English
Related papers

Related papers: Projections of Discovery Potentials from Expected …

200 papers

Many experiments that aim at the direct detection of Dark Matter are able to distinguish a dominant background from the expected feeble signals, based on some measured discrimination parameter. We develop a statistical model for such…

The main technique that has been used to estimate the rate of gravitational wave (gw) bursts is to search for coincidence among times of arrival of candidate events in different detectors. Coincidences are modeled as a (possibly…

Astrophysics · Physics 2014-10-13 Lucio Baggio , Giovanni A. Prodi

The measurements with the background estimation from an off-zone are widely used in astrophysics, accelerator physics and other areas. Usually, the expected number of the background events in the off-zone and in the on-zone is known with a…

Applications · Statistics 2013-05-02 Vladimir Kulikovskiy

A comprehensive uncertainty estimation is vital for the precision program of the LHC. While experimental uncertainties are often described by stochastic processes and well-defined nuisance parameters, theoretical uncertainties lack such a…

High Energy Physics - Phenomenology · Physics 2023-05-08 Aishik Ghosh , Benjamin Nachman , Tilman Plehn , Lily Shire , Tim M. P. Tait , Daniel Whiteson

Detecting and measuring confounding effects from data is a key challenge in causal inference. Existing methods frequently assume causal sufficiency, disregarding the presence of unobserved confounding variables. Causal sufficiency is both…

Artificial Intelligence · Computer Science 2024-09-27 Abbavaram Gowtham Reddy , Vineeth N Balasubramanian

We propose a new scientific application of unsupervised learning techniques to boost our ability to search for new phenomena in data, by detecting discrepancies between two datasets. These could be, for example, a simulated standard-model…

High Energy Physics - Phenomenology · Physics 2019-04-11 Andrea De Simone , Thomas Jacques

Performance of nuclear threat detection systems based on gamma-ray spectrometry often strongly depends on the ability to identify the part of measured signal that can be attributed to background radiation. We have successfully applied a…

Machine Learning · Computer Science 2016-05-30 P. Tandon , P. Huggins , A. Dubrawski , S. Labov , K. Nelson

The paper addresses general aspects of experimental data analysis, dealing with the separation of ``signal vs. background''. It consists of two parts. Part I is a tutorial on statistical event classification, Bayesian inference, and test…

Data Analysis, Statistics and Probability · Physics 2023-06-30 Rudolf Frühwirth , Winfried Mitaroff

In the first part of this thesis, we discuss the algebraic approach to classical and quantum physics and develop information theoretic concepts within this setup. In the second part, we discuss the uncertainty principle in quantum…

Quantum Physics · Physics 2013-10-18 Mario Berta

In this paper, we present a successful implementation of a subtraction-noise projection method into a simple, simulated data analysis pipeline of a gravitational-wave search. We investigate the problem to reveal a weak stochastic background…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Jan Harms , Christoph Mahrdt , Markus Otto , Malte Priess

We consider the standard Neyman-Pearson hypothesis test of a signal-plus-background hypothesis and background-only hypothesis in the presence of uncertainty on the background-only prediction. Surprisingly, this problem has not been…

Data Analysis, Statistics and Probability · Physics 2014-11-18 Kyle S. Cranmer

Expected coverage and expected length of 90% upper and lower limit and 68.27% central intervals are plotted as functions of the true signal for various values of expected background. Results for several objective priors are shown, and…

High Energy Physics - Experiment · Physics 2007-05-23 Ilya Narsky

Germanium detectors have very good capabilities for the investigation of rare phenomena like the neutrinoless double beta decay. Rejection of the background entangling the expected signal is one primary goal in this kind of experiments.…

Nuclear Experiment · Physics 2008-11-26 H. Gómez , S. Cebrián , J. Morales , J. A. Villar

We show that density models describing multiple observables with (i) hard boundaries and (ii) dependence on external parameters may be created using an auto-regressive Gaussian mixture model. The model is designed to capture how observable…

Data Analysis, Statistics and Probability · Physics 2022-02-01 Stephen B. Menary , Darren D. Price

