Solving the 3D Heat Equation with VQA via Remeshing-Based Warm Starts

Fuente: arXiv
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Main Authors: Donachie, Samuel, Remond, Ulysse, Mathorel, Arthur, Kazymyrenko, Kyryl
Format: Preprint
Published: 2025
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author Donachie, Samuel
Remond, Ulysse
Mathorel, Arthur
Kazymyrenko, Kyryl
author_facet Donachie, Samuel
Remond, Ulysse
Mathorel, Arthur
Kazymyrenko, Kyryl
contents Quantum computing holds great promise for solving classically intractable problems such as linear systems and partial differential equations (PDEs). While fully fault-tolerant quantum computers remain out of reach, current noisy intermediate-scale quantum (NISQ) devices enable the exploration of hybrid quantum-classical algorithms. Among these, Variational Quantum Algorithms (VQAs) have emerged as a leading candidate for near-term applications. In this work, we investigate the use of VQAs to solve PDEs arising in stationary heat transfer. These problems are discretized via the finite element method (FEM), yielding linear systems of the form Ku=f, where K is the stiffness matrix. We define a cost function that encodes the thermal energy of the system, and optimize it using various ansatz families. To improve trainability and bypass barren plateaus, we introduce a remeshing strategy which gradually increases resolution by reusing optimized parameters from coarser discretizations. Our results demonstrate convergence of scalar quantities with mesh refinement. This work provides a practical methodology for applying VQAs to PDEs, offering insight into the capabilities and limitations of current quantum hardware.
format Preprint
id arxiv_https___arxiv_org_abs_2510_15645
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Solving the 3D Heat Equation with VQA via Remeshing-Based Warm Starts
Donachie, Samuel
Remond, Ulysse
Mathorel, Arthur
Kazymyrenko, Kyryl
Quantum Physics
Emerging Technologies
Quantum computing holds great promise for solving classically intractable problems such as linear systems and partial differential equations (PDEs). While fully fault-tolerant quantum computers remain out of reach, current noisy intermediate-scale quantum (NISQ) devices enable the exploration of hybrid quantum-classical algorithms. Among these, Variational Quantum Algorithms (VQAs) have emerged as a leading candidate for near-term applications. In this work, we investigate the use of VQAs to solve PDEs arising in stationary heat transfer. These problems are discretized via the finite element method (FEM), yielding linear systems of the form Ku=f, where K is the stiffness matrix. We define a cost function that encodes the thermal energy of the system, and optimize it using various ansatz families. To improve trainability and bypass barren plateaus, we introduce a remeshing strategy which gradually increases resolution by reusing optimized parameters from coarser discretizations. Our results demonstrate convergence of scalar quantities with mesh refinement. This work provides a practical methodology for applying VQAs to PDEs, offering insight into the capabilities and limitations of current quantum hardware.
title Solving the 3D Heat Equation with VQA via Remeshing-Based Warm Starts
topic Quantum Physics
Emerging Technologies
url https://arxiv.org/abs/2510.15645