Hands On DM@LHC : Glossary

First key point. Brief Answer to questions. (FIXME)

All we know about DM is that it interacts gravitionally … therefore ‘matter’.

DM does not seem to interact with anything else, particularly light … therefore ‘dark’.

DM is not necessarily a particle, but we work under this assumption much of time time.

MadGraph simulates the matrix element physics process.

Pythia simulated the parton shower physics process.

MadGraph+Pythia allows you to produce a HEPMC file which contains information about the ensemble of stable particles that enter the detector.

Missing transverse energy is not a thing - it is missing transverse momentum because it has a magnitude and a direction.

Detector smearing results from the physical limitations of our detectors precision.

Inferential statistics can be used to transform the observations made about an ensemble of events into statements about a physics model through the use of likelihoods.

Likelihoods connect observations with parameters by giving us a sense of ‘how likely a particular dataset was given a set of parameters’.

Rivet is a platform by which we can ‘safely’ analyze particle physics truth record data.

An unfolded spectra is one for which the effects of detector resolution have been removed through a deconvolution.

We can infer things about parameters in a model by using the CLs test statistic.

First key point. Brief Answer to questions. (FIXME)