Solving 1D Poisson problem with a Variational Quantum Linear Solver
Giorgio Tosti Balducci, Boyang Chen, Matthias M\"oller, Roeland De, Breuker

TL;DR
This paper introduces a new method using the variational quantum linear solver (VQLS) to efficiently solve 1D tridiagonal linear systems, demonstrating its effectiveness through simulations and real hardware experiments.
Contribution
It proposes a novel matrix decomposition for tridiagonal systems tailored for VQLS, balancing circuit depth and term complexity, and provides the first hardware implementation results.
Findings
Successful simulation of VQLS on tridiagonal systems.
First real-hardware demonstration of VQLS for this problem.
Decomposition reduces circuit complexity and improves implementability.
Abstract
Different hybrid quantum-classical algorithms have recently been developed as a near-term way to solve linear systems of equations on quantum devices. However, the focus has so far been mostly on the methods, rather than the problems that they need to tackle. In fact, these algorithms have been run on real hardware only for problems in quantum physics, such as Hamiltonians of a few qubits systems. These problems are particularly favorable for quantum hardware, since their matrices are the sum of just a few unitary terms and since only shallow quantum circuits are required to estimate the cost function. However, for many interesting problems in linear algebra, it appears far less trivial to find an efficient decomposition and to trade it off with the depth of the cost quantum circuits. A first simple yet interesting instance to consider are tridiagonal systems of equations. These arise,…
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Taxonomy
TopicsNonlinear Waves and Solitons · Advanced Mathematical Theories · Mathematical functions and polynomials
