Probability-Phase Mutual Information

Quantum coherence is an exquisitely quantum phenomenon that depends on both probability amplitudes and relative phases. Standard coherence measures quantify superposition within density matrices but cannot distinguish ensembles that produce the same mixed state through different distributions of pure states. Building on the geometric formulation of quantum mechanics, we introduce the probability-phase mutual information $I(P;Φ)$. We show that it characterizes quantum coherence at the ensemble level and that ensemble coherence systematically exceeds density-matrix coherence, thus quantifying the structure lost when averaging over pure states. Eventually, its relevance for quantum thermodynamics, quantum information theory, and deep thermalization is highlighted by explicit examples: canonical ensembles reveal temperature-dependent probability-phase correlations absent from thermal density matrices; we show that the probability of converting an ensemble into another one is bound by the ratio of their $I(P;Φ)$; and, that a non-vanishing $I(P;Φ)$ signals the breakdown of deep thermalization.

Publication Details

Journal
arXiv (Cornell University)
Published
2025-10-01
Primary Topic
Data Analysis with R
Type
article
Field-Weighted Citation Impact
0.00

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article

Probability-Phase Mutual Information

arXiv (Cornell University)
Data Analysis with R
article

Probability-Phase Mutual Information

article en

Abstract

Quantum coherence is an exquisitely quantum phenomenon that depends on both probability amplitudes and relative phases. Standard coherence measures quantify superposition within density matrices but cannot distinguish ensembles that produce the same mixed state through different distributions of pure states. Building on the geometric formulation of quantum mechanics, we introduce the probability-phase mutual information $I(P;Φ)$. We show that it characterizes quantum coherence at the ensemble level and that ensemble coherence systematically exceeds density-matrix coherence, thus quantifying the structure lost when averaging over pure states. Eventually, its relevance for quantum thermodynamics, quantum information theory, and deep thermalization is highlighted by explicit examples: canonical ensembles reveal temperature-dependent probability-phase correlations absent from thermal density matrices; we show that the probability of converting an ensemble into another one is bound by the ratio of their $I(P;Φ)$; and, that a non-vanishing $I(P;Φ)$ signals the breakdown of deep thermalization.

arXiv (Cornell University)
University of Maryland, Baltimore County
Openalex Percentile: Top 24%
Data Analysis with R
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