This paper presents the performance of the ATLAS muon reconstruction during the LHC run with [Formula: see text] collisions at [Formula: see text]-8 TeV in 2011-2012, focusing mainly on data collected in 2012. Measurements of the reconstruction efficiency and of the momentum scale and resolution, based on large reference samples of [Formula: see text], [Formula: see text] and [Formula: see text] decays, are presented and compared to Monte Carlo simulations. Corrections to the simulation, to be used in physics analysis, are provided. Over most of the covered phase space (muon [Formula: see text] and [Formula: see text] GeV) the efficiency is above [Formula: see text] and is measured with per-mille precision. The momentum resolution ranges from [Formula: see text] at central rapidity and for transverse momentum [Formula: see text] GeV, to [Formula: see text] at large rapidity and [Formula: see text] GeV. The momentum scale is known with an uncertainty of [Formula: see text] to [Formula: see text] depending on rapidity. A method for the recovery of final state radiation from the muons is also presented.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4371046 | PMC |
http://dx.doi.org/10.1140/epjc/s10052-014-3130-x | DOI Listing |
Sci Rep
December 2024
Radiating Systems Group, Department of Applied Physics, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain.
The following paper presents the findings of a study conducted on the distances at which the field generated by a ϕ-symmetric circular Taylor aperture distribution can be classified as far-field, and also the efficiency across various study parameters. The [Formula: see text] transition integers that produce a monotonic distribution, which have been traditionally used and analyzed, are compared with those that yield a peaked distribution, and offer greater efficiency. Additionally, modified circular Taylor [Formula: see text] distributions featuring synthesized patterns with one or two depressed inner sidelobes, which have not been previously explored, are also examined.
View Article and Find Full Text PDFAnn Surg Oncol
December 2024
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
Background: We sought to define whether and how hepatic ischemia/reperfusion (I/R) as manifested by perioperative aspartate aminotransferase (AST) and alanine aminotransaminase (ALT) levels impact long-term outcomes after curative-intent resection of hepatocellular carcinoma (HCC).
Patients And Methods: Intrasplenic injection of HCC cells was used to establish a murine model of HCC recurrence with versus without I/R injury. Patients who underwent curative resection for HCC were identified from a multi-institutional derivative cohort (DC) and separate external validation (VC) cohort.
Sci Rep
December 2024
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
This study explores the problem of train scheduling (or) train timetabling and its impact on the administration of railway management. This is a highly dependable and effective public transportation system. The problem considers both single and multiple tracks along with multiple platforms with varying train capacities (like speed, passengers, and so on).
View Article and Find Full Text PDFSci Rep
December 2024
Department of Mathematics, Faculty of Science, The Hashemite University, P.O.Box 330127, Zarqa, 13133, Jordan.
In this study, we developed a Caputo-Fractional Chlamydia pandemic model to describe the disease's spread. We demonstrated the model's positivity and boundedness, ensuring biological relevance. The existence and uniqueness of the model's solution were established, and we investigated the stability of the α-fractional order model.
View Article and Find Full Text PDFSci Rep
December 2024
ETH Zurich, Zurich, Switzerland.
Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remains opaque. This makes it difficult for humans to validate a prediction made by AI against their own domain knowledge.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!