by Alessia Saggio

I’m very pleased to announce that… the 1st release of MoMEMta is out! From now on, you’ll be able to use the Matrix Element Method by yourself in a really easy way!

Before letting you have fun with MoMEMta, I would like to spend just a few words on the reason why we need it and why its development is (and will be!) so important in the Particle Physics world.

The purpose of this framework is to provide a fast computation of weights under a large number of theoretical hypotheses (if you don’t remember what weights in the Matrix Element Method are, please check out my previous post).

MoMEMta is the acronym for “Modular Matrix Element Method Implementation” and in fact it is a C++-based framework. It’s built around the concept of “modules”, that are nothing more than C++ classes linked together in order to provide the computation of the integrand, with each module’s output feeding the input of another one.

MoMEMta takes as input a configuration file, written in the Lua scripting language, where one can set the parameters (e.g. energy, masses, and widths of the particles involved), the integration variables and much more. It also establishes the various links between the modules.

To perform the integration, MoMEMta uses the VEGAS algorithm as implemented in the CUBA library.

One of the main features of this framework (and also one of its purposes, actually) is that it’s been designed to be user-friendly and easily configurable by the user, allowing everybody to use it!

MoMEMta is set up on different subsets of variables called blocks, each one defining a (part of a) final state. If you’re interested and you decide to have a look at the website (see below), you’ll find out that for now we have two blocks implemented and validated (blockD and blockF) and another one implemented but not yet validated (blockB). But that’s enough to start!

Maybe you’re asking yourselves: what does an output from MoMEMta look like? To give you an idea, in MadGraph I generated a pp→W+W and a pp→H→W+W sample, both in the fully leptonic channel. I passed them through Delphes in order to include detector effects, and I computed the distribution of the weights for the two samples, both under the pp→W+W fully leptonic hypothesis (implemented in MoMEMta through the blockF). I obtained two different distributions or, in other words, a method to discriminate the signal from the background! You can see the result in Fig. 1.

Of course I’m not alone in this work. Here are the names of the MoMEMta team: Sébastian Brochet, Alessia Saggio, Miguel Vidal, and Sébastian Wertz.

I think it’s time to stop bothering you. Now it’s your turn! Discover MoMEMta through the MoMEMta website or the MoMEMta github!

If you have any question do not hesitate to comment, to contact me or to contact one of our team via the MoMEMta website.

The MoMEMta team is always there for you!