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In this paper, the parameter estimation problem for a multi-timescale adaptive threshold (MAT) neuronal model is investigated. By manipulating the system dynamics, which comprise of a non-resetting leaky integrator coupled with an adaptive…

Neurons and Cognition · Quantitative Biology 2018-03-13 Amirhossein Jabalameli , Aman Behal

Quantum networks of growing complexity play a key role as resources for quantum computation; the ability to identify the quality of their internal correlations will play a crucial role in addressing the buiding stage of such states. We…

Random dynamical systems with countably many maps which admit countable Markov partitions on complete metric spaces such that the resulting Markov systems are uniformly continuous and contractive are considered. A non-degeneracy and a…

Dynamical Systems · Mathematics 2014-11-18 Ivan Werner

In this paper I propose a new way for counting the microstates of a system out of equilibrium. As, according to quantum mechanics, things happen as if a given particle can be found in more than one state at once, I extend this concept to…

Quantum Physics · Physics 2009-11-13 Norton G. de Almeida

Vast developments in quantum technology have enabled the preparation of quantum states with more than a dozen entangled qubits. The full characterization of such systems demands distinct constructions depending on their specific type and…

In dealing with nonlinear systems, it is common to use numerical solutions. Unlike the careful behavior towards the numerical results in chaotic regions, the validity of numerical results in regions of transient chaos might not always be…

Dynamical Systems · Mathematics 2023-10-23 Ali Goodarzi , Maryam Rahimi , MohammadJavad Valizadeh , Fakhteh Ghanbarnejad

We study polynomial optimization problems whose objective has a composition or tensor train structure. These polynomials can be evaluated as a sequence of maps, giving rise to intermediate variables (``states'') of dimension lower than the…

Optimization and Control · Mathematics 2026-04-21 Llorenç Balada Gaggioli , Didier Henrion , Milan Korda

We review methods that allow one to detect and characterise quantum correlations in many-body systems, with a special focus on approaches which are scalable. Namely, those applicable to systems with many degrees of freedom, without…

Quantum Physics · Physics 2023-09-28 Irénée Frérot , Matteo Fadel , Maciej Lewenstein

In Machine Learning, the $\mathsf{SHAP}$-score is a version of the Shapley value that is used to explain the result of a learned model on a specific entity by assigning a score to every feature. While in general computing Shapley values is…

Artificial Intelligence · Computer Science 2023-03-31 Marcelo Arenas , Pablo Barceló , Leopoldo Bertossi , Mikaël Monet

A variational approach based on the multi-coherent-state ansatz with asymmetric parameters is employed to study the ground state of the spin-boson model. Without any artificial approximations except for the finite number of the coherent…

Quantum Gases · Physics 2014-12-22 Liwei Duan , Shu He , Qing-Hu Chen

A set of orthogonal multipartite quantum states is said to be distinguishability-based genuinely nonlocal (also genuinely nonlocal, for abbreviation) if the states are locally indistinguishable across any bipartition of the subsystems. This…

Quantum Physics · Physics 2023-11-22 Zong-Xing Xiong , Mao-Sheng Li , Zhu-Jun Zheng , Lvzhou Li

Global dynamics in nonlinear stochastic systems is often difficult to analyze rigorously. Yet, many excellent numerical methods exist to approximate these systems. In this work, we propose a method to bridge the gap between computation and…

Dynamical Systems · Mathematics 2019-01-07 Maxime Breden , Christian Kuehn

We consider the problem of synthesizing provably non-overflowing integer arithmetic expressions or Boolean relations among integer arithmetic expressions. First we use a numerical abstract domain to infer numerical properties among program…

Programming Languages · Computer Science 2013-09-23 Francesco Logozzo , Matthieu Martel

The information bottleneck principle provides an information-theoretic method for representation learning, by training an encoder to retain all information which is relevant for predicting the label while minimizing the amount of other,…

Machine Learning · Computer Science 2020-02-19 Marco Federici , Anjan Dutta , Patrick Forré , Nate Kushman , Zeynep Akata

It is well-known that observing nonlocal correlations allows us to draw conclusions about the quantum systems under consideration. In some cases this yields a characterisation which is essentially complete, a phenomenon known as…

Quantum Physics · Physics 2020-04-02 Tim Coopmans , Jędrzej Kaniewski , Christian Schaffner

We introduce new sufficient conditions for verifying stability and recurrence properties in singularly perturbed stochastic hybrid dynamical systems. Specifically, we focus on hybrid systems with deterministic continuous-time dynamics that…

Optimization and Control · Mathematics 2023-10-25 Jorge I. Poveda

We study the verification of maximally entangled states by virtue of the simplest measurement settings: local projective measurements without adaption. We show that optimal protocols are in one-to-one correspondence with complex projective…

Quantum Physics · Physics 2020-01-01 Huangjun Zhu , Masahito Hayashi

We present a number of second order maps, which pass the singularity confinement test commonly used to identify integrable discrete systems, but which nevertheless are non-integrable. As a more sensitive integrability test, we propose the…

solv-int · Physics 2009-10-30 Jarmo Hietarinta , Claude Viallet

In this paper, we consider the problem of quantifying systemic redundancy in reliable systems having multiple controllers with overlapping functionality. In particular, we consider a multi-channel system with multi-controller configurations…

Dynamical Systems · Mathematics 2015-02-17 Getachew K. Befekadu , Panos J. Antsaklis

The unknown inputs in a dynamical system may represent unknown external drivers, input uncertainty, state uncertainty, or instrument faults and thus unknown-input reconstruction has several wide-spread applications. In this paper we…

Optimization and Control · Mathematics 2015-09-22 Roshan A Chavan , Harish J. Palanthandalam-Madapusi
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