Mitigating high energy anomalous signals in the CMS barrel Electromagnetic Calorimeter

Transcription

1 Mitigating high energy anomalous signals in the CMS barrel Electromagnetic Calorimeter Summary report Ali Farzanehfar University of Southampton University of Southampton Spike mitigation May 28, / 33

2 Introduction Introduction University of Southampton Spike mitigation May 28, / 33

3 Introduction Introduction CMS is one of the two general purpose detectors at CERN The Electromagnetic Calorimeter (ECAL) is responsible for electron/photon (eγ) measurements in CMS At the start of LHC run 1 in 2009, anomalous isolated high energy signals (spikes) were observed in the ECAL These signals put at risk the acquisition of proper physics data and may affect accurate reconstruction of CMS events The aim of this project was to understand the nature of spikes and develop spike rejection methods needed for the future LHC running at higher luminosities University of Southampton Spike mitigation May 28, / 33

4 Introduction Example of a spike signal. It originates from just a single channel A cross section of CMS is visible. The spike represents 690 GeV of energy. This was recorded during s = 2.36 TeV runs. University of Southampton Spike mitigation May 28, / 33

5 Introduction Outline The CMS experiment and ECAL Origin and properties of spikes Pulse shape analysis of 2012 data Development of a pulse shape Monte Carlo Results of optimising the Monte Carlo Summary and future studies University of Southampton Spike mitigation May 28, / 33

6 The CMS experiment The CMS experiment University of Southampton Spike mitigation May 28, / 33

7 The CMS experiment An overview of the CMS detector 14,000 Tonnes 3.8 T magnetic field 100 m under ground University of Southampton Spike mitigation May 28, / 33

8 The CMS experiment The electromagnetic calorimeter (ECAL) eγ are detected via a scintillation process Electromagnetic showers result from eγ interactions in the scintillators The scintillators are made of Lead Tungstate crystals Avalanche Photo Diodes (APDs) measure the scintillation light Lead Tungstate crystals with the APDs are displayed[1]. University of Southampton Spike mitigation May 28, / 33

9 The CMS experiment The electromagnetic calorimeter (ECAL) The CMS ECAL layout University of Southampton Spike mitigation May 28, / 33

10 The CMS experiment The event selection system (Trigger) Localised nature of eγ in ECAL are used to trigger The trigger reduces event rate in steps from 40 MHz to 100 KHz to 1 KHz Electrons and photons are selected based on their pattern of energy deposition in ECAL[2] They deposit most (>90%) of their energy in two strips [red] They deposit very little of their energy (<5%) outside ECAL University of Southampton Spike mitigation May 28, / 33

11 The CMS experiment The event selection system (Trigger) Spikes dominate eγ trigger rate if unmitigated Spikes pass eγ trigger requirements: Spikes are high energy Spikes are highly localised (occur in a single crystal channel) Spikes only exist in ECAL The spike rate increases with energy and luminosity[3] If there were no mitigation: More than 60% of the trigger rate would be due to spikes (2012 data)[2] Even with current mitigation efforts there would be more spikes than the trigger could cope with in the future 1 This means a dramatic loss of eγ events (such as H γγ) 1 This is the case for the High Luminosity LHC (HL-LHC) which begins running in University of Southampton Spike mitigation May 28, / 33

12 Origin and properties of spikes Origin and properties of spikes University of Southampton Spike mitigation May 28, / 33

13 Origin and properties of spikes Origin of spikes Spikes originate within the APDs APDs are covered with a protective epoxy 400µm thick Epoxy is a hydrocarbon polymer Neutrons (produced in calorimeters) undergo n p scattering within this epoxy coating Resulting proton heavily ionises APD active layer Left: Normal operation of APD. Right: Spike being produced. University of Southampton Spike mitigation May 28, / 33

14 Origin and properties of spikes Properties of spikes Spikes occur in isolation Spike signals are produced within an individual APD Spikes are not associated with electromagnetic showers (unlike eγ) eγ spread their energy across several channels (Left) unlike spikes (Right) This is currently being used to distinguish between spikes and eγ signals. University of Southampton Spike mitigation May 28, / 33

15 Origin and properties of spikes Properties of spikes Spike pulses rise faster than eγ pulses Spike pulses [red] are not associated with the scintillation process Scintillation decay time of crystals is 10 ns on average[4] The peak time of pulses is currently being used in spike mitigation after the trigger. University of Southampton Spike mitigation May 28, / 33

