MQT Bench: Benchmarking Software and Design Automation Tools for Quantum Computing

Abstract

Quantum software tools for a wide variety of design tasks on and across different levels of abstraction are crucial in order to eventually realize useful quantum applications. This requires practical and relevant benchmarks for new software tools to be empirically evaluated and compared to the current state of the art. Although benchmarks for specific design tasks are commonly available, the demand for an overarching cross-level benchmark suite has not yet been fully met and there is no mutual consolidation in how quantum software tools are evaluated thus far. In this work, we propose the MQT Bench benchmark suite (as part of the Munich Quantum Toolkit, MQT) based on four core traits: (1) cross-level support for different abstraction levels, (2) accessibility via an easy-to-use web interface (https://www.cda.cit.tum.de/mqtbench) and a Python package, (3) provision of a broad selection of benchmarks to facilitate generalizability, as well as (4) extendability to future algorithms, gate-sets, and hardware architectures. By comprising more than 70,000 benchmark circuits ranging from 2 to 130 qubits on four abstraction levels, MQT Bench presents a first step towards benchmarking different abstraction levels with a single benchmark suite to increase comparability, reproducibility, and transparency.

14 pages, 4 figures, MQT Bench is hosted at https://www.cda.cit.tum.de/mqtbench/, revised layout and updated tool

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Cited by in corpus (48)

• Benchmarking quantum computers
• The MQT Handbook: A Summary of Design Automation Tools and Software for Quantum Computing
• QFaaS: A Serverless Function-as-a-Service Framework for Quantum Computing
• Equivalence Checking of Quantum Circuits with the ZX-Calculus
• Compiler Optimization for Quantum Computing Using Reinforcement Learning
• Quantum Architecture Search: A Survey
• MQT QMAP: Efficient Quantum Circuit Mapping
• Computational Capabilities and Compiler Development for Neutral Atom Quantum Processors: Connecting Tool Developers and Hardware Experts
• Predicting Good Quantum Circuit Compilation Options
• MQT Predictor: Automatic Device Selection with Device-Specific Circuit Compilation for Quantum Computing
• Benchmarking the performance of quantum computing software
• Simulation Paths for Quantum Circuit Simulation with Decision Diagrams
• Quantum algorithms for scientific computing
• An Abstract Model and Efficient Routing for Logical Entangling Gates on Zoned Neutral Atom Architectures
• SCIM MILQ: An HPC Quantum Scheduler
• An Accurate and Efficient Analytic Model of Fidelity Under Depolarizing Noise Oriented to Large Scale Quantum System Design
• FragQC: An Efficient Quantum Error Reduction Technique using Quantum Circuit Fragmentation
• Near-Term Spin-Qubit Architecture Design via Multipartite Maximally-Entangled States
• beSnake: A routing algorithm for scalable spin-qubit architectures
• Quantum Circuit Mutants: Empirical Analysis and Recommendations
• Quantum Data Centers in the Presence of Noise
• Towards Supporting QIR: Steps for Adopting the Quantum Intermediate Representation
• Mantra: Rewriting Quantum Programs to Minimize Trap-Movements for Zoned Rydberg Atom Arrays
• Quantum Circuit Simulation with Fast Tensor Decision Diagram
• MIRAGE: Quantum Circuit Decomposition and Routing Collaborative Design using Mirror Gates
• AEQUAM: Accelerating Quantum Algorithm Validation through FPGA-Based Emulation
• The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
• Improving Figures of Merit for Quantum Circuit Compilation
• Multi-controlled Phase Gate Synthesis with ZX-calculus applied to Neutral Atom Hardware
• Synchronization for Fault-Tolerant Quantum Computers
• Multithreaded parallelism for heterogeneous clusters of QPUs
• QSteed: A Resource-Virtualized and Hardware-Aware Quantum Compilation Framework for Real Quantum Computing Processors
• Equivalence Checking of Quantum Circuits via Path-Sum and Weighted Model Counting
• Typical Machine Learning Datasets as Low-Depth Quantum Circuits
• Qonductor: A Cloud Orchestrator for Quantum Computing
• Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures
• Routing-Aware Placement for Zoned Neutral Atom-based Quantum Computing
• Exploration of Design Alternatives for Reducing Idle Time in Shor's Algorithm: A Study on Monolithic and Distributed Quantum Systems
• Compilation Techniques for Spin Qubits in a Shuttling Bus Architecture
• Distributing Quantum Computations, Shot-wise
• High-Precision Multi-Qubit Clifford+T Synthesis by Unitary Diagonalization
• Overhead in Quantum Circuits with Time-Multiplexed Qubit Control
• Graph Neural Network-Based Predictor for Optimal Quantum Hardware Selection
• Quantum Circuit Pruning: Improving Fidelity via Compilation-Aware Circuit Approximation
• Dependency-Aware Circuit Scheduling for Multi-Core Quantum Systems to Minimize Makespan
• PyQBench: a Python library for benchmarking gate-based quantum computers
• QAISim: A Toolkit for Modeling and Simulation of AI in Quantum Cloud Computing Environments
• Quantum Resource Management in the NISQ Era: Challenges, Vision, and a Runtime Framework