Quick Navigation

Overview Topics Abstract Importance Paper Tools References Reactions Discussion Publication Related

Topics

Quantum Machine Learning

RepLAB: a computational/numerical approach to representation theory

arXiv

Authors: Denis Rosset, Felipe Montealegre-Mora, Jean-Daniel Bancal

Year

2019

Paper ID

14658

Status

Preprint

Abstract Read

~2 min

Abstract Words

Citations

N/A

Abstract

We present a MATLAB/Octave toolbox to decompose finite dimensionial representations of compact groups. Surprisingly, little information about the group and the representation is needed to perform that task. We discuss applications to semidefinite programming.

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 present a MATLAB/Octave toolbox to decompose finite dimensionial representations of compact groups.

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:1911.09154 [2] arXiv https://arxiv.org/abs/1911.09154 [3] Publisher https://arxiv.org/abs/1911.09154

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.