Reconstruction of strange hadrons in collisions of nuclei at RHIC Jakub Kubát Research Project at Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Outline Quark-gluon plasma STAR + fixed target experiment Intro to KF Particle framework Results Au+Au at 27 AGeV (KF Particle Finder + TMVA) Au+Au at 14.6 AGeV (KF Particle Finder) Fixed target at 3.9 AGeV (KF Particle Finder) Summary 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Quark-gluon plasma QGP – new state of matter at high temperatures or energy densities Experimental evidence RHIC, LHC Strangeness enhancement, suppression of jets, quarkonia, flow, … Transition between QGP and hadron gas in QCD diagram Nature? Critical point? Mapping out QCD diagram – collisions at various energies (different baryon chemical potential 𝜇 𝐵 ) Increasing luminosity at low 𝑠 𝑁𝑁 - BES, fixed target, CBM 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Experiment STAR Au+Au at 27 AGeV (2018) FXT at 3.9 AGeV iTPC Continuous pad rows Replace all inner TPC sectors Better dE/dx and momentum resolution 𝜂 <1.5 (was 𝜂 <1.0) 𝒑 𝑻 >𝟔𝟎 MeV/c (was 𝒑 𝑻 >𝟏𝟓𝟎 MeV/c) Au+Au at 14.6 AGeV (2019) 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Intro to KF Particle Package developed for complete reconstruction of short- lived particles and their parameters by FIAS group for CBM Based on Kalman Filter Describes particles with state vector and covariance matrix Covariance matrix reflects track errors and detector efficiency Enables to calculate statistic criteria which can be used for background rejection Independent of geometry - successful implementation at STAR Other properties Treats mother and daughter particles in the same way Allows reconstruction of decay chains Fully SIMDized KF Particle — S. Gorbunov, “On-line reconstruction algorithms for the CBM and ALICE experiments,” Dissertation thesis, Goethe University of Frankfurt, 2012, http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/29538 KF Particle Finder — M. Zyzak, “Online selection of short-lived particles on many-core computer architectures in the CBM experiment at FAIR,” Dissertation thesis, Goethe University of Frankfurt, 2016, http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/41428 KF Particle Tutorial – M. Zyzak, https://drupal.star.bnl.gov/STAR/system/files/KFParticleTutorial_11.12.2018.pdf 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Lambda with KF Particle With covariance matrix full information about track parameters is available Parameter uncertainties are used to calculate statistical criteria based on 𝜒 2 distribution Within KFP framework one cuts on probabilities (params. normalized on error) rather than absolute values of topological variables Statistical approach expected to be more effective for multi-strange baryons (cascades) Default KFPF cuts 𝜒 𝑓𝑖𝑡 2 <10 𝑙/𝑑𝑙>5 𝑙>5 cm 𝜒 𝑝𝑟𝑖𝑚 2 >18.6 𝜒 𝑡𝑜𝑝𝑜 2 <5 𝑑 𝑚𝑎𝑥 <1 cm 𝜒 𝑓𝑖𝑡 2 𝜒 𝑡𝑜𝑝𝑜 2 𝑙/𝑑𝑙 𝜒 𝑝𝑟𝑖𝑚 2 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Au+Au at 27 AGeV Run 2018, Au+Au 27 GeV Production P19ib, library SL19b MB events after selection: 370M 𝑉 𝑧 <70 cm More than 10% primary tracks 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Lambda extraction with KF Particle Finder Default KFPF cuts 𝜒 𝑓𝑖𝑡 2 <10 𝑙/𝑑𝑙>5 𝑙>5 cm 𝜒 𝑝𝑟𝑖𝑚 2 >18.6 𝜒 𝑡𝑜𝑝𝑜 2 <5 𝑑 𝑚𝑎𝑥 <1 cm Signal extracted from 0.2 to 6.0 GeV/c Lowest 𝑝 𝑇 = 0.2 – 0.4 GeV/c, while published 𝑝 𝑇 =0.4−0.6 GeV/c Fitting: double Gaussian with polynomial background 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering TMVA training Cuts for training 𝜒 𝑓𝑖𝑡 2 <14 𝑙/𝑑𝑙>3 𝑙>1 cm 𝜒 𝑝𝑟𝑖𝑚 2 >3 𝜒 𝑡𝑜𝑝𝑜 2 <5 𝑑 𝑚𝑎𝑥 <1 cm Soft ToF PID mode Further improvement with Boosted Decision Trees Learning Looser particle cuts in KFPF Signal: VMC pure signal simulation, thermal pT spectrum Background: Sidebands from data sample (20%) Significance scan Applied BDT on different sample (3%) and searched for ideal BDT cut value Used TMVA::Reader directly in KFPF to apply weights on whole statistics 18.9.2019 Faculty of Nuclear Science and Physical Engineering

