b6b11443cd75e6fba0632818edbf13b7.ppt

- Количество слайдов: 35

From the ATLAS electromagnetic calorimeter to SUSY Freiburg, 15/06/05 Dirk Zerwas LAL Orsay • Introduction • ATLAS EM-LARG • Electrons and Photons • SUSY measurements • Reconstruction of the fundamental parameters • Conclusions

Introduction • LHC: CERN’s proton-proton collider at 14 Te. V • 2800 bunches of 1011 protons • bunch crossing frequency: 40. 08 MHz • Low Luminosity: 1033 cm-2/s meaning 10 fb-1 per experiment (3 years) • High Luminosity 1034 cm-2/s meaning 100 fb-1 per experiment (n years) • SLHC: most likely 1035 cm-2/s meaning 1000 fb-1 per experiment (2015+) • startup for physics: late 2007 Two multipurpose detectors: ATLAS, CMS The experimental challenges of the LHC environment: • bunch crossing every 25 ns • 22 events par BX (fast readout, 40 MHz 200 Hz, event-size 1. 6 MB) • High radiation FE electronics difficult (military and/or space technology) and with that do precision physics!

Physics at the LHC Process W eν Z ee tt bb QCD jets p. T>200 Ge. V Events/s Events/year 15 1. 5 0. 8 105 102 108 107 1012 109 If the machine works well: Factory of Z, W, top and QCD jets. Will be limited quickly by systematics! other machines 104 LEP/ 107 Te. V. 107 LEP 104 Te. Vatron 108 Belle/Babar 107 You have heard already much about the physics from Sven Heinemeyer, Tilman Plehn, Christian Weiser, … plus in-house expertise on ATLAS-Tracker, ATLASMuons, Higgs physics, …. . so try to find things of added value not covered so far: Calo+SUSYreco Measurements: • W mass to 20 Me. V needs control of the linearity/energy scale (0. 02% energy scale) • Higgs mass measurement (if etc) in γγ • SUSY precision measurements with leptons Stringent requirements on the energy scale, uniformity and linearity of the ATLAS-EM Calorimeter response! Startup date getting closer, need to prove that we understand are prepared Calo!

The ATLAS Electromagnetic Calorimeter Liquid Argon Sampling Calorimeter: • lead (+s. s. ) absorbers (1. 1, 1. 5 mm Barrel) • liquid Argon gap 2. 2 mm 2 k. V (barrel) • varying gap and HV in the endcap • accordion structure no dead area in φ • “easy” to calibrate φ R 2. 8 m R 4 m Z 0 m Z 3. 2 m

The barrel and endcap EM-calorimeters! Some numbers: 2048 barrel absorbers 2048 barrel electrodes giving 32 barrel modules (4 years of production and assembly) 16 endcap modules All assembled and inserted in their cryostats Barrel cryostat in pit waiting for electronics Barrel Thickness: 24 -30 X 0 Granularity (typical Δη X Δφ ): Presampler = 0. 025 x 0. 1 (up to η=1. 8) Strips = 0. 003 x 0. 1 (EC ) Middle = 0. 025 x 0. 025 (main energy dep) Back = 0. 05 x 0. 025 Endcaps

Calibration of the ATLAS EM calorimeter General Strategy and Sequence for electrons and photons: • Calibration of Electronics • necessitates a good understanding of the physics and calibration signal • Corrections at the cluster level: • position corrections • correction of local response variations • corrections for losses in upstream (Inner detector) material and longitudinal leakage • Refinement of corrections depending on the particle type (e/γ) • uniformity 0. 7% with a local uniformity in ΔηXΔφ=0. 2 x 0. 4 better than 0. 5% • inter-calibrate region with Zee What can be studied where? • Calibration of electronics studied in testbeam • Corrections at cluster level: testbeam and ATLAS simulations • uniformity: testbeam • Zee: simulation The best Monte Carlo is the DATA! For ATLAS: Testbeam. MC ATLAS

ATLAS series modules in testbeam 1998 -2002: prototype and single module tests at CERN: 4 ATLAS barrel modules 3 ATLAS endcap modules Single electron beams FE electronics 20 -245 Ge. V Sitting directly on the Studies of: feedthrough • energy resolution as in ATLAS • linearity • uniformity • particle ID 2004: combined testbeam endcap and barrel including tracking and muons

The Signal/Electronics Calibration Preamp + shaper (3 gains) + SCA Calibration signal : ~0. 2% Physics signal Electronics: • bipolar signal • time to peak 50 ns (variable) • 40 MHz sampling of 5 samples (125 ns) • three gain system 1/9. 5/10 (automatic choice) L (n. H) L non-uniform: 2 -3 % effect on E along 60 30 10 0 1. 4 From 5 samples in time to one “energy”: Optimal Filtering coefficients: • exponential versus linear • different entry points • inductance effect: parallel versus serial • electronic gains

