Method and system for determining reactivity of material molecules based on quantum computing

Abstract

The application discloses a kind of based on quantum computing's material molecule's reactive activity determination method and system, it is related to based on quantum computing's material performance analysis technical field, method includes: generating the UCCSD of target material molecule Theoretical setup, it contains multiple double-excitation operator and single-excitation operator;Using approximate method to calculate each double-excitation operator relative contribution estimate value to molecular ground state energy level;Filtering the operator of estimate value higher than threshold value or selecting the first N as key double-excitation operator according to order;It is combined into final UCCSD Theoretical setup with all single-excitation operator;Quantum circuit is constructed based on the setup, and then determine molecular reactivity.The application calculates relative contribution estimate value by approximation and filters key double-excitation operator, while significantly reducing resource consumption, to ensure calculation accuracy, so as to reliably determine the reactivity of material molecules, overcome the defects that efficiency and accuracy are difficult to consider in prior art.

Description

Technical Field

[0001] This invention relates to the field of quantum computing-based material property analysis technology, and in particular to a method and system for determining the reactivity of material molecules based on quantum computing. Background Technology

[0002] Predicting the reactivity of material molecules plays a crucial role in catalyst design, new energy material development, and chemical process optimization. The core of accurately predicting molecular reactivity lies in calculating its ground-state energy level and related electronic structure properties. However, when using classical computational methods and existing quantum simulation techniques to process medium-to-large-scale material molecular systems, problems such as high computational costs, insufficient accuracy, or poor scalability still exist, severely restricting the efficiency of new material research and development.

[0003] To address the aforementioned issues, researchers have attempted to apply the Variational Quantum Eigenvalue Solver (VQE) algorithm to molecular simulations of materials. VQE, through a quantum-classical hybrid computation approach, promises to achieve high-precision simulations of complex molecular systems while maintaining polynomial-level resource consumption. Among these, the unitary coupled cluster truncation to second-order approximation (UCCSD) fitting is a commonly used wavefunction fitting form in VQE, which includes single-excitation operators and double-excitation operators. Since the number of double-excitation operators increases fourth-orderly with the number of molecular orbitals, specifically for a molecular system with… The proposed UCCSD for each molecular orbital includes... There are several biexcitation operators. It is important to emphasize that not all biexcitation operators are equally important; directly using all operators to construct quantum circuits would result in enormous resource requirements, making practical applications difficult. Therefore, existing technologies propose various methods for contribution estimation and selection of biexcitation operators, such as the MP2 method based on perturbation theory (with a computational complexity of O(n log n)). ), variational algorithm CCSD (computational complexity is O(n log n) ) and Energy Sorting (computational complexity is respectively ), and the recently proposed Gradient Basis Excitation Filter (GBEF) algorithm (which calculates an inner product based on the gradient of the excitation operator in the Hartree Fock state). The inner product is used as the basis for comparing the contributions of each triggering operator, and its computational complexity is O(n log n). However, further optimization can achieve These methods evaluate operator contributions using information such as perturbation energy, variational amplitude, or gradient inner product, and then perform screening based on this information to reduce the proposed size.

[0004] However, these existing methods still have significant shortcomings. Specifically, while the MP2 method has high computational efficiency, it is based on low-order perturbation theory and has limited accuracy; the CCSD and Energy Sorting algorithms have high complexity and are difficult to scale to large-scale systems; while the GBEF method reduces computational costs to some extent, its sorting accuracy still has considerable room for improvement. When estimating and sorting the contributions of dual-excitation operators, these methods often cannot simultaneously balance efficiency and accuracy. This results in the final VQE hypothesis either having excessive redundant operators leading to huge resource consumption, or omitting key operators, causing the simulation results to deviate from the true values. This seriously affects the reliability and practicality of predicting the molecular reactivity of materials.

[0005] Therefore, there is an urgent need for a method that can efficiently and accurately estimate the contribution of dual-excitation operators in the proposed UCCSD model during the classical calculation stage and achieve reliable screening, so as to support the practical application of the VQE algorithm in the prediction of molecular reactivity of materials and promote the development of related fields. Summary of the Invention

[0006] The technical problem to be solved by this invention is to address the shortcomings of existing technologies, specifically by providing a method and system for determining the reactivity of material molecules based on quantum computing, as detailed below:

[0007] 1) In a first aspect, the present invention provides a method for determining the reactivity of material molecules based on quantum computing, the specific technical solution of which is as follows:

[0008] The UCCSD scheme for generating molecules of the target material includes multiple dual-excitation operators and single-excitation operators.

[0009] An approximate method was used to calculate the estimated relative contribution of each dual-excitation operator to the ground state energy level of the target material's molecules;

[0010] Select double-stimulated operators whose absolute value of relative contribution estimate is greater than the preset relative contribution estimate threshold as key double-stimulated operators; or, sort all double-stimulated operators in descending order of relative contribution estimate and select the first N double-stimulated operators from the sorted sequence as key double-stimulated operators, where N is a positive integer.

[0011] The final UCCSD of the target material's molecules is determined by the key dual-excitation operator and all single-excitation operators.

[0012] Based on the final UCCSD design, construct quantum circuitry;

[0013] Based on quantum circuits, the reactivity of molecules in the target material is determined.

[0014] The beneficial effects of the method for determining the reactivity of material molecules based on quantum computing provided by this invention are as follows:

[0015] By employing an approximate method to calculate the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material's molecules, and using this estimate as a basis for screening key dual-excitation operators or performing effective sorting, the efficiency and scalability of dual-excitation operator contribution assessment are significantly improved. Furthermore, by combining the key dual-excitation operators with all single-excitation operators to form a final UCCSD hypothesis, and constructing a quantum circuit based on this final UCCSD hypothesis, the accuracy of molecular ground state energy level calculation can be guaranteed while greatly reducing resource consumption, thereby accurately and reliably determining the reactivity of the target material's molecules. This method achieves efficient simplification of the UCCSD hypothesis during the classical calculation stage, overcoming the limitation of prior art in balancing efficiency and accuracy, and providing a feasible path for the practical application of the VQE algorithm in material molecular simulation.

[0016] Based on the above scheme, the method for determining the reactivity of material molecules based on quantum computing of the present invention can be further improved as follows.

[0017] Furthermore, before calculating the relative contribution estimate of each dual-excitation operator to the ground-state energy level of the target material's molecules using an approximate method, the following steps are also included:

[0018] Construct the Hamiltonian of the second quantized form of the molecules of the target material;

[0019] Based on the Hamiltonian in the form of second-order quantization, a first calculation formula is proposed to solve for the true contribution of each double-excitation operator to the ground state energy level of the target material molecule.

[0020] An approximate method was used to calculate the estimated relative contribution of each dual-excitation operator to the ground-state energy level of the target material's molecules, including:

[0021] The first calculation formula is approximated using an approximation method to obtain the second calculation formula;

[0022] The second calculation formula is solved to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

[0023] The advantages of adopting the above-mentioned further approach are as follows: Firstly, the Hamiltonian in the second quantized form of the target material's molecules is pre-constructed, and based on this Hamiltonian, a first calculation formula for the true contribution value of the dual-excitation operator is derived, laying a rigorous mathematical and physical foundation for subsequent approximation processing. Further, an approximation method is used to reasonably simplify the first calculation formula, resulting in a more easily solvable second calculation formula, significantly reducing computational complexity while maintaining the accuracy of the contribution estimation. This process ensures that the solution of the relative contribution estimate is theoretically reliable and computationally efficient, providing a crucial guarantee for the subsequent accurate screening of key dual-excitation operators and the efficient construction of quantum circuits for determining reactivity.

[0024] Furthermore, based on quantum circuits, the molecular reactivity of the target material is determined, including:

[0025] Based on quantum circuits, the energy level distribution of molecules in the target material is determined;

[0026] The reactivity of the target material molecules is determined based on the energy level distribution of the target material molecules.

[0027] The beneficial effects of adopting the above-mentioned further scheme are: this method establishes a direct and quantitative relationship between molecular electronic structure and reactivity, which enables the prediction of reactivity to be based on more accurate quantum computing, and significantly improves the reliability of the evaluation results.

[0028] Furthermore, based on quantum circuits, the energy level distribution of the target material's molecules is determined, including:

[0029] Based on quantum circuits and using the VQE algorithm, the energy level distribution of the target material's molecules is determined.

[0030] The advantages of adopting the above-mentioned further scheme are: it fully leverages the efficiency advantage of the VQE algorithm in handling quantum many-body problems, enabling the acquisition of high-precision ground state and low excited state energy level information with relatively low computational resources. This provides crucial electronic structure data for subsequent accurate evaluation of molecular reactivity or photoelectric properties, ensuring the reliability of the entire method from quantum simulation to property prediction, and enhancing the practicality and feasibility of the VQE process in materials research and development.

[0031] Furthermore, based on the energy level distribution of the target material's molecules, the reactivity of the target material's molecules is determined, including:

[0032] Based on the energy level distribution of the target material's molecules and using Alling's formula, the reactivity of the target material's molecules is determined.

[0033] The beneficial effects of adopting the above-mentioned further approach are as follows: Using energy level distribution data, the Alling formula can accurately calculate key kinetic parameters such as the reaction rate constant, thereby achieving quantitative and reliable prediction of molecular reactivity. This method establishes a rigorous physical bridge from microscopic electronic structure to macroscopic reaction properties, greatly improving the accuracy and physical significance of the prediction results. It ensures that energy level data obtained based on VQE quantum computing can be efficiently and accurately transformed into key indicators guiding materials research and development, powerfully promoting the practical application of the entire process in actual materials design.

[0034] Furthermore, it also includes:

[0035] When the target material is a fluorescent material, the luminescence properties of the target material are determined based on the energy level distribution of the molecules of the target material, and the target material is then used for fluorescent labeling based on the luminescence properties.

[0036] When the target material is a photocatalyst, the photocatalytic activity of the target material is determined based on the energy level distribution of its molecules; and based on the photocatalytic activity of the target material, it is determined whether the target material can be used for visible light-driven chemical reactions.

[0037] The advantages of adopting the above-mentioned further approach are as follows: For fluorescent materials, the accurate prediction of their luminescence properties based on energy level distribution provides a direct and reliable quantum mechanical basis for determining whether the material is suitable for fluorescent labeling, avoiding the high cost and blindness of traditional trial-and-error methods. For photocatalysts, evaluating their photocatalytic activity, especially their adaptability to visible light-driven chemical reactions, through energy level distribution can efficiently screen candidate materials with application potential, accelerating the design and development process of photocatalysts. Finally, this feature allows the same quantum computing process to serve the performance prediction of various functional materials, greatly improving the versatility and industrialization value of the method.

[0038] 2) In a second aspect, the present invention also provides a system for determining the reactivity of material molecules based on quantum computing, the specific technical solution of which is as follows:

[0039] It includes a generation module, a relative contribution estimate calculation module, a screening module, a first construction module, a second construction module, and a determination module;

[0040] The generation module is used to generate the UCCSD model of the target material's molecules. The UCCSD model includes multiple dual-excitation operators and single-excitation operators.

[0041] The relative contribution estimation module is used to: calculate the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material's molecules using an approximate method;

[0042] The filtering module is used to: filter out double-stimulation operators whose absolute value of relative contribution estimate is greater than a preset relative contribution estimate threshold as key double-stimulation operators, or sort all double-stimulation operators in descending order of relative contribution estimate and select the first N double-stimulation operators from the sorted sequence as key double-stimulation operators, where N is a positive integer;

[0043] The first building module is used to: simulate the final UCCSD of the molecules of the target material composed of key dual-excitation operators and all single-excitation operators;

[0044] The second building module is used to: construct quantum circuits based on the final UCCSD design;

[0045] The determination module is used to: determine the molecular reactivity of a target material based on quantum circuits.

[0046] Based on the above scheme, the system for determining the reactivity of material molecules based on quantum computing of the present invention can be further improved as follows.

[0047] Furthermore, it also includes a calculation formula determination module, which is used for:

[0048] Construct the Hamiltonian of the second quantized form of the molecules of the target material;

[0049] Based on the Hamiltonian in the form of second-order quantization, a first calculation formula is proposed to solve for the true contribution of each double-excitation operator to the ground state energy level of the target material molecule.

[0050] The relative contribution estimate calculation module is used for:

[0051] The first calculation formula is approximated using an approximation method to obtain the second calculation formula;

[0052] The second calculation formula is solved to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

[0053] Furthermore, the determination module includes an energy level distribution determination module and a reaction activity determination module;

[0054] The energy level distribution determination module is used to: determine the energy level distribution of molecules in a target material based on quantum circuits;

[0055] The reactivity determination module is used to determine the reactivity of the target material molecules based on the energy level distribution of the target material molecules.

[0056] Furthermore, the energy level distribution determination module is specifically used to determine the energy level distribution of the target material's molecules based on quantum circuits and using the VQE algorithm.

[0057] Furthermore, the reactivity determination module is specifically used to: determine the reactivity of the target material molecules based on the energy level distribution of the target material molecules and using the Alling equation.

[0058] Furthermore, it also includes an application module, which is used for:

[0059] When the target material is a fluorescent material, the luminescence properties of the target material are determined based on the energy level distribution of the molecules of the target material, and the target material is then used for fluorescent labeling based on the luminescence properties.

[0060] When the target material is a photocatalyst, the photocatalytic activity of the target material is determined based on the energy level distribution of its molecules; and based on the photocatalytic activity of the target material, it is determined whether the target material can be used for visible light-driven chemical reactions.

[0061] 3) In a third aspect, the present invention also provides an electronic device, the electronic device including a processor coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor, so as to enable the electronic device to realize any of the above-mentioned methods for determining the reactivity of material molecules based on quantum computing.

[0062] 4) In a fourth aspect, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements any of the above-mentioned methods for determining the reactivity of material molecules based on quantum computing.

[0063] It should be noted that the beneficial effects of the technical solutions of the second to fourth aspects of the present invention and their corresponding possible implementations can be found in the above description of the technical effects of the first aspect and its corresponding possible implementations, and will not be repeated here. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below:

[0065] Figure 1 This is a flowchart illustrating a method for determining the reactivity of material molecules based on quantum computing, according to an embodiment of the present invention.

[0066] Figure 2 This is a schematic diagram of the structure of a system for determining the reactivity of material molecules based on quantum computing, according to an embodiment of the present invention.

[0067] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0068] The principles and features of the present invention are described below. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0069] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0070] like Figure 1 As shown in the figure, a method for determining the reactivity of material molecules based on quantum computing according to an embodiment of the present invention includes the following steps:

[0071] S1. The UCCSD scheme for generating the target material molecules, which includes multiple dual-excitation operators and single-excitation operators;

[0072] In the process of generating the UCCSD of the target material molecules, a suitable threshold is set. If the threshold is too high, it will cause some double-excitation operators to be missed in the screening process, while if it is too low, it will lead to too many double-excitation operators, which will increase the cost of the VQE algorithm. Therefore, the threshold can be adjusted appropriately according to the actual situation.

