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We study the macroscopic entanglement properties of a low dimensional quantum spin system by investigating its magnetic properties at low temperatures and high magnetic fields. The tempera- ture and magnetic field dependence of entanglement…

Quantum Physics · Physics 2016-11-26 Diptaranjan Das , Tanmoy Chakraborty , Harkirat Singh , Chiranjib Mitra

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

Physical systems have some degree of disorder present in them. We discuss how to treat natural, thermal entanglement in any random macroscopic system from which a thermodynamic witness bounded by a constant can be found. We propose that…

Quantum Physics · Physics 2009-03-25 Jenny Hide , Wonmin Son , Vlatko Vedral

We analyze the recently developed folding algorithm [Phys. Rev. Lett. 102, 240603 (2009)] to simulate the dynamics of infinite quantum spin chains, and relate its performance to the kind of entanglement produced under the evolution of…

Quantum Physics · Physics 2012-07-04 Alexander Müller-Hermes , J. Ignacio Cirac , Mari Carmen Bañuls

Quantum machine learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure…

Chemical Physics · Physics 2021-10-29 Manas Sajjan , Shree Hari Sureshbabu , Sabre Kais

Chemical and biological networks can describe a wide variety of processes, from gene regulatory networks to biochemical oscillations. Modeled by chemical master equations, these processes are inherently stochastic, as fluctuations dominate…

Statistical Mechanics · Physics 2025-12-23 Schuyler B. Nicholson , Luis Pedro García-Pintos

Determining phase diagrams and phase transitions semi-automatically using machine learning has received a lot of attention recently, with results in good agreement with more conventional approaches in most cases. When it comes to more…

Disordered Systems and Neural Networks · Physics 2019-12-04 Hugo Théveniaut , Fabien Alet

Understanding how closed quantum systems dynamically approach thermal equilibrium presents a major unresolved problem in statistical physics. Generically, non-integrable quantum systems are expected to thermalize as they comply with the…

In this thesis, we focus on the energetic analysis within autonomous quantum systems. To this aim, we propose a novel and general formalism for a dynamic description of the energy exchanges between interacting subsystems. From the Schmidt…

Quantum Physics · Physics 2022-11-15 André Hernandes Alves Malavazi

We introduce a numerical method of the adaptive time-dependent density-matrix renormalization-group to compute one-dimensional quantum spin systems with periodic boundary condition. We check our algorithm to study the dynamic correlation in…

Statistical Mechanics · Physics 2011-06-01 Jie Ren

We present an efficient way to compute diagonal and off-diagonal n-point correlation functions for quantum spin-systems within the loop algorithm. We show that the general rules for the evaluation of these correlation functions take an…

Condensed Matter · Physics 2009-10-31 J. V. Alvarez , Claudius Gros

"Deep thermalization" describes the emergence of universal wavefunction distributions in quantum many-body dynamics, appearing on a local subsystem upon measurement of its environment. In this work, we study in detail the effect of…

Quantum Physics · Physics 2025-06-11 Rui-An Chang , Harshank Shrotriya , Wen Wei Ho , Matteo Ippoliti

Aimed at a more realistic classical description of natural quantum systems, we present a two-dimensional tensor network algorithm to study finite temperature properties of frustrated model quantum systems and real quantum materials. For…

Strongly Correlated Electrons · Physics 2024-06-12 Philipp Schmoll , Christian Balz , Bella Lake , Jens Eisert , Augustine Kshetrimayum

Long-range quantum systems, in which the interactions decay as $1/r^{\alpha}$, are of increasing interest due to the variety of experimental set-ups in which they naturally appear. Motivated by this, we study fundamental properties of…

Quantum Physics · Physics 2026-01-08 Jorge Sánchez-Segovia , Jan T. Schneider , Álvaro M. Alhambra

Energy conversion in nanosized devices is studied in the framework of state-space models. We use a network representation of the underlying master equation to describe the dynamics by a graph. Particular segments of this network represent…

Statistical Mechanics · Physics 2021-12-28 M. Einax

Quantum many-body scarred systems host nonthermal excited eigenstates immersed in a sea of thermal ones. In cases where exact expressions for these special eigenstates are not known, it is computationally demanding to distinguish them from…

Strongly Correlated Electrons · Physics 2023-07-13 Shun-Yao Zhang , Dong Yuan , Thomas Iadecola , Shenglong Xu , Dong-Ling Deng

Random electron systems show rich phases such as Anderson insulator, diffusive metal, quantum and anomalous quantum Hall insulator, Weyl semimetal, as well as strong/weak topological insulators. Eigenfunctions of each matter phase have…

Disordered Systems and Neural Networks · Physics 2016-11-21 Tomoki Ohtsuki , Tomi Ohtsuki

In this paper, we investigate the energy minimization model of the ensemble Kohn-Sham density functional theory for metallic systems, in which a pseudo-eigenvalue matrix and a general smearing approach are involved. We study the invariance…

Numerical Analysis · Mathematics 2022-01-19 Xiaoying Dai , Stefano de Gironcoli , Bin Yang , Aihui Zhou

Here we investigate how local properties of particles in a thermal bath influence the thermodynamics of the bath. We utilize nanothermodynamics, based on two postulates: that small systems can be treated self-consistently by coupling to an…

Statistical Mechanics · Physics 2022-10-26 Ralph V. Chamberlin , Michael R. Clark , Vladimiro Mujica , George H. Wolf

We perform quantum simulation on classical and quantum computers and set up a machine learning framework in which we can map out phase diagrams of known and unknown quantum many-body systems in an unsupervised fashion. The classical…

Quantum Physics · Physics 2022-10-21 Korbinian Kottmann
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