Estimation of Capacity for Channels Connected with Elementary Quantum Random Walks

Finite-dimensional restrictions of the channel describing elementary quantum random walk are discussed in this paper. Capacity of such channels can be accounted via Holevo upper bound, which is evaluated here. Upper estimation is the difference between maximal and minimal output entropy, and lower estimation is given by an ensemble of states with minimal output entropy, such that the output entropy for medium state is as big as possible. For these computations, we use complementary channels because they are much easier to deal with. Both estimations coincide in case of dimension 2. Moreover, in this case the complementary channel is unital cubit, so that the Holevo upper bound equals to the capacity. In large dimensions, the asymptotical estimation is an interval of length $$\log(\frac{e}{2})$$ .

Authors

Institutions

Publication Details

Journal
Lobachevskii Journal of Mathematics
Published
2024-10-01
DOI
https://doi.org/10.1134/s1995080224605666
Citations
1
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimation of Capacity for Channels Connected with Elementary Quantum Random Walks

S. V. Grishin
1 citations
Lobachevskii Journal of Mathematics
Quantum Computing Algorithms and Architecture
0.35
article

Estimation of Capacity for Channels Connected with Elementary Quantum Random Walks

S. V. Grishin
article en
1 citations

Abstract

Finite-dimensional restrictions of the channel describing elementary quantum random walk are discussed in this paper. Capacity of such channels can be accounted via Holevo upper bound, which is evaluated here. Upper estimation is the difference between maximal and minimal output entropy, and lower estimation is given by an ensemble of states with minimal output entropy, such that the output entropy for medium state is as big as possible. For these computations, we use complementary channels because they are much easier to deal with. Both estimations coincide in case of dimension 2. Moreover, in this case the complementary channel is unital cubit, so that the Holevo upper bound equals to the capacity. In large dimensions, the asymptotical estimation is an interval of length $$\log(\frac{e}{2})$$ .

Lobachevskii Journal of MathematicsVol. 45(10)
Russian Academy of Sciences (RU), Steklov Mathematical Institute (RU)
Openalex Percentile: Top 29%
Quantum Computing Algorithms and Architecture
0.35
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.

Estimation of Capacity for Channels Connected with Elementary Quantum Random Walks — S. V. Grishin · Lobachevskii Journal of Mathematics (2024) | TGRS Research Map | TGRS