cres

This crate implements the cell resampling algorithm for the elimination of negative weights in Monte Carlo collider event samples. The algorithm is described in

Unbiased Elimination of Negative Weights in Monte Carlo Samples
J. Andersen, A. Maier
arXiv:2109.07851

Efficient negative-weight elimination in large high-multiplicity Monte Carlo event samples
Jeppe R. Andersen, Andreas Maier, Daniel Maître
arXiv:2303.15246

Installation

If Rust and Cargo are installed on your system, run

cargo install cres

Precompiled executables are available on hepforge.

To install the development version, run

cargo install --git https://github.com/a-maier/cres

Check the Features section for more options.

To generate shell command completion, run

cres-generate-shell-completion SHELL

For bash and fish, command completion should work upon the next login. For other shells, the completion code is written to standard output. Consult your shell's documentation if you are unsure what to do with it. To list the supported shells, run

cres-generate-shell-completion --help

Usage

The basic usage is

cres -a JETALGO -R JETR --jetpt JETPT --max-cell-size R -o OUTDIR EVENTFILES...

This takes a a number of input events files in HepMC2 or Les Houches Event format with mixed-weight events and for each file produces an output file of the same name inside OUTDIR with a smaller contribution from negative weights. The input file can be compressed with bzip2, gzip, zstd, or lz4. The input format is detected automatically.

We recommend to set the jet algorithm JETALGO, jet radius JETR, and minimum jet transverse momentum JETPT to the same values that were used to generate the input events. The supported jet algorithms are anti-kt, kt, and Cambridge-Aachen. When including QED corrections, for instance through a shower, one should also set --leptonalgorithm, --leptonradius, and --leptonpt.

Setting a maximum cell radius R is optional, but highly recommended. Lower values lead to much faster resampling and smaller smearing effects. Larger values eliminate a larger fraction of negative weights. It is recommended to start with a value between 1 and 10 and adjust as needed.

Options

To see a full list of options with short descriptions run

cres --help

The most important options are

• --max-cell-size can be used to limit the size of the generated cells. This ensures that weights are only transferred between events which are sufficiently similar. The downside is that not all negative event weights will be removed.

  Cell resampling is much faster with a small cell size limit. It is therefore recommended to start with a small value, for example 10, and gradually increase the value if too many negative weights are left.

• --leptonalgorithm, --leptonradius, --leptonpt enable clustering for leptons and photons. These options should be set whenever QED corrections are included, for example through showering.

• --ptweight specifies how much transverse momenta affect distances between particles with momenta p and q according to the formula

  d(p, q) = \sqrt{ ptweight^2 (p_\perp - q_\perp)^2 + \sum (p_i - q_i)^2 }
  

• With --minweight events are also unweighted in addition to the resampling. Events with weight w < minweight are discarded with probability 1-|w|/minweight and reweighted to sign(w) * minweight otherwise. Finally, all event weights are rescaled to exactly preserve the original sum of weights. The seed for unweighting can be chosen with the --seed option.

There are too many options

To avoid cluttering the command line, options can be saved in an argfile. Each line should contain exactly one option, and option name and value have to be separated by '='. For example:

--jetalgorithm=anti-kt
--jetradius=0.4
--jetpt=30

The argfile can be used like this:

cres @argfile -o OUT.HEPMC2 IN.HEPMC2

Scaling to huge samples

Ideally, cres should be run on as many events as possible. Naive parallelisation over several nodes is discouraged, as the cell resampling quality will not benefit from higher event statistics.

For very large samples consisting of many smaller subsamples the following work flow is recommended:

1. Run

    cres-partition @partitionargs -o partition --regions N SUBSAMPLE.HEPMC2
   

   on a a single subsample, e.g. 10^6 events. N is the number of nodes on which cres should be later run in parallel. cres-partition should be fast and memory-efficient enough to be run on a single node.

2. Using the partition file created in step 1., run

    cres-classify @classifyargs -p partition SUBSAMPLE.HEPMC2
   

   on each subsample. Each subsample can be treated in parallel. This will split SUBSAMPLE.HEPMC2 into N parts SUBSAMPLE.X.HEPMC2.

3. For each part X, run cres on all subsamples

    cres @argfile SUBSAMPLE0.X.HEPMC2 SUBSAMPLE1.X.HEPMC2 ...
   

   Each instance can be run on a separate node.

Environment variables

The CRES_LOG environment variable allows fine-grained control over the command line output. For example, to see the debugging output of the jet clustering, set

CRES_LOG=jetty=debug,cres=info

See the env_logger crate for a comprehensive documentation.

By default, cres uses as many cores as possible. For small event samples, limiting the number of threads can be faster. You can set the number of threads with the --threads command line option or with the RAYON_NUM_THREADS environment variable.

Features

To install cres with additional features, add --features name1,name2 to your installation command. Default features don't have to be added manually. To disable them, add the --no-default-features flag.

Default features

• multiweight: Enables the --weights option for treating multiple weights in one run. If you only want to consider a single weight you can disable this feature to save some memory and computing time.

• lhef: Support for reading and writing files in the Les Houches Event format.

Non-default features

• ntuple: Support for reading and writing ROOT ntuple files. This requires a recent version of libclang and a ROOT installation with root-config in the executable path.

• stripper-xml: Experimental support for the XML format used by STRIPPER.

• capi: Enables the C API for using cres as a C library. For examples, see the examples subdirectory. The API is limited and only available on unixoid platforms. It will be extended on request.

Use as a library

For full flexibility like custom distance functions cres can be used as a library. For examples, see the examples subdirectory. The API is documented on docs.rs.