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The entanglement entropy in one dimensional critical systems with boundaries has been associated with the noninteger ground state degeneracy. This quantity, being a characteristic of boundary fixed points, decreases under renormalization…

Statistical Mechanics · Physics 2017-08-30 Eyal Cornfeld , Eran Sela

Entanglement R\'enyi-$\alpha$ entropy is an entanglement measure. It generalizes the entanglement of formation, and they coincide when $\alpha$ tends to 1. We derive analytical lower and upper bounds for the entanglement R\'enyi-$\alpha$…

Quantum Physics · Physics 2017-03-07 Wei Song , Lin Chen , Zhuo-Liang Cao

Present theoretical predictions for the entanglement entropy through topological defects are violated by numerical simulations. In order to resolve this, we introduce a paradigm shift in the preparation of reduced density matrices in the…

High Energy Physics - Theory · Physics 2026-01-07 Christian Northe , Paolo Rossi

The entanglement entropy in a quantum field theory between two regions of space has been shown in simple cases to be proportional to the volume of the hypersurface separating the regions. We prove that this is true for a free scalar field…

High Energy Physics - Theory · Physics 2008-11-26 Micheal S. Berger , Roman V. Buniy

Counting problems such as determining how many bit strings satisfy a given Boolean logic formula are notoriously hard. In many cases, even getting an approximate count is difficult. Here we propose that entanglement, a common concept in…

Statistical Mechanics · Physics 2013-04-03 Claudio Chamon , Eduardo R. Mucciolo

We derive differential equations for the flow of entanglement entropy as a function of the metric and the couplings of the theory. The variation of the universal part of entanglement entropy under a local Weyl transformation is related to…

High Energy Physics - Theory · Physics 2014-12-31 Vladimir Rosenhaus , Michael Smolkin

We mainly study the R\'enyi entropy and entanglement entropy of the states locally excited by the descendent operators in two dimensional conformal field theories (CFTs). In rational CFTs, we prove that the increase of entanglement entropy…

High Energy Physics - Theory · Physics 2015-08-10 Bin Chen , Wu-Zhong Guo , Song He , Jie-qiang Wu

A machine learning method to predict steady external fluid flows using elliptic input features is introduced. Using data from as few as one high-fidelity simulation, the proposed method produces models generalizable under changes to…

We study the scaling of the Renyi entanglement entropy of two disjoint blocks of critical lattice models described by conformal field theories with central charge c=1. We provide the analytic conformal field theory result for the second…

Statistical Mechanics · Physics 2015-03-19 Vincenzo Alba , Luca Tagliacozzo , Pasquale Calabrese

We propose a simple approach to the calculation of the entanglement entropy of a spherically symmetric quantum system composed of two separate regions. We consider bound states of the system described by a wave function that is scale…

Quantum Physics · Physics 2019-02-12 Maurizio Melis

Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an abundance of high-fidelity databases can be generated by experimental…

Fluid Dynamics · Physics 2022-08-12 Mustafa Z. Yousif , Linqi Yu , Sergio Hoyas , Ricardo Vinuesa , HeeChang Lim

The entropy of a quantum system is a measure of its randomness, and has applications in measuring quantum entanglement. We study the problem of measuring the von Neumann entropy, $S(\rho)$, and R\'enyi entropy, $S_\alpha(\rho)$ of an…

Quantum Physics · Physics 2022-04-19 Jayadev Acharya , Ibrahim Issa , Nirmal V. Shende , Aaron B. Wagner

Twist fields are a powerful formal tool to compute R\'enyi entropies in quantum many-body systems, but their conventional formulation in tensor network states involves operations acting on virtual degrees of freedom, which are not directly…

Quantum Physics · Physics 2026-05-27 Andrea Bulgarelli , Marco Panero , Paolo Stornati , Luca Tagliacozzo

We study "field space entanglement" in certain quantum field theories consisting of N number of free scalar fields interacting with each other via kinetic mixing terms. We present exact analytic expressions for entanglement end Renyi…

High Energy Physics - Theory · Physics 2016-03-23 M. Reza Mohammadi Mozaffar , Ali Mollabashi

In two recent papers we have proposed a program of study which allows us to compute the correlation functions of local and semi-local fields in generalised $\mathrm{T}\bar{\mathrm{T}}$-deformed integrable quantum field theories. This new…

High Energy Physics - Theory · Physics 2023-06-21 Olalla A. Castro-Alvaredo , Stefano Negro , Fabio Sailis

Entropy Estimation is an important problem with many applications in cryptography, statistic,machine learning. Although the estimators optimal with respect to the sample complexity have beenrecently developed, there are still some…

Data Structures and Algorithms · Computer Science 2020-02-24 Maciej Skorski

In this thesis, we study a variety of phenomena in strongly coupled quantum field theories by performing calculations in their gravitational duals. We compute entanglement entropy in a variety of holographic systems, paying particular…

High Energy Physics - Theory · Physics 2019-12-23 Ronnie Rodgers

In this note, I revisit the problem of computing the entanglement entropy of a single interval in the ground state of a 2d CFT. I write the leading-order result in three different ways: once by doing the replica trick with the…

High Energy Physics - Theory · Physics 2021-10-25 Jennifer Lin

Learned field transformations may help address ubiquitous critical slowing down and signal-to-noise problems in lattice field theory. In the context of an annealed sequence of distributions, field transformations are defined by integrating…

High Energy Physics - Lattice · Physics 2026-03-03 Michael S. Albergo , Gurtej Kanwar

Neural networks have dramatically increased our capacity to learn from large, high-dimensional datasets across innumerable disciplines. However, their decisions are not easily interpretable, their computational costs are high, and building…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Mackenzie J. Meni , Ryan T. White , Michael Mayo , Kevin Pilkiewicz
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