MDC2018Ensembles

Introduction

Fake data ensembles were assembled to mimic what a real dataset from the experiment would look like in order to allow tests of analyses. This means that background and signals are mixed together in a single file, and all events are unweighted. For more information on the construction of the ensembles, please refer to docdb 27037, 26271, 24376, 22693.

The scripts used to produce the simulations for the ensembles are all in the JobConfig/ensembles directory in Offline. The simulation was run using Offline v7_4_0, but the ensemble scripts used come from a more up to date version. Additionally, the scripts used to build the actual mixed ensemble files are in the same directory. JobConfig/ensembles/genEnsemble.py is used to randomly select Rue,Rup, etc. for a given ensemble, then JobConfig/ensembles/run_si.py creates and runs the fcl to mix together the various signals and backgrounds into a single art file. JobConfig/ensembles/normalizations.py contains the code that is used to calculate the normalization of the signal and backgrounds.

Analyses currently using the ensembles can be listed at https://docs.google.com/spreadsheets/d/1So88Z1RYXwGCEGFcapGpdnmrWGR8TfpurxMdsADZ7do/edit

Ensemble Datasets

Currently, a single ensemble representing an approximately 1 week dataset is available. Art files are available in 'reco' format, with "ensemble-Data" files containing only the output of the reconstruction algorithms, and with "ensemble-MC" files containing reconstruction algorithm output as well as corresponding Monte Carlo truth information.

Files are located on persistent disk at

 /pnfs/mu2e/persistent/users/mu2epro/workflow/MDC2018_ensembles

with datasets names of the form mcs.mu2e.ensemble-Data.MDC2018i.art and mcs.mu2e.ensemble-MC.MDC2018i.art.

The currently available dataset is the "open ensemble", meaning that the monte carlo truth information is available from the start. Additionally, the randomized parameters used to generate the dataset (effective mean PBI, RMC kMax, Rue, Rup) can be found at

 /pnfs/mu2e/persistent/users/mu2epro/workflow/MDC2018_ensembles/openEnsemble_#/

Although only one open ensemble was simulated, the backgrounds were reused to create 7 separate sets of files with different values of Rue and Rup. Note that due to the random sampling the exact number of background events will vary slightly from file to file but the large majority of background events will be identical between them. The different values are labelled by run with

Run #	Rue	Rup
1	random	random
2	0	0
3	1e-14	1e-14
4	2e-14	2e-14
5	4e-14	4e-14
6	8e-14	8e-14
7	1.6e-13	1.6e-13

Encrypting and decrypting closed ensemble data

RSA public/private key pair was created on the Fermilab machines in the mu2epro account using

 gpg --gen-key

The public key id is 6827CEA8 and the private key id is C8268954. The recipient was set to "Richie Bonventre <rbonventre@lbl.gov>", and the private key was password protected with the default mu2e docdb password.

The private key was exported using

 gpg --export-secret-keys C8268954 > mu2eSecretKey.asc

Afterwards, the secret key was deleted from the keyring using

 gpg --delete-secret-key C8268954

The public key remains and so any file can be encrypted from the mu2epro account using

 gpg --output myfile.enc --encrypt --recipient 6827CEA8 myfile

The file mu2eSecretKey.asc has been saved on several usb drives. To decrypt the files, copy mu2ePrivateKey.asc to a fermilab machine, then:

 gpg --import --no-default-keyring --secret-keyring temporary mu2eSecretKey.asc
 gpg --no-default-keyring --secret-keyring temporary --trust-model always --output myfile --decrypt myfile.enc
 rm ~/.gnupg/temporary