Report from the MoEDAL Software Group Janusz Chwastowski, Dominik - - PowerPoint PPT Presentation

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Aug 17, 2022 261 likes •465 views

Report from the MoEDAL Software Group Janusz Chwastowski, Dominik Derendarz, Pawel Malecki, Rafal Staszewski, Maciej Trzebinski (Cracow) Akshay Katre, Philippe Mermod (Geneva) Matthew King, Vasiliki A. Mitsou, Vicente Vento (Valencia) Jim

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SLIDE 1

Report from the MoEDAL Software Group

Janusz Chwastowski, Dominik Derendarz, Pawel Malecki, Rafal Staszewski, Maciej Trzebinski (Cracow) Akshay Katre, Philippe Mermod (Geneva) Matthew King, Vasiliki A. Mitsou, Vicente Vento (Valencia) Jim Pinfold, Richard Soluk (Alberta)

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SLIDE 2

MoEDAL Software Group

  • Coordinator: Philippe Mermod & Jim Pinfold
  • Groups

▫ Alberta ▫ Cracow ▫ Geneva ▫ Valencia

  • Meetings: every two weeks; Thursday 16:00
  • Mailing list: MoEDAL-Software@cern.ch
  • Web page: under construction

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SLIDE 3

Action plan 2014

  • Material description (short term)

▫ component implementation into the LHCb geometry ▫ gathering info from picture database and CERN Drawing Database (CDD)

  • Model-independent simulations (short term)

▫ single-particle generator ▫ Geant4 propagation

  • Model-specific simulations (long term)

▫ Drell-Yan monopole production ▫ other monopole models with different kinematics ▫ Long-lived sparticle (sleptons, R-hadrons) production

 identify optimum model for MoEDAL reach

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SLIDE 4

LHCb software

  • LHCb software is organised into:

 Packages: Sets of classes for a particular purpose (tools, algorithms, etc)  Groups: Sets of packages that perform similar operations

  • r work in a particular processing step (Generation,

Simulation, etc)  Projects: Complete Gaudi software packages consisting of several groups

  • LHCb contact: Gloria Corti
  • Relevant for MoEDAL

▫ Panoramix: Interactive Data Visualisation project ▫ Gauss: The LHCb Simulation Program ▫ GiGa (Geant4 in Gauss): interface package between Gauss and Geant4

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SLIDE 5

Material description

  • MoEDAL placed around the

LHCb interaction point on the backward side of the detector

  • Estimating the amount of

material on the back of LHCb provides the trapping potential of MoEDAL

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SLIDE 6

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Vacuum vessel I

CDD drawing

https://edms.cern.ch/cdd/plsql/c4w.get_in

photo Fluka

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SLIDE 7

Vacuum vessel II

  • Combining previous information in Panoramix Project

from LHCb

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7 existing description after including actual material

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SLIDE 8

Magnetic Monopole Trapper (MMT)

  • Aluminium absorber
  • Induction technique for signature of magnetic

monopole

  • 2012 deployment

▫ array placed 1.8 m away from the interaction point, covers 1.3 % of the total solid angle ▫ search for monopoles performed in SQUID magnetometer in ETH Zurich ▫ Bendtz, Katre, Lacarrère, Mermod, Milstead, Pinfold, Soluk “Search in 8 TeV proton-proton collisions with the MoEDAL monopole-trapping test array”, arXiv:1311.6940 [physics.ins-det]

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SLIDE 9

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MMT geometry in simulation

Rods of aluminium absorber Boxes

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SLIDE 10

MoEDAL simulation

  • GiGa provides a set of base classes for: Physics lists, Field

setups, etc

▫ New physics is implemented in an inheriting class and added to the Gauss algorithm

