English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The maximum-entropy principle (Max-Ent) is a valuable and extensively usedtool in statistical mechanics and quantum information theory. It provides amethod for inferring the state of a system by utilizing a reduced set ofparameters associated with measurable quantities. However, the computationalcost of employing Max-Ent projections in simulations of quantum many-bodysystems is a significant drawback, primarily due to the computational cost ofevaluating these projections. In this work, a novel approach for estimatingMax-Ent projections is proposed. The approach involves replacing the expensiveMax-Ent induced local geometry, represented by the Kubo-Mori-Bogoliubov (KMB)scalar product, with a less computationally demanding geometry. Specifically, anew local geometry is defined in terms of the quantum analog of the covariancescalar product for classical random variables. Relations between induceddistances and projections for both products are explored. Connections withstandard variational and dynamical Mean-Field approaches are discussed. Theeffectiveness of the approach is calibrated and illustrated by its applicationto the dynamic of excitations in a XX Heisenberg spin-$\frac{1}{2}$ chainmodel.

Quantum Covariance Scalar Products, Thermal Correlations and Efficient Estimation of Max-Ent projections