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Experimental particle physics : understanding the measurements and searches at the Large Hadron Collider /

This book is written for advanced undergraduate or beginning postgraduate student starting data analysis in experimental particle physics, more specifically at the Large Hadron Collider (LHC) at CERN. Only assuming basic knowledge of quantum mechanics and special relativity, it recaps the current st...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kar, Deepak (Autor), Suri, Jasjit S. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2019]
Colección:IOP (Series). Release 6.
IOP expanding physics.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. Groundwork
  • 1.1. Natural units
  • 1.2. Particle content
  • 1.3. Relativistic kinematics
  • 2. Collisions
  • 2.1. Effecting collisions
  • 2.2. Measure of collisions
  • 2.3. Coordinates
  • 2.4. Types of collisions
  • 3. Analysis objects
  • 3.1. Detector objects
  • 3.2. Jets and making them
  • 3.3. Trigger
  • 3.4. Preparing the data
  • 4. Theoretical view of collisions and simulating them
  • 4.1. Theoretical overview from an experimentalist's perspective
  • 4.2. Simulation programmes
  • 5. Analysis
  • 5.1. Measurements and searches
  • 5.2. Observables/techniques
  • 5.3. Analyses steps
  • 5.4. Detour : basic statistics
  • 5.5. ROOT terms
  • 6. Uncertainties
  • 6.1. Types of uncertainties
  • 6.2. Sources of systematic uncertainties
  • 6.3. Estimation of systematic uncertainties
  • 6.4. Statistical methods used in uncertainty estimation
  • 7. Presenting and interpreting the results
  • 7.1. Constructing the plots
  • 7.2. Interpreting the plots
  • 8. Advanced topic : jet substructure
  • 8.1. Large-radius jets
  • 8.2. Grooming
  • 8.3. Observables/taggers
  • 8.4. Experimental results using jet substructure
  • 8.5. Miscellaneous theoretical and experimental aspects
  • 9. Advanced topic : machine learning
  • 9.1. Precursor : multivariate analyses
  • 9.2. Machine learning in a nutshell
  • 9.3. Applications in data analysis.