Quantum multi-row iteration algorithm for linear systems with non-square coefficient matrices

Fuente: arXiv
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Hauptverfasser: Lin, Weitao, Tian, Guojing, Sun, Xiaoming
Format: Preprint
Veröffentlicht: 2024
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author Lin, Weitao
Tian, Guojing
Sun, Xiaoming
author_facet Lin, Weitao
Tian, Guojing
Sun, Xiaoming
contents In the field of quantum linear system algorithms, quantum computing has realized exponential computational advantages over classical computing. However, the focus has been on square coefficient matrices, with few quantum algorithms addressing non-square matrices. Towards this kind of problems defined by $ Ax = b $ where $ A $$ \in\mathbb{R}^{m \times n} $, we propose a quantum algorithm inspired by the classical multi-row iteration method and provide an explicit quantum circuit based on the quantum comparator and Quantum Random Access Memory (QRAM). The time complexity of our quantum multi-row iteration algorithm is $ O(K \log m) $, with $ K $ representing the number of iteration steps, which demonstrates an exponential speedup compared to the classical version. Based on the convergence of the classical multi-row iteration algorithm, we prove that our quantum algorithm converges faster than the quantum one-row iteration algorithm presented in [Phys. Rev. A, 101, 022322 (2020)]. Moreover, our algorithm places less demand on the coefficient matrix, making it suitable for solving inconsistent systems and quadratic optimization problems.
format Preprint
id arxiv_https___arxiv_org_abs_2409_04010
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum multi-row iteration algorithm for linear systems with non-square coefficient matrices
Lin, Weitao
Tian, Guojing
Sun, Xiaoming
Quantum Physics
Emerging Technologies
In the field of quantum linear system algorithms, quantum computing has realized exponential computational advantages over classical computing. However, the focus has been on square coefficient matrices, with few quantum algorithms addressing non-square matrices. Towards this kind of problems defined by $ Ax = b $ where $ A $$ \in\mathbb{R}^{m \times n} $, we propose a quantum algorithm inspired by the classical multi-row iteration method and provide an explicit quantum circuit based on the quantum comparator and Quantum Random Access Memory (QRAM). The time complexity of our quantum multi-row iteration algorithm is $ O(K \log m) $, with $ K $ representing the number of iteration steps, which demonstrates an exponential speedup compared to the classical version. Based on the convergence of the classical multi-row iteration algorithm, we prove that our quantum algorithm converges faster than the quantum one-row iteration algorithm presented in [Phys. Rev. A, 101, 022322 (2020)]. Moreover, our algorithm places less demand on the coefficient matrix, making it suitable for solving inconsistent systems and quadratic optimization problems.
title Quantum multi-row iteration algorithm for linear systems with non-square coefficient matrices
topic Quantum Physics
Emerging Technologies
url https://arxiv.org/abs/2409.04010