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The correlations in the spectra of quantum systems are intimately related to correlations which are of genuine classical origin, and which appear in the spectra of actions of the classical periodic orbits of the corresponding classical…

Chaotic Dynamics · Physics 2009-11-07 Uzy Smilansky , Basile Verdene

A quantum network is an open system consisting of several component Markovian input-output subsystems interconnected by boson field channels carrying quantum stochastic signals. Generalizing the work of Chebotarev and Gregoratti, we…

Quantum Physics · Physics 2009-04-01 J. Gough , M. R. James

We develop a unified theory that encompasses the macroscopic dynamics of recurrent interactions of binary units within arbitrary network architectures. Using the martingale theory, our mathematical analysis provides a complete description…

Biological Physics · Physics 2017-11-22 Farzad Farkhooi , Wilhelm Stannat

It is shown that the matrix models which give non-perturbative definitions of string and M theory may be interpreted as non-local hidden variables theories in which the quantum observables are the eigenvalues of the matrices while their…

High Energy Physics - Theory · Physics 2009-11-07 Lee Smolin

The algebraic structure of the 1D Hubbard model is studied by means of the fermionic R-operator approach. This approach treats the fermion models directly in the framework of the quantum inverse scattering method. Compared with the graded…

Statistical Mechanics · Physics 2009-10-31 Yukiko Umeno

A detailed algorithmic explanation is required for how a network of chemical reactions can generate the sophisticated behavior displayed by living cells. Though several previous works have shown that reaction networks are computationally…

Emerging Technologies · Computer Science 2018-04-25 Muppirala Viswa Virinchi , Abhishek Behera , Manoj Gopalkrishnan

We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the…

Physics and Society · Physics 2018-01-17 V. I. Yukalov , E. P. Yukalova , D. Sornette

In this paper, we introduce a conceptual framework that model human social networks as an undirected dot-product graph of independent individuals. Their relationships are only determined by a cost-benefit analysis, i.e. by maximizing an…

Probability · Mathematics 2024-11-26 Aldric Labarthe , Yann Kerzreho

Around 1950, Wigner introduced the idea of modelling physical reality with an ensemble of random matrices while studying the energy levels of heavy atomic nuclei. Since then, the field of random-matrix theory has grown tremendously, with…

Atomic Physics · Physics 2012-08-22 Jean-Christophe Pain

Quantum networks are distributed quantum many-body systems with tailored topology and controlled information exchange. They are the backbone of distributed quantum computing architectures and quantum communication. Here we present a…

We introduce the notion of corresponding a chemical reaction network to a split network translation, and use this novel process to extend the scope of existing network-based theory for characterizing the steady state set of mass-action…

Dynamical Systems · Mathematics 2021-04-09 Matthew D. Johnston

We study fermionic one-matrix, two-matrix and $D$-dimensional gauge invariant matrix models. In all cases we derive loop equations which unambiguously determine the large-$N$ solution. For the one-matrix case the solution is obtained for an…

High Energy Physics - Theory · Physics 2009-10-22 Yu. Makeenko , K. Zarembo

Learning representations of nodes in a low dimensional space is a crucial task with numerous interesting applications in network analysis, including link prediction, node classification, and visualization. Two popular approaches for this…

Social and Information Networks · Computer Science 2022-08-10 Abdulkadir Celikkanat , Yanning Shen , Fragkiskos D. Malliaros

Field theories on the plane wave background are considered. We discuss that for such field theories one can only form 1+1 dimensional freely propagating wave packets. We analyze tree level four point functions of scalar field theory as well…

High Energy Physics - Theory · Physics 2009-11-07 Dongsu Bak , Mohammad M. Sheikh-Jabbari

The field of artificial neural networks is expected to strongly benefit from recent developments of quantum computers. In particular, quantum machine learning, a class of quantum algorithms which exploit qubits for creating trainable neural…

Quantum Physics · Physics 2022-01-12 Marco Maronese , Claudio Destri , Enrico Prati

Scattering is an important phenomenon which is observed in systems ranging from the micro- to macroscale. In the context of nuclear reaction theory the Heidelberg approach was proposed and later demonstrated to be applicable to many chaotic…

We introduce superposition-based quantum networks composed of (i) the classical perceptron model of multilayered, feedforward neural networks and (ii) the algebraic model of evolving reticular quantum structures as described in quantum…

Neurons and Cognition · Quantitative Biology 2009-11-10 Christopher Altman , Jaroslaw Pykacz , Roman Zapatrin

We investigate the scattering phenomena in two dimensions produced by a general finite-range nonseparable potential. This situation can appear either in a Cartesian geometry or in a heterostructure with cylindrical symmetry. Increasing the…

Mesoscale and Nanoscale Physics · Physics 2010-09-03 P. N. Racec , E. R. Racec , H. Neidhardt

Entangled quantum networks provide great flexibilities and scalabilities for quantum information processing or quantum Internet. Most of results are focused on the nonlocalities of quantum networks. Our goal in this work is to explore new…

Quantum Physics · Physics 2021-08-06 Ming-Xing Luo

Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a…

Neurons and Cognition · Quantitative Biology 2022-07-21 Chris Fields , James F. Glazebrook , Michael Levin
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