A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Differential equations (DEs) serve as fundamental tools in mathematical modeling across scientific disciplines, yet classical numerical solvers face limitations with large-scale or computationally intensive problems. This study explores a quantum-inspired approach to solving DEs, combining quantum-inspired techniques with classical methods. It focuses on fixed-point arithmetic on quantum circuits, utilizing basic quantum gates to manipulate DE solutions. We expand upon the techniques introduced by Zanger et al. [Quantum, 5, 502 (2021)] by offering a precise computation for a fixed-point signed multiplication scheme, while also presenting a quantum circuit capable of executing the fixed-point division algorithm. We demonstrate the feasibility of our approach through the simulation of a linear Ordinary Differential Equation (ODE), where initial conditions and parameters are encoded into quantum circuits using fixed-point representation. By executing sequences of quantum gates mimicking numerical integration steps, we obtain approximate solutions to the ODE with specified fixed-point precision.

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Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.00016
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
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article

A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Riccardo Lattanzi, Oluwadara Ogunkoya, Norm M. Tubman, Dog̃a Murat Kürkçüog̃lu et al.
Matrix Theory and Algorithms
article

A Quantum Approach for Implementing Fixed-Point Arithmetic in Solving Ordinary Differential Equations

Riccardo Lattanzi, Oluwadara Ogunkoya, Norm M. Tubman, Dog̃a Murat Kürkçüog̃lu, Nicholas Bornman, José E. Cruz Serrallés, Silvia Zorzetti
article en

Abstract

Differential equations (DEs) serve as fundamental tools in mathematical modeling across scientific disciplines, yet classical numerical solvers face limitations with large-scale or computationally intensive problems. This study explores a quantum-inspired approach to solving DEs, combining quantum-inspired techniques with classical methods. It focuses on fixed-point arithmetic on quantum circuits, utilizing basic quantum gates to manipulate DE solutions. We expand upon the techniques introduced by Zanger et al. [Quantum, 5, 502 (2021)] by offering a precise computation for a fixed-point signed multiplication scheme, while also presenting a quantum circuit capable of executing the fixed-point division algorithm. We demonstrate the feasibility of our approach through the simulation of a linear Ordinary Differential Equation (ODE), where initial conditions and parameters are encoded into quantum circuits using fixed-point representation. By executing sequences of quantum gates mimicking numerical integration steps, we obtain approximate solutions to the ODE with specified fixed-point precision.

Ames Research Center (US), Fermi National Accelerator Laboratory (US), New York University (US)
Openalex Percentile: Top 70%
Matrix Theory and Algorithms
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