SCIENCE BRINGS NATIONS TOGETHER
PWG1-MPD Meeting, Thusrday, the 3rd of June 2021, 18:00 Moscow time

Europe/Moscow
Description

Vidyo room: Join

The main topic  is to dicsuss and to fix the  near tasks  for the MC production of a common set of data

using  the UrQMD, SMASH and  DCM-QGSM-SMM event-generators

for Bi+Bi collsions  at sqrt(s_NN)=9.2 GeV.

 

In  view of the preparation  of the 1st Physics MPD Paper, we have to prepare the relevant requests  

to produce of about 100 mln events  for each case of reconstructed data:

1) multipicity-based classes  of centrality using the standard approach with the  UrQMD, SMASH and  DCM-QGSM-SMM

2) FHCal classes  of centrality with the DCM-QGSM-SMM  account of fragmentation processes

 

We propose also to discuss the additionalproduction for Au+Au collsions at sqrt(s_NN)=9.2 GeV using  some of the event-generators mentioned. This  will be needed to give a clear estimate on the possible relevant bias  that could  occur to be different

for the different observanles that will be used to compare with STAR.

 

Please, send us also your proposals for your  contributions.

    • 18:00 18:20
      Tasks for the MC production of a common set of data using the UrQMD, SMASH and DCM-QGSM-SMM event-generators 20m

      The main topic is to dicsuss and to fix the near tasks for the MC production of a common set of data

      using the UrQMD, SMASH and DCM-QGSM-SMM event-generators

      for Bi+Bi collsions at sqrt(s_NN)=9.2 GeV.

      In view of the preparation of the 1st Physics MPD Paper, we have to prepare the relevant requests

      to produce of about 100 mln events for each case of reconstructed data:

      1) multipicity-based classes of centrality using the standard approach with the UrQMD, SMASH and DCM-QGSM-SMM

      2) FHCal classes of centrality with the DCM-QGSM-SMM account of fragmentation processes

      We propose also to discuss the additionalproduction for Au+Au collsions at sqrt(s_NN)=9.2 GeV using some of the event-generators mentioned. This will be needed to give a clear estimate on the possible relevant bias that could occur to be different

      for the different observanles that will be used to compare with STAR.

      Speaker: Grigory Feofilov (Saint-Petersburg State University)