Topics: Radio Program, Formal sciences, Exponentials, Neural networks, Computational neuroscience,...

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Topics: Radio Program, Formal sciences, Artificial intelligence, Cybernetics, Republics, Divided regions,...

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10.0

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Topics: Radio Program, Artificial intelligence, Cybernetics, Learning, Neural networks, Computational...

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4.0

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Topics: Radio Program, Computer vision, Artificial intelligence, Cybernetics, Industry, Learning, Divided...

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9.0

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Topics: Radio Program, Fertility, Neural networks, Planetary science, Reproduction, Team sports, Solar...

Topics: Radio Program, Artificial intelligence, Cybernetics, Formal sciences, Machine learning, Learning,...

3
3.0

Jun 29, 2018
06/18

by
Stefan Kettemann

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We consider the orthogonality catastrophe at the Anderson Metal-Insulator transition (AMIT). The typical overlap $F$ between the ground state of a Fermi liquid and the one of the same system with an added potential impurity is found to decay at the AMIT exponentially with system size $L$ as $F \sim \exp (- \langle I_A\rangle /2)= \exp(-c L^{\eta})$, where $I_A$ is the so called Anderson integral, $\eta $ is the power of multifractal intensity correlations and $\langle ... \rangle$ denotes the...

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1606.02243

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3.0

Jun 30, 2018
06/18

by
Richard Vasques; Kai Krycki

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We present a first numerical investigation of the accuracy of the recently proposed {\em non-classical transport equation}. This equation contains an extra independent variable (the path-length $s$), and models particle transport taking place in random media in which a particle's distance-to-collision is {\em not} exponentially distributed. To solve the non-classical equation, one needs to know the $s$-dependent ensemble-averaged total cross section $\Sigma_t(s)$, or its corresponding...

Topics: Nuclear Theory, Mathematics, Mathematical Physics, Disordered Systems and Neural Networks,...

Source: http://arxiv.org/abs/1412.3386

Topics: Radio Program, Banking, Radio formats, Hearing, Neural networks, Actors from California, Banks,...

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3.0

Jun 28, 2018
06/18

by
Giuseppe Genovese; Daniele Tantari

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We investigate a multipartite ferromagnetic model without self-interactions between spins of the same party, so that the Hamiltonian is not a definite quadratic form of the magnetisations. We find the free energy and study the phase transition for all zero external fields. Moreover in the bipartite case we analyse the fluctuations of the rescaled magnetisations, below and at the critical point, and we study the phase transitions with non zero magnetic fields.

Topics: Disordered Systems and Neural Networks, Mathematics, Probability, Mathematical Physics, Condensed...

Source: http://arxiv.org/abs/1511.01307

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3.0

Jun 29, 2018
06/18

by
Takashi Shinzato

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In the present work, eigenvalue distributions defined by a random rectangular matrix whose components are neither independently nor identically distributed are analyzed using replica analysis and belief propagation. In particular, we consider the case in which the components are independently but not identically distributed; for example, only the components in each row or in each column may be {identically distributed}. We also consider the more general case in which the components are...

Topics: Quantitative Finance, Condensed Matter, Mathematics, Disordered Systems and Neural Networks,...

Source: http://arxiv.org/abs/1605.06840

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4.0

Jun 30, 2018
06/18

by
G. G. Kozlov

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Exactly solvable model of disordered system representing the generalized Lloyd model with correlated random potential is described. It is shown, that for the model under consideration, the averaged Green's function does not depend on random potential correlation radius and, similarly to the classical Lloyd model, has the form of Green's function of a crystal system, with energy argument supplied by an imaginary part which depends on degree of disorder.

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1402.5754

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Jun 28, 2018
06/18

by
Emanuele Levi; Markus Heyl; Igor Lesanovsky; Juan P. Garrahan

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Many-body localization (MBL) has emerged as a novel paradigm for robust ergodicity breaking in closed quantum many-body systems. However, it is not yet clear to which extent MBL survives in the presence of dissipative processes induced by the coupling to an environment. Here we study heating and ergodicity for a paradigmatic MBL system---an interacting fermionic chain subject to quenched disorder---in the presence of dephasing. We find that, even though the system is eventually driven into an...

Topics: Disordered Systems and Neural Networks, Statistical Mechanics, Strongly Correlated Electrons,...

Source: http://arxiv.org/abs/1510.04634

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Feb 23, 2021
02/21

by
Changelog Master Feed

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What's the most practical of practical AI things? Data labeling of course! It's also one of the most time consuming and error prone processes that we deal with in AI development. Michael Malyuk of Heartex and Label Studio joins us to discuss various data labeling challenges and open source tooling to help us overcome those challenges.

