How to make the most of LHC data

Transcription

1 How to make the most of LHC data low-mass resonances, triggering opportunities Antonio Boveia - CERN Caterina Doglioni - Lund University Matt Strassler 11/05/ KITP plenary

2 Introduction LHC: the biggest man-made discovery machine 2 2

3 Data volumes at the LHC LHC: if everything was recorded up to 40 million collisions/second (MHz) MB/data per collision 40 MHz * 1 MB = 40 TB/s 40 TB/s * 10e+6 s/year = 0.05 ZB/year Facebook: 600 TB/day ~ 200 PB/year [Facebook] LHC experiments need to: 1. process all data, fast 2. select only interesting events Wikipedia/NASA (after selecting interesting events) 3

4 Trigger systems in ATLAS/CMS/LHCb ATLAS CMS LHCb 40 MHz bunch crossing 40 Level-1: custom hardware Software HLT: 20k cores 1 khz to storage H. Brun, LP

5 Limitations to recording all data Limited by: fast read-out of o(100m) detector channels computing resources (reconstruction) disk storage (saving for further processing) everyone else s favourite physics channel Bandwidth = Event rate x Event size LHC: 40 MHz ATLAS: 1 khz LHCb: 12.5 khz CMS: 1 khz (Reconstructed) ATLAS: o(mb) LHCb: ~100 kb CMS: o(mb) Wikipedia/NASA Also to keep in mind: it s not all about bandwidth, it s also about implementation ( > outside the box) 5

6 Today s experimental plenary we even convinced a theorist to do it 3x 20 minute slots that should serve as taster for Bloc 3 Feel free to interrupt and ask questions, but we ll interrupt after 20 and shift the discussion to dedicated bloc sessions from tomorrow Motivation and implementation of trigger-level Analysis/Data Scouting A. Boveia When do LHC analyses get done? Data complexity vs data availability C. Doglioni Composite Higgs as use case to trigger outside the box M. Strassler Wikipedia/NASA 6

7 Dark Matter as a motivation for TLA A. Boveia LHC: the biggest man-made discovery machine 7

8 Data Scouting / Trigger-Level Analysis Probing for low-rate processes is important: LHC luminosity will increase but energy will not. Readout bandwidth is an important limitation of searches when irreducible backgrounds are large. Bandwidth = Event rate x Event size ATLAS: Trigger-Level Analysis CMS: Data Scouting LHCb: Real-Time Analysis / Turbo Stream ATLAS Run 2 More efficient use of available bandwidth: record the subset of the information necessary and/or move analysis online requires improvements in trigger that benefit offline analyses CMS Run 2 Wikipedia/NASA 8

9 9 Dijet Resonances: Constraints on Coupling Values vs. Mass Coupling of new particle to quarks Coupling g B CMS -1 UA pb (1993) pp, s = 0.63 TeV, [21] pp, -1 CMS 18.8 fb (Data scouting) -1 CMS 18.8 fb (Expected) ± 1 std. deviation (Expected) ± 2 std. deviation (Expected) -1 CDF 106 pb (1997) s = 1.8 TeV, [21] -1 CMS 19.7 fb (2015) pp, s = 8 TeV, [18] -1 CDF 1.13 fb (2009) pp, s = 1.96 TeV, [21] fb (8 TeV) -1 ATLAS 20.3 fb (2015) pp, s = 8 TeV, [14] (Gaussian resonance shapes) [GeV] New particle mass M Z'B arxiv:

10 Dirac WIMP mediators: s- and t-channel vector/axial-vector/scalar/pseudo-scalar MET+heavy flavor, W, Z, and Higgs 10

11 11 DM Mass [TeV] DM Simplified Model Exclusions ATLAS Preliminary April 2016 miss E T +γ arxiv: Dijet 8 TeV Phys. Rev. D (2015) Perturbative unitarity 13 TeV Axial-vector mediator, Dirac DM g q = 0.25, g DM 2 = 1 h Thermal relic Ω c = 0.12 DM Mass = Mediator Mass 2 h Thermal relic Ω c 2 = 0.12 miss E T +jet 13 TeV arxiv: Dijet 13 TeV < Phys. Lett. B (2016) h Ω c Mediator Mass [TeV]