KFP: TMVA vs. default cuts 𝒑 𝑻 = 0.1 – 0.2 GeV/c ! standard geom. cuts This thesis: KFP + BDT 𝒑 𝑻 = 0.1 – 0.2 GeV/c ! KFP: TMVA vs. default cuts TMVA improves significance throughout whole 𝑝 𝑇 spectrum Also enables reconstruction at very low 𝑝 𝑇 =0.1−0.2 GeV/c KFP more effective than conventional analysis with topological cuts Default cuts BDT application Analysis note - https://drupal.star.bnl.gov/STAR/system/files/Analysis_note_KsLaXi.pdf Invariant mass plots - https://www.star.bnl.gov/protected/lfsupc/zhux/beslongpaper/massfitting/la/auau27_la_invmass_cut0_ngaus4.0.pdf 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Au + Au at 14.6 AGeV Run 2019, Au+Au 14.6 AGeV Express production with iTPC No official data production yet MB events after selection: 200M 𝑉 𝑧 <70 cm More than 10% primary tracks 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Sidenote: express production at STAR High Level Trigger, Tracking Focus Group STAR HLT uses high performance computers to do real time event reconstruction and analysis Provide additional event selection capability based on physics analysis on top of hardware trigger layers Beam line monitoring Online 3D primary vertex reconstruction Real time beam position monitoring in RHIC low energy runs Live feedback to CA for accelerator monitoring and performance tuning Benefited all BES-I physics analyses Likely to be used again in BES-II 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Au + Au at 14.6 AGeV Run 2019, Au+Au 14.6 AGeV Express production with iTPC No official data production yet MB events after selection: 200M 𝑉 𝑧 <70 cm More than 10% primary tracks 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Signal reconstruction Reconstruction was done in the same way as before With iTPC one can go almost to zero transverse momentum Ongoing work on BDT training, expecting improvement at low pT 𝒑 𝑻 = 0.0 – 0.1 GeV/c 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Fixed target at 3.9 AGeV Run 2019, fixed target, 𝐸 beam = 7.3 AGeV Different geometry, different acceptance Express production MB events sampled: 2.8M 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Signal reconstruction, 𝒑 𝑻 and 𝒚 spectrum 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Raw yield and significance 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Summary KF Particle framework was introduced Results from Λ reconstruction Au+Au at 27 AGeV (2018) – KFPF + BDT Au+Auat 14.6 AGeV (2019, express production) Fixed target at 3.9 AGeV (2019, express production) KF Particle gives promising results in lambda reconstruction at low 𝑝 𝑇 region, especially with BDT KF Particle is more effective at low pT with respect to conventional analysis with topological cuts Future work: multistrange baryons, BDT with iTPC data 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering References KF Particle — S. Gorbunov, “On-line reconstruction algorithms for the CBM and ALICE experiments,” Dissertation thesis, Goethe University of Frankfurt, 2012, http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/29538 KF Particle Finder — M. Zyzak, “Online selection of short-lived particles on many- core computer architectures in the CBM experiment at FAIR,” Dissertation thesis, Goethe University of Frankfurt, 2016, http://publikationen.ub.uni- frankfurt.de/frontdoor/index/index/docId/41428 KF Particle Tutorial – M. Zyzak, https://drupal.star.bnl.gov/STAR/system/files/KFParticleTutorial_11.12.2018.pdf Strange particle measurements in Au+Au 27 GeV - Yue Hang Leng, https://drupal.star.bnl.gov/STAR/system/files/LFSUPC20190603.pdf Analysis note for 𝐾 𝑆 0 , Λ, Λ , Ξ − , Ξ + production in Au+Au collisions at 𝑠 𝑁𝑁 = 7.7, 11.5, 19.6, 27 and 39 GeV – Xianglei Zhu, https://drupal.star.bnl.gov/STAR/system/files/Analysis_note_KsLaXi.pdf 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Thank you for your attention. 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Backup slides 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Dataset, event selection, KFPF selection, 27 AGeV Run 2018, Au+Au 27 GeV Production P19ib, library SL19b MB events sampled: 6.1⋅ 10 8 Events after selection: 3.7⋅ 10 8 𝑉 𝑧 <70 cm More than 10% primary tracks Default KFPF cuts 𝜒 𝑔𝑒𝑜𝑚 2 <10 𝑙/𝑑𝑙>5 𝑙>5 cm 𝜒 𝑝𝑟𝑖𝑚 2 >18.6 𝜒 𝑡𝑜𝑝𝑜 2 <5 𝑑 𝑚𝑎𝑥 <1 cm 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Raw yield calculation Fitting: For 𝑝 𝑇 =0.2−0.4 GeV: double Gaussian with pol3 background For 𝑝 𝑇 >0.4 GeV: double Gaussian with pol1 background S = bin count in 3𝜎 window – integral of polynomial background significance = 𝑆/ 𝑆+𝐵 Lowest transverse momentum bin: 𝑝 𝑇 = 0.2 – 0.4 GeV/c 18.9.2019 Faculty of Nuclear Science and Physical Engineering

STAR Collaboration Meeting, Cracow, Poland TMVA training example TMVA plots for 𝒑 𝑻 =𝟎.𝟐−𝟎.𝟒 GeV 19.8.2019 STAR Collaboration Meeting, Cracow, Poland

Significance scan example, 𝒑 𝑻 = 𝟎.𝟐 – 𝟐.𝟒 GeV/c B C SG =749.53 B C Default cuts A SG = 476.37 C B 19.8.2019 STAR Collaboration Meeting, Cracow, Poland

STAR Collaboration Meeting, Cracow, Poland TMVA vs. default cuts 𝒑 𝑻 = 0.1 – 0.2 GeV/c ! TMVA improves significance throughout whole 𝑝 𝑇 spectrum Low pT enhancement up to 50% Also enables reconstruction in very low 𝒑 𝑻 = 0.1 – 0.2 GeV/c Default cuts BDT application 19.8.2019 STAR Collaboration Meeting, Cracow, Poland

Comparison with conventional analysis BES I reconstruction of Λ Dataset AuAu, 27 GeV, 2011, P11id 72.8⋅ 10 6 MB events Lambdas at midrapidity, 𝑦 <0.5 For comparison extracted yields and errors from plots in analysis note “by hand” Conventional analysis does not go under 𝑝 𝑇 =0.4 GeV/c Analysis note - https://drupal.star.bnl.gov/STAR/system/files/Analysis_note_KsLaXi.pdf Invariant mass plots - https://www.star.bnl.gov/protected/lfsupc/zhux/beslongpaper/massfitting/la/auau27_la_invmass_cut0_ngaus4.0.pdf 19.8.2019 STAR Collaboration Meeting, Cracow, Poland

Faculty of Nuclear Science and Physical Engineering AuAu, 27 GeV, default cuts 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering AuAu, 27 GeV, BDT 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering AuAu, 14 GeV, default cuts 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering Fxt, default cuts, 𝑬 𝒃𝒆𝒂𝒎 =𝟕.𝟑 GeV 18.9.2019 Faculty of Nuclear Science and Physical Engineering

Faculty of Nuclear Science and Physical Engineering 18.9.2019 Faculty of Nuclear Science and Physical Engineering