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Related papers: Discontinuous BBP transitions

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The baryon-acoustic oscillation (BAO) feature in the Lyman-$\alpha$ forest is one of the key probes of the cosmic expansion rate at redshifts z~2.5, well before dark energy is believed to have become dynamically significant. A key advantage…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-27 Christopher M. Hirata

A phase diagram for a 2D metal with variable carrier density has been derived. It consists of a normal phase, where the order parameter is absent; a so-called ``abnormal normal'' phase where this parameter is also absent but the mean number…

Superconductivity · Physics 2009-10-30 Valery P. Gusynin , Vadim M. Loktev , Sergei G. Sharapov

The standard mean-field treatment of low-temperature superconductors leads to a square-root divergent density of states at the gap value. This feature can lead to unphysical logarithmic divergences in various quantities, such as currents…

Superconductivity · Physics 2025-12-22 G. Marchegiani , G. Catelani

Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since ResNet, we are able to train very deep CNNs as the gradient vanishing issue has been largely addressed by the introduction of skip…

Computer Vision and Pattern Recognition · Computer Science 2020-02-18 Yong Guo , Jian Chen , Qing Du , Anton Van Den Hengel , Qinfeng Shi , Mingkui Tan

In this paper we compare and contrast the behavior of the posterior predictive distribution to the risk of the maximum a posteriori estimator for the random features regression model in the overparameterized regime. We will focus on the…

Machine Learning · Statistics 2023-10-30 Youngsoo Baek , Samuel I. Berchuck , Sayan Mukherjee

This study proposes the novel Bayesian and inverse Bayesian (BIB) inference framework that incorporates symmetry bias into the Bayesian updating process to perform both conventional and inverse Bayesian updates concurrently. Conventional…

The aim of the present study is to detect abrupt trend changes in the mean of a multidimensional sequential signal. Directly inspired by papers of Fernhead and Liu ([4] and [5]), this work describes the signal in a hierarchical manner : the…

Machine Learning · Computer Science 2021-06-11 Olivier Sorba , C Geissler

A scheme is proposed that combines probabilistic signal shaping with bit-metric decoding. The transmitter generates symbols according to a distribution on the channel input alphabet. The symbols are labeled by bit strings. At the receiver,…

Information Theory · Computer Science 2014-04-22 Georg Böcherer

The measured B -> pi pi, pi K branching ratios exhibit puzzling patterns. We point out that the B -> pi pi hierarchy can be nicely accommodated in the Standard Model (SM) through non-factorizable hadronic interference effects, whereas the B…

High Energy Physics - Phenomenology · Physics 2009-11-10 Andrzej J. Buras , Robert Fleischer , Stefan Recksiegel , Felix Schwab

Recent work has highlighted the utility of methods for early warning signal detection in dynamic systems approaching critical tipping thresholds. Often these tipping points resemble local bifurcations, whose low dimensional dynamics can…

Computational Physics · Physics 2024-08-08 Daniel Dylewsky , Madhur Anand , Chris T. Bauch

Structural resonance involves the absorption of inertial loads by a tuned structural elasticity: a process playing a key role in a wide range of biological and technological systems, including many biological and bio-inspired locomotion…

Pattern Formation and Solitons · Physics 2023-07-20 Arion Pons , Tsevi Beatus

As an extension of previous theoretical study on the coherent structure resonance due to space charge effects [Chao Li and R. A. Jameson, Phys. Rev. Accel. Beams 21, 024204, 2018], this paper aims to demonstrate how the beam, as a whole, is…

Accelerator Physics · Physics 2019-06-05 Zhicong Liu , Chao Li , Qing Qin

We simulate the transition from amplified spontaneous emission (ASE) to lasing in random systems with varying degrees of mode overlap. This is accomplished by solving the stochastic Maxwell-Bloch equations with the finite-difference…

Optics · Physics 2010-12-30 Jonathan Andreasen , Hui Cao

Intrigued by a recent Belle result for a large direct CP asymmetry in $B^0\to D^+D^-$, we study the effects of a $\bar b\to \bar uu\bar d$ quark transition by combining the asymmetry information with rates and asymmetries in isospin-related…

High Energy Physics - Phenomenology · Physics 2008-11-26 Michael Gronau , Jonathan L. Rosner , Dan Pirjol

We introduce a generalized version of the Biswas-Chatterjee-Sen (BChS) model \cite{Biswas} with group interactions of size $q$, extending the original pairwise interaction dynamics. Within a mean-field framework, we derive an exact…

Statistical Mechanics · Physics 2026-04-15 Amit Pradhan

Modern wireless channels are increasingly dense and mobile making the channel highly non-stationary. The time-varying distribution and the existence of joint interference across multiple degrees of freedom (e.g., users, antennas, frequency…

Information Theory · Computer Science 2022-11-14 Zhibin Zou , Maqsood Careem , Aveek Dutta , Ngwe Thawdar

The boson peak is a characteristic anomaly of amorphous solids broadly defined as a low-energy excess in the density of states and heat capacity compared to the textbook predictions of Debye theory. The origin of this anomaly has long been…

This paper presents a deep unfolding-supported coordinated multipoint beam pattern synthesis (DUCoMP-BPS) scheme to overcome the high complexity, poor adaptability, and limited scalability of traditional cell-free anti-jamming beamforming.…

Signal Processing · Electrical Eng. & Systems 2026-04-28 Zilong Wang , Cheng Zhang , Zhilei Zhang , Yaxuan Hu , Wen Wang , Yongming Huang

The contact process is a stochastic process which exhibits a continuous, absorbing-state phase transition in the Directed Percolation (DP) universality class. In this work, we consider a contact process with a bias in conjunction with an…

Statistical Mechanics · Physics 2013-05-20 A. Costa , R. A. Blythe , M. R. Evans

Learning stochastic functions from partially observed context-target pairs requires models that are expressive, uncertainty-aware, and strongly conditioned on inputs. Neural Diffusion Processes (NDPs) improve expressivity with denoising…

Machine Learning · Computer Science 2026-04-30 Jian Xu , Yican Liu , Delu Zeng , John Paisley , Qibin Zhao