Pith. sign in

REVIEW 5 cited by

QASMBench: A Low-level QASM Benchmark Suite for NISQ Evaluation and Simulation

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2005.13018 v3 pith:MYKX5HSQ submitted 2020-05-26 quant-ph

classification quant-ph
keywords nisqqasmbenchbenchmarkcircuitdensityevaluationexecutionibm-q
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, etc., trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, which comprises 25K circuit evaluations. We also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system. QASMBench is released at: http://github.com/pnnl/QASMBench.

Discussion (0). Sign in to comment.

Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. InferQ: A Database-Oriented Benchmark for Quantum Circuits Simulation

    quant-ph 2026-07 conditional novelty 7.0 of 10

    InferQ generates 202,975 compositional quantum circuits as SQL workloads and shows RDBMS engines beat Qiskit Aer on peak memory for ~51% of them, with ML selectors predicting the best backend at up to 95-97% accuracy.

  2. Finding trail covers: near-optimal decompositions of graph states as linear fusion networks

    quant-ph 2025-08 conditional novelty 7.0 of 10

    The fusion-minimization problem for photonic graph states is formalized as minimum trail cover; most bounded variants are NP-hard, but heuristics plus a TSP reduction give near-optimal fusion counts in benchmarks.

  3. Harvest: Resource-Aware Quantum Compilation for Magic State Protocols

    quant-ph 2026-08 conditional novelty 6.0 of 10

    Harvest co-optimizes placement, routing, scheduling, and magic-state supply for lattice-surgery quantum programs, reporting up to 17.8x speedup over sequential execution and reclaiming up to 72% of unused magic-state patches.

  4. Magnetohydrodynamic drag on an oscillating sphere in a rotating spherical cavity

    physics.flu-dyn 2026-04 unverdicted novelty 6.0 of 10

    A unified asymptotic theory for oscillatory magnetohydrodynamic drag on a sphere in a rotating spherical cavity, covering confinement, viscosity, rotation and magnetic coupling, with DNS checks.

  5. Quantum Fidelity-per-Cost: A Metric for Evaluation of Quantum Computing Systems

    quant-ph 2026-07 conditional novelty 5.5 of 10

    Cost-aware ranking of cloud QPUs via QFC disagrees with fidelity-only ranking; billing model, not hardware, fixes how the score scales with shot count.

Pith tools