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We develop a theory of the local density of states (LDOS) of disordered superconductors, employing the non-linear sigma-model formalism and the renormalization-group framework. The theory takes into account the interplay of disorder and…

Mesoscale and Nanoscale Physics · Physics 2016-08-09 I. S. Burmistrov , I. V. Gornyi , A. D. Mirlin

Neural implicit fields, such as the neural signed distance field (SDF) of a shape, have emerged as a powerful representation for many applications, e.g., encoding a 3D shape and performing collision detection. Typically, implicit fields are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Guying Lin , Lei Yang , Yuan Liu , Congyi Zhang , Junhui Hou , Xiaogang Jin , Taku Komura , John Keyser , Wenping Wang

Intracellular recordings of cortical neurons in vivo display intense subthreshold membrane potential (Vm) activity. The power spectral density (PSD) of the Vm displays a power-law structure at high frequencies (>50 Hz) with a slope of about…

Neurons and Cognition · Quantitative Biology 2009-11-13 Claude Bedard , Alain Destexhe

Various neurophysiological and cognitive functions are based on transferring information between spiking neurons via a complex system of synaptic connections. In particular, the capacity of presynaptic inputs to influence the postsynaptic…

Neurons and Cognition · Quantitative Biology 2018-10-30 Y. Dabaghian

Cortical pyramidal neurons have a complex dendritic anatomy, whose function is an active research field. In particular, the segregation between its soma and the apical dendritic tree is believed to play an active role in processing…

Neurons and Cognition · Quantitative Biology 2021-07-13 Fabian Schubert , Claudius Gros

Noise-delayed decay (NDD) phenomenon emerges when the first-spike latency of a periodically forced stochastic neuron exhibits a maximum for a particular range of noise intensity. Here, we investigate the latency response dynamics of a…

Neurons and Cognition · Quantitative Biology 2015-12-23 M. Uzuntarla , M. Ozer , U. Ileri , A. Calim , J. J. Torres

The center-bound excitonic diffusion on dendrimers subjected to several types of non-homogeneous funneling potentials, is considered. We first study the mean-first passage time (MFPT) for diffusion in a linear potential with different types…

Statistical Mechanics · Physics 2009-11-07 Subhadip Raychaudhuri , Yonathan Shapir , Shaul Mukamel

The anisotropic and non-linear transport properties of the quasi one-dimensional organic conductor (TMTSF)_2PF_6 have been studied by dc, radiofrequency, and microwave methods. Microwave experiments along all three axes reveal that…

Strongly Correlated Electrons · Physics 2010-10-05 P. Zornoza , K. Petukhov , M. Dressel , N. Biskup , T. Vuletic , S. Tomic

Scheduling flexible sources to promote the integration of renewable generation is one fundamental problem for operating active distribution networks (ADNs). However, existing works are usually based on power flow models, which require…

Optimization and Control · Mathematics 2022-08-09 Ge Chen , Hongcai Zhang , Yonghua Song

In neural circuits, synaptic strengths influence neuronal activity by shaping network dynamics, and neuronal activity influences synaptic strengths through activity-dependent plasticity. Motivated by this fact, we study a recurrent-network…

Neurons and Cognition · Quantitative Biology 2024-01-12 David G. Clark , L. F. Abbott

We study bifurcations in networks of integrate-and-fire neurons with stochastic spike emission, focusing on the effects of the spatial and temporal structure of the synaptic interactions. Using a deterministic mean-field approximation of…

Neurons and Cognition · Quantitative Biology 2026-05-19 Lauren Forbes , Jared Grossman , Montie Avery , Ryan Goh , Gabriel Koch Ocker

Neocortical pyramidal neurons have many dendrites, and such dendrites are capable of, in isolation of one-another, generating a neuronal spike. It is also now understood that there is a large amount of dendritic growth during the first…

Neurons and Cognition · Quantitative Biology 2022-10-31 William B Levy , Robert A. Baxter

We extend the density-functional theory for superconductors (SCDFT) to take account of the dynamical structure of the screened Coulomb interaction. We construct an exchange-correlation kernel in the SCDFT gap equation on the basis of the…

Superconductivity · Physics 2014-01-08 Ryosuke Akashi , Ryotaro Arita

The ability of cells to sense and respond to the mechanical properties of their environments is fundamental to a range of cellular behaviours, with substrate stiffness increasingly being found to be a key signalling factor. Although active…

Cell Behavior · Quantitative Biology 2019-09-04 Carina M. Dunlop

Symbol-level precoding (SLP) has recently emerged as a new paradigm for physical-layer transmit precoding in multiuser multi-input-multi-output (MIMO) channels. It exploits the underlying symbol constellation structure, which the…

Signal Processing · Electrical Eng. & Systems 2022-05-04 Yatao Liu , Mingjie Shao , Wing-Kin Ma , Qiang Li

We investigate the capability of density functional theory (DFT) to appropriately describe the spin susceptibility, $\chi_s$, and the intervalley electron-phonon coupling in Li$_x$ZrNCl. At low doping, Li$_x$ZrNCl behaves as a…

Superconductivity · Physics 2016-07-08 Betül Pamuk , Jacopo Baima , Roberto Dovesi , Matteo Calandra , Francesco Mauri

The Hurst effect in the signals describing ion channels' activity has been known for many years. This effect is present in the experimental recordings of single-channel currents, but not only. The sequences of dwell times of functionally…

Place cells in the hippocampus are active when an animal visits a certain location (referred to as a place field) within an environment. Grid cells in the medial entorhinal cortex (MEC) respond at multiple locations, with firing fields that…

Neurons and Cognition · Quantitative Biology 2018-05-17 David M. Schwartz , O. Ozan Koyluoglu

The circuits comprising superconducting optoelectronic synapses, dendrites, and neurons are described by numerically cumbersome and formally opaque coupled differential equations. Reference 1 showed that a phenomenological model of…

Neural and Evolutionary Computing · Computer Science 2024-09-27 Jeffrey M. Shainline , Bryce A. Primavera , Ryan O'Loughlin

Recent empirical evidence has demonstrated that the training dynamics of large-scale deep neural networks occur within low-dimensional subspaces. While this has inspired new research into low-rank training, compression, and adaptation,…

Machine Learning · Computer Science 2026-02-09 Alec S. Xu , Can Yaras , Matthew Asato , Qing Qu , Laura Balzano