Digression: From physics to industry. Hamac SCA: Atlas Calorimeter Electronics. Sampling of 3 x 4 signals at 40 MHz, 13. 5 bits of dynamic range with simultaneous write and read in rad-hard technology (DMILL). Same type of chip used in digital oscilloscope: keep the high dynamic range and increase the sampling rate and bandwidth while using the cheapest technology on the market: 0. 8µ pure CMOS (patent filed in April 2001). Instruments are based on the MATACQ chip which is a sampling matrix able to sample data at 2 GS/s over 2560 points and 12 bits of dynamic range with a very low power consumption compared to standard systems. This structure has first been used in the design of the new digital oscilloscope family of Metrix (0 X 7000). This product is the first autonomous 12 -bit scope on the market. Award for technology transfer to industry of the SFP ( DPG) Also used in a 4 -channel VME and GPIB board. The latter offers the 2 GS/s – 12 bits facility with low power at low cost. It’s perfectly suited for high dynamic range precise measurements in harsh environments (CAEN). Dominique Breton LAL-Orsay, Eric Delagnes CEA-Saclay

Cluster Corrections Clustering with fixed size • Correct position S-shape in eta • Correct phi offset • S shape eta in strips • local energy variations phi (accordion) • local energy variations eta Testbeam: phi modulation Endcap: Variation of correction as function of η under control (smooth behaviour) ATLAS simulation: S-shape

Cluster Corrections: longitudinal weighting Non-negligeable amount of material before the calorimeter Reconstruction needs to optimise simultaneously energy resolution and linearity. Method based on Monte Carlo and tested with data in one point η= 0. 68: EPS = energy in presampler Ei =energy in calorimeter compartments Correct for energy loss upstream of Presampler (cryostat+beam line material) 1. 5 X 0, 3. 6 %@10 Ge. V Energy lost between PS and calo (Cable/board) Small dependence of calo sampling fraction+ lateral leakage with energy 0. 9 X 0, 4. 1 %@10 Ge. V Longitudinal leakage depth function of depth only > 30 X 0, 0. 3 %@10 Ge. V fbrem extracted from simulation and beam transport of H 8 beam line, not present in ATLAS

Linearity Dedicated setup was used in 2002 to have a very precise beam energy measurement : - Degaussing cycle for the magnet to ensure B field reproducibility at each energy (same hysteresis) - Use a precise Direct Current-Current Transformer with a precision of 0. 01 % - Hall probe from ATLAS-Muon in magnet to cross-check magnet calibration lots of help from EA-team (I. Efthymiopoulos) Limitation of calorimeter linearity measurement is 0. 03 % from beam energy knowledge - Absolute energy scale is not known in beam test to better than ~1 % - Relative variation is important Achieved better than 0. 1 % over 20 -180 Ge. V but : - done only at one position in a setup with less material than in ATLAS and no B field -No Presampler in Endcap (ATLAS) for >1. 8 Systematics at low energy ~0. 1 %

Energy resolution Resolution at =0. 68 Good agreement for longitudinal shower development between data and testbeam MC Local energy resolution well understood since Module 0 beam tests and well reproduced by simulation : àUniformity is at 1% level quasi online but achieving ATLAS goal (0. 7 %) difficult

Cluster Energy Corrections In ATLAS: use a simplified formula: E(corr) = Scale(eta)*(Offset(eta)+W 0(eta)*EPS+E 1+E 2+W 3(eta)*E 3) 3 x 7 50 Ge. V 100 Ge. V 0. 1%-0. 2% spread from 10 Ge. V to 1 Te. V over all eta remember testbeam was 1 point: proof that the method works!

Energy resolution in ATLAS Simulation Energy resolution in ATLAS wrt testbeam 20% worse Typically 2 -4 X 0 in front of calorimeter Good correlation with resolution Current method at the limit of its sensitivity For historians: wrt TDR 25% degradation, but in TDR simulation Inner Detector Material description incomplete 100 Ge. V resolution X 0 in front of strips

Barrel uniformity @ 245 Ge. V in testbeam Module P 13 > 7 Module P 15 > 7 rms 0. 62% 0. 45% 4. 5‰ 0. 49% In beam setup, one feedthrough had quality problem ( open symbols) due to large resistive cross talk (non-ATLAS FT). > 7 is ATLAS like and can be used as reference : uniformity better than 0. 5 % Energy scale differs by 0. 13 % quality of module construction is excellent Module P 13 Energy resolution Similar results for endcap modules

Position/Direction measurements in TB 245 Ge. V Electrons mid ~550 μm at =0 strip ~250 μm at =0 s. Z~20 mm H γγ vertex reconstructed with 2 -3 cm accuracy in ATLAS in z Precision of theta measurement 50 mrad/sqrt(E) Good agreement of data and simulation s. Z~5 mm

Z ee • uniformity 0. 2 x 0. 4 ok in testbeam • description of testbeam data by Monte Carlo satisfactory • make use of Z ee Monte Carlo and Data in ATLAS for intercalibration of regions • 448 regions in ATLAS (denoted by i) • mass of Z know precisely • Eireco = Eitrue(1+αi) • Mijreco =Mijtrue(1+(αi+αj)/2) • fit to reference distribution (Monte Carlo!!!) • beware of correlations, biases etc… At low (but nominal) luminosity, 0. 3% of intercalibration can be achieved in a week (plus E/P later on)! Global constant term of 0. 7% achievable!