[0073] S2. The relative contribution of each dual-excitation operator to the ground state energy level of the target material molecule is estimated using an approximate method;

[0074] Before S2, it also includes:

[0075] S020, Constructing the Hamiltonian in the second quantized form of the target material's molecules;

[0076] Among them, the Hamiltonian in the second quantized form is:

[0077]

[0078] in:

[0079] Represents: Hamiltonian; and All are electronic integrals, specifically, Indicates: Electrons from index 1 Excited to index 0 on spin orbit The single-electron integral corresponding to the spin orbital, This means: simultaneously moving two electrons from index 1 to 2. Excitation to index 0 on spin orbit On the spin orbit and from the index of Excitation to index 0 on spin orbit The two-electron integral corresponding to the spin orbitals can be efficiently solved using a classical computer, with the index being... The spin orbitals and their indices are The spin orbitals are electron-occupied orbitals, with indices of . The spin orbitals and their indices are Its spin orbit is a virtual orbit.

[0080] Indicates: operates on index 1 The operator for producing electrons in their spin orbitals;

[0081] Indicates: operates on index 1 The annihilation operator of electrons in their spin orbitals;

[0082] Indicates: operates on index 1 The operator for producing electrons in their spin orbitals;

[0083] Indicates: operates on index 1 The annihilation operator of electrons in their spin orbitals;

[0084] Indicates: Moving a single electron from index 1 Excited to index 0 on spin orbit On its spin orbit;

[0085] This means: simultaneously moving two electrons from index 1 to 2. Excitation to index 0 on spin orbit On the spin orbit and from the index of Excitation to index 0 on spin orbit On its spin orbit.

[0086] In actual calculations, the molecular index of the target material is... The spin orbitals of the target material molecules are the first... The index of the target material molecule is _ spin orbitals_. The spin orbitals of the target material molecules are the first... The index of the target material molecule is _ spin orbitals_. The spin orbitals of the target material molecules are the first... The index of the target material molecule is _ spin orbitals_. The spin orbitals of the target material molecules are the first... A spin orbit.

[0087] S021. Based on the Hamiltonian in its second-order quantization form, a first calculation formula is proposed to determine the true contribution of each double-excitation operator to the ground-state energy level of the target material's molecules. The first calculation formula is as follows:

[0088]

[0089] in, For: Double-excitation operators in the UCCSD excitation operator pool The actual contribution value, ( This means: simultaneously moving two electrons from index 1 to 2. Excitation to index 0 on spin orbit On the spin orbit and from the index of Excitation to index 0 on spin orbit The excitation process on the spin orbit, , and These are the corresponding double excited states in the FCI results. and Hartree Fock state The amplitude coefficient, FCI result refers to the calculation result of the molecular ground state energy accurately solved by the FCI (Full Configuration Interaction) method on a classical computer. Specifically, it includes the accurate reference value of the amplitude coefficient of each excited state (such as Hartree-Fock state and double excited state) in the electronic wavefunction. However, because its computational complexity increases exponentially with the scale of the system, it cannot be used for large molecules.

[0090] In S2, an approximate method is used to calculate the estimated relative contribution of each dual-excitation operator to the ground-state energy level of the target material's molecules, including:

[0091] S20. The first calculation formula is approximated using an approximation method to obtain the second calculation formula;

[0092] because and This requires exponential computational cost, therefore directly using the first calculation formula cannot be extended to calculate energy level distributions applicable to large molecules. The inner product term... This can be obtained at low cost through the GBEF algorithm or other methods. To reduce computational cost, this application proposes using an approximate method to estimate the relative contribution of the dual-excitation operator. Specifically:

[0093] Since the calculation of the true contribution value of each double-excitation operator involves the same non-zero amplitude. Ignoring these values ​​will not affect the filtering results, and the amplitude in the results will be calculated using the CCSD algorithm. Alternate amplitude The second calculation formula is obtained, which is:

[0094]

[0095] This represents the double-excitation operator in the UCCSD excitation operator pool. The relative contribution estimate.

[0096] S21. Solve the second calculation formula to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

[0097] Amplitude calculation using CCSD algorithm The computational complexity is The inner product term is calculated using the GBEF algorithm. The computational complexity is Therefore, the overall computational complexity is . Therefore, it is suitable for calculating the energy level distribution of large molecules.

[0098] S3. Select double-stimulated operators whose absolute value of relative contribution estimate is greater than the preset relative contribution estimate threshold as key double-stimulated operators, or sort all double-stimulated operators in descending order of relative contribution estimate, and select the first N double-stimulated operators from the sorted sequence as key double-stimulated operators, where N is a positive integer.

[0099] S4. The final UCCSD of the target material molecule is proposed by combining the key dual-excitation operator and all single-excitation operators;

[0100] S5. Construct quantum circuitry based on the final UCCSD design;

[0101] S6. Based on quantum circuits, determine the molecular reactivity of the target material.

