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Differential Equation Quantum Solvers: Engineering Measurements to Reduce Cost by Paine, Annie; Gyurik, Casper; Gentile, Antonio Andrea is a scholarly article available to read on EtoBox.

What is Differential Equation Quantum Solvers: Engineering Measurements to Reduce Cost about?

Quantum computers have been proposed as a solution for efficiently solving non-linear differential equations (DEs), a fundamental task across diverse technological and scientific domains. However, a crucial milestone in this regard is to design protocols that are hardware-aware, making efficient use of limited available quantum resources. We focus here on promising variational methods derived from scientific machine learning: differentiable quantum circuits (DQC), addressing specifically their cost in number of circuit evaluations. Reducing the number of quantum circuit evaluations is particularly valuable in hybrid quantum/classical protocols, where the time required to interface and run quantum hardware at each cycle can impact the total wall-time much more than relatively inexpensive classical post-processing overhead. Here, we propose and test two sample-efficient protocols for solving non-linear DEs, achieving exponential savings in quantum circuit evaluations. These protocols are based on redesigning the extraction of information from DQC in a ``measure-first" approach, by introducing engineered cost operators similar to the randomized-measurement toolbox (i.e. classical shad

Author

Paine, Annie; Gyurik, Casper; Gentile, Antonio Andrea

Published

2025

Language

EN