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The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application where such new methods improved the results, substantially.…

Instrumentation and Methods for Astrophysics · Physics 2018-01-31 Antonio D'Isanto , Kai Lars Polsterer

We consider the effect on LHC jet cross sections on partons distribution functions (PDFs), in particular the MSTW2008 set of PDFs. We first compare the published inclusive jet data to the predictions using MSTW2008, finding a very good…

High Energy Physics - Phenomenology · Physics 2014-08-05 B. J. A. Watt , P. Motylinski , R. S. Thorne

Language models for scientific tasks are trained on text from scientific publications, most distributed as PDFs that require parsing. PDF parsing approaches range from inexpensive heuristics (for simple documents) to computationally…

The parton distribution functions (PDFs) which characterize the structure of the proton are currently one of the dominant sources of uncertainty in the predictions for most processes measured at the Large Hadron Collider (LHC). Here we…

We investigate the polarized parton distribution functions (PDFs) and their uncertainties by using the world data on the spin asymmetry A_1. The uncertainties of the polarized PDFs are estimated by the Hessian method. The up and down…

High Energy Physics - Phenomenology · Physics 2008-11-26 M. Hirai , S. Kumano , N. Saito

We study the potential of the LHCb 13 TeV single $W^{\pm}$ and $Z$ boson pseudo-data for constraining the parton distribution functions (PDFs) of the proton. As an example, we demonstrate the sensitivity of the LHCb 13 TeV data, collected…

High Energy Physics - Phenomenology · Physics 2021-01-26 Qilin Deng , Qundong Han , Hang Yin , Sayipjamal Dulat , Tie-Jiun Hou , C. -P. Yuan

Bayesian estimation strategies represent the most fundamental formulation of the state estimation problem available, and apply readily to nonlinear systems with non-Gaussian uncertainties. The present paper introduces a novel method for…

Optimization and Control · Mathematics 2013-01-22 T R Bewley , A S Sharma

A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z's). A wide plethora of methods have been developed, based either on template models fitting or on empirical…

Instrumentation and Methods for Astrophysics · Physics 2016-12-13 Stefano Cavuoti , Valeria Amaro , Massimo Brescia , Civita Vellucci , Crescenzo Tortora , Giuseppe Longo

We propose a stochastic prediction-control framework to promote safety in automated driving by directly controlling the joint state probability density functions (PDFs) subject to the vehicle dynamics via trajectory-level state feedback. To…

Systems and Control · Electrical Eng. & Systems 2020-11-10 Shadi Haddad , Kenneth F. Caluya , Abhishek Halder , Baljeet Singh

We present new parton distribution functions (PDFs) up to next-to-next-to-leading order (NNLO) from the CTEQ-TEA global analysis of quantum chromodynamics. These differ from previous CT PDFs in several respects, including the use of data…

High Energy Physics - Phenomenology · Physics 2016-03-09 Sayipjamal Dulat , Tie Jiun Hou , Jun Gao , Marco Guzzi , Joey Huston , Pavel Nadolsky , Jon Pumplin , Carl Schmidt , Daniel Stump , C. P. Yuan

In this work, we explored data acquisition protocols and improved data reduction protocols using PDFgetX3 to obtain reliable data for atomic pair distribution function (PDF) analysis from a laboratory-based Mo x-ray source. A variable…

PET requires accurate, precise, and efficient scatter correction techniques. Conventional scatter estimation typically relies on tail-fitted single-scatter simulation (SSS) strategy. However, the accuracy of tail-fitted SSS is limited, for…

When machine learning systems meet real world applications, accuracy is only one of several requirements. In this paper, we assay a complementary perspective originating from the increasing availability of pre-trained and regularly…

Signal processing techniques will lean on blind methods in the near future, where no redundant, resource allocating information will be transmitted through the channel. To achieve a proper decision, however, it is essential to know at least…

Quantum Physics · Physics 2007-05-23 Ferenc Balázs , Sándor Imre

We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calculation of particle physics observables through Monte Carlo…

High Energy Physics - Phenomenology · Physics 2021-05-19 Stefano Carrazza , Juan M. Cruz-Martinez , Marco Rossi

A new combined next to leading order QCD analysis of the polarized inclusive and semi-inclusive deep inelastic lepton-hadron scattering (DIS) data is presented. In contrast to previous combined analyses, the $1/Q^2$ terms (kinematic -…

High Energy Physics - Phenomenology · Physics 2015-03-17 Elliot Leader , Aleksander V. Sidorov , Dimiter B. Stamenov

The problem of sequentially detecting an abrupt change in a sequence of independent and identically distributed (IID) random variables is addressed. Whereas previous approaches assume a known probability density function (PDF) at the start…

Statistics Theory · Mathematics 2017-12-11 James Falt , Steven D. Blostein

We explore the sensitivity of W and Z boson production in hadronic collisions to uncertainties in parton distribution functions (PDFs) at large x arising from uncertainties in nuclear corrections when using deuterium data in global QCD…

High Energy Physics - Phenomenology · Physics 2015-05-30 L. T. Brady , A. Accardi , W. Melnitchouk , J. F. Owens

The high computational cost of approaching the performance of Maximum-likelihood (ML) decoding has limited its practical use for decades. Because the complexity grows exponentially with the message length, researchers have spent years…

Signal Processing · Electrical Eng. & Systems 2026-04-21 Marwan Jalaleddine , Jiajie Li , Syed Mohsin Abbas , Warren J. Gross

Computer models are commonly used to represent a wide range of real systems, but they often involve some unknown parameters. Estimating the parameters by collecting physical data becomes essential in many scientific fields, ranging from…

Applications · Statistics 2020-05-27 Chih-Li Sung , Beau David Barber , Berkley J. Walker