial coherence time and the first coherence time.

[0151] The first determining unit is used to determine the degree of influence of the single-event effect on the coherence time of the sub-chip to be measured based on the coherence time decay.

[0152] In one embodiment, the first chip reference parameters include a first initial fidelity; the first determining module 903 includes: a second input unit, used to input the first initial fidelity and the preset bombardment parameters into a pre-constructed fidelity evolution model to obtain the first fidelity of the sub-chip to be measured after being bombarded by a single particle.

[0153] Furthermore, the first chip reference parameters also include a first initial pulse amplitude; the second determination module 904 includes a second calculation unit, a third calculation unit, and a second determination unit, wherein:

[0154] The second calculation unit is used to calculate the electrical signal amplitude after a single-particle bombardment based on the first initial pulse amplitude, the first fidelity, and the first initial fidelity.

[0155] The third calculation unit is used to calculate the electrical signal distortion degree based on the amplitude of the first initial pulse and the amplitude of the electrical signal;

[0156] The second determining unit is used to determine the degree of influence of the single-event effect on the electrical signal of the sub-chip to be measured based on the electrical signal distortion degree.

[0157] In one embodiment, the device further includes a third acquisition module, a training module, and a replacement module. Wherein:

[0158] The third acquisition module is used to acquire the second chip reference parameter set, the second bombardment parameter set, and the second quantum state parameter set corresponding to the experimental quantum chip;

[0159] The domestication module is used to take the second chip reference parameter set and the second bombardment parameter set as inputs, and to domesticate the parameters of the initial quantum state evolution model based on the second quantum state parameter set to obtain preset model parameters, wherein the model parameters of the initial quantum state evolution model are initial values;

[0160] The replacement module is used to replace the initial values ​​of the model parameters of the initial quantum state evolution model with the preset model parameters to obtain a pre-constructed quantum state evolution model.

[0161] Each module in the aforementioned detection device for the effect of single-event effects on quantum chips can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0162] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores detection data on the effects of single-event effects on the quantum chip. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for detecting the effects of single-event effects on the quantum chip.

[0163] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0164] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method for detecting the effect of single-event effects on quantum chips according to the above embodiments of this application.

[0165] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method for detecting the effect of single-event effects on quantum chips according to the above embodiments of this application.

[0166] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the method for detecting the effect of single-event effects on a quantum chip as described in the above embodiments of this application.

[0167] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0168] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0169] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for detecting the influence of single-event effects on quantum chips, characterized in that, The method includes: Obtain the preset bombardment parameters of a single particle on the sub-chip to be measured; Obtain the first chip reference parameters of the sub-chip under test when it is not subjected to single-particle bombardment; Based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle are determined. Based on the first chip reference parameters and the first quantum state parameters, determine the degree of influence of single-event effects on the sub-chip to be measured; The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and the influencing parameters of the quantum chip, including the bombardment parameters and the chip reference parameters.

2. The method according to claim 1, characterized in that, The first chip reference parameters include a first initial coherence time; The step of determining the first quantum state parameters of the sub-chip under test after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, includes: The first initial coherence time and the preset bombardment parameters are input into a pre-constructed coherence time evolution model to obtain the first coherence time of the sub-chip to be measured after being bombarded by a single particle.

3. The method according to claim 2, characterized in that, The step of determining the degree of influence of single-event effects on the sub-chip under test based on the first chip reference parameters and the first quantum state parameters includes: Calculate the coherence time decay rate after single-particle bombardment based on the first initial coherence time and the first coherence time; The degree of influence of single-event effects on the coherence time of the measured sub-chip is determined based on the coherence time decay.

4. The method according to claim 1, characterized in that, The first chip reference parameters include a first initial fidelity; The step of determining the first quantum state parameters of the sub-chip under test after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model, includes: The first initial fidelity and the preset bombardment parameters are input into a pre-constructed fidelity evolution model to obtain the first fidelity of the sub-chip to be measured after being bombarded by a single particle.

5. The method according to claim 4, characterized in that, The first chip reference parameters also include the first initial pulse amplitude; The step of determining the degree of influence of single-event effects on the sub-chip under test based on the first chip reference parameters and the first quantum state parameters includes: The amplitude of the electrical signal after a single-particle bombardment is calculated based on the first initial pulse amplitude, the first fidelity, and the first initial fidelity. The electrical signal distortion is calculated based on the amplitude of the first initial pulse and the amplitude of the electrical signal. The degree of influence of single-event effects on the electrical signal of the sub-chip under test is determined based on the electrical signal distortion.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Obtain the second chip reference parameter set, the second bombardment parameter set, and the second quantum state parameter set corresponding to the experimental quantum chip; The second chip reference parameter set and the second bombardment parameter set are used as inputs, and the initial quantum state evolution model is conditioned based on the second quantum state parameter set to obtain preset model parameters, wherein the model parameters of the initial quantum state evolution model are initial values; The initial values ​​of the model parameters of the initial quantum state evolution model are replaced with the preset model parameters to obtain the pre-constructed quantum state evolution model.

7. A device for detecting the effect of single-event effects on quantum chips, characterized in that, The device includes: The first acquisition module is used to acquire the preset bombardment parameters of a single particle on the sub-chip to be measured; The second acquisition module is used to acquire the first chip reference parameters of the sub-chip to be measured when it is not bombarded by a single particle. The first determining module is used to determine the first quantum state parameters of the sub-chip to be measured after being bombarded by a single particle, based on the preset bombardment parameters, the first chip reference parameters, and the pre-constructed quantum state evolution model. The second determining module is used to determine the degree of influence of single-event effects on the sub-chip to be measured based on the first chip reference parameters and the first quantum state parameters. The pre-constructed quantum state evolution model characterizes the relationship between the quantum state parameters and the influencing parameters of the quantum chip, including the bombardment parameters and the chip reference parameters.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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