Minimax estimation of low-rank quantum states and their linear functionals
Samriddha Lahiry, Michael Nussbaum

TL;DR
This paper extends classical and quantum asymptotic equivalence results to low-rank quantum states, providing optimal estimation methods for these states and their linear functionals in high-dimensional quantum systems.
Contribution
It generalizes quantum local asymptotic equivalence to low-rank states and develops minimax optimal estimators for quantum states and their linear functionals.
Findings
Established asymptotic minimax bounds for low-rank quantum state estimation.
Constructed optimal estimators for linear functionals of quantum states.
Extended quantum local asymptotic equivalence to low-rank scenarios.
Abstract
In classical statistics, a well known paradigm consists in establishing asymptotic equivalence between an experiment of i.i.d. observations and a Gaussian shift experiment, with the aim of obtaining optimal estimators in the former complicated model from the latter simpler model. In particular, a statistical experiment consisting of i.i.d observations from d-dimensional multinomial distributions can be well approximated by an experiment consisting of dimensional Gaussian distributions. In a quantum version of the result, it has been shown that a collection of qudits (d-dimensional quantum states) of full rank can be well approximated by a quantum system containing a classical part, which is a dimensional Gaussian distribution, and a quantum part containing an ensemble of shifted thermal states. In this paper, we obtain a generalization of this result when…
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Taxonomy
TopicsQuantum Information and Cryptography · Statistical Methods and Inference · Quantum Mechanics and Applications