[0102] S6. Based on quantum circuits, determine the molecular reactivity of the target material, specifically:

[0103] S60. Based on quantum circuits, determine the energy level distribution of the molecules of the target material. Specifically, based on quantum circuits and using the VQE algorithm, determine the energy level distribution of the molecules of the target material.

[0104] Setting a preset threshold ε for relative contribution estimates is a crucial hyperparameter, and its setting requires a trade-off between computational efficiency and accuracy. Analysis of algorithm complexity reveals that the screening process itself (computing all...) The cost of comparing the preset relative contribution estimates of each operator is relatively controllable, but the selection result directly determines the scale of the subsequent VQE algorithm, thus greatly affecting the consumption of quantum computing resources. The physical meaning of the preset relative contribution estimate threshold ε is the minimum standard for determining whether a key double-excitation operator has a significant contribution to the ground state energy; the preset relative contribution estimate threshold ε represents the lower limit of the absolute value of the contribution to the ground state energy level. Setting the preset relative contribution estimate threshold ε is usually an empirical process, requiring consideration of the specific characteristics of the molecular system and the required computational accuracy. If the preset relative contribution estimate threshold ε is set too high, operators will be filtered out too aggressively. Although this can greatly reduce the scale of the proposed algorithm, it may miss some operators with small contributions but necessary for convergence, causing VQE to fail to converge to sufficient accuracy or even obtain incorrect results. If the preset relative contribution estimate threshold ε is set too low, the selection effect will be poor, retaining too many operators and failing to achieve significant cost reduction. In practice, the following strategy is usually adopted:

[0105] Calculate the preset relative contribution estimates for all dual-excitation operators. Considering the maximum scale of the simulation that a quantum computer can precisely execute (the maximum number of dual-excitation operators), manually determine the minimum value of the preset relative contribution estimate threshold, for example, 0.01. Use the largest preset relative contribution estimate as the initial value. Continuously try to decrease the initial value, thereby adding more key dual-excitation operators to the final UCCSD simulation. Run the VQE algorithm based on this final UCCSD simulation to obtain the predicted molecular energy levels. Repeat the above steps until the molecular energy levels no longer decrease after further decreasing the initial value; this initial value is the optimal value, and it is used as the preset relative contribution estimate threshold ε. During the iteration process, the initial value used in each iteration cannot be less than the aforementioned minimum value. Clearly, the preset relative contribution estimate threshold ε is not a fixed global optimum, but a parameter that needs to be optimized specifically according to the specific computational task.

[0106] In another feasible approach, the top N biexcitation operators with the largest relative contribution estimates from the sorted sequence are selected as key biexcitation operators. These key biexcitation operators are considered to contribute most significantly to the ground state energy, and retaining them can significantly reduce the computational complexity of subsequent VQE algorithms while maintaining accuracy. The value of N is pre-set based on computational experience with similar molecular systems or resource constraints (such as the maximum number of operators a quantum processor can support), or the convergence and accuracy of the VQE algorithm under different N values ​​are iteratively tested to select the optimal N value within acceptable resource limits that yields the best results for each energy level.

[0107] S61. Determine the reactivity of the target material molecules based on the energy level distribution of the target material molecules.

[0108] Optionally, in S61, determining the reactivity of the target material molecules based on the energy level distribution of the target material molecules includes: determining the reactivity of the target material molecules based on the energy level distribution of the target material molecules and using the Alling formula.

[0109] The Eyring equation is a fundamental formula in Transition State Theory (TST), used to describe the relationship between chemical reaction rates and activation free energy, temperature, and quantum effects. The Eyring equation can be used to calculate the reaction rate constant, which characterizes the reactivity of molecules in a target material. Based on the reaction rate constant, the reaction conditions of the target material can be optimized, the degradation rate of the target material can be predicted, and the properties of the target material, such as rubber elasticity and plastic strength, can be controlled.

[0110] Optionally, the above technical solution also includes:

[0111] 1) When the target material is a fluorescent material, the luminescence properties of the target material are determined based on the energy level distribution of its molecules. Based on these luminescence properties, it is then determined whether the target material is suitable for fluorescent labeling. Specifically:

[0112] By analyzing the energy level distribution of the target material's molecules using the VQE algorithm, the focus is on the energy difference between the excited and ground states, i.e., the excitation energy, and the characteristics of the key excited states (usually the first excited state S1) directly related to the fluorescence emission process are extracted. Determining the luminescence properties depends on calculating the transition probabilities between energy levels, which is achieved by calculating the transition dipole moments between relevant electronic states. This physical quantity directly determines the magnitude of the radiative transition rate and is a core parameter for evaluating fluorescence intensity (i.e., quantum yield). A strong transition dipole moment implies a high radiative transition rate and strong fluorescence emission intensity. Simultaneously, the competition for non-radiative transition channels (such as internal conversion and intersystem crossing) needs to be evaluated. This can be indirectly inferred by analyzing the band gap between different electronic states; a larger band gap can suppress non-radiative transitions, thus favoring fluorescence emission. The fluorescence quantum yield of the fluorescent material can be theoretically estimated by combining the ratio of the radiative to the non-radiative transition rates. Finally, the suitability for fluorescent labeling is determined based on the identified luminescent properties (including excitation wavelength, emission wavelength, Stokes shift, fluorescence intensity, and quantum yield); materials used for fluorescent labeling must meet the following quantification threshold conditions:

[0113] The calculated fluorescence quantum yield must be no less than 0.8 to ensure a sufficiently bright signal; the calculated excitation wavelength must be strictly within the visible light range of 400 nm to 700 nm to match the light source of conventional optical instruments, while the calculated emission wavelength should also be within the effective response range of the detector of 400 nm to 800 nm; and the calculated Stokes shift must be greater than 50 nm to ensure that the excitation and emission light can be effectively separated.