Topics: Podcast, changelog, open source, oss, software, development, developer, hackerchangelog, ai,...

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Jun 28, 2018
06/18

by
Francesca Pietracaprina; Valentina Ros; Antonello Scardicchio

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In this paper we analyze the predictions of the forward approximation in some models which exhibit an Anderson (single-) or many-body localized phase. This approximation, which consists in summing over the amplitudes of only the shortest paths in the locator expansion, is known to over-estimate the critical value of the disorder which determines the onset of the localized phase. Nevertheless, the results provided by the approximation become more and more accurate as the local coordination...

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1508.05097

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Feb 24, 2021
02/21

by
Changelog Master Feed

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We met up with Wojciech Zaremba at the O'Reilly AI conference in SF. He took some time to talk to us about some of his recent research related to reinforcement learning and robots. We also discussed AI safety and the hype around OpenAI.

Topics: Podcast, changelog, open source, oss, software, development, developer, hackerchangelog, ai,...

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Jun 28, 2018
06/18

by
Yan V. Fyodorov; Pierre Le Doussal

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We study three instances of log-correlated processes on the interval: the logarithm of the Gaussian unitary ensemble (GUE) characteristic polynomial, the Gaussian log-correlated potential in presence of edge charges, and the Fractional Brownian motion with Hurst index $H \to 0$ (fBM0). In previous collaborations we obtained the probability distribution function (PDF) of the value of the global minimum (equivalently maximum) for the first two processes, using the {\it freezing-duality...

Topics: Statistical Mechanics, Mathematics, Condensed Matter, Disordered Systems and Neural Networks,...

Source: http://arxiv.org/abs/1511.04258

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Jun 29, 2018
06/18

by
Walter Kob; Simona Ispas

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In this article we review results of computer simulation of glasses carried out using first principles approaches, notably density functional theory. We start with a brief introduction to this method and compare the pros and cons of this approach with the ones of simulations with classical potentials. This is followed by a discussion of simulation results of various glass-forming systems that have been obtained via ab initio simulations and that demonstrate the usefulness of this approach to...

Topics: Disordered Systems and Neural Networks, Materials Science, Condensed Matter, Statistical Mechanics

Source: http://arxiv.org/abs/1604.07959

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4.0

Jun 30, 2018
06/18

by
S. Das Sarma; E. H. Hwang

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Low-disorder and high-mobility 2D electron (or hole) systems undergo an apparent metal-insulator-transition (MIT) at low temperatures as the carrier density (n) is varied. In some situations, the 2D MIT can be caused at a fixed low carrier density by changing an externally applied in-plane magnetic field parallel to the 2D layer. d\rho/dT changes its sign at some nonuniversal sample-dependent critical carrier density n_c separating an effective 2D metal (d\rho/dT >0) for n>n_c from an...

Topics: Mesoscale and Nanoscale Physics, Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1401.4762

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Jun 29, 2018
06/18

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Pierre Barrat-Charlaix; Matteo Figliuzzi; Martin Weigt

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The inverse Ising problem and its generalizations to Potts and continuous spin models have recently attracted much attention thanks to their successful applications in the statistical modeling of biological data. In the standard setting, the parameters of an Ising model (couplings and fields) are inferred using a sample of equilibrium configurations drawn from the Boltzmann distribution. However, in the context of biological applications, quantitative information for a limited number of...

Topics: Quantitative Biology, Disordered Systems and Neural Networks, Quantitative Methods, Statistical...

Source: http://arxiv.org/abs/1609.05692

Topics: Radio Program, Atlantic Records artists, Email, Computational neuroscience, Formal sciences, Neural...

Topics: Radio Program, Artificial intelligence, Formal sciences, Cybernetics, Neural networks, Shipping,...

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Topics: Radio Program, Central nervous system, American rock music groups, Brain, Clubs and societies,...

Topics: Radio Program, Divided regions, Republics, East Asian countries, Artificial intelligence, Fuzzy...

Topics: Radio Program, Mass media, Revolutionary tactics, International relations, English songwriters,...

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Jun 26, 2018
06/18

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Santanu Sinha; Jonas T. Kjellstadli; Alex Hansen

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We consider the local load sharing fiber bundle model in one to five dimensions. Depending on the breaking threshold distribution of the fibers, there is a transition where the fracture process becomes localized. In the localized phase, the model behaves as the invasion percolation model. The difference between the local load sharing fiber bundle model and the equal load sharing fiber bundle model decreases with increasing dimensionality as a power law.

