Data Analysis in Physics involves extracting meaningful information from experimental or simulation data. Modern physics experiments generate large and complex datasets requiring advanced analysis techniques. Data analysis includes statistical inference, pattern recognition, and model fitting. Physicists use data analysis to test hypotheses, estimate parameters, and validate theoretical models. Proper data analysis ensures reliability and reproducibility of results. This field incorporates uncertainty quantification and error estimation. In particle physics and astrophysics, data analysis is essential for detecting rare events. Advances in computing and algorithms have transformed data analysis methods. Data analysis in physics bridges experimental observation and theoretical understanding.
Title : Photoaligned azodye nanolayers: New trends for liquid crystal devices
Vladimir Chigrinov, Hong Kong University of Science and Technology, Hong Kong
Title : Using physics to eliminate implant infection in over 25000 patients to date
Thomas J Webster, Brown University, United States
Title : How the Rad Lab helped avert nuclear war
Thomas F Ramos, Lawrence Livermore National Laboratory, United States
Title : Anisotropic stiffness matrix of bed joint mesh-reinforced masonry: A numerical homogenization approach
Omar Mohammed Daud Shakarneh, Novosibirsk State University of Architecture and Civil Engineering, Russian Federation
Title : Global photochemical model CHARM-DE of the Earth’s atmosphere for altitudes 0-130 km
Alexei Krivolutsky, Central Aerological Observatory (CAO), Russian Federation
Title : Enhanced ferromagnetism in carbon dots polyaniline nanocomposite
Paulo Cesar De Morais, University of Brasilia, Brazil