[0114] If the calculated luminescence characteristic parameters simultaneously meet all the above threshold conditions, the target material can be determined to be suitable for fluorescent labeling; otherwise, if any condition is not met, the target material can be determined to be unsuitable for fluorescent labeling.

[0115] 2) When the target material is a photocatalyst, its photocatalytic activity is determined based on the energy level distribution of its molecules; based on this activity, it is determined whether the target material can be used for visible light-driven chemical reactions. Specifically:

[0116] First, based on the energy level distribution of the target material molecules accurately calculated using the VQE algorithm, the focus is on analyzing the energy difference between its highest occupied molecular orbital (HOMO) level and its lowest unoccupied molecular orbital (LUMO) level, i.e., the band gap. This band gap energy must be less than the maximum energy of a visible light photon; this is a prerequisite for determining whether the material can be excited by visible light to generate electron-hole pairs, and is the foundation for its visible light photocatalytic activity. Determining photocatalytic activity further relies on comparing the aforementioned molecular orbital energy level positions with the energy level benchmark of the standard redox potential. Specifically, the material's conduction band or LUMO level must be more negative than the potential of the target reduction reaction to ensure sufficient reduction driving force for photogenerated electrons; simultaneously, its valence band or HOMO level must be more positive than the potential of the target oxidation reaction to ensure sufficient oxidation driving force for photogenerated holes. Furthermore, the recombination probability of photogenerated carriers (electrons and holes) needs to be indirectly evaluated from the energy level structure. A well-separated energy level distribution facilitates the effective separation and migration of carriers, thereby improving photocatalytic efficiency. By considering the band gap energy, the matching degree between energy level positions and redox potentials, and the potential carrier separation efficiency, the photocatalytic activity of the target material can be theoretically determined. Finally, the determined photocatalytic activity is used to determine whether it is suitable for visible light-driven chemical reactions.

[0117] If the calculated bandgap value of the target material is within the visible light absorption range of 1.6 eV to 3.2 eV, and its LUMO energy level is below -4.44 eV (relative to the vacuum energy level, to meet the requirements) (Reduction potential requirement), while its HOMO energy level is higher than -5.67 eV (relative to the vacuum energy level, to meet the requirement). If the oxidation potential requirement is met, the photocatalyst can be determined to be suitable for visible light-driven chemical reactions (such as photocatalytic water splitting to produce hydrogen, photocatalytic degradation of pollutants, etc.); conversely, if any of the above threshold conditions are not met, the photocatalyst can be determined to be unsuitable for visible light-driven chemical reactions.

[0118] The target material's molecules are hydrogen chain molecules. For example, the invention will be further described below:

[0119] hydrogen chain molecules The proposed UCCSD includes 26 excitation operators, 18 of which are double excitation operators:

[0120]

[0121] hydrogen chain molecules The Hamiltonian in its second quantized form can be obtained using development packages such as OpenFermion. Then, in the second calculation formula, the CCSD algorithm is used to calculate the amplitude. The inner product term is calculated using the GBEF algorithm. The process continues until the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material molecule is calculated. Dual-excitation operators whose absolute values ​​of the relative contribution estimates are greater than a preset relative contribution estimate threshold are selected as key dual-excitation operators. Alternatively, all dual-excitation operators are sorted in descending order of their relative contribution estimates, and the top N dual-excitation operators from the sorted sequence are selected as key dual-excitation operators, where N is a positive integer. The key dual-excitation operators and all single-excitation operators form the final UCCSD of the target material molecule. Based on the final UCCSD, a quantum circuit is constructed. Based on the quantum circuit, the reactivity of the target material molecule is determined.

[0122] Although the steps have been numbered in the above embodiments, they are only specific embodiments given by the present invention. Those skilled in the art can adjust the execution order of the steps according to the actual situation, which is also within the protection scope of the present invention. It can be understood that some embodiments may include some or all of the above embodiments.

[0123] like Figure 2 As shown, an embodiment of the present invention provides a quantum computing-based system for determining the reactivity of material molecules, comprising a generation module 201, a relative contribution estimation calculation module 202, a screening module 203, a first construction module 204, a second construction module 205, and a determination module 206.

