Quantum Rounding

TL;DR

This paper presents novel quantum rounding techniques that leverage multiple samples to reduce arithmetic errors in quantum computations, significantly improving efficiency in quantum multiplication.

Contribution

Introduction of quantum rounding methods that use multiple samples to stochastically suppress rounding errors, reducing gate counts and depths in quantum multiplication.

Findings

Gate counts and depths reduced by 2-3X

Maintains similar qubit usage

Effective for fixed-point multiplication

Abstract

We introduce new rounding methods to improve the accuracy of finite precision quantum arithmetic. These quantum rounding methods are applicable when multiple samples are being taken from a quantum program. We show how to use multiple samples to stochastically suppress arithmetic error from rounding. We benchmark these methods on the multiplication of fixed-point numbers stored in quantum registers. We show that the gate counts and depths for multiplying to a target accuracy can be reduced by approximately 2-3X over state of the art methods while using roughly the same number of qubits.