  • Monopole physics is added to Gauss by adding

G i Ga Ph ysContruc t or M o n op o l e (MonopolePhysics) to

the algorithm’s Physics List

  • Simulation with single monopole production

▫ momentum 1 – 100 GeV ▫ monopole mass set to 100 GeV ▫ magnetic field set off in transportation code ▫ MMT geometry is included – yet not seen → under investigation

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SLIDE 11

Geometry profile

  • MoEDAL is in negative z

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11 y [mm] x [mm] z [mm] r [mm]

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SLIDE 12

Monopole range vs. φ

  • Flat range in φ save for

variations due to known material

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12 1 GeV 10 GeV 100 GeV Range [mm] Range [mm] Range [mm] φ [rad] φ [rad] φ [rad]

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SLIDE 13

Monopole range vs. θ

  • MoEDAL is in θ > π/2
  • Cavern wall at high-θ,

high-range region(“curve”)

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13 10 GeV 100 GeV Range [mm] Range [mm] Range [mm] θ [rad] θ [rad] 1 GeV θ [rad]

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SLIDE 14
  • MoEDAL is in θ > π/2

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14 10 GeV 100 GeV φ [rad] Range [mm] θ [rad] θ [rad] 1 GeV θ [rad] Range [mm] φ [rad] Range [mm] φ [rad]

Monopole range vs. θ and φ

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SLIDE 15

Simulation ntuple contents

  • Currently include

▫ initial vertex position ▫ initial momentum ▫ particle PDG code ▫ particle mass ▫ final vertex position

  • Desired content to be decided

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SLIDE 16

Modifications leading to a smaller effective coupling i) Ginzburg et al. loop effects g  g E/m ii) Milton et al. for real monopoles beta coupling g  g p/E  Both effects reduce the coupling close to threshold

Simulation of monopole production Ι

  • 1st monopole revolution: Dirac Theory

i. monopole coupling  Dirac quantisation condition : e g = N/2  g2 ~ 34 ii. monopole mass  parameter iii. spin unknown iv. Dirac string

 No well-defined field theory exists  Schwinger-Zwanziger not useful for calculations

  • Naive calculations:

Drell-Yan production at LHC included in MADGRAPH e  gβ

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SLIDE 17

Simulation of monopole production ΙΙ

  • 2nd monopole revolution: ‘t Hooft-Polyakov soliton

i. GUT mass scale ii. the monopole has structure

  • We would like to go beyond the naive calculations guided by the solitonic

picture!

  • Assumptions

i. there is a monopole at the TeV scale ii. it is (solitonic) not elementary iii. its mass is unknown iv. its spin is unknown

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SLIDE 18

Simulation of monopole production ΙΙΙ

  • Future plan:

We are resuscitating old ideas by Schiff and Goebel (before soliton) giving the monopole a structure, larger than its classical radius, with the magnetic charge distributed in it. This structure leads in the calculations to a form-factor which allows reasonable calculations like in the pi-N interaction where the coupling is also large.

  • Moreover, it allows the description of Monopolium, a monopole- anti-monopole bound

state, which might lead to other observable effects in MoEDAL

  • We are analysing different density distributions and sizes studying model dependence
  • The approach can also be extended to cosmological scenarios
  • Caveat:

It is important to realise, that once the monopole is formed, the DETECTION in MoEDAL

  • ccurs via a classical process, and therefore well determined, by the corresponding

Maxwell equations. This implies that once a production rate is calculated (or assumed) the detection rate is easy to calculate depending on the geometry and efficiency of MoEDAL.

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SLIDE 19

ICHEP2014

  • Abstract on MoEDAL software results accepted for poster

presentation: “Simulation of the MoEDAL experiment”

  • Presenter: Matt King (Valencia)

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SLIDE 20

Summary

  • Experience acquired with LHCb software

▫ framework to which MoEDAL simulation is implemented

  • MMT material already implemented in MoEDAL

geometry description

▫ priority item in view of the MMT results from 2012 deployment

  • First tests done with single-monopole production and

propagation are positive

  • Different monopole production mechanisms under study

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