With the support of the national program on measurements, standards, and evaluation of quantum technologies MetriQs-France, a part of the French national  quantum strategy, the BACQ project(Application-oriented Benchmarks for Quantum Computing)  is dedicated to application-oriented benchmarks for quantum computing. The consortium gathering THALES, EVIDEN, an Atos business, CEA, CNRS, TERATEC, and LNE aims at establishing performance evaluation criteria of reference, meaningful for industry users. Partners will present progress of BACQ project.

In the framework of the BACQ project, a joint effort has been made by the collaboration and several partners to carry out an initial measurement campaign on the existing QPUs using the Q-score metric. In this session, we present groundbreaking achievements by leading quantum computing players: IQM, Pasqal, Quandela, and TNO. They will showcase their Q-score implementations on various qubit technologies and different approaches.

 – Introduction: Damien Nicolazic, Quantum Computing consultant, EVIDEN
IQM: Q-score/Max-Cut With QAOA
– Qubit technology: Superconducting
– Presented by Jami Rönkkö, Quantum engineer
Pasqal: Q-score/Max-Cut with Maximum Independent Set (MIS)
– Qubit technology: Neutral Atom
– Presented by Louis-Paul Henry, researcher
Quandela: Q-score/Max-Cut with Variational Quantum Eigensolver (VQE)
– Qubit technology: Photonic
– Presented by Vassilis Apostolou, researcher
TNO: Q-score/Max-Cut implementation on D-wave
– Research institute: Toegepast Natuurwetenschappelijk Onderzoek
– Presented by Ward van der Schoot, researcher

We give an overview of some important benchmark problems in plasma physics and computational fluid dynamics and discuss their utility. Specifically, we will talk about the Vlasov equation and its applications in inertial confinement fusion. We will also discuss stability problems in magnetohydrodynamics. We will then move to computational fluid dynamics and discuss the lattice Boltmann method. We will talk about current classical approaches to solve them and their approximate complexity. Finally, we will present some interesting and promising quantum approaches to solve these problems.

Benchmarking quantum computers helps to quantify them and bring the technology to the market. Various application-level metrics exist to benchmark a quantum device at an application level. This work presents a revised holistic scoring method called the Quantum Application Score (QuAS) incorporating strong points of previous metrics, such as QPack and the Q-score. We discuss how to integrate both, and thereby obtain an application-level metric that better quantifies the practical utility of quantum computers. We evaluate the new metric on different hardware platforms such as D-Wave and IBM as well as quantum simulators of Quantum Inspire and Rigetti.

This talk provides an overview of research and development efforts, published results, and future plans of the Quantum Economic Development Consortium (QED-C) in establishing an open-source framework for assessing the performance of quantum computing systems through the use of quantum algorithms and applications.  We review the requirements and challenges in developing these methodologies from the perspective of both the developer and the end user.  We show how these benchmarks are structured to sweep over a range of problem sizes and input characteristics, systematically capturing key performance metrics, i.e. quality of result, execution effectiveness (tradeoff between quality and runtime), and resources consumed, with supporting infrastructure and abstractions that make them accessible to a broad audience of users.  Looking to the future, we introduce upcoming work and proposals for additional efforts to facilitate the exploration of quantum algorithmic options and their impact on performance in this continually evolving benchmarking framework.

Quantum systems are now entering HPC centers and their integration as accelerators into HPC workflows is underway. Given their early technological state, diverse architectures and rapid evolution, quantum accelerators pose unique challenges for reliable and useful benchmarks to characterize their performance and error profiles. Further, as we integrate quantum processors into HPC, there is a growing need for benchmarks tailored to these hybrid workflows to accurately characterize the interplay of these resources and guide optimization and resource allocation. This talk will explore the overall state of quantum-HPC integration, the challenges of benchmarking quantum and quantum-HPC systems, and our efforts at LRZ on these topics.

There is little or no consensus on what constitutes a representative and useful benchmark for quantum computers. Literature on quantum benchmarks exists in disparate journals and repositories, comparison between published ad hoc benchmark metrics is difficult, and there is no central community hub to vet and discuss published results. Despite this, many hardware providers developing prototypes are already attempting to pivot to commercialization of NISQ devices. The Metriq platform (https://metriq.info) is an open-source community hub and repository for review of the capabilities of quantum computers in general public use and in peer-reviewed literature. Metriq fits open-ended community-contributed research literature results to a simple standardized schema that enables automatic comparison and graphing of quantum technologies across the field on common “tasks,” comparing “methods” operating on “platforms,” achieving “results” that can be fairly compared over time. Through Unitary Fund’s online community-building initiative and support by a recently inaugurated quantum open-benchmark committee, we aim to simplify publication and tracking of quantum benchmarks.