12 12 Dark Matter Simplified Model Exclusions: Varying Coupling Values /JHEP07(2015)089 Axial-Vector Z Mass DM Mass SpS and Tevatron constraints on light dijet resonances are not strong enough

13 Data Scouting / Trigger Level Analysis 13

14 14 Points for Discussion - limitations of scouting/tla/online analyses - other important applications of online analysis trigger design additional online processing capability - model-dependent questions: how low to go in dijet resonance coupling? interplay with dilepton searches - other signatures for TLA where can we used reduced information beyond jets

15 Differently timed LHC analyses C. Doglioni LHC: the biggest man-made discovery machine 15 15

16 Timing of LHC analyses Time to access data for analysis ATLAS/LHCf Joint measurements Delayed data analysis CMS Data Parking ATLAS Delayed Stream Analysis with trigger objects ATLAS/CMS Trigger-Level Analysis and Data Scouting Real-time analysis LHCb Turbo Stream/TESLA ALICE Compressed reconstructed data Standard data analysis ATLAS/CMS/LHCb Fully reconstructed data Monitoring ATLAS TAg Data Analysis Data complexity/size 16

17 LHCb: cases for turbo stream New physics at low mass Same principle as dijets: very large background but good mass resolution online can discover new particles Run-3 proposal: Dark Photon Wikipedia/NASA Turbo Stream: 20% of the trigger at 2% of the cost arxiv:

18 LHCb Offline vs online reconstruction Run-2: online and offline reconstructions effectively the same B. Storaci, CERN Seminar Run 2 Real-time calibration in Turbo Stream: in minutes, realign with fresh data and Wikipedia/NASA update constants if needed Possible thanks to HLT/calibration farm computing power Run-1 buffering LHCb-TALK See also: ALICE 18

19 LHCb Offline vs online reconstruction Run-2: online and offline reconstructions effectively the same Mini-poll: If you saw new physics in a trigger-level analysis, would you B. Storaci, CERN Seminar believe it? Run 2 Real-time calibration in Turbo Stream: in minutes, realign with fresh data and Wikipedia/NASA update constants if needed Possible thanks to HLT/calibration farm computing power Run-1 buffering LHCb-TALK See also: ALICE 19

20 LHCb: Upgrade towards software HLT Run-1 Upgrade LHCb-PUB Every event is signal(s)! - move analyses to turbo stream - increase capability of HLT farm 20 20

21 LHCb: Upgrade towards software HLT Run-1 Upgrade Future triggers: Hardware-based or software-based? LHCb-PUB Every event is signal(s)! - move analyses to turbo stream - increase capability of HLT farm 21 21

22 Timing of LHC analyses Time to access data for analysis ATLAS/LHCf Joint measurements Delayed data analysis CMS Data Parking ATLAS Delayed Stream Analysis with trigger objects ATLAS/CMS Trigger-Level Analysis and Data Scouting Real-time analysis LHCb Turbo Stream/TESLA ALICE Compressed reconstructed data Standard data analysis ATLAS/CMS/LHCb Fully reconstructed data Monitoring ATLAS TAg Data Analysis Data complexity/size 22

23 Express analysis in ATLAS: TADA Framework to automatically perform data analysis, applying detector/object calibrations Monitor: Performance Physics channels ATL-COM-DAPR Run at Tier-0: Produce small standardised ROOT-ntuple files (TAGs) Perform analysis on TAGs Publish plot on web display Wikipedia/NASA 23

24 Express analysis in ATLAS: TADA Framework to automatically perform data analysis, applying detector/object calibrations Monitor: Performance Physics channels What about blind analyses? ATL-COM-DAPR Run at Tier-0: Produce small standardised ROOT-ntuple files (TAGs) Perform analysis on TAGs Publish plot on web display Wikipedia/NASA 24

