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Related papers: Testing a best-fit hydrodynamical model using PCA

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Principal component analysis (PCA) is a widespread technique for data analysis that relies on the covariance-correlation matrix of the analyzed data. However to properly work with high-dimensional data, PCA poses severe mathematical…

Quantitative Methods · Quantitative Biology 2018-10-18 Luigi Leonardo Palese

A recent experiment driving colloids electromagnetically, by B\'erut et al. [2014 Europhys. Lett. 107, 60004], is an ideal paradigm for illustrating a linear response theory for nonequilibrium overdamped systems including hydrodynamic…

Statistical Mechanics · Physics 2016-03-22 Cem Yolcu , Marco Baiesi

In this work we introduce a new residual for normal linear models that are suitable for situations in which we are dealing with heteroskedasticity of unknown form, they are referred to by principal component analysis (PCA) residuals. These…

Methodology · Statistics 2017-09-01 Andréa V. Rocha , Evelina Shamarova , Alexandre B. Simas

Predictive dynamical models for marine ecosystems are used for a variety of needs. Due to sparse measurements and limited understanding of the myriad of ocean processes, there is however significant uncertainty. There is model uncertainty…

Computational Engineering, Finance, and Science · Computer Science 2023-06-06 Abhinav Gupta , Pierre F. J. Lermusiaux

The "Underlying Event" at CMS (under nominal and start-up conditions) is studied by examining charged particle and momentum densities in the "transverse" region in charged particle jet production. The predictions of various QCD models with…

High Energy Physics - Experiment · Physics 2008-10-28 Yuan Chao

Investigating properties of phase change materials (PCMs) is an important issue due to their extensive use in heat storage systems and thermal regulation devices. Improvement of the efficiency of such systems should be based on a better…

Applied Physics · Physics 2022-07-18 L. Klochko , J. Noel , N. R. Sgreva , S. Leclerc , C. Métivier , D. Lacroix , M. Isaiev

Principal component analysis (PCA) is a well-known linear dimension-reduction method that has been widely used in data analysis and modeling. It is an unsupervised learning technique that identifies a suitable linear subspace for the input…

Machine Learning · Statistics 2021-09-10 Shaojie Xu , Joel Vaughan , Jie Chen , Agus Sudjianto , Vijayan Nair

The viscosity and self-diffusion constant of particle-based mesoscale hydrodynamic methods, multi-particle collision dynamics (MPC) and dissipative particle dynamics (DPD), are investigated, both with and without angular-momentum…

Soft Condensed Matter · Physics 2009-11-13 Hiroshi Noguchi , Gerhard Gompper

Principal Component Analysis (PCA) is an important tool of dimension reduction especially when the dimension (or the number of variables) is very high. Asymptotic studies where the sample size is fixed, and the dimension grows [i.e., High…

Statistics Theory · Mathematics 2009-11-20 Sungkyu Jung , J. S. Marron

Hydrodynamic interactions in a suspension of spherical particles confined between two parallel planar walls are studied under creeping-flow conditions. The many-particle friction matrix in this system is evaluated using our novel numerical…

Fluid Dynamics · Physics 2009-11-11 S. Bhattacharya , J. Blawzdziewicz , E. Wajnryb

This paper describes the results of our theoretical and numerical studies of hydrodynamic interactions in a suspension of spherical particles confined between two parallel planar walls, under creeping-flow conditions. We propose a novel…

Soft Condensed Matter · Physics 2009-11-11 S. Bhattacharya , J. Blawzdziewicz , E. Wajnryb

In high energy heavy ion collisions a new state of matter, the strongly coupled quark gluon plasma is formed that exhibits the similar properties as our Universe had just a couple of microseconds after the Big Bang, hence such collisions…

High Energy Physics - Phenomenology · Physics 2025-07-15 Sándor Lökös , Gábor Kasza

Recent development of a hydrodynamic model is discussed by putting an emphasis on realistic treatment of the early and late stages in relativistic heavy ion collisions. The model, which incorporates a hydrodynamic description of the…

Nuclear Theory · Physics 2008-11-26 Tetsufumi Hirano

Two-particle correlations in relative rapidity and azimuth are studied for the p-Pb collisions at the LHC energy of 5.02 TeV in the framework of event-by-event 3+1-dimensional viscous hydrodynamics. It is found that for the…

Nuclear Theory · Physics 2013-01-16 Piotr Bozek , Wojciech Broniowski

Quantum plasma physics is a rapidly evolving research field with a very inter-disciplinary scope of potential applications, ranging from nano-scale science in condensed matter to the vast scales of astrophysical objects. The theoretical…

Plasma Physics · Physics 2013-10-02 Shabbir A. Khan , Michael Bonitz

Probabilistic principal component analysis (PCA) and its Bayesian variant (BPCA) are widely used for dimension reduction in machine learning and statistics. The main advantage of probabilistic PCA over the traditional formulation is…

Machine Learning · Statistics 2025-05-23 Arghya Datta , Philippe Gagnon , Florian Maire

The aim of hybrid methods in simulations is to communicate regions with disparate time and length scales. Here, a fluid described at the atomistic level within an inner region P is coupled to an outer region C described by continuum fluid…

Soft Condensed Matter · Physics 2009-11-10 R. Delgado-Buscalioni , P. V. Coveney

Recent discussions of RHIC data emphasized the exciting possibility that the matter produced in nucleus-nucleus collisions shows properties of a near-perfect fluid. Here, we aim at delineating the applicability of fluid dynamics, which is…

High Energy Physics - Phenomenology · Physics 2008-11-26 Rudolf Baier , Paul Romatschke , Urs Achim Wiedemann

We present a multiparticle collision dynamics (MPC) implementation of layered immiscible fluids $A$ and $B$ of different shear viscosities separated by planar interfaces. The simulated flow profile for imposed steady shear motion and the…

Soft Condensed Matter · Physics 2021-09-07 Zihan Tan , Vania Calandrini , Jan K. G. Dhont , Gerhard Nägele , Roland G. Winkler

Relativistic hydrodynamics has been quite successful in explaining the collective behaviour of the QCD matter produced in high energy heavy-ion collisions at RHIC and LHC. We briefly review the latest developments in the hydrodynamical…

Nuclear Theory · Physics 2016-10-28 Amaresh Jaiswal , Victor Roy