Papers
Topics
Authors
Recent
Search
2000 character limit reached

The Moreau-Yosida approximation of the Entanglement of Formation: basic properties and accuracy estimates

Published 24 Sep 2026 in quant-ph and math-ph | (2609.30246v1)

Abstract: We describe a family of convex uniformly continuous functions E<sup>λFE<sup>λ_F, $λ&gt;0$, on the set of states of a bipartite quantum system (consisting of finite-dimensional or infinite-dimensional subsystems), which monotonically increase and converge pointwise to the Entanglement of Formation (EoF) as λ→0λ\to0. These functions are "nonselective" entanglement monotones defined by the way close to the construction of the Moreau-Yosida regularization (the Moreau envelope) of a convex function on a convex set used in the modern convex analysis. So, we call the functions E<sup>λFE<sup>λ_F the Moreau-Yosida approximations of the EoF and describe their equivalent definitions and basic properties. The semicontinuity bounds for the EoF (presented in [Lob.J.Math., 46(6), 2632-2658]) allow us to obtain easily computable upper bounds on the difference EF(ρ)−E<sup>λF(ρ)E_F(ρ)-E<sup>λ_F(ρ) for a given state ρρ. These bounds give easily computable bounds on the rate of uniform convergence of the function E<sup>λFE<sup>λ_F to the EoF as λ→0<sup>+λ\to0<sup>+ on the sets of states with bounded rank/energy of one of the marginal states. We also discuss sufficient conditions for the coincidence of EF(ρ)E_F(ρ) and E<sup>λF(ρ)E<sup>λ_F(ρ) at a given state ρρ for all λλ small enough and consider several classes of states for which such coincidence takes place. The conjectured selective LOCC-monotonicity of the functions E<sup>λFE<sup>λ_F and a possible way to prove it are briefly discussed. Secondary parts of the article are written with the help of ChatGPT-5.6.

Authors (1)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Tweets

Sign up for free to view the 1 tweet with 0 likes about this paper.