EOS—AHEP ProgramforFlavorPhysics
EOS -- A HEP Program for Flavor Physics
User Manual
Danny van Dyk Christoph Bobeth Frederik Beaujean
version 0.2.3
January 10, 2019
Contents
Acknowledgments
v
How to read this manual
vii
1. Installation
3
1.1. Installing the dependencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1.2. Linux: Installing the dependencies with APT (Debian, Ubuntu) . . . . . . . . . . 4
1.1.3. Linux: Installing Minuit2 and pmclib from source . . . . . . . . . . . . . . . . . 5
1.1.4. MacOSX: Installing the Dependencies with Homebrew and PyPi . . . . . . . . . 6
1.2. Installing EOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.1. MacOS X short cuts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2. Usage
9
2.1. Browsing the List of Parameters, Observables and Constraints . . . . . . . . . . . . . . 9
2.2. Evaluating Observables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3. Producing Random Parameter Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4. Merging Markov Chains from multiple files . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.5. Finding the Mode of a Probability Density . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.6. Bayesian Uncertainty Propagation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.7. Plotting Random Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3. Library Interface
21
3.1. Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2. Core Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2.1. Class Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.2.2. Class Kinematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.3. Class Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.4. Class Observable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4. Extending EOS
25
4.1. How to add a new parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2. How to add a new observable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3. How to add a new constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3.1. Type Amoroso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.3.2. Type Gaussian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.3.3. Type MultivariateGaussian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.3.4. Type MultivariateGaussian(Covariance) . . . . . . . . . . . . . . . . . . . . 28
5. Effective Field Theories
33
5.1. |B| = |S| = 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.2. |B| = |U | = 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.3. |B| = |C| = 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
iii
Contents
A. List of default parameters
39
iv
Acknowledgments
The creation and continued maintenance of EOS would not have been possible without the assistance and encouragement of Gudrun Hiller. Furthermore, we would like to extend our thanks to the following people whose input and support were most helpful either the development or the maintenance of EOS, either through personal contributions to the code, independent code review, or helpful suggestions: Thomas Blake, Marzia Bordone, Elena Graverini, Daniel Greenwald, Nico Gubernari, Ahmet Kokulu, Christoph Langenbruch, David Leverton, Nazila Mahmoudi, Ciaran McCreesh, Hideki Miyake, Bastian M?ller, Konstantinos Petridis, Stefanie Reichert, Martin Ritter, Eduardo Romero, Denis Rosenthal, Alexander Shires, Rafael Silva Coutinho, Ismo Toijala, Keri Vos, Christian Wacker . Further development and maintenance of EOS and this manual is presently funded by the Deutsche Forschungsgemeinschaft (DFG) within the Emmy-Noether Programme under contract 'DY 130/1-1'.
v
How to read this manual
To improve readability, the following concepts or entities discussed in this manual are highlighted. shell specific Shell commands are monospaced-lowercase-and-grayed . Environment variables are $ALL_CAPS_DOLLAR_PREFIXED .
echo "Example commands are boxed with a gray background." # Comments are prefixed with a hash mark.
OS specific File names are light-blue, and /directories/end/with/a/slash//. Package names try to follow the original typesetting and are green and bold.
File contents are boxed with a light-blue background.
EOS specific Obserservables, options and parameters are orange and adhere to a syntax defined later in this manual. Classes are CamelCaseNoUnderscores. Methods are (almost always) lower_case_with_underscores.
1 print('Source code is boxed with a light orange back ground.') 2 # Source code listings have line numbers.
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