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The recent observations from CMB have imposed a very stringent upper-limit on the tensor/scalar ratio $r$ of inflation models, $r < 0.064$, which indicates that the primordial gravitational waves (PGW), even though possible to be detected,…

Cosmology and Nongalactic Astrophysics · Physics 2021-02-03 Taotao Qiu , Taishi Katsuragawa , Shulei Ni

In this paper, we propose a novel behavior model for wideband PAs using a real-valued time-delay convolutional neural network (RVTDCNN). The input data of the model are sorted and arranged as the graph composed of the in-phase and…

Signal Processing · Electrical Eng. & Systems 2020-05-21 Xin Hu , Zhijun Liu , Xiaofei Yu , Yulong Zhao , Wenhua Chen , Biao Hu , Xuekun Du , Xiang Li , Mohamed Helaoui , Weidong Wang , Fadhel M. Ghannouchi

I study the space-time evolution of transverse flow and effective temperatures in the dense parton phase with the string melting version of a multi-phase transport model. Parameters of the model are first constrained to reproduce the bulk…

Nuclear Theory · Physics 2015-06-19 Zi-Wei Lin

Using 3+1D viscous relativistic fluid dynamics, we show that electromagnetic probes are sensitive to the initial conditions and to the out-of-equilibrium features of relativistic heavy-ion collisions. Within the same approach, we find that…

High Energy Physics - Phenomenology · Physics 2015-10-28 Gojko Vujanovic , Jean-Francois Paquet , Gabriel S. Denicol , Matthew Luzum , Bjoern Schenke , Sangyong Jeon , Charles Gale

The nuclear modification factor $R_{\rm AA}$ has been satisfactorily described by various jet quenching models. Nonetheless, all these formalisms, until very recently, underpredicted the high-$p_{\rm T}$ (> 10 GeV) elliptic flow $v_2$. We…

High Energy Physics - Phenomenology · Physics 2019-02-21 Carlota Andres , Néstor Armesto , Harri Niemi , Risto Paatelainen , Carlos A. Salgado

Quarkonia and open heavy flavour production are crucial to study the properties of the nuclear matter at high energy densities and of the Quark Gluon Plasma (QGP). In proton-proton collisions at LHC, the measurement of their production…

High Energy Physics - Experiment · Physics 2019-08-13 Raphael Tieulent

In order to probe the dynamics of parton evolution in deep inelastic scattering at small x, high-p_T particles produced centrally in pseudorapidity are studied. In the BFKL mechanism gluon radiation is expected to be more abundant than for…

High Energy Physics - Experiment · Physics 2016-08-31 M. Kuhlen

Much attention has recently been devoted to data-based computing of evolution of physical systems. In such approaches, information about data points from past trajectories in phase space is used to reconstruct the equations of motion and to…

Machine Learning · Computer Science 2026-03-24 Christopher Eldred , François Gay-Balmaz , Vakhtang Putkaradze

Hydrodynamics with cylindrical symmetry in transverse direction and longitudinal scaling flow is employed to calculate the transverse momentum spectra of various hadrons and clusters (e.g. pi, K, N, Phi, Lambda, d, He) in central heavy-ion…

Nuclear Theory · Physics 2008-11-26 A. Dumitru , D. H. Rischke

We perform a global analysis of deep-inelastic $e+p$ scattering data from HERA and transverse energy distributions in $p+p$ and $p+\mathrm{Pb}$ collisions, alongside charged hadron multiplicities in $\mathrm{Pb}+\mathrm{Pb}$ collisions at…

In spite of their original discrepancy, both dark energy and modified theory of gravity can be parameterized by the effective equation of state (EOS) $\omega$ for the expansion history of the Universe. A useful model independent approach to…

Cosmology and Nongalactic Astrophysics · Physics 2011-03-18 Seokcheon Lee

Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickly. This paper presents a new approach to mitigate this…

Neural and Evolutionary Computing · Computer Science 2020-02-10 Jakub M. Tomczak , Ewelina Weglarz-Tomczak , Agoston E. Eiben

For the past ten years $R_{AA}(p_T)$, the nuclear modification factor that encodes the suppression of high $p_T$ particles due to energy loss within the medium was fairly well described by many theoretical models. However, the same models…

Nuclear Theory · Physics 2016-09-21 Jacquelyn Noronha-Hostler

We perform a global Bayesian analysis of a modern event-by-event heavy-ion collision model and LHC data at $\sqrt s$ = 2.76 and 5.02 TeV. After calibration, the model simultaneously describes multiplicity, transverse momentum, and flow data…

Nuclear Theory · Physics 2018-03-14 Jonah E. Bernhard , J. Scott Moreland , Steffen A. Bass

Influence of statistically stationary, homogeneous, and isotropic turbulence on the mean area of a passive self-propagating front and, hence, on the rate of fluid consumption by the front is analysed in the case of asymptotically high…

Fluid Dynamics · Physics 2018-06-27 Vladimir A. Sabelnikov , Andrei N. Lipatnikov

We study how the inclusion of energy dependence as dictated by quantum chromodynamic (QCD) small-$x$ evolution equations affects key observables in ultra-relativistic heavy-ion collisions. Specifically, we incorporate JIMWLK evolution into…

Nuclear Theory · Physics 2026-03-20 Heikki Mäntysaari , Björn Schenke , Chun Shen , Wenbin Zhao

The data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2021-02-10 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

One important challenge in our field is to understand the initial condition of the QGP and constrain it using sensitive experimental observables. Recent studies show that the Pearson Correlation Coefficient between ${\bm V}_n$ and…

Nuclear Experiment · Physics 2022-10-04 Somadutta Bhatta

The ability to generate physically plausible ensembles of variable sources is critical to the optimization of time-domain survey cadences and the training of classification models on datasets with few to no labels. Traditional data…

Instrumentation and Methods for Astrophysics · Physics 2020-05-19 Jorge Martínez-Palomera , Joshua S. Bloom , Ellianna S. Abrahams

Deep generative models have emerged as a powerful tool for learning useful molecular representations and designing novel molecules with desired properties, with applications in drug discovery and material design. However, most existing deep…

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