[0124] The generation module 201 is used to: generate the UCCSD model of the target material's molecules, wherein the UCCSD model includes multiple dual-excitation operators and single-excitation operators;

[0125] The relative contribution estimation module 202 is used to: calculate the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material's molecules using an approximate method;

[0126] The filtering module 203 is used to: filter out double-stimulation operators whose absolute value of relative contribution estimate is greater than a preset relative contribution estimate threshold as key double-stimulation operators, or sort all double-stimulation operators in descending order of relative contribution estimate and select the first N double-stimulation operators from the sorted sequence as key double-stimulation operators, where N is a positive integer;

[0127] The first building module 204 is used to: simulate the final UCCSD of the molecules of the target material composed of key dual-excitation operators and all single-excitation operators;

[0128] The second building module 205 is used to: construct quantum circuits based on the final UCCSD design;

[0129] The determination module 206 is used to: determine the molecular reactivity of the target material based on quantum circuits.

[0130] Optionally, the above technical solution further includes a calculation formula determination module, which is used for:

[0131] Construct the Hamiltonian of the second quantized form of the molecules of the target material;

[0132] Based on the Hamiltonian in the form of second-order quantization, a first calculation formula is proposed to solve for the true contribution of each double-excitation operator to the ground state energy level of the target material molecule.

[0133] The relative contribution estimate calculation module 202 is used for:

[0134] The first calculation formula is approximated using an approximation method to obtain the second calculation formula;

[0135] The second calculation formula is solved to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

[0136] Optionally, in the above technical solution, the determining module 206 includes an energy level distribution determining module and a reaction activity determining module;

[0137] The energy level distribution determination module is used to: determine the energy level distribution of molecules in a target material based on quantum circuits;

[0138] The reactivity determination module is used to determine the reactivity of the target material molecules based on the energy level distribution of the target material molecules.

[0139] Optionally, in the above technical solution, the energy level distribution determination module is specifically used to: determine the energy level distribution of the target material's molecules based on quantum circuits and using the VQE algorithm.

[0140] Optionally, in the above technical solution, the reactivity determination module is specifically used to: determine the reactivity of the target material molecules based on the energy level distribution of the target material molecules and using the Alling formula.

[0141] Optionally, the above technical solution also includes an application module, which is used for:

[0142] When the target material is a fluorescent material, the luminescence properties of the target material are determined based on the energy level distribution of the molecules of the target material, and the target material is then used for fluorescent labeling based on the luminescence properties.

[0143] When the target material is a photocatalyst, the photocatalytic activity of the target material is determined based on the energy level distribution of its molecules; and based on the photocatalytic activity of the target material, it is determined whether the target material can be used for visible light-driven chemical reactions.

[0144] It should be noted that the beneficial effects of the quantum computing-based material molecule reactivity determination system 200 provided in the above embodiments are the same as those of the quantum computing-based material molecule reactivity determination method described above, and will not be repeated here. Furthermore, the system provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to the actual situation to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiments, and will not be repeated here.

[0145] The quantum computing-based system for determining the reactivity of material molecules of the present invention can be a computer program (including program code) running on a computer device. For example, the quantum computing-based system for determining the reactivity of material molecules of the present invention is an application software that can be used to execute the corresponding steps in the quantum computing-based method for determining the reactivity of material molecules of the present invention.

[0146] In some embodiments, the quantum computing-based system for determining the reactivity of material molecules of the present invention can be implemented using a combination of hardware and software. As an example, the quantum computing-based system for determining the reactivity of material molecules of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the quantum computing-based method for determining the reactivity of material molecules of the present invention. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0147] The modules described in the embodiments of this invention can be implemented in software or hardware. The names of the modules are not, in some cases, limiting the scope of the module itself.

[0148] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned methods for determining the reactivity of material molecules based on quantum computing. That is, an electronic device according to an embodiment of the present invention may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the method for determining the reactivity of material molecules based on quantum computing as shown in any embodiment of the present invention by calling the computer program.

[0149] In one alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0150] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0151] Bus 4002 may include a path for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus 4002 is represented by only one thick line, but this does not mean that there is only one bus or one type of bus.

[0152] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0153] The memory 4003 stores application code (computer program) for executing the present invention, and its execution is controlled by the processor 4001. The processor 4001 executes the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0154] Among them, electronic devices can also be terminal devices, which can be any device that can install applications, including at least one of smartphones, tablets, laptops, desktop computers, smart speakers, smartwatches, smart TVs, and smart in-vehicle devices.

[0155] It should be noted that, Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0156] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-mentioned methods for determining the reactivity of material molecules based on quantum computing.

[0157] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0158] In an exemplary embodiment, a computer program product or computer program is also provided, comprising computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform any of the aforementioned methods for determining the reactivity of material molecules based on quantum computing.

[0159] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0160] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0161] The computer-readable storage medium provided in this invention can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EEPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0162] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the method shown in the above embodiments.

