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For piecewise expanding one-dimensional maps without periodic turning points we prove that isolated eigenvalues of small (random) perturbations of these maps are close to isolated eigenvalues of the unperturbed system. (Here ``eigenvalue''…

chao-dyn · Physics 2009-10-30 Michael Blank , Gerhard Keller

We study the problem of efficiently estimating the effect of an intervention on a single variable (atomic interventions) using observational samples in a causal Bayesian network. Our goal is to give algorithms that are efficient in both…

Machine Learning · Computer Science 2020-08-07 Arnab Bhattacharyya , Sutanu Gayen , Saravanan Kandasamy , Ashwin Maran , N. V. Vinodchandran

Recent advances in analog and digital quantum-simulation platforms have enabled exploration of the spectrum of entanglement Hamiltonians via variational algorithms. In this work we analyze the convergence properties of the variationally…

Quantum Physics · Physics 2025-05-16 Yanick S. Kind , Benedikt Fauseweh

In polymer physics it is typically assumed that excluded volume interactions are effectively screened in polymer melts. Hence, chains could be described by an effective random walk without excluded volume interactions. In this letter, we…

Soft Condensed Matter · Physics 2017-10-31 Hendrik Meyer , Eric Horwath , Peter Virnau

Recovering an unknown Hamiltonian from measurements is an increasingly important task for certification of noisy quantum devices and simulators. Recent works have succeeded in recovering the Hamiltonian of an isolated quantum system with…

Quantum Physics · Physics 2019-01-24 Eyal Bairey , Itai Arad , Netanel H. Lindner

Evaluating accessible conformational space is computationally expensive and thermal motions are partly neglected in computer models of molecular interactions. This produces error into the estimates of binding strength. We introduce a method…

Quantitative Methods · Quantitative Biology 2016-12-13 Riku Hakulinen , Santeri Puranen

Estimating the transition dynamics of controlled Markov chains is crucial in fields such as time series analysis, reinforcement learning, and system exploration. Traditional non-parametric density estimation methods often assume independent…

Statistics Theory · Mathematics 2025-05-21 Imon Banerjee , Vinayak Rao , Harsha Honnappa

Electronic nearsightedness is one of the fundamental principles governing the behavior of condensed matter and supporting its description in terms of local entities such as chemical bonds. Locality also underlies the tremendous success of…

Computational Physics · Physics 2020-09-01 Andrea Grisafi , Jigyasa Nigam , Michele Ceriotti

We introduce a general model for a network of quantum sensors, and we use this model to consider the question: when do correlations (quantum or classical) between quantum sensors enhance the precision with which the network can measure an…

Quantum Physics · Physics 2017-02-15 T. J. Proctor , P. A. Knott , J. A. Dunningham

We develop a theory for the interaction of classical light fields with an a chain of coupled quantum dots (QDs), in the strong-coupling regime, taking into account the local-field effects. The QD chain is modeled by a one-dimensional (1D)…

We investigate the static and dynamical behavior of 1D interacting fermions in disordered Hubbard chains, contacted to semi-infinite leads. The chains are described via the repulsive Anderson-Hubbard Hamiltonian, using static and…

Mesoscale and Nanoscale Physics · Physics 2013-03-27 V. Vettchinkina , A. Kartsev , D. Karlsson , C. Verdozzi

We propose a methodology to parallelize Hamiltonian Monte Carlo estimators. Our approach constructs a pair of Hamiltonian Monte Carlo chains that are coupled in such a way that they meet exactly after some random number of iterations. These…

Computation · Statistics 2018-08-28 Jeremy Heng , Pierre E. Jacob

Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speedup the collection of network data and improve the validity of network models. Many algorithms now exist…

Machine Learning · Statistics 2020-10-05 Amir Ghasemian , Homa Hosseinmardi , Aram Galstyan , Edoardo M. Airoldi , Aaron Clauset

We propose a structure-preserving model-reduction methodology for large-scale dynamic networks with tightly-connected components. First, the coherent groups are identified by a spectral clustering algorithm on the graph Laplacian matrix…

Systems and Control · Electrical Eng. & Systems 2023-05-15 Hancheng Min , Enrique Mallada

Random Threshold Networks with sparse, asymmetric connections show complex dynamical behavior similar to Random Boolean Networks, with a transition from ordered to chaotic dynamics at a critical average connectivity $K_c$. In this type of…

Statistical Mechanics · Physics 2009-11-07 Thimo Rohlf , Stefan Bornholdt

We present a systematic hierarchy of approximations for {\it local} exact-decoupling of four-component quantum chemical Hamiltonians based on the Dirac equation. Our ansatz reaches beyond the trivial local approximation that is based on a…

Chemical Physics · Physics 2012-06-28 Daoling Peng , Markus Reiher

Particle transport and localization phenomena in condensed-matter systems can be modeled using a tight-binding lattice Hamiltonian. The ideal experimental emulation of such a model utilizes simultaneous, high-fidelity control and readout of…

Entanglement has been widely investigated in condensed matter systems since they are considered good candidates for developing quantum technologies. Additionally, entanglement is a powerful tool to explore quantum phase transitions in…

For a transverse-field Ising chain with weak long-range interactions we develop a perturbative scheme, based on quantum kinetic equations, around the integrable nearest-neighbour model. We introduce, discuss, and benchmark several…

Quantum Physics · Physics 2019-03-14 Clément Duval , Michael Kastner

We show that local correlators in a wide class of kicked chains can be calculated exactly at light cone edges. Extending previous works on dual-unitary systems, the correlators between local operators are expressed through the expectation…

Statistical Mechanics · Physics 2020-11-18 Boris Gutkin , Petr Braun , Maram Akila , Daniel Waltner , Thomas Guhr
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