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insight - Quantum Information Theory - # Quantum Doeblin Coefficients and Their Applications

Efficiently Bounding Contraction and Expansion Coefficients for Quantum Channels Using Quantum Doeblin Coefficients


Conceitos essenciais
Quantum Doeblin coefficients provide an efficiently computable upper bound on a wide class of contraction coefficients, which quantify the decrease in information under quantum channels. The author also introduces reverse Doeblin coefficients that lower bound certain expansion coefficients.
Resumo

The author introduces the concept of quantum Doeblin coefficients as a quantum generalization of the classical Doeblin minorization condition. The quantum Doeblin coefficient α(N) of a quantum channel N is defined as the largest erasure probability ϵ such that the quantum erasure channel Eϵ is degradable with respect to N.

The author proves that the quantum Doeblin coefficient provides an upper bound on the contraction coefficients ηf(N) for a wide class of f-divergences, including the relative entropy and trace distance. This makes the quantum Doeblin coefficient a valuable tool, as contraction coefficients are notoriously hard to compute.

The author also introduces the transpose quantum Doeblin coefficient αT(N), which gives an improved bound for positive partial transpose (PPT) channels. Additionally, the author defines reverse Doeblin coefficients q
α(N) and q
αT(N) that lower bound the expansion coefficients for the trace distance.

The author discusses several properties of the Doeblin coefficients, such as concavity, super-multiplicativity, and concatenation. The coefficients can also be expressed as semidefinite programs, making them efficiently computable.

The author provides examples for the depolarizing channel and the generalized amplitude damping channel, demonstrating the usefulness of the Doeblin coefficients in bounding contraction and expansion coefficients. The author also discusses potential applications in resource theories and bounds on information-theoretic quantities like quantum capacity.

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Principais Insights Extraídos De

by Christoph Hi... às arxiv.org 05-02-2024

https://arxiv.org/pdf/2405.00105.pdf
Quantum Doeblin coefficients: A simple upper bound on contraction  coefficients

Perguntas Mais Profundas

How can the quantum Doeblin coefficients be further improved or generalized to tighten the bounds on contraction coefficients for a wider range of quantum channels

To further improve or generalize the quantum Doeblin coefficients and tighten the bounds on contraction coefficients for a wider range of quantum channels, several approaches can be considered: Exploring Different Channel Orders: Investigate other partial orders beyond degradability, transpose degradability, and more capable orders. By defining new partial orders that capture different aspects of channel behavior, it may be possible to derive alternative Doeblin-type coefficients that provide tighter bounds on contraction coefficients. Incorporating Resource Theories: Extend the concept of quantum Doeblin coefficients to specific resource theories. By defining partial orders based on the free operations and states of a given resource theory, it may be possible to derive coefficients that offer more nuanced insights into the information processing capabilities of quantum channels within the context of specific resources. Utilizing Different Channel Classes: Investigate the behavior of quantum channels within different classes, such as unitary channels, entanglement-breaking channels, or channels with specific properties. By analyzing how these channels interact with various partial orders, it may be possible to derive specialized Doeblin coefficients that provide more refined bounds on contraction coefficients for specific types of channels. Considering Information Measures Beyond Contraction Coefficients: Explore the implications of quantum Doeblin coefficients on other information measures beyond contraction coefficients. By analyzing how these coefficients relate to capacities, entropies, or other information-theoretic quantities, it may be possible to gain a deeper understanding of the overall information processing capabilities of quantum channels.

Are there other partial orders or channels that could be used to define alternative Doeblin-type coefficients, and how would those compare to the ones introduced in this work

To define alternative Doeblin-type coefficients, other partial orders or channels can be considered: More Capable Partial Order: Explore the implications of the more capable partial order on defining Doeblin coefficients. By comparing quantum channels to channels that are more capable in terms of information transmission, it may be possible to derive coefficients that capture the relative information processing efficiency of different channels. Entanglement Measures: Investigate the use of entanglement measures or entanglement-breaking channels in defining Doeblin coefficients. By analyzing how quantum channels interact with entanglement resources, it may be possible to derive coefficients that quantify the impact of entanglement on information processing capabilities. Non-Linear Channel Orders: Consider non-linear channel orders that capture more complex relationships between channels. By defining partial orders that go beyond linear comparisons, it may be possible to derive coefficients that offer a more nuanced understanding of the information processing dynamics of quantum channels. Resource-Dependent Orders: Define partial orders based on specific quantum resources, such as coherence, discord, or quantum correlations. By analyzing how channels behave with respect to these resources, it may be possible to derive coefficients that reflect the resource-dependent information processing capabilities of quantum channels.

What are the implications of the trivial expansion coefficients observed for certain divergences, and how can this be leveraged to gain a better understanding of the data processing range of different information measures

The implications of trivial expansion coefficients for certain divergences suggest that for those specific cases, the channels do not introduce any additional information or complexity to the input states. This can be leveraged to gain a better understanding of the data processing range of different information measures in the following ways: Identifying Informationally Trivial Channels: Trivial expansion coefficients indicate channels that do not alter the information content of the input states. By recognizing these channels, one can identify scenarios where the information processing range is limited, and the channels do not contribute to information transformation or enhancement. Analyzing Information Preservation: Trivial expansion coefficients highlight channels that preserve the information content of the input states. This can be valuable in scenarios where information retention or fidelity is crucial, providing insights into the behavior of channels that maintain the integrity of quantum information. Exploring Channel Redundancy: Trivial expansion coefficients may indicate redundant or unnecessary channels in certain information processing tasks. By understanding the data processing range of these channels, one can optimize information flows and streamline communication processes by eliminating redundant channels that do not contribute to information enhancement.
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