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Enhancing Cone Jet Reconstruction with Modified Preclustering Techniques

This work discusses significant modifications to cone jet reconstruction processes, particularly focusing on the preclustering phase. Vishnu's proposal introduces criteria for selecting seed cells based on energy thresholds, aiming to reduce the number of fake jets while maintaining the integrity of good jets. The preclustering utilizes a modified approach where only cells exceeding a certain energy are considered, followed by effective clustering around those high-energy towers. Implementation details and results from Monte Carlo studies demonstrate potential improvements in jet analysis.

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Enhancing Cone Jet Reconstruction with Modified Preclustering Techniques

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  1. Modification in cone jets reconstruction Preclustering with Simple Cone algo Clustering with cone algorithm Emmanuel Busato How are cone jets reconstructed ? Vishnu's proposal to improve reconstruction : At preclustering level : not let a CH cell become a seed if it's energy is less than some sigma

  2. List of towers (pT ordered) Take the highest pT tower in the list « T » ? pT > seedET =500MeV yes no Go to clustering around T (with R=coneSize=0.3). Remove progressively towers from the list. Stop preclustering Current preclustering (Simple Cone)

  3. List of towers (pT ordered) Take the highest pT tower in the list « T » ? pT > seedET =500MeV yes Take highest ET cell in T : « C » if C is CH or ECMG and if C has E < n * sigma  pT = pT  ETC no pT > seedET =500MeV ? yes Stop preclustering no Go to clustering around T (with R=coneSize=0.3). Remove progressively towers from the list. Modified preclustering

  4. Implementation Everything is on coco-clued0 : /work/coco-clued0/busato/jetanalyze_p13.06.01 - Major modifications are in SconeClusterAlgo.hpp - Needed to create a class (ReadNoiseFile) to read in the noise file (energycluster/energycluster/ReadNoiseFile.hpp) ReadNoiseFile uses official cal_nlc and em_util packages methods to . convert channel (0 55295) (ieta, iphi, layer) . convert ADC  GeV (problem with GeV  rawADC) Current algo works with linearized ADCs gain 8, should we work with raw ADCs and/or gain 1 ? - 3 new parameters in the rcps.

  5. CalPreSCILCone05(07,03).rcp string PackageName = "CalClusterReco" string data_type = "MC" string algo_type = "PreSCilcone" bool drop_negative_mass2 = true // preclustering parameters float coneSize = 0.3 float seedET = 0.5 float pTmin = 1.0 int minItems = 2 bool dropCHseed = false float dropCHseedsigma = 3.5 string offline_zero_supp_file = "/work/coco- clued0/busato/jetanalyze_p13.06.01/cal_zsup_noise.dat" // cone clustering parameters float Item_ET_threshold = 0. float Radius_of_Cone= 0.5 float Min_Jet_ET= 8.0 float ET_Split_Frac= 0.5 float Far_ratio = 0.5 float ET_min_ratio = 0.5 bool Kill_duplicate = true float Duplicate_dR = 0.005 float Duplicate_dPT = 0.01 // if useMCvertex is true: use Monte Carlo vertex // if useD0vertex is true: use reconstructed vertex // if both true use Monte Carlo vertex if there is no reconstructed vertex bool useMCvertex = false bool useD0vertex = true To run the algo with modified preclustering, set dropCHseed to true

  6. Status - This modification was first made to reduce the number of fake jets, but - good jets can have high f90 - Apparently number of fake jets with 2.5 sigma ZS small More to come to confirm this (jets in dijet events study). - Could be used instead to reduce the effect of noise on good jets MC study done by Vishnu

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