Pith. sign in

REVIEW 1 cited by

Q#: Enabling scalable quantum computing and development with a high-level domain-specific language

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 1803.00652 v1 pith:VSTB55QI submitted 2018-03-01 quant-ph cs.ETcs.PL

classification quant-phcs.ETcs.PL
keywords quantumcomputinglanguageapproachclassicalcomputationsconstructsdomain-specific
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Quantum computing exploits quantum phenomena such as superposition and entanglement to realize a form of parallelism that is not available to traditional computing. It offers the potential of significant computational speed-ups in quantum chemistry, materials science, cryptography, and machine learning. The dominant approach to programming quantum computers is to provide an existing high-level language with libraries that allow for the expression of quantum programs. This approach can permit computations that are meaningless in a quantum context; prohibits succinct expression of interaction between classical and quantum logic; and does not provide important constructs that are required for quantum programming. We present Q#, a quantum-focused domain-specific language explicitly designed to correctly, clearly and completely express quantum algorithms. Q# provides a type system, a tightly constrained environment to safely interleave classical and quantum computations; specialized syntax, symbolic code manipulation to automatically generate correct transformations of quantum operations, and powerful functional constructs which aid composition.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Taxonomy of migration scenarios for Qiskit refactoring using LLMs

    cs.SE 2025-06 conditional novelty 5.0 of 10

    LLMs can generate a structured taxonomy of Qiskit migration and refactoring scenarios that largely overlaps with an expert-built taxonomy and adds some scenarios.

Pith tools