Topics: Condensed Matter, Disordered Systems and Neural Networks

Source: http://arxiv.org/abs/1501.02489

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Feb 24, 2021
02/21

by
Changelog Master Feed

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Mike Bugembe teaches us how to build a culture of data-driven decision making within a company, leverage behavioral economics, and identify high value use cases for AI.

Topics: Podcast, changelog, open source, oss, software, development, developer, hackerchangelog, ai,...

Topics: Radio Program, Single-party states, Divided regions, Republics, East Asian countries, Fuzzy logic,...

Topics: Radio Program, Cybernetics, Artificial intelligence, Computational neuroscience, Technology in...

Topics: Radio Program, Cybernetics, Technology in society, New religious movements, Psychological...

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5.0

Jun 30, 2018
06/18

by
Hassan Bassereh; Vahid Salari; Farhad Shahbazi

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In this paper, we investigate the effect of noise and disorder on the efficiency of excitation energy transfer (EET) in a $N=5$ sites linear chain with "static" dipole-dipole couplings. In fact, here, the disordered chain is a toy model for one strand of the selectivity filter backbone in ion channels. It is recently discussed that the presence of quantum coherence in the selectivity filter is possible and can play a role in mediating ion-conduction and ion-selectivity in the...

Topics: Biological Physics, Physics, Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1408.6256

Topics: Radio Program, Formal sciences, Artificial intelligence, Cybernetics, Republics, Divided regions,...

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4.0

Jun 30, 2018
06/18

by
V. K. Chandrasekar; R. Gopal; A. Venkatesan; M. Lakshmanan

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We identify the mechanism behind the existence of intensity induced chimera states in globally coupled oscillators. We find that the effect of intensity in the system is to cause multistability by increasing the number of fixed points. This in turn increases the number of multistable attractors and we find that their stability is determined by the strength of coupling . This causes the coexistence of different collective states in the system depending upon the initial state. We demonstrate that...

Topics: Nonlinear Sciences, Adaptation and Self-Organizing Systems, Disordered Systems and Neural Networks,...

Source: http://arxiv.org/abs/1406.7504

Topics: Radio Program, Cybernetics, Artificial intelligence, Formal sciences, Computer science, Theoretical...

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01:00:00AM-06:00:00AM GMT — As BBC Radio 5 live 02/02/2020 BBC Radio Devon joins BBC Radio 5 live.

Topics: Radio Program, Pollution, Climate change, Sustainable technologies, Environment, Retailing, Systems...

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Feb 23, 2021
02/21

by
Changelog Master Feed

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Redis is a an open source, in-memory data structure store, widely used as a database, cache and message broker. It now also support tensor data types and deep learning models via the RedisAI module. Why did they build this module? Who is or should be using it? We discuss this and much more with Pieter Cailliau.

Topics: Podcast, changelog, open source, oss, software, development, developer, hackerchangelog, ai,...

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7.0

Jun 29, 2018
06/18

by
Alexander Altland; Tobias Micklitz

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We construct an analytic theory of many-body localization (MBL) in random spin chains. The approach is based on a first quantized perspective in which MBL is understood as a localization phenomenon on the high dimensional lattice defined by the discrete Hilbert space of the clean system. We construct a field theory on that lattice and apply it to discuss the stability of a weak disorder (`Wigner-Dyson') and a strong disorder (`Poisson') phase.

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1609.00877

Topics: Radio Program, Mass media, Business, Nervous system, Sociological theories, County seats in...

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4.0

Jun 30, 2018
06/18

by
Ilia Zintchenko; Matthew B. Hastings; Matthias Troyer

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We consider whether it is possible to find ground states of frustrated spin systems by solving them locally. Using spin glass physics and Imry-Ma arguments in addition to numerical benchmarks we quantify the power of such local solution methods and show that for the average low-dimensional spin glass problem outside the spin- glass phase the exact ground state can be found in polynomial time. In the second part we present a heuristic, general-purpose hierarchical approach which for spin glasses...

Topics: Quantum Physics, Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1408.1901

Topics: Radio Program, Central nervous system, Member states of the United Nations, Brain, Neural networks,...

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3.0

Jun 30, 2018
06/18

by
Xun Gao; Lu-Ming Duan

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The challenge of quantum many-body problems comes from the difficulty to represent large-scale quantum states, which in general requires an exponentially large number of parameters. Recently, a connection has been made between quantum many-body states and the neural network representation (\textit{arXiv:1606.02318}). An important open question is what characterizes the representational power of deep and shallow neural networks, which is of fundamental interest due to popularity of the deep...

