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We analyze the dynamics of an algorithm for approximate inference with large Gaussian latent variable models in a student-teacher scenario. To model nontrivial dependencies between the latent variables, we assume random covariance matrices…

Machine Learning · Computer Science 2020-08-26 Burak Çakmak , Manfred Opper

We present a tree structure algorithm for optimal control problems with state constraints. We prove a convergence result for a discrete time approximation of the value function based on a novel formulation of the constrained problem. Then…

Numerical Analysis · Mathematics 2020-09-29 Alessandro Alla , Maurizio Falcone , Luca Saluzzi

We propose a new statistical model suitable for machine learning of systems with long distance correlations such as natural languages. The model is based on directed acyclic graph decorated by multi-linear tensor maps in the vertices and…

Computation and Language · Computer Science 2017-10-31 Vasily Pestun , Yiannis Vlassopoulos

Invariant theory is concerned with functions that do not change under the action of a given group. Here we communicate an approach based on tensor networks to represent polynomial local unitary invariants of quantum states. This graphical…

Quantum Physics · Physics 2013-11-13 Jacob Biamonte , Ville Bergholm , Marco Lanzagorta

Simulating many-body open quantum systems is an extremely challenging problem, with methods often restricted to either models with nearest-neighbor interactions or semi-classical approximations. In particular, modeling two-dimensional…

Quantum Physics · Physics 2025-12-02 Jack Dunham , Marzena H. Szymańska

Time-averaged two-point currents are derived and shown to be spatially invariant within domains of local translation or inversion symmetry for arbitrary time-periodic quantum systems in one dimension. These currents are shown to provide a…

Quantum Physics · Physics 2016-05-25 Thomas Wulf , Christian V. Morfonios , Fotis K. Diakonos , Peter Schmelcher

Changes in the timescales at which complex systems evolve are essential to predicting critical transitions and catastrophic failures. Disentangling the timescales of the dynamics governing complex systems remains a key challenge. With this…

Methodology · Statistics 2024-03-11 Giona Casiraghi , Georges Andres

We study the quantum phases of bosons with repulsive contact interactions on a two-leg ladder in the presence of a uniform Abelian gauge field. The model realizes many interesting states, including Meissner phases, vortex-fluids,…

Quantum Gases · Physics 2016-12-30 S. Greschner , M. Piraud , F. Heidrich-Meisner , I. P. McCulloch , U. Schollwöck , T. Vekua

Starting from a simple discrete model which exhibits a supersymmetric invariance we construct a local, interacting, two-dimensional Euclidean lattice theory which also admits an exact supersymmetry. This model is shown to correspond to the…

High Energy Physics - Lattice · Physics 2007-05-23 S. Catterall , S. Karamov

Simulating many-body quantum systems poses significant challenges due to the large size of the state space. To address this issue, we propose using an SU(2) coherent state for individual spins to simulate spins on a lattice and derive…

Quantum Physics · Physics 2025-02-14 Grace Hsiao-Han Chuang , Abhijit Pendse

Mapping the system evolution of a two-state system allows the determination of the effective system Hamiltonian directly. We show how this can be achieved even if the system is decohering appreciably over the observation time. A method to…

A brief pedagogical overview of recent advances in tensor network state methods are presented that have the potential to broaden their scope of application radically for strongly correlated molecular systems. These include global fermionic…

Strongly Correlated Electrons · Physics 2025-01-31 Miklós Antal Werner , Andor Menczer , Örs Legeza

The entanglement properties of the phase transition in a two dimensional harmonic lattice, similar to the one observed in recent ion trap experiments, are discussed both, for finite number of particles and thermodynamical limit. We show…

Quantum Physics · Physics 2015-05-13 Elisabeth Rieper , Janet Anders , Vlatko Vedral

Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods…

High Energy Physics - Lattice · Physics 2021-04-08 Phiala E. Shanahan , Amalie Trewartha , William Detmold

The study of nonlinear phenomena in systems with many degrees of freedom often relies on complex numerical simulations. In trying to model realistic situations, these systems may be coupled to an external environment which drives their…

High Energy Physics - Lattice · Physics 2009-10-28 Julian Borrill , Marcelo Gleiser

We propose a numerical method of estimating various physical quantities in lattice (supersymmetric) quantum mechanics. The method consists only of deterministic processes such as computing a product of transfer matrix, and has no…

High Energy Physics - Lattice · Physics 2018-07-04 Daisuke Kadoh , Katsumasa Nakayama

The present paper is devoted to estimating the speed of convergence towards consensus for a general class of discrete-time multi-agent systems. In the systems considered here, both the topology of the interconnection graph and the weight of…

Optimization and Control · Mathematics 2020-10-02 David Angeli , Pierre-Alexandre Bliman

Dynamic processes of interacting units on a network are out of equilibrium in general. In the case of a directed tree, the dynamic cavity method provides an efficient tool that characterises the dynamic trajectory of the process for the…

Disordered Systems and Neural Networks · Physics 2022-05-25 Giuseppe Torrisi , Reimer Kühn , Alessia Annibale

Topological order in a 2d quantum matter can be determined by the topological contribution to the entanglement R\'enyi entropies. However, when close to a quantum phase transition, its calculation becomes cumbersome. Here we show how…

Strongly Correlated Electrons · Physics 2014-12-24 Roman Orus , Tzu-Chieh Wei , Oliver Buerschaper , Artur Garcia-Saez

We introduce and demonstrate two linear inverse modelling methods for systems of stochastic ODE's with accuracy that is independent of the dimensionality (number of elements) of the state vector representing the system in question.…

Data Analysis, Statistics and Probability · Physics 2015-04-29 Fenwick C. Cooper
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