Generalized subsystems defined as quantum-channel outputs equilibrate when their dimension is small relative to the effective dimension of discarded microscopic information, with the bound holding for typical initial states in large subspaces and recovering standard results.
Renyi-entropic bounds on quantum communication
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abstract
In this article we establish new bounds on the quantum communication complexity of distributed problems. Specifically, we consider the amount of communication that is required to transform a bipartite state into another, typically more entangled, state. We obtain lower bounds in this setting by studying the Renyi entropy of the marginal density matrices of the distributed system. The communication bounds on quantum state transformations also imply lower bounds for the model of communication complexity where the task consists of the the distributed evaluation of a function f(x,y). Our approach encapsulates several known lower bound methods that use the log-rank or the von Neumann entropy of the density matrices involved. The technique is also effective for proving lower bounds on problems involving a promise or for which the "hard" distributions of inputs are correlated. As examples, we show how to prove a nearly tight bound on the bounded-error quantum communication complexity of the inner product function in the presence of unlimited amounts of EPR-type entanglement and a similarly strong bound on the complexity of the shifted quadratic character problem.
fields
quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Defines antiflatness of entanglement spectra, introduces antiflat majorization and FPOs for state convertibility, unifies measures via escort distributions and Bregman divergences, expresses Capacity of Entanglement as KL divergence derivative linked to QFI, and identifies maximal antiflatness on a
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Equilibration of generalized subsystems: a quantum-channel approach
Generalized subsystems defined as quantum-channel outputs equilibrate when their dimension is small relative to the effective dimension of discarded microscopic information, with the bound holding for typical initial states in large subspaces and recovering standard results.
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A journey through Flatland: What does the antiflatness of a spectrum teach us?
Defines antiflatness of entanglement spectra, introduces antiflat majorization and FPOs for state convertibility, unifies measures via escort distributions and Bregman divergences, expresses Capacity of Entanglement as KL divergence derivative linked to QFI, and identifies maximal antiflatness on a