16 Origin and properties of spikes Properties of spikes The pulse shape has not been directly used in spike mitigation The combination of energy topology and time based selections have allowed ECAL to perform to design requirements thus far They are not 100% efficient In higher luminosity conditions the spike rate will increase The trigger will become less efficient by 2025 We looked into using the pulse shape directly in spike mitigation University of Southampton Spike mitigation May 28, / 33

17 Pulse shape analysis of 2012 CMS data Pulse shape analysis of 2012 CMS data University of Southampton Spike mitigation May 28, / 33

18 Pulse shape analysis of 2012 CMS data A χ 2 test A goodness of fit test for digitised pulses is used in CMS x i are values from a sampled pulse σ i are the statistical errors of sampled values t i are samples from an eγ template shape N=10 is the total number of samples Agreement means χ 2 = 1 χ 2 = 1 N N (x i t i ) 2 σ 2 i=1 i University of Southampton Spike mitigation May 28, / 33

19 Pulse shape analysis of 2012 CMS data The χ 2 CMS behaviour eγ and spike χ 2 CMS distributions mix non-negligibly CMS use χ 2 CMS where: χ 2 CMS = 7(3 + ln( χ 2) ) eγ and spike signals have separate peaks There is some overlap Efficient separation is not possible This inefficiency needs investigation University of Southampton Spike mitigation May 28, / 33

20 Pulse shape analysis of 2012 CMS data CMS χ 2 blind spot The χ 2 CMS distribution has periodic blind spots χ 2 CMS plotted as a function of time CMS pulses are sampled every 25 ns In this dataset collisions took place every 50 ns (grey bands) Some eγ and spike digitised pulses have similar χ 2 CMS for the same reconstructed time Adjusting the time of digitisation may move the blind spot. A simulation is necessary to confirm this as well as investigate other features of digitisation process University of Southampton Spike mitigation May 28, / 33

21 Pulse shape analysis of 2012 CMS data CMS χ 2 blind spot Spike and eγ pulses are identical at the blind spots University of Southampton Spike mitigation May 28, / 33

22 Monte Carlo simulation of CMS pulse shapes Monte Carlo simulation of CMS pulse shapes University of Southampton Spike mitigation May 28, / 33

23 Monte Carlo simulation of CMS pulse shapes Pulse digitisation process 3 main steps exist in the CMS digitisation process APD eγ signals are extended via convolution with the shaping function with shaping time τ e Digitisation start time of the pulse is adjusted Finally the pulse is digitised with a set number of samples CMS will be upgraded in 2023 for HL-LHC. This is our chance to optimise the ECAL electronics for spike mitigation. University of Southampton Spike mitigation May 28, / 33

24 Monte Carlo simulation of CMS pulse shapes Calculation of χ 2 of simulated pulses The Monte Carlo reproduces the blind spot behaviour in CMS data The simulation generates eγ and spike pulses to mimic CMS data Convoluted pulse shapes are digitised Convoluted eγ is used as χ 2 reference Noise is added to each digitised value by sampling a Gaussian with σ = 60 MeV University of Southampton Spike mitigation May 28, / 33

25 Improving χ 2 discrimination using the Monte Carlo Improving χ 2 discrimination using the Monte Carlo University of Southampton Spike mitigation May 28, / 33

26 Improving χ 2 discrimination using the Monte Carlo Tuning the electronic shaping time Shorter shaping time results in better spike rejection Shorter shaping time increases spike-eγ pulse shape differences APD noise depends on shaping time τ e and dark current I d University of Southampton Spike mitigation May 28, / 33

27 Improving χ 2 discrimination using the Monte Carlo Tuning the electronic shaping time This takes the following form: σ τe = A τ e + B(τ e )(I d ) I d is due to APD irradiation ( L) During HL-LHC conditions I d will be large and σ τe τ e eγ acceptance efficiency is 98% for all data points Based on this study CMS should consider reducing the shaping time to τ e = 20 ns during the HL-LHC upgrade. University of Southampton Spike mitigation May 28, / 33

28 Improving χ2 discrimination using the Monte Carlo Adjusting the digitisation start time Adjusting the moment of digitisation removes the blind spot This study has found for any shaping time, blind spots can be removed by adjusting the digitisation moment. For shaping times 43 and 20 ns, the adjustment necessary is -9 ns and -7 ns respectively. This can be implemented before 2023 and should be considered. University of Southampton Spike mitigation May 28, / 33

