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We present a general method for calculating R\'enyi entropies in the ground state of a one-dimensional critical system with mixed open boundaries, for an interval starting at one of its ends. In the conformal field theory framework, this…

Statistical Mechanics · Physics 2025-11-12 Benoit Estienne , Yacine Ikhlef , Andrei Rotaru

The efficient generation of random quantum states is a long-standing challenge, motivated by their diverse applications in quantum information processing tasks. In this work, we identify entanglement as the key resource that enables local…

Quantum Physics · Physics 2026-01-26 Wonjun Lee , Hyukjoon Kwon , Gil Young Cho

An uncertainty relation for the R\'enyi entropies of conjugate quantum observables is used to obtain a strong Heisenberg limit of the form ${\rm RMSE} \geq f(\alpha)/(\langle N\rangle+\frac12)$, bounding the root mean square error of any…

Quantum Physics · Physics 2022-11-21 Michael J. W. Hall

The Ryu-Takayanagi conjecture establishes a remarkable connection between quantum systems and geometry. Specifically, it relates the entanglement entropy to minimal surfaces within the setting of AdS/CFT correspondence. This Letter shows…

Strongly Correlated Electrons · Physics 2017-03-14 Stefan Kehrein

Entanglement entropy quantifies the amount of uncertainty of a quantum state. For quantum fields in curved space, entanglement entropy of the quantum field theory degrees of freedom is well-defined for a fixed background geometry. In this…

High Energy Physics - Theory · Physics 2020-10-28 Xi Dong , Xiao-Liang Qi , Zhou Shangnan , Zhenbin Yang

In this paper, we study the entanglement entropy in a large class of states of two-dimensional conformal field theory in the the large central charge limit. This class of states includes the states created by the insertion of a finite…

High Energy Physics - Theory · Physics 2016-09-21 Bin Chen , Jie-qiang Wu

We derive a generalized version of the Ryu-Takayanagi formula for the entanglement entropy in arbitrary diffeomorphism invariant field theories. We use a recent framework which expresses the measurable quantities of a quantum theory as a…

High Energy Physics - Theory · Physics 2025-08-21 Artem Averin

Recurrent Neural Networks (RNNs) represent the de facto standard machine learning tool for sequence modelling, owing to their expressive power and memory. However, when dealing with large dimensional data, the corresponding exponential…

Machine Learning · Computer Science 2021-05-12 Yao Lei Xu , Giuseppe G. Calvi , Danilo P. Mandic

Estimation of Shannon and R\'enyi entropies of unknown discrete distributions is a fundamental problem in statistical property testing and an active research topic in both theoretical computer science and information theory. Tight bounds on…

Quantum Physics · Physics 2023-07-19 Tongyang Li , Xiaodi Wu

Recent years have enjoyed substantial progress in capturing properties of complex quantum systems by means of random tensor networks (RTNs), which form ensembles of quantum states that depend only on the tensor network geometry and bond…

Quantum Physics · Physics 2025-08-25 Shozab Qasim , Jens Eisert , Alexander Jahn

Recurrent Neural Network (RNN) are a popular choice for modeling temporal and sequential tasks and achieve many state-of-the-art performance on various complex problems. However, most of the state-of-the-art RNNs have millions of parameters…

Machine Learning · Computer Science 2017-10-31 Andros Tjandra , Sakriani Sakti , Satoshi Nakamura

Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution of an RGG, which is crucial for studying its random…

Information Theory · Computer Science 2018-01-16 Mihai-Alin Badiu , Justin P. Coon

The Ryu-Takayanagi (RT) formula has been a key ingredient in our understanding of holography. Recent work on TT deformations has also boosted our understanding of holography away from the conformal boundary of AdS. In this short note, we…

High Energy Physics - Theory · Physics 2019-07-24 Chitraang Murdia , Yasunori Nomura , Pratik Rath , Nico Salzetta

Although tensor networks are powerful tools for simulating low-dimensional quantum physics, tensor network algorithms are very computationally costly in higher spatial dimensions. We introduce quantum gauge networks: a different kind of…

Quantum Physics · Physics 2023-09-20 Kevin Slagle

We propose and test several tensor network based algorithms for reconstructing the ground state of an (unknown) local Hamiltonian starting from a random sample of the wavefunction amplitudes. These algorithms, which are based on completing…

Quantum Physics · Physics 2023-10-04 Aaron Stahl , Glen Evenbly

We introduce R\'enyi entropy of a subsystem energy as a natural quantity which closely mimics the behavior of the entanglement entropy and can be defined for all the quantum many body systems. For this purpose, consider a quantum chain in…

Strongly Correlated Electrons · Physics 2019-11-13 Khadijeh Najafi , M. A. Rajabpour

We propose an analogue of the Ryu-Takayanagi formula for holographic entanglement entropy applicable to non-relativistic holographic dualities involving Horava gravity. This is a powerful tool for the duality to have, as topological order…

High Energy Physics - Theory · Physics 2017-07-27 Stefan Janiszewski

Using the positivity of relative entropy arising from the Ryu-Takayanagi formula for spherical entangling surfaces, we obtain constraints at the nonlinear level for the gravitational dual. We calculate the Green's function necessary to…

High Energy Physics - Theory · Physics 2015-02-27 Shamik Banerjee , Apratim Kaviraj , Aninda Sinha

In quantum mechanics, stringnet condensed states - a family of prototypical states exhibiting non-trivial topological order - can be classified via their long-range entanglement properties, in particular topological corrections to the…

Statistical Mechanics · Physics 2014-05-12 M. Hermanns , S. Trebst

In this paper, we study the entropy of a hard random geometric graph (RGG), a commonly used model for spatial networks, where the connectivity is governed by the distances between the nodes. Formally, given a connection range $r$, a hard…

Information Theory · Computer Science 2026-01-19 Praneeth Kumar Vippathalla , Justin P. Coon , Mihai-Alin Badiu