Heisenberg scaling based on population coding

We study Heisenberg scaling of quantum metrology in the viewpoint of population coding. Although Fisher information has been used for a figure of merit to characterize Heisenberg scaling in quantum metrology, several studies pointed out it does not work as a figure of merit because it does not reflect the global structure. As an alternative figure of merit, we propose the mutual information, which connects the number of distinguishable elements of the parameter space in the viewpoint of population coding. We show that several unitary models achieve Heisenberg scaling in this context.

Authors

Institutions

Publication Details

Journal
Quantum
Published
2025-02-26
DOI
https://doi.org/10.22331/q-2025-02-26-1648
Citations
1
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heisenberg scaling based on population coding

Masahito Hayashi
1 citations
Quantum
Blind Source Separation Techniques
1.49
article

Heisenberg scaling based on population coding

Masahito Hayashi
article en
1 citations

Abstract

We study Heisenberg scaling of quantum metrology in the viewpoint of population coding. Although Fisher information has been used for a figure of merit to characterize Heisenberg scaling in quantum metrology, several studies pointed out it does not work as a figure of merit because it does not reflect the global structure. As an alternative figure of merit, we propose the mutual information, which connects the number of distinguishable elements of the parameter space in the viewpoint of population coding. We show that several unitary models achieve Heisenberg scaling in this context.

QuantumVol. 9
Chinese University of Hong Kong, Shenzhen (CN), Beijing Academy of Quantum Information Sciences (CN), Nagoya University (JP)
Openalex Percentile: Top 23%
Blind Source Separation Techniques
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.