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Sleuth at CDF

Sleuth at CDF PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 4

Book Description
These proceedings describe Sleuth, a quasi-model-independent search strategy targeting new electroweak scale physics, and its application to 927 pb−1 of CDF II data. Exclusive final states are analyzed for an excess of data beyond the Standard Model prediction at large summed scalar transverse momentum. This analysis of high-pT data represents one of the most encompassing searches so far conducted for new physics at the energy frontier.

Sleuth at CDF

Sleuth at CDF PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 4

Book Description
These proceedings describe Sleuth, a quasi-model-independent search strategy targeting new electroweak scale physics, and its application to 927 pb−1 of CDF II data. Exclusive final states are analyzed for an excess of data beyond the Standard Model prediction at large summed scalar transverse momentum. This analysis of high-pT data represents one of the most encompassing searches so far conducted for new physics at the energy frontier.

General Model Independent Searches for Physics Beyond the Standard Model

General Model Independent Searches for Physics Beyond the Standard Model PDF Author: Saranya Samik Ghosh
Publisher: Springer Nature
ISBN: 3030537838
Category : Science
Languages : en
Pages : 77

Book Description
This primer describes the general model independent searches for new physics phenomena beyond the Standard Model of particle physics. First, the motivation for performing general model independent experimental searches for new physics is presented by giving an overview of the current theoretical understanding of particle physics in terms of the Standard Model of particle physics and its shortcomings. Then, the concept and features of general model independent search for new physics at collider based experiments is explained. This is followed by an overview of such searches performed in past high energy physics experiments and the current status of such searches, particularly in the context of the experiments at the LHC. Finally, the future prospects of such general model independent searches, with possible improvements using new tools such as machine learning techniques, is discussed.

Deep Inelastic Scattering

Deep Inelastic Scattering PDF Author: Masahiro Kuze
Publisher: World Scientific
ISBN: 9812568719
Category : Science
Languages : en
Pages : 996

Book Description
These proceedings present the most up-to-date status of deep inelastic scattering (DIS) physics. Topics such as structure function measurements and phenomenology, quantum chromodynamics (QCD) studies in DIS and photoproduction, spin physics and diffractive interactions are reviewed in detail, with emphasis on those studies that push the test of QCD and the Standard Model to the limits of their present range of validity, towards both the very high and the very low four-momentum transfers in lepton-proton scattering.

The Statistical Sleuth

The Statistical Sleuth PDF Author: Fred L. Ramsey
Publisher: Duxbury Resource Center
ISBN:
Category : Mathematics
Languages : en
Pages : 774

Book Description
Intended for the one- or two-term algebra-based course in statistical methods, this innovative book takes full advantage of the computer both as a computational and as an analytical tool. The focus is on a serious analysis of real case studies; on strategies and tools of modern statistical data analysis, on the interplay of statistics and scientific learning, and on the communication of results.

Something about a Soldier

Something about a Soldier PDF Author: Charles Ray Willeford
Publisher: Random House (NY)
ISBN:
Category : Biography & Autobiography
Languages : en
Pages : 280

Book Description


This Book-collecting Game

This Book-collecting Game PDF Author: Alfred Edward Newton
Publisher: Boston : Little, Brown
ISBN:
Category : Book collecting
Languages : en
Pages : 436

Book Description


Cities of the Plain

Cities of the Plain PDF Author: Cormac McCarthy
Publisher: Knopf Publishing Group
ISBN: 0679423907
Category : New Mexico
Languages : en
Pages : 305

Book Description
The setting is New Mexico in 1952, where John Grady Cole and Billy Parham are working as ranch hands. To the North lie the proving grounds of Alamogordo; to the South, the twin cities of El Paso and Juarez, Mexico. Their life is made up of trail drives and horse auctions and stories told by campfire light. It is a life that is about to change forever, and John Grady and Billy both know it. The catalyst for that change appears in the form of a beautiful, ill-starred Mexican prostitute. When John Grady falls in love, Billy agrees--against his better judgment--to help him rescue the girl from her suavely brutal pimp. The ensuing events resonate with the violence and inevitability of classic tragedy

Old Sleuth, the Detective, Or, The Bay Ridge Mystery

Old Sleuth, the Detective, Or, The Bay Ridge Mystery PDF Author: Old Sleuth
Publisher:
ISBN:
Category :
Languages : en
Pages : 32

Book Description


Using R for Introductory Statistics

Using R for Introductory Statistics PDF Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522

Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Model-Based Machine Learning

Model-Based Machine Learning PDF Author: John Winn
Publisher: CRC Press
ISBN: 1498756824
Category : Business & Economics
Languages : en
Pages : 469

Book Description
Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.