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Multipartite entanglement tomography, namely the quantum Fisher information (QFI) calculated with respect to different collective operators, allows to fully characterize the phase diagram of the quantum Ising chain in a transverse field…

Quantum Physics · Physics 2019-05-22 Marco Gabbrielli , Luca Lepori , Luca Pezzè

We introduce and analyze an open quantum generalization of the q-state Potts-Hopfield neural network, which is an associative memory model based on multi-level classical spins. The dynamics of this many-body system is formulated in terms of…

Quantum Physics · Physics 2022-03-23 Eliana Fiorelli , Igor Lesanovsky , Markus Müller

We train spiking deep networks using leaky integrate-and-fire (LIF) neurons, and achieve state-of-the-art results for spiking networks on the CIFAR-10 and MNIST datasets. This demonstrates that biologically-plausible spiking LIF neurons can…

Machine Learning · Computer Science 2015-10-30 Eric Hunsberger , Chris Eliasmith

When stimulated by a very large number of Poisson-like presynaptic current input spikes, the temporal dynamics of the soma membrane potential $V(t)$ of a leaky integrate-and-fire (LIF) neuron is typically modeled in the diffusion limit and…

Neurons and Cognition · Quantitative Biology 2015-01-19 Ken Kreutz-Delgado

Variability in neural responses is an ubiquitous phenomenon in neurons, usually modeled with stochastic differential equations. In particular, stochastic integrate-and-fire models are widely used to simplify theoretical studies. The…

Neurons and Cognition · Quantitative Biology 2009-06-12 Eugenio Urdapilleta , Ines Samengo

In $d > 2$ dimensional, homogeneous threshold models discontinuous transition occur, but the mean-field solution provides $1/t$ power-law activity decay and other power-laws, thus it is called mixed-order or hybrid type. It has recently…

Disordered Systems and Neural Networks · Physics 2021-02-10 Géza Ódor , Beatriz de Simoni

Up to now, modern Machine Learning is mainly based on fitting high dimensional functions to enormous data sets, taking advantage of huge hardware resources. We show that biologically inspired neuron models such as the…

Neural and Evolutionary Computing · Computer Science 2022-10-03 Richard C. Gerum , Achim Schilling

One of the most important challenges in mathematical neuroscience is to properly illustrate the stochastic nature of neurons. Among different approaches, the noisy leaky integrate-and-fire and the escape rate models are probably the most…

Analysis of PDEs · Mathematics 2017-02-07 Grégory Dumont , Jacques Henry , Carmen Oana Tarniceriu

We study the global dynamics of integrate and fire neural networks composed of an arbitrary number of identical neurons interacting by inhibition and excitation. We prove that if the interactions are strong enough, then the support of the…

Dynamical Systems · Mathematics 2013-09-10 E. Catsigeras , P. Guiraud

Spike correlations between neurons are ubiquitous in the cortex, but their role is at present not understood. Here we describe the firing response of a leaky integrate-and-fire neuron (LIF) when it receives a temporarily correlated input…

Neurons and Cognition · Quantitative Biology 2007-10-15 Ruben Moreno-Bote , Alfonso Renart , Nestor Parga

We propose a computational model of neuron, called firing cell (FC), properties of which cover such phenomena as attenuation of receptors for external stimuli, delay and decay of postsynaptic potentials, modification of internal weights due…

Neural and Evolutionary Computing · Computer Science 2017-04-24 Jacek Bialowas , Beata Grzyb , Pawel Poszumski

There is a wide range of mathematical models that describe populations of large numbers of neurons. In this article, we focus on nonlinear noisy leaky integrate-and-fire (NNLIF) models that describe neuronal activity at the level of the…

Analysis of PDEs · Mathematics 2024-12-12 María J. Cáceres , José A. Cañizo , Alejandro Ramos-Lora

We study the critical properties of the non-interacting integer quantum Hall to insulator transition (IQHIT) in a "dual" composite-fermion (CF) representation. A key advantage of the CF representation over electron coordinates is that at…

Strongly Correlated Electrons · Physics 2021-02-17 Kevin S. Huang , S. Raghu , Prashant Kumar

The quadratic phase Fourier transform (QPFT) is a generalization of several well-known integral transforms, including the linear canonical transform (LCT), fractional Fourier transform (FrFT), and Fourier transform (FT). This paper…

Functional Analysis · Mathematics 2025-05-06 Sarga Varghese , Gita Rani Mahato , Manab Kundu

The theta rhythm is important for many cognitive functions including spatial processing, memory encoding, and memory recall. The information processing underlying these functions is thought to rely on consistent, phase-specific spiking…

Neurons and Cognition · Quantitative Biology 2025-10-16 Oleg Makarenkov , Marianne Bezaire , Michael Hasselmo

We investigate how the activation function can be used to describe neural firing in an abstract way, and in turn, why it works well in artificial neural networks. We discuss how a spike in a biological neurone belongs to a particular…

Neurons and Cognition · Quantitative Biology 2022-12-27 Dalton A R Sakthivadivel

Quantum phase transitions (QPTs) in coherent Ising machines (CIMs) are studied via a spectral mapping between the one-dimensional XY spin model and a network of degenerate optical parametric oscillators (DOPOs). This exact correspondence…

Quantum Physics · Physics 2025-12-30 Jing-Yi-Ran Jin , Shuang-Quan Ma , Qing Ai

The $q-$state clock model, sometimes called the discrete $XY$ model, is known to show a second-order (symmetry breaking) phase transition in two-dimension (2D) for $q\le 4$ ($q=2$ corresponds to the Ising model). On the other hand, the…

Statistical Mechanics · Physics 2025-06-25 Arpita Goswami , Ravi Kumar , Monikana Gope , Shaon Sahoo

This paper studies a generalization of the Curie-Weiss model (the Ising model on a complete graph) to quantum mechanics. Using a natural probabilistic representation of this model, we give a complete picture of the phase diagram of the…

Probability · Mathematics 2009-11-13 Lincoln Chayes , Nicholas Crawford , Dmitry Ioffe , Anna Levit

Analytical expressions are put forward to investigate the forced spiking activity of abstract neuron models such as the driven leaky integrate-and-fire (LIF) model. The method is valid in a wide parameter regime beyond the restraining…

Neurons and Cognition · Quantitative Biology 2007-05-23 Michael Schindler , Peter Talkner , Peter Hänggi