Quick Navigation

Overview Topics Abstract Importance Paper Tools References Reactions Discussion Publication Related

Topics

Quantum Machine Learning

staq - A full-stack quantum processing toolkit

arXiv

Authors: Matthew Amy, Vlad Gheorghiu

Year

2019

Paper ID

39926

Status

Preprint

Abstract Read

~2 min

Abstract Words

Citations

N/A

Abstract

We describe 'staq', a full-stack quantum processing toolkit written in standard C++. 'staq' is a quantum compiler toolkit, comprising of tools that range from quantum optimizers and translators to physical mappers for quantum devices with restricted connectives. The design of 'staq' is inspired from the UNIX philosophy of "less is more", i.e. 'staq' achieves complex functionality via combining (piping) small tools, each of which performs a single task using the most advanced current state-of-the-art methods. We also provide a set of illustrative benchmarks.

Why This Paper Matters

This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
It adds a 2019 reference point for readers tracking recent quantum research.
We describe 'staq', a full-stack quantum processing toolkit written in standard C++.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Become a member Sign in

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

[1] DOI https://doi.org/arXiv:1912.06070 [2] arXiv https://arxiv.org/abs/1912.06070 [3] Publisher https://arxiv.org/abs/1912.06070

Local Citation Graph (Related-Paper Links)

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0

Likes: 0 Dislikes: 0

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.