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Solving the Schrödinger equation using program synthesis
We demonstrate that a program synthesis approach based on a linear code representation can be used to generate algorithms that approximate the ground-state solutions of one-dimensional time-independent Schrödinger equations constructed with bound polynomial potential energy surfaces (PESs). Here, an...
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Published in: | The Journal of chemical physics 2021-10, Vol.155 (15), p.154102-154102 |
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container_title | The Journal of chemical physics |
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creator | Habershon, Scott |
description | We demonstrate that a program synthesis approach based on a linear code representation can be used to generate algorithms that approximate the ground-state solutions of one-dimensional time-independent Schrödinger equations constructed with bound polynomial potential energy surfaces (PESs). Here, an algorithm is constructed as a linear series of instructions operating on a set of input vectors, matrices, and constants that define the problem characteristics, such as the PES. Discrete optimization is performed using simulated annealing in order to identify sequences of code-lines, operating on the program inputs that can reproduce the expected ground-state wavefunctions ψ(x) for a set of target PESs. The outcome of this optimization is not simply a mathematical function approximating ψ(x) but is, instead, a complete algorithm that converts the input vectors describing the system into a ground-state solution of the Schrödinger equation. These initial results point the way toward an alternative route for developing novel algorithms for quantum chemistry applications. |
doi_str_mv | 10.1063/5.0062497 |
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source | American Institute of Physics (AIP) Publications; American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Algorithms Mathematical analysis Mathematical functions Optimization Polynomials Potential energy Quantum chemistry Schrodinger equation Sequences Simulated annealing Synthesis Vectors (mathematics) Wave functions |
title | Solving the Schrödinger equation using program synthesis |
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