Quick Navigation

Topics

Quantum Algorithms

Quantum guessing games with posterior information

arXiv
Authors: Claudio Carmeli, Teiko Heinosaari, Alessandro Toigo

Year

2021

Paper ID

62919

Status

Preprint

Abstract Read

~2 min

Abstract Words

111

Citations

N/A

Abstract

Quantum guessing games form a versatile framework for studying different tasks of information processing. A quantum guessing game with posterior information uses quantum systems to encode messages and classical communication to give partial information after a quantum measurement has been performed. We present a general framework for quantum guessing games with posterior information and derive structure and reduction theorems that enable to analyze any such game. We formalize symmetry of guessing games and characterize the optimal measurements in cases where the symmetry is related to an irreducible representation. The application of guessing games to incompatibility detection is reviewed and clarified. All the presented main concepts and results are demonstrated with examples.

Why This Paper Matters

  • It adds a 2021 reference point for readers tracking recent quantum research.
  • Quantum guessing games form a versatile framework for studying different tasks of information processing.

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.

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

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #62919 #69028 Unified Framework for Functiona... #69026 Bures geodesics for non-faithfu... #69024 Cyclic ladder operators and hid... #69021 Nonreciprocal optomechanical en...

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.