Statistical Geometry in Quantum Mechanics
Dorje C. Brody (ADMTP), Lane P. Hughston (Merrill Lynch)

TL;DR
This paper explores the geometric structure of statistical models in quantum mechanics, generalizing classical bounds and deriving higher order corrections to uncertainty relations using information geometry.
Contribution
It introduces a geometric framework for quantum statistical models, extending classical variance bounds to quantum settings with higher order corrections.
Findings
Generalized Cramer-Rao and Bhattacharyya inequalities for quantum models
Higher order corrections to Heisenberg uncertainty relations
Geometric interpretation of quantum state space and estimation bounds
Abstract
A statistical model M is a family of probability distributions, characterised by a set of continuous parameters known as the parameter space. This possesses natural geometrical properties induced by the embedding of the family of probability distributions into the Hilbert space H. By consideration of the square-root density function we can regard M as a submanifold of the unit sphere in H. Therefore, H embodies the `state space' of the probability distributions, and the geometry of M can be described in terms of the embedding of in H. The geometry in question is characterised by a natural Riemannian metric (the Fisher-Rao metric), thus allowing us to formulate the principles of classical statistical inference in a natural geometric setting. In particular, we focus attention on the variance lower bounds for statistical estimation, and establish generalisations of the classical Cramer-Rao…
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