Mass resolution of Higgs bosons H ZZ 4 e: Mass scale correct within 0. 1 Ge. V σ=2. 2 Ge. V H γγ Note that the generated Higgs mass is 120 Ge. V: Effect: calibration with electrons, so the photon calibration is off by 1 -2% Getting from Electron to photon in ATLAS will require MC! H γγ 120. 96 Ge. V σ= 1. 5 Ge. V

Particle Identification/jet rejection Dijet cross section ~1 mb Z ee 1. 5 10 -6 mb W eν 1. 5 10 -5 mb Need a rejection factor of 105 for electrons Use the shower shape in the calorimeter Use the tracker Use the combination of the calo+tracker Cut based analysis gives for electrons an efficiency of about 75 -80% with a rejection factor of 105 Multivariate techniques are being studied for possible improvements (likelihood, neural net, boost decision tree)

Soft electrons H bb Two possibilities for seeded electron pions reconstruction • calo • tracker Reconstruction of electrons close to jets difficult, and interesting (btagging) especially for soft electrons. Dedicated algorithm: • builds clusters around extrapolated impact point of the tracks • calculates properties of the clusters e id efficiency = 80% • PDF and neural net for ID Pion rejection in: • useful per se as well as for b. J/Psi : 1050± 50 tagging WH(bb) : 245± 17 tt. H : 166 ± 6 J/Psi WH tt. H What can we do now with all that?

Supersymmetry See talks by Sven and Tilman: Here only a reminder for completeness sake 3 neutral Higgs bosons: h, A, H 1 charged Higgs boson: H± and supersymmetric particles: spin-0 Squarks: ~ q q R, ~ L spin-1/2 spin-1 q ~ Gluino: g The parameters of the Higgs sector: • m. A : mass of the pseudoscalar Higgs boson • tanβ: ratio of vacuum expectation values • mass of the top quark ~ t • stop (t. R, ~L) sector: masses and mixing Theoretical limit: mh 140 Ge. V/c 2 g Sleptons: ~ ~ ℓR, ℓL ℓ h, H, A Neutralino χi=1 -4 Z, γ H± Charginos: χ±i=1 -2 W± Many different models: • MSSM (minimal supersymmetric extension SM) • m. SUGRA (minimal supergravity) • GMSB • AMB • NMSSM Conservation of R-parity • production of SUSY particules in pairs • (cascade) decays to the lightest sparticle • LSP stable and neutral: neutralino (χ1) • signature: missing ET

At the LHC Large cross section for squarks and gluinos of several pb, i. e. several k. Events sum jet-PT and ET effective mass Squarks and gluinos up to 2. 5 Te. V “straight forward” Largest background for SUSY is SUSY (but…) SUSY SM Large masses means long decay chains Selection: multijet with large PT (typically 150, 100, 50 Ge. V) and OS-SF leptons Invariant masses jet-lepton, lepton-lepton-jet related to masses

SUSY at the LHC (and ILC) m 0 = 100 Ge. V m 1/2 = 250 Ge. V A 0 = -100 Ge. V tanβ =10 favourable for LHC and ILC (Complementarity) sign(μ)=+ Moderately heavy gluinos and squarks Heavy and light gauginos Higgs at the limit of LEP reach light sleptons ~ τ1 lighter than lightest χ± : • χ± BR 100% τν~ • χ2 BR 90% ττ~ • cascade: ~ q. L χ2 q ℓR ℓ q ℓ ℓ qχ1 ~ visible

Examples of measurements at LHC Gjelsten et al: ATLAS-PHYS-2004 -007/29 plus other mass differences and edges… From edges to masses: System overconstrained

Using the kinematical formula (no use of model) and a toy MC for the correlated energy scale error: • energy scale leptons 0. 1% • energy scale jets 1% Mass determination for 300 fb-1 (thus 2014): Coherent set of “measurements” for LHC (and ILC) “Physics Interplay of the LHC and ILC” Editor G. Weiglein hep-ph/0410364 Polesello et al: use of χ1 from ILC (high precision) in LHC analyses improves the mass determination

From Mass measurements to Parameters SFITTER (R. Lafaye, T. Plehn, D. Z. ): tool to determine supersymmetric parameters from measurