INSTRUCTIONS FOR TUTORIAL 2 =========================== ** Assuming you have followed the Pre-tutorial steps ** Requirements ------------ * Modules: SpecBit, DecayBit, DarkBit, GUM * Scanners: diver * Backends: CalcHEP, MicrOmegas * Other: Mathematica (FeynRules) Running GUM ----------- * First the model needs to be known to gum mkdir Models/MDMSM mv Tutorial/MDMSM.fr Models/MDMSM * Run the gum file ./gum -f Tutorial/MDMSM.gum This will take a while Re-build GAMBIT --------------- * GUM will give you the instructions on how to rebuild GAMBIT, in this case cd ../build cmake .. make calchep micromegas_MDMSM * Do not build gambit yet as we also need to build other things for the scan make diver cmake .. make ddcalc make gamlike make darksusy_generic_wimp make -j4 Model ----- * MDMSM_Tute.yaml (get form the gum/Tutorial directory) Parameters: mchi, mY, gchi, cY Likelihoods: lnL_oh2, lnL_FermiLATdwarfs, LUX_2016_LogLikelihood, XENON1T_2018_LogLikelihood Running scan ------------ * Run scan with various MPI process for speed mpirun -np 4 ./gambit -f yaml_files/MDMSM_Tute.yaml And just wait... (this could take about 12 hours) Check results ------------- * Results are written in the "output" directory (e.g. runs/MDMSM/samples) h5ls runs/MDMSM/samples/MDMSM.hdf5 Plotting results ---------------- * To generate plots we use pippi Pippi file: MDMSM.pip ./pippi/pippi gum/Tutorial/MDMSM.pip * Best fit point is printed in the parse directory (e.g. runs/MDMSM/parse) less runs/MDMSM/parse/MDMSM.best_all * Plots are generated in the selected plots directory (e.g runs/MDMSM/plots) okular runs/MDMSM/plots/*