29 Improving χ 2 discrimination using the Monte Carlo Increasing the number of digitised samples Doubling the number of samples also removes the blind spots Increase the number of samples from 10 to 20 eγ [blue] and spike [red] distributions are separated Blind spots are removed Increasing the number of samples from 10 to 20 is most effective and should be considered for the HL-LHC upgrade. University of Southampton Spike mitigation May 28, / 33

30 Summary and proposals for future studies Summary and proposals for future studies University of Southampton Spike mitigation May 28, / 33

31 Summary and proposals for future studies There is still work to be done If doubling the bandwidth (number of samples) is not practical a spike bit should be developed Spike bit will effectively use the analogue shape in a goodness of fit test This could compare pulse widths at half maximum to discriminate between pulses The current simulation contains the flexibility to be used for such a study Study is required to find a compromise digitisation time adjustment for spike rejection and trigger efficiency University of Southampton Spike mitigation May 28, / 33

32 Summary and proposals for future studies Summary Spikes in the CMS ECAL have the potential to dominate the trigger rate Previous mitigation methods have allowed ECAL to perform to design requirements thus far Situation will get progressively worse for higher energies and luminosities Viable solutions to be implemented in the HL-LHC were presented By using the properties of spikes in energy topology, pulse shape and time, the CMS trigger can be used to mitigate spikes to the required level University of Southampton Spike mitigation May 28, / 33

33 Summary and proposals for future studies [1] D. A. Petyt, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 695, 293 (2012), ISSN , URL sciencedirect.com/science/article/pii/s [2] A. Zabi, EPJ Web of Conferences 28, (2012), ISSN , arxiv: v1. [3] T. F. of Anomalous Signals in Calorimeters (Presented at a CMS Wednesday General Meeting on May 26, 2010), URL material/slides/1.pdf. [4] The CMS Collaboration, Journal of Instrumentation 3, S08004 (2008), ISSN , URL [5] The CMS Collaboration, Journal of Instrumentation 5, T03011 (2010), ISSN , URL University of Southampton Spike mitigation May 28, / 33 References

34 Current spike mitigation efforts Current spike mitigation efforts University of Southampton Spike mitigation May 28, / 33

35 Current spike mitigation efforts Topological and time based discrimination >98.5% of spikes are rejected using energy topology and reconstructed time The Swiss-Cross variable is used to distinguish spikes from eγ Spike reconstructed time is early due to their faster pulse shape[5] University of Southampton Spike mitigation May 28, / 33

36 Current spike mitigation efforts Unaffected spikes Spikes in-time with LHC collisions are unmitigated Swiss-Cross[red] and time[blue] are the only properties used thus far Spikes within red boxes are not removed Time reconstruction is not available at trigger (Only Swiss-Cross) In future high luminosity conditions[6], the overlap of spikes and electromagnetic showers will increase Detailed pulse shape information has not been used in spike mitigation as of yet University of Southampton Spike mitigation May 28, / 33

37 Efficiency curves Efficiency curves University of Southampton Spike mitigation May 28, / 33

38 Efficiency curves Shaping time efficiency curves Left: Spike rejection efficiency of a sliding χ 2 cut is plotted against eγ acceptance efficiency for signals within the collision time windows for τ e = 43 ns as was the case in Right: The same as the plot on the left with a shaping time of τ e = 20 ns. University of Southampton Spike mitigation May 28, / 33

39 Efficiency curves Digitisation time efficiency curves and example Left: Spike rejection efficiency of a sliding χ 2 cut is plotted against eγ acceptance efficiency for signals within the collision time windows for pulses as was the case in CMS in Right: The same as on the left with optimised digitisation. University of Southampton Spike mitigation May 28, / 33

40 Efficiency curves Digitisation time effect on pulses Left: The blind spot with simulated pulses. Right: The digitisation time is optimised here. University of Southampton Spike mitigation May 28, / 33

41 The data based energy and time PDFs The data based energy and time PDFs University of Southampton Spike mitigation May 28, / 33

42 The data based energy and time PDFs Time probability distributions Left: Time probability distribution for spike signals extracted from CMS. Right: The same as the left for eγ signals. University of Southampton Spike mitigation May 28, / 33

43 The data based energy and time PDFs Energy probability distributions Left: Energy probability distribution for spike signals extracted from CMS. Right: The same as the left for eγ signals. University of Southampton Spike mitigation May 28, / 33