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A pre-trained unconditional diffusion model, combined with posterior sampling or maximum a posteriori (MAP) estimation techniques, can solve arbitrary inverse problems without task-specific training or fine-tuning. However, existing…

Machine Learning · Computer Science 2026-02-09 Sai Bharath Chandra Gutha , Ricardo Vinuesa , Hossein Azizpour

We propose a further development of a multi-pomeron exchange model of pp and p$\bar p$ collisions at high energy. The model describes consistently multiplicity, transverse momentum of charged particles and their correlation in wide energy…

High Energy Physics - Phenomenology · Physics 2017-10-25 G. Feofilov , V. Kovalenko , A. Puchkov

We present a method to match the multi-parton states generated by the High Energy Jets Monte Carlo with parton showers generated by the Ariadne program using the colour dipole model. The High Energy Jets program already includes a full…

High Energy Physics - Phenomenology · Physics 2015-03-19 Jeppe R. Andersen , Leif Lonnblad , Jennifer M. Smillie

Differential dijet cross sections in diffractive deep-inelastic scattering are measured with the H1 detector at HERA using an integrated luminosity of 51.5 pb-1. The selected events are of the type ep --> eXY, where the system X contains at…

High Energy Physics - Experiment · Physics 2012-08-27 H1 Collaboration

The jet quenching phenomenon in heavy ion collisions provides a strong evidence of the modification of parton shower in the quark-gluon plasma (QGP). Jet substructure observables can probe various aspects of the jet formation mechanism.…

High Energy Physics - Phenomenology · Physics 2016-11-22 Yang-Ting Chien

A novel point cloud diffusion model for relativistic heavy-ion collisions, capable of ultra-fast generation of complete, event-by-event collision output, is introduced. When trained on UrQMD cascade simulations, the model generates…

High Energy Physics - Phenomenology · Physics 2025-12-19 Manjunath Omana Kuttan , Kai Zhou , Jan Steinheimer , Horst Stoecker

In this work we analyze how quadrature rules of different precisions and piecewise polynomial test functions of different degrees affect the convergence rate of Variational Physics Informed Neural Networks (VPINN) with respect to mesh…

Numerical Analysis · Mathematics 2022-08-02 Stefano Berrone , Claudio Canuto , Moreno Pintore

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near net shape parts with high material utilization and uniform microstructures. Despite being used frequently to produce small-scale…

Numerical Analysis · Mathematics 2025-08-14 Subrato Sarkar , Jason R Mayeur , KPK Ajjarapu , Fred A List , Soumya Nag , Ryan R Dehoff

A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) that originate from genuine tau leptons in the CMS detector against $\tau_\mathrm{h}$ candidates that originate from quark or…

High Energy Physics - Experiment · Physics 2022-07-18 CMS Collaboration

Algorithms for mutual interference mitigation and object parameter estimation are a key enabler for automotive applications of frequency-modulated continuous wave (FMCW) radar. In this paper, we introduce a signal separation method to…

Signal Processing · Electrical Eng. & Systems 2024-10-03 Mate Toth , Erik Leitinger , Klaus Witrisal

In this paper we present a new method that can accelerate the computation of the PageRank importance vector. Our method, called D-Iteration (DI), is based on the decomposition of the matrix-vector product that can be seen as a fluid…

Data Structures and Algorithms · Computer Science 2015-05-07 Dohy Hong , The Dang Huynh , Fabien Mathieu

Direct photons are important probes in high energy collisions. They play an important role in determining the parton distribution function directly inside a proton as well as the nature of the matter formed in heavy ion collisions. However…

Nuclear Experiment · Physics 2009-03-18 Mriganka Mouli Mondal , Subhasis Chattopadhyay

This paper presents studies of the performance of several jet-substructure techniques, which are used to identify hadronically decaying top quarks with high transverse momentum contained in large-radius jets. The efficiency of identifying…

High Energy Physics - Experiment · Physics 2016-07-05 ATLAS Collaboration

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of $\sqrt{s} =$ 13 TeV at the CERN LHC. The algorithm is trained on a large…

Data Analysis, Statistics and Probability · Physics 2020-11-09 CMS Collaboration

Bayesian inference has become an important tool to solve inverse problems and to quantify uncertainties in their solutions. Variational inference is a method that provides probabilistic, Bayesian solutions efficiently by using optimization.…

Geophysics · Physics 2025-10-15 Xin Zhang , Andrew Curtis

Bayesian inference provides principled uncertainty quantification, but accurate posterior sampling with MCMC can be computationally prohibitive for modern applications. Variational inference (VI) offers a scalable alternative and often…

Methodology · Statistics 2026-05-14 Laura Battaglia , Stefano Cortinovis , Chris Holmes , David T. Frazier , Jack Jewson

Adding flexible polymers to a Newtonian solvent confers complex properties to the resulting solution. The additional complexity substantially increases the computational cost of numerical simulations, which often makes them prohibitively…

Fluid Dynamics · Physics 2026-04-30 Christian Amor , Adrián Corrochano , Marco Edoardo Rosti , Soledad Le Clainche

The D0 Collaboration has studied for the first time the properties of hadron-collider jets reconstructed with a successive-combination algorithm based on relative transverse momenta ($k_{\perp}$) of energy clusters. Using the standard value…

High Energy Physics - Experiment · Physics 2008-11-26 D0 collaboration , V. M. Abazov

In this paper the projection hybrid FV/FE method presented in Busto et al. 2014 is extended to account for species transport equations. Furthermore, turbulent regimes are also considered thanks to the $k-\varepsilon$ model. Regarding the…

Numerical Analysis · Mathematics 2023-01-23 Saray Busto , Jose Luis Ferrin , Eleuterio F. Toro , Maria Elena Vazquez-Cendon

A conventional Bayesian approach to prediction uses the posterior distribution to integrate out parameters in a density for unobserved data conditional on the observed data and parameters. When the true posterior is intractable, it is…

Methodology · Statistics 2026-02-27 Lucas Kock , Scott A. Sisson , G. S. Rodrigues , David J. Nott