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Method for predicting reaction barrier energy based on quantum full-connection neural network algorithm

A neural network, fully connected technology, applied in the field of predicting reaction potential barrier energy based on quantum fully connected neural network algorithm, can solve the problems of complexity, consume a lot of time and resources, cannot meet large-scale screening of catalysts, etc., to simplify the calculation process, Satisfy large-scale screening of suitable effects

Pending Publication Date: 2022-05-06
上海图灵智算量子科技有限公司
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Problems solved by technology

Obtaining the reaction barrier of a reaction on a certain catalyst can be done through experiments or quantum chemical calculation methods. However, experimental methods and quantum chemical calculation methods are very complicated in the process of processing, consume a lot of time and resources, and cannot meet large-scale The need to screen for suitable catalysts

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  • Method for predicting reaction barrier energy based on quantum full-connection neural network algorithm
  • Method for predicting reaction barrier energy based on quantum full-connection neural network algorithm
  • Method for predicting reaction barrier energy based on quantum full-connection neural network algorithm

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Embodiment Construction

[0025] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0026]

[0027] figure 1 It is a flowchart of a method for predicting reaction barrier energy based on a quantum fully connected neural network algorithm in an embodiment of the present invention.

[0028] Such as figure 1 As shown, the method for predicting the reaction barrier energy based on the quantum fully connected neural network algorithm provided in this embodiment includes the following steps:

[0029] Step S1, obtaining the electron density input vector of the reactant state.

[0030] In this embodiment, the reactant state is to transform the initial state into an unbiased state, which is the lowest computational basis state for n qubit circuits. The electron density input vector of the reactant is concatenat...

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Abstract

The invention provides a method for predicting reaction barrier energy based on a quantum full-connection neural network algorithm, and belongs to the technical field of quantum computing. According to the method, an electron density descriptor is converted into an electron density input vector, and the electron density input vector is input into a constructed quantum full-connection neural network, so that reaction barrier energy prediction is carried out. The quantum full-connection neural network comprises a quantum coding circuit and a variable component sub-circuit, the quantum coding circuit converts an electron density input vector into an electron density quantum state through an amplitude coding mode, and the variable component sub-circuit performs quantum entanglement and quantum rotation through an entanglement module and a parameterized rotation module. According to the method, the calculation process of the quantum chemistry calculation method is simplified, a large amount of time and resources do not need to be consumed, and the requirement for screening appropriate catalysts on a large scale can be met.

Description

technical field [0001] The invention relates to the technical field of quantum computing, in particular to a method for predicting reaction barrier energy based on a quantum fully connected neural network algorithm. Background technique [0002] A common chemical reaction process does not directly generate products from the reactants, and the reactants need to be excited to a higher energy state by means of heating, that is, the reaction transition state. The reaction barrier, defined as the energy difference between the transition state and the reactants, is key to our understanding of chemical reactivity and catalysis. [0003] The reaction barrier is a key indicator for evaluating the performance of a catalyst. An excellent catalyst can greatly reduce the reaction barrier, thereby accelerating the rate of chemical reactions. Obtaining the reaction barrier of a reaction on a certain catalyst can be done through experiments or quantum chemical calculation methods. However,...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16C10/00G06N3/04G06N10/00
CPCG16C10/00G06N3/04G06N10/00
Inventor 王诗瑜
Owner 上海图灵智算量子科技有限公司