A suggestion is made for improving the Feldman Cousins method of estimating signal counts in the presence of background. The method concentrates on finding essential information about the signal and ignoring extraneous information about…

Data Analysis, Statistics and Probability · Physics 2009-10-31 Byron P. Roe , Michael B. Woodroofe

Background modelling is one of the main challenges in particle physics data analysis. Commonly employed strategies include the use of simulated events of the background processes, and the fitting of parametric background models to the…

High Energy Physics - Experiment · Physics 2022-10-19 A. Chisholm , T. Neep , K. Nikolopoulos , R. Owen , E. Reynolds , J. Silva

We study the statistical significances for exclusion and discovery of proton decay at current and future neutrino detectors. Various counterintuitive flaws associated with frequentist and modified frequentist statistical measures of…

High Energy Physics - Phenomenology · Physics 2023-03-29 Prudhvi N. Bhattiprolu , Stephen P. Martin , James D. Wells

Analysis of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nHz frequency band. The most plausible source of such a background is the superposition of signals from millions of supermassive…

General Relativity and Quantum Cosmology · Physics 2023-12-05 Bence Bécsy , Neil J. Cornish , Patrick M. Meyers , Luke Zoltan Kelley , Gabriella Agazie , Akash Anumarlapudi , Anne M. Archibald , Zaven Arzoumanian , Paul T. Baker , Laura Blecha , Adam Brazier , Paul R. Brook , Sarah Burke-Spolaor , J. Andrew Casey-Clyde , Maria Charisi , Shami Chatterjee , Katerina Chatziioannou , Tyler Cohen , James M. Cordes , Fronefield Crawford , H. Thankful Cromartie , Kathryn Crowter , Megan E. DeCesar , Paul B. Demorest , Timothy Dolch , Elizabeth C. Ferrara , William Fiore , Emmanuel Fonseca , Gabriel E. Freedman , Nate Garver-Daniels , Peter A. Gentile , Joseph Glaser , Deborah C. Good , Kayhan Gültekin , Jeffrey S. Hazboun , Sophie Hourihane , Ross J. Jennings , Aaron D. Johnson , Megan L. Jones , Andrew R. Kaiser , David L. Kaplan , Matthew Kerr , Joey S. Key , Nima Laal , Michael T. Lam , William G. Lamb , T. Joseph W. Lazio , Natalia Lewandowska , Tyson B. Littenberg , Tingting Liu , Duncan R. Lorimer , Jing Luo , Ryan S. Lynch , Chung-Pei Ma , Dustin R. Madison , Alexander McEwen , James W. McKee , Maura A. McLaughlin , Natasha McMann , Bradley W. Meyers , Chiara M. F. Mingarelli , Andrea Mitridate , Cherry Ng , David J. Nice , Stella Koch Ocker , Ken D. Olum , Timothy T. Pennucci , Benetge B. P. Perera , Nihan S. Pol , Henri A. Radovan , Scott M. Ransom , Paul S. Ray , Joseph D. Romano , Shashwat C. Sardesai , Ann Schmiedekamp , Carl Schmiedekamp , Kai Schmitz , Brent J. Shapiro-Albert , Xavier Siemens , Joseph Simon , Magdalena S. Siwek , Sophia V. Sosa Fiscella , Ingrid H. Stairs , Daniel R. Stinebring , Kevin Stovall , Abhimanyu Susobhanan , Joseph K. Swiggum , Stephen R. Taylor , Jacob E. Turner , Caner Unal , Michele Vallisneri , Rutger van Haasteren , Sarah J. Vigeland , Haley M. Wahl , Caitlin A. Witt , Olivia Young

Filtered Poisson processes are often used as reference models for intermittent fluc- tuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical…

Data Analysis, Statistics and Probability · Physics 2018-05-04 Audun Theodorsen , Odd Erik Garcia , Martin Rypdal

Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to overcome many of the issues that have hampered standard data mining approaches to pattern discovery. Most importantly, application of…

Methodology · Statistics 2019-01-07 Wilhelmiina Hämäläinen , Geoffrey I. Webb