Variational quantum algorithms on cat qubits

TL;DR

This paper investigates the implementation of Variational Quantum Algorithms on cat qubits, analyzing noise resilience through simulations with different noise models to identify thresholds for reliable quantum computation.

Contribution

It introduces a comparison of hardware-agnostic and cat qubit-specific noise models for VQAs, highlighting the importance of accurate noise modeling for quantum algorithm reliability.

Findings

Noise thresholds for reliable VQA execution on cat qubits identified

Hardware-specific noise models provide more accurate insights than generic models

Simulations demonstrate the resilience of cat qubits to certain noise levels

Abstract

Variational Quantum Algorithms (VQA) have emerged with a wide variety of applications. One question to ask is either they can efficiently be implemented and executed on existing architectures. Current hardware suffers from uncontrolled noise that can alter the expected results of one calculation. The nature of this noise is different from one technology to another. In this work, we chose to investigate a technology that is intrinsically resilient to bit-flips: cat qubits. To this end, we implement two noise models. The first one is hardware-agnostic -- in the sense that it is used in the literature to cover different hardware types. The second one is specific to cat qubits. We perform simulations on two types of problems that can be formulated with VQAs (Quantum Approximate Optimization Algorithm (QAOA) and the Variatinoal Quantum Linear Soler (VQLS)), study the impact of noise on the evolution of the cost function and extract noise level thresholds from which a noise-resilient regime can be considered. By tackling compilation issues, we discuss the need of implementing hardware-specific noise models as hardware-agnostic ones can lead to misleading conclusions regarding the regime of noise that is acceptable for an algorithm to run.