[0163] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

[0164] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0165] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this invention can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this invention can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0166] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for determining the reactivity of material molecules based on quantum computing, characterized in that, include: The UCCSD scheme for generating molecules of the target material includes multiple dual-excitation operators and single-excitation operators; An approximate method was used to calculate the estimated relative contribution of each dual-excitation operator to the ground state energy level of the target material's molecules; Select the double-stimulation operators whose absolute value of the relative contribution estimate is greater than the preset relative contribution estimate threshold as key double-stimulation operators; or, sort all the double-stimulation operators in descending order of the relative contribution estimate, and select the first N double-stimulation operators from the sorted sequence as key double-stimulation operators, where N is a positive integer. The final UCCSD of the target material's molecules is determined by the key dual-excitation operator and all single-excitation operators. Based on the proposed final UCCSD, a quantum circuit is constructed. Based on the quantum circuit, the reactivity of the target material molecules is determined; Before calculating the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material's molecules using an approximate method, the following steps are also included: Construct the Hamiltonian of the second quantized form of the molecules of the target material; Based on the Hamiltonian in its second quantized form, a first calculation formula is derived to determine the true contribution of each double-excitation operator to the ground-state energy level of the target material's molecules. The first calculation formula is as follows: ,in, For: Double-excitation operators in the UCCSD excitation operator pool The true contribution value, , and These are the corresponding double excited states in the FCI results. and Hartree Fock state The coefficient of amplitude, The Hamiltonian is in its second quantized form; An approximate method was used to calculate the estimated relative contribution of each dual-excitation operator to the ground-state energy level of the target material's molecules, including: The first calculation formula is approximated using an approximation method to obtain the second calculation formula, which is as follows: , This represents the double-excitation operator in the UCCSD excitation operator pool. The relative contribution estimate; The second calculation formula is solved to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

2. The method for determining the reactivity of material molecules based on quantum computing according to claim 1, characterized in that, Based on the quantum circuit, the reactivity of the target material molecules is determined, including: Based on the quantum circuit, the energy level distribution of the molecules of the target material is determined; The reactivity of the target material molecules is determined based on the energy level distribution of the target material molecules.

3. The method for determining the reactivity of material molecules based on quantum computing according to claim 2, characterized in that, Based on the quantum circuit, the energy level distribution of the molecules of the target material is determined, including: Based on the quantum circuit and using the VQE algorithm, the energy level distribution of the molecules of the target material is determined.

4. The method for determining the reactivity of material molecules based on quantum computing according to claim 2, characterized in that, Based on the energy level distribution of the molecules of the target material, the reactivity of the molecules is determined, including: The reactivity of the target material molecules is determined based on the energy level distribution of the molecules and using the Alling equation.

5. A method for determining the reactivity of material molecules based on quantum computing according to any one of claims 2 to 4, characterized in that, Also includes: When the target material is a fluorescent material, the luminescence characteristics of the target material are determined based on the energy level distribution of the molecules of the target material, and whether the target material is to be used for fluorescent labeling is determined based on the luminescence characteristics of the target material. When the target material is a photocatalyst, the photocatalytic activity of the target material is determined based on the energy level distribution of its molecules; and the target material is then used to determine whether it is suitable for visible light-driven chemical reactions based on its photocatalytic activity.

6. A system for determining the reactivity of material molecules based on quantum computing, characterized in that, It includes a generation module, a relative contribution estimate calculation module, a screening module, a first construction module, a second construction module, and a determination module; The generation module is used to: generate a UCCSD simulation of the molecules of the target material, wherein the UCCSD simulation includes multiple dual-excitation operators and single-excitation operators; The relative contribution estimation module is used to: calculate the relative contribution estimate of each dual-excitation operator to the ground state energy level of the target material's molecules using an approximate method; The filtering module is used to: filter out double-excitation operators whose absolute value of the relative contribution estimate is greater than a preset relative contribution estimate threshold as key double-excitation operators, or sort all the double-excitation operators in descending order of the relative contribution estimate, and select the first N double-excitation operators from the sorted sequence as key double-excitation operators, where N is a positive integer; The first construction module is used to: formulate the final UCCSD of the molecules of the target material composed of key dual-excitation operators and all single-excitation operators; The second building module is used to: construct quantum circuits based on the final UCCSD design; The determining module is used to: determine the reactivity of the molecules of the target material based on the quantum circuit; It also includes a calculation formula determination module, which is used for: Construct the Hamiltonian of the second quantized form of the molecules of the target material; Based on the Hamiltonian in its second quantized form, a first calculation formula is derived to determine the true contribution of each double-excitation operator to the ground-state energy level of the target material's molecules. The first calculation formula is as follows: ,in, For: Double-excitation operators in the UCCSD excitation operator pool The true contribution value, , and These are the corresponding double excited states in the FCI results. and Hartree Fock state The coefficient of amplitude, The Hamiltonian is in its second quantized form; The relative contribution estimate calculation module is used for: The first calculation formula is approximated using an approximation method to obtain the second calculation formula, which is as follows: , This represents the double-excitation operator in the UCCSD excitation operator pool. The relative contribution estimate; The second calculation formula is solved to calculate the estimated relative contribution of each double-excitation operator to the ground state energy level of the target material's molecules.

7. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the reactivity of material molecules based on quantum computing as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for determining the reactivity of material molecules based on quantum computing as described in any one of claims 1 to 5.

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