25 Timing of LHC analyses Time to access data for analysis ATLAS/LHCf Joint measurements Delayed data analysis CMS Data Parking ATLAS Delayed Stream Analysis with trigger objects ATLAS/CMS Trigger-Level Analysis and Data Scouting Real-time analysis LHCb Turbo Stream/TESLA ALICE Compressed reconstructed data Standard data analysis ATLAS/CMS/LHCb Fully reconstructed data Monitoring ATLAS TAg Data Analysis Data complexity/size 25

26 Data parking / delayed stream Bandwidth = Event rate x Event size Extra bandwidth = Event rate x Event size processed later If computing resources for reconstruction limited: park the raw data and wait (delay) until everything else is processed Run

27 ATLAS delayed stream results Number of events Signal Actual recorded events from delayed triggers Run 1 arxiv: Actual events recorded with standard trigger Mass of di-jet system Other analyses using delayed stream in ATLAS/CMS: SUSY search for RPV stops Dijet angular analysis Higgs bbar Fully hadronic top DM searches 27 27

28 ATLAS delayed stream results Number of events Signal Actual events recorded with standard trigger Actual recorded events from delayed triggers What events Run 1 would you store in a delayed Run-2 stream? arxiv: Mass of di-jet system Other analyses using delayed stream in ATLAS/CMS: SUSY search for RPV stops Dijet angular analysis Higgs bbar Fully hadronic top DM searches 28 28

29 Timing of LHC analyses Time to access data for analysis ATLAS/LHCf Joint measurements Delayed data analysis CMS Data Parking ATLAS Delayed Stream Analysis with trigger objects ATLAS/CMS Trigger-Level Analysis and Data Scouting Real-time analysis LHCb Turbo Stream/TESLA ALICE Compressed reconstructed data Standard data analysis ATLAS/CMS/LHCb Fully reconstructed data Monitoring ATLAS TAg Data Analysis Data complexity/size 29

30 Introduction LHCf and ATLAS Aim: cosmic ray physics Other example: Moedal, 30

31 Introduction LHCf and ATLAS Any other ideas for parasitic detectors and triggers Aim: cosmic ray physics Other example: Moedal, 31

32 M. Strassler LHC: the biggest man-made discovery machine 32 32

33 Exotic Decays of 125 GeV Higgs Arise in many (MANY!) models A very common consequence of Neutral Naturalness Often occur in models of dark matter (but not necessarily invisible!!!) Large variety of final states possible Higgs is low energy, hard to trigger

34 Exotic Decays of 125 GeV Higgs Fully visible Few- body (e.g. b b mu mu) Many- body (soft objects) (e.g. 4 b b- bar pairs) Invisible Partly- Visible Soft objects + MET (e.g. 2 photons + MET, mu+ mu- + MET) Neutral long- lived objects 2 observable LLPs 1 observable LLPs >2 observable LLPs

35 Trigger approaches Focus on Higgs production, inclusive to decay VBF trigger Lepton trigger Focus on decay, inclusive to production Jet + MET + soft object LLP Combination VBF + MET + soft object VBF + LLP Ok to have # LLPs = 1 Also good for (non- Higgs- related) Dark Matter searches

36 Connections and Extensions Non- VBF triggers relevant for other unknown particles Invisible particles (i.e. dark matter) New light particles (e.g. light Higgs bosons with dominantly exotic decays) LLPs from non- Higgs sources Lepton+X trigger obviously widely useful

37 Opportunities FTK B layer of silicon at ATLAS b physics, multi- b tags, LLPs Level- 1 improvements at both experiments Kinematic information

38 Some questions to address in Bloc 3 Where in the repertoire of standard searches are we losing ground due to rising thresholds? What could be newly feasible with the improvements at levels 1 and 1.5? Higgs ExoDK, DM, Compressed Spectra good benchmarks for low- HT triggers. Are there others? Triggers for boosted objects; Need? Status? Improvements? Triggers for long- lived paticles; Optimized? Worth additional effort right now? Any places where moderate improvements in processing power could make a big difference?