Topics: Disordered Systems and Neural Networks, Condensed Matter, Quantum Physics

Source: http://arxiv.org/abs/1701.05039

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Jun 29, 2018
06/18

by
Yoav Lahini; Omer Gottesman; Ariel Amir; Shmuel M. Rubinstein

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We observe non-monotonic aging and memory effects, two hallmarks of glassy dynamics, in two disordered mechanical systems: crumpled thin sheets and elastic foams. Under fixed compression, both systems exhibit monotonic non-exponential relaxation. However, when after a certain waiting time the compression is partially reduced, both systems exhibit a non-monotonic response: the normal force first increases over many minutes or even hours until reaching a peak value, and only then relaxation is...

Topics: Soft Condensed Matter, Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1608.02429

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4.0

Jun 29, 2018
06/18

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Jonathan J. Heckman; Jeffrey G. Bernstein; Ben Vigoda

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Motivated by the physics of strings and branes, we introduce a general suite of Markov chain Monte Carlo (MCMC) "suburban samplers" (i.e., spread out Metropolis). The suburban algorithm involves an ensemble of statistical agents connected together by a random network. Performance of the collective in reaching a fast and accurate inference depends primarily on the average number of nearest neighbor connections. Increasing the average number of neighbors above zero initially leads to an...

Topics: High Energy Physics - Theory, Computational Physics, Condensed Matter, Physics, Disordered Systems...

Source: http://arxiv.org/abs/1605.06122

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Jun 28, 2018
06/18

by
R. Baviera; M. A. Virasoro

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In the study of disordered models like spin glasses the key object of interest is the rugged energy hypersurface defined in configuration space. The statistical mechanics calculation of the Gibbs-Boltzmann Partition Function gives the information necessary to understand the equilibrium behavior of the system as a function of the temperature but is not enough if we are interested in more general aspects of the hypersurface: it does not give us, for instance, the different degrees of ruggedness...

Topics: Disordered Systems and Neural Networks, Statistical Mechanics, Condensed Matter

Source: http://arxiv.org/abs/1508.01232

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4.0

Jun 29, 2018
06/18

by
Hao Hu; Robert M. Ziff; Youjin Deng

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The no-enclave percolation (NEP) model introduced recently by Sheinman et al. can be mapped to a problem of holes within a standard percolation backbone, and numerical measurements of these holes gives the size-distribution exponent $\tau = 1.82(1)$ of the NEP model. An argument is given that $\tau=1 + d_B/2 \approx 1.822$ where $d_B$ is the backbone dimension. On the other hand, a model of simple holes within a percolation cluster implies $\tau = 1 + d_f/2 = 187/96 \approx 1.948$, where $d_f$...

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1605.03685

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2.0

Jun 29, 2018
06/18

by
Florent Krzakala; Jiaming Xu; Lenka Zdeborová

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We consider the estimation of a n-dimensional vector x from the knowledge of noisy and possibility non-linear element-wise measurements of xxT , a very generic problem that contains, e.g. stochastic 2-block model, submatrix localization or the spike perturbation of random matrices. We use an interpolation method proposed by Guerra and later refined by Korada and Macris. We prove that the Bethe mutual information (related to the Bethe free energy and conjectured to be exact by Lesieur et al. on...

Topics: Condensed Matter, Mathematics, Disordered Systems and Neural Networks, Information Theory,...

Source: http://arxiv.org/abs/1603.08447

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2.0

Jun 29, 2018
06/18

by
Cyril Furtlehner; Aurélien Decelle

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We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We...

Topics: Disordered Systems and Neural Networks, Condensed Matter

Source: http://arxiv.org/abs/1602.03102

Topics: Radio Program, Artificial intelligence, Cybernetics, Formal sciences, Learning, Nuclear weapons,...

Topics: Radio Program, Cybernetics, Health care, NPR programs, Neural networks, Machine learning,...

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4.0

Jun 29, 2018
06/18

by
Gilberto M. Nakamura; Ana Carolina P. Monteiro; George C. Cardoso; Alexandre S. Martinez

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Two simple agent based models are often employed in epidemic studies: the susceptible-infected (SI) and the susceptible-infected-susceptible (SIS). Both models describe the time evolution of infectious diseases in networks in which vertices are either susceptible (S) or infected (I) agents. Predicting the effects of disease spreading is one of the major goals in epidemic studies, but often restricted to numerical simulations. Analytical methods using operatorial content are subjected to the...

Topics: Disordered Systems and Neural Networks, Condensed Matter, Physics, Physics and Society

Source: http://arxiv.org/abs/1606.07825