McMule

Yannick Ulrich [1], Pulak Banerjee [2], Antonio Coutinho [3], Tim Engel [4], Andrea Gurgone [5] [6], Franziska Hagelstein [7] [8], Sophie Kollatzsch [8] [9], Luca Naterop [8] [9], Marco Rocco [8], Nicolas Schalch [1], Vladyslava Sharkovska [8] [9], Adrian Signer [8] [9]

[1] (1,2)

Albert Einstein Center for Fundamental Physics, Universität Bern, CH-3012 Bern, Switzerland

[2]

Department of Physics, Indian Institute of Technology Guwahati, Guwahati-781039, Assam, India

[3]

IFIC, Universitat de València - CSIC, Parc Científic, Catedrático José Beltrán, 2, E-46980 Paterna, Spain

[4]

Albert-Ludwigs-Universität Freiburg, Physikalisches Institut, Hermann-Herder-Straße 3, D-79104 Freiburg, Germany

[5]

Dipartimento di Fisica, Università di Pavia, I-27100 Pavia, Italy

[6]

INFN, Sezione di Pavia, I-27100 Pavia, Italy

[7]

Institut für Kernphysik & PRISMA⁺ Cluster of Excellence, Johannes Gutenberg Universität Mainz, D-55099 Mainz, Germany

[8] (1,2,3,4,5,6)

Paul Scherrer Institut, CH-5232 Villigen PSI, Switzerland

[9] (1,2,3,4)

Physik-Institut, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland

Contents:

• Getting started
  • Obtaining the code
  • Simple runs at LO
  • Running at NLO and beyond
  • More complicated runs
• Structure of McMule
  • Modular structure of the code
  • What happens when running
• General aspects of using McMule
  • Statistics
  • Analysis
  • Manual compilation
• Technical aspects of McMule
  • Phase-space generation
  • Implementation of FKS schemes
  • Calling procedures and function pointers
  • Optional parameters for integrands
  • Random number generation
  • Differential distributions and intermediary state files
  • Basics of containerisation
• Implementing new processes in McMule
  • Creating a new process group
  • Study of \(\xi_{c}\) dependence
  • Example calculations in Mathematica
  • Coding style and best practice
• The FKS\(^2\) scheme
  • FKS\(^\ell\): extension to N\(^\ell\)LO
• Glossary
  • Acronyms
  • Technical terms
• Bibliography
• Particle ID
• Available processes and which_piece
• Fortran reference guide
  • User-modifiable parameters
  • Technical parameters
  • User-facing functions
  • The user file
  • Technical routines
• pymule user guide
  • Working with files
  • Working with errors
  • Plotting
• pymule reference guide
  • Working with errors
  • Working with abstract records
  • Working with vegas records
  • Working with records of data
  • Working with \(\xi_c\) data
  • Working with plots
  • Useful other functions

(Monte carlo for Muons and other leptons) is a generic framework for higher-order QED calculations of scattering and decay processes involving leptons. It is written in Fortran 95 with two types of users in mind. First, several processes are implemented, some at NLO, some at NNLO. For these processes, the user can define an arbitrary (infrared safe), fully differential observable and compute cross sections and distributions. McMule’s processes, present and, future, are listed in Table 7 together with the relevant experiments for which the cuts are implemented. Second, the program is set up s.t. additional processes can be implemented by supplying the relevant matrix elements.

Table 7 Processes implemented in McMule

process	order	experiments	comments
\(\mu\to\nu\bar\nu e\)	NNLO	MEG I&II	polarised, massified & exact
\(\mu\to\nu\bar\nu e\gamma\)	NLO	MEG I	polarised
\(\mu\to\nu\bar\nu eee\)	NLO	Mu3e	polarised
\(\mu\to\nu\bar\nu e\gamma\gamma\)	LO	MEG	polarised
\(\tau\to\nu\bar\nu e\gamma\)	NLO	BaBar	cuts in lab frame
\(\tau\to\nu\bar\nu l\ell\ell\)	NLO	Belle II
	NLO	MUonE
		NNLO	purely electronic corrections
			mixed (massified)
\(\ell p\to\ell p\)	NNLO	P2, MUSE, Prad	only leptonic corrections
\(e^-e^-\to e^-e^-\)	NNLO	Prad	complete
\(e^+e^-\to e^+e^-\)	NNLO		no \(n_f\)
\(e^+e^-\to \gamma\gamma\)	NNLO	PADME
\(e^+e^-\to \mu^+\mu^-\)	NNLO	Belle	massified

The public version of the code can be found at

https://gitlab.com/mule-tools/mcmule

To obtain a copy of the code, git is recommended

$ git clone --recursive https://gitlab.com/mule-tools/mcmule

Alternatively, we provide a Docker container for easy deployment and legacy results (cf. Section Basics of containerisation). In multi-user environments, udocker can be used instead. In either case, a pre-compiled copy of the code can be obtained by calling

$ docker pull yulrich/mcmule  # requires Docker to be installed
$ udocker pull yulrich/mcmule # requires udocker to be installed

We provide instructions on how is used in Section Getting started.

Indices and tables

• Index

• Module Index

• Search Page