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Entanglement Distillation Optimization using Fuzzy Relations for Quantum State Tomography
Version 1
: Received: 1 June 2023 / Approved: 2 June 2023 / Online: 2 June 2023 (14:08:44 CEST)
A peer-reviewed article of this Preprint also exists.
Ganesan, T.; Elamvazuthi, I. Entanglement Distillation Optimization Using Fuzzy Relations for Quantum State Tomography. Algorithms 2023, 16, 313. Ganesan, T.; Elamvazuthi, I. Entanglement Distillation Optimization Using Fuzzy Relations for Quantum State Tomography. Algorithms 2023, 16, 313.
Abstract
Practical entanglement distillation is a critical component in quantum information theory. Entanglement distillation is often utilized for designing quantum computer networks and quantum repeaters. The practical entanglement distillation problem is formulated as a bilevel optimization problem. A fuzzy formulation is introduced to estimate the quantum state (density matrix) from pseudo-likelihood functions (i.e., quantum state tomography). A scale-independent relationship between fuzzy relations in terms of the pseudo-likelihood functions is obtained. The entanglement distillation optimization problem was solved using the combined coupled map lattice and dual annealing approach. Comparative analysis of the results is then conducted against a standard dual annealing algorithmic implementation.
Keywords
practical entanglement distillation; bilevel optimization; fuzzy formulation; quantum state tomography; coupled map lattices; dual annealing
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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