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Related papers: Coarse graining flow of spin foam intertwiners

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We consider a system of two-level quantum quasi-spins and gauge bosons put on a 3+1D lattice. As a model of neural network of the brain functions, these spins describe neurons quantum-mechanically, and the gauge bosons describes weights of…

Disordered Systems and Neural Networks · Physics 2016-10-19 Shinya Sakane , Takashi Hiramatsu , Tetsuo Matsui

This thesis is dedicated to the study of open spin networks. We formulate quasi-local descriptions of loop quantum gravity. We investigate the coarse-graining procedure via tracing over bulk degrees of freedom, which encodes all that we can…

General Relativity and Quantum Cosmology · Physics 2023-06-08 Qian Chen

The diversity of neuron models used in contemporary theoretical neuroscience to investigate specific properties of covariances raises the question how these models relate to each other. In particular it is hard to distinguish between…

Neurons and Cognition · Quantitative Biology 2022-05-17 Dmytro Grytskyy , Tom Tetzlaff , Markus Diesmann , Moritz Helias

Kernel-based methods such as Rocket are among the most effective default approaches for univariate time series classification (TSC), yet they do not perform equally well across all datasets. We revisit the long-standing intuition that…

Machine Learning · Computer Science 2026-01-13 Honey Singh Chauhan , Zahraa S. Abdallah

We present a wavelet-based adaptive method for computing 3D multiscale flows in complex, time-dependent geometries, implemented on massively parallel computers. While our focus is on simulations of flapping insects, it can be used for other…

Numerical Analysis · Mathematics 2021-01-07 Thomas Engels , Kai Schneider , Julius Reiss , Marie Farge

Shear flow of dense, non-Brownian suspensions is simulated using the discrete element method, taking particle contact and hydrodynamic lubrication into account. The resulting flow regimes are mapped in the parametric space of solid volume…

Soft Condensed Matter · Physics 2015-01-06 Christopher Ness , Jin Sun

Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.) across multiple domains at the cost of high computational and memory requirements. Thus, leveraging CNNs…

Computer Vision and Pattern Recognition · Computer Science 2018-11-21 Pravendra Singh , Vinay Sameer Raja Kadi , Nikhil Verma , Vinay P. Namboodiri

Although the behavior of entangled polymers in startup shear flows with constant shear rates has been thoroughly investigated, the response under creep has not been frequently considered. In this study, primitive chain network simulations,…

Soft Condensed Matter · Physics 2026-02-03 Yuichi Masubuchi , Giovanni Ianniruberto , Giuseppe Marrucci

This work presents a rigorous framework based on coarse-graining to analyze highly compressible turbulence. We show how the requirement that viscous effects on the dynamics of large-scale momentum and kinetic energy be negligible ---an…

Fluid Dynamics · Physics 2012-12-27 Hussein Aluie

Granular materials are involved in most industrial and environmental processes, as well as many civil engineering applications. Although significant advances have been made in understanding the statics and dynamics of cohesionless grains…

Soft Condensed Matter · Physics 2025-11-21 Ram Sudhir Sharma , Alban Sauret

In the class of immersed boundary (IB) methods, the choice of the delta function plays a crucial role in transferring information between fluid and solid domains. Most prior work has used isotropic kernels that do not preserve the…

Numerical Analysis · Mathematics 2024-12-23 Lianxia Li , Cole Gruninger , Jae H. Lee , Boyce E. Griffith

We show that the degenerate sector of Spin(4) Plebanski formulation of four-dimensional gravity is exactly solvable and describes covariantly embedded SU(2) BF theory. This fact ensures that its spin foam quantization is given by the SU(2)…

General Relativity and Quantum Cosmology · Physics 2012-10-12 Sergei Alexandrov

We present a detailed analysis of the dynamical regimes observed in a balanced network of identical Quadratic Integrate-and-Fire (QIF) neurons with a sparse connectivity for homogeneous and heterogeneous in-degree distribution. Depending on…

Neurons and Cognition · Quantitative Biology 2025-05-29 Matteo Di Volo , Marco Segneri , Denis Goldobin , Antonio Politi , Alessandro Torcini

TCP BBR's behavior has been explained by various theoretical models, and in particular those that describe how it co-exists with other types of flows. However, as new versions of the BBR protocol have emerged, it remains unclear to what…

Networking and Internet Architecture · Computer Science 2025-05-13 Fatih Berkay Sarpkaya , Ashutosh Srivastava , Fraida Fund , Shivendra Panwar

In the recent years, deep learning approaches have shown much promise in modeling complex systems in the physical sciences. A major challenge in deep learning of PDEs is enforcing physical constraints and boundary conditions. In this work,…

Computational Physics · Physics 2020-02-18 Arvind T. Mohan , Nicholas Lubbers , Daniel Livescu , Michael Chertkov

In this paper, we examine how to build coarse-grain transport models consistently from the kinetic to fluid regimes. The internal energy of the gas particles is described through a state-to-state approach. A kinetic equation allows us to…

Fluid Dynamics · Physics 2021-03-15 Erik Torres , Georgios Bellas-Chatzigeorgis , Thierry E. Magin

A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach groups of monomers are mapped onto a single pseudoatom (a blob) and the…

Soft Condensed Matter · Physics 2015-01-07 Giuseppe D'Adamo , Andrea Pelissetto , Carlo Pierleoni

Two coarse-grained models which capture some universal characteristics of stripe forming systems are stud- ied. At high temperatures, the structure factors of both models attain their maxima on a circle in reciprocal space, as a consequence…

Statistical Mechanics · Physics 2012-12-18 Alejandro Mendoza-Coto , Daniel A. Stariolo

Consistency models have recently been introduced to accelerate sampling from diffusion models by directly predicting the solution (i.e., data) of the probability flow ODE (PF ODE) from initial noise. However, the training of consistency…

Machine Learning · Computer Science 2025-01-24 Sangyun Lee , Yilun Xu , Tomas Geffner , Giulia Fanti , Karsten Kreis , Arash Vahdat , Weili Nie

We use quantum Monte Carlo simulations to study a quantum $S=1/2$ spin model with competing multi-spin interactions. We find a quantum phase transition between a columnar valence-bond solid (cVBS) and a N\'eel antiferromagnet (AFM), as in…

Strongly Correlated Electrons · Physics 2020-07-09 Bowen Zhao , Jun Takahashi , Anders W. Sandvik