2021
DOI: 10.1109/tit.2020.3034471
|View full text |Cite
|
Sign up to set email alerts
|

Computing Quantum Channel Capacities

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
29
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
2

Relationship

1
7

Authors

Journals

citations
Cited by 26 publications
(29 citation statements)
references
References 38 publications
0
29
0
Order By: Relevance
“…For any two channels B and B, each either degradable or anti-degradable, the joint channel B ⊗ B has additive coherent information. For a degradable channel B, the coherent information ∆(B, ρ a ) is concave in ρ a [64], and thus Q (1) (B) can be computed with relative ease [65,66]. As a result the quantum capacity of a degradable channel, which simply equals Q (1) (B), can also be computed efficiently.…”
Section: Special Channel Classesmentioning
confidence: 99%
“…For any two channels B and B, each either degradable or anti-degradable, the joint channel B ⊗ B has additive coherent information. For a degradable channel B, the coherent information ∆(B, ρ a ) is concave in ρ a [64], and thus Q (1) (B) can be computed with relative ease [65,66]. As a result the quantum capacity of a degradable channel, which simply equals Q (1) (B), can also be computed efficiently.…”
Section: Special Channel Classesmentioning
confidence: 99%
“…For any two channels B and B, each either degradable or anti-degradable, the joint channel B ⊗B has additive coherent information, i.e., equality holds in (7) [11,32]. For a degradable channel B, the coherent information ∆(B, ρ a ) is concave in ρ a [64], and thus Q (1) (B) can be computed with relative ease [15,40]. As a result the quantum capacity of a degradable channel, which simply equals Q (1) (B), can also be computed efficiently.…”
Section: Special Channel Classesmentioning
confidence: 99%
“…and 0 ≤ u ≤ 1. In ( 39), (40), and (41) the maximization is over a density operator ρ a (u) which is supported over a subspace of the H ai form (21). In Secs.…”
Section: Channel Coherent Informationmentioning
confidence: 99%
“…Hence, the optimization ( 30) is a convex optimization that can be carried out efficiently for small system sizes [30]. Indeed, we have successfully computed the thermodynamic capacity of simple example quantum channels acting on few qubits with Python code, using the QuTip framework [31,32] and the CVXOPT optimization software [33] (see also [34] for a direct algorithm). The thermodynamic capacity is additive [21].…”
Section: Propertiesmentioning
confidence: 99%