Observation of Single Top Quark Production Tevatron 20091110

Observation of Single Top Quark Production @Tevatron 2009/11/10

Top Quark Production 1995 2009 Pair Single strong interaction (gtt vertex) weak interaction (Wtb vertex) q q g t b W+ t-channel s-channel W- l W+ u d W*+ u d t b b l ν W*+ W+ ν g b t • 測定の難しさ – B. G. に対してCross section が小さい。 • 理論値 σst ~ 2. 9 pb • tt pair (σ ~ 7 pb) の約40% – Single top event である特徴が少なく、バックグランドとの分離が難しい。 • Cut base event selection した後でさえ、S/N比が5~6% → 様々な多変数解析(Multivariate technique ) が行われた。 b b

Signal events tree-level matrix-element generator を用いてシミュレーションした。 (MADEVENT) • t → b. W (100%) • S/N 比をよくするため、W がleptonic に崩壊したイベントを探した。 t-channel s-channel u d W*+ t b g b t b

B. G. events QCD multi-jet events W + HF jets g q’ b q b W q q g q l q(e) ν + mistags ( mistakenly b-tagged light-flavor jets) → Prediction derived from data control samples tt-pair Di-boson W- q q g q t b W+ W q q l ν → MC prediction scaled to the total integrated luminosity

Selection Cut l + missing-Et + 2 or 3 jets • e or μ: Isolated leptons with Pt > 20 Ge. V • ν : missing-Et > 25 Ge. V • jets : Et > 20 Ge. V and |η| < 2. 8 At least one jet identified as b-tagged (displaced secondary vertex algorithm) Veto • Di-lepton – To reduce the Z + jets, tt-pair and di-boson • multi-jet events without a leptonic W decay • photon and cosmic ray s-channel (W+2 -jets) l W+ u ν t W*+ d b b t-channel (W+3 -jets) u d l ν W*+ W+ g b t b b

Selection Cut (no lepton) レプトンを検出できなかった事象を探す ( → MJ analysis で用いる) missing-Et + 2 or 3 jets • no lepton : veto events selected for “l + missing-Et + jets”. • ν : missing Et > 50 Ge. V ( ←大量のQCD B. G. を除去) • jets : Two jets within |η| < 2. 0, at least one of which has |η| < 0. 9 1 st jet Et > 35 Ge. V, 2 nd Et > 25 Ge. V angular separation between the two jets, ΔR > 1. 0 Veto four or more jets with Et > 15 Ge. V in |η| < 2. 4 – To reduce the QCD multi-jet and tt-pair B. G. . B-tagging • Neural network (NNQCD) to reduce the QCD multi-jet B. G. . – missing-Et とmissing-Pt の絶対値 – Angle between missing-Et and missing-Pt – Azimuthal angle missing-Et or missing-Pt and jet directions → Removing 77 % of the QCD B. G. while keeping 91 % of the signal acceptance.

Yield and Multivariate Analysis B. G. • Likelihood function – for t-channel (LF) – for s-channel (LFS) • Matrix element (ME) • Neural network – for l + missing-Et + jets (NN) – for missing-Et + jets (MJ) Sig. Selection cut をした後でもB. G. が圧倒的にdominant。 Multivariate technique • Boosted decision tree (BDT) Improved b-tag (bnn) • neural network tool (NEUROBAYES) • Trained to distinguish b jets from charm and light-flavor jets based on secondary vertex tracking information.

Likelihood Function for t-channel (LF) • Combine several sensitive variables into a single one ビンの中のシグナルの割合 sign al B. G. Likelihood function 2つのlikelihood function を用意した。 • 2 -jet イベント用 (L 2 j) … 7 input variables • 3 -jet イベント用 (L 3 j) … 10 input variables

Likelihood Function for t-channel (LF) • b-tagged jet is assumed as a jet from top decay. • For double-b-tagged event, L 2 j is set to zero. 7 Input variables for L 2 j • • Improved b-tagging (bnn) Reconstructed top mass (Mtop) Di-jet mass (Mjj) lepton charge x pseudo-rapidity of jet not assigned to be the b from top decay (Q x η ) • Total scalar sum of the transverse energy in the event (Ht) • cosθ*lj (θ : between the lepton and jet not assigned to be the b from top decay, in the top quark rest frame) • t-channel matrix element

Likelihood Function for s-channel (LFS) 2つ以上のb-tagged jets を要求 (→ 609 events) • W+HF と tt-pair がmain B. G. • Kinematic fitter を使用。 – z component of neutrino momentum – b-jet that most likely came from the top decay Important input variables • Output of the kinematic fitter • Invariant mass of the two b-tagged jets (Mbb) • Transverse momentum of the bb system • • Reconstructed top mass (Mtop) Total scalar sum of the transverse energy in the event (Ht) Leading jet transverse momentum Missing-Et

Matrix Element (ME) Compute an event probability for signal and B. G. based on calculations of the SM differential cross sections. PDF (parton distribution functions) Lepton and jets 4 -vectors Partonic quantities Transfer function (detector resolution effects) Event Probability Discriminant B-tagging by NN

Neural Network (NN) Network are developed using NEUROBAYES analysis package. Important input variables • • Improved b-tagging (bnn) Reconstructed top mass (Mtop) Di-jet mass (Mjj) lepton charge x pseudo-rapidity of jet not assigned to be the b from top decay (Q x η ) Total scalar sum of the transverse energy in the event (Ht) cosθ*lj (θ : between the lepton and jet not assigned to be the b from top decay, in the top quark rest frame) Transverse mass of the W boson Total scalar sum of the transverse energy in the event (Ht)

Boosted Decision Tree (BDT) • Decision tree method : Sequence of binary splits using the discriminating variable which gives best sig-bkg separation. • Boosting algorithm : Events misclassified during DT training are given a higher weight in the next training. • Use over 20 input variables

Data Check The modeling of each input variable was checked by the B. G. dominated data control samples. l + missing-Et + jets analysis • l + b-tagged 4 jets samples – Enriched in tt-pair events • 2 or 3 jets samples (no b-tagging) – 3 jets samples are enriched in W+jets and QCD events Mismodeling がないか2000以上の分布を確認した。 small discrepancies • Angle between two jets in the untagged lepton + 2 -jets samples • Modeling of jets with rapidity greater than 2. 4 → systematic uncertainties に含めている。

Output from “l + missing-Et + jets” Analysis

Combined Output 一番右側のビンで、 significance が5σ 以上

Analysis of events with Missing-Et and Jets (MJ) レプトンを検出できなかったイベントを解析 • Data : 2. 1 fb-1 • Use a neural network Important input variables • • • Invariant mass of the miss-Et Second leading jet Scalar sum of the jet energies missing-Et Azimuthal angle between miss-Et and the jets

Measurement of cross section • Simultaneous fit over two exclusive channels (SD and MJ) • Bayesian binned likelihood technique を使用。 SD discriminant MJ discriminant →Cross section : 2. 3 (+0. 6 -0. 5 stat+syst) pb → |Vtb| = 0. 91 ± 0. 11 (stat + syst) ± (theory)

Summary Single top production を観測した。 • Data : 3. 2 fb-1 (ppbar-collision, √s = 1. 96 Te. V) • Significance : 5. 0 σ • Sensitivity : 5. 9 σ • Cross section : 2. 3 (+0. 6 -0. 5 stat+syst) pb Cross section から | Vtb | を求めた。 • |Vtb| = 0. 91 ± 0. 11 (stat + syst) ± (theory) • |Vtb| > 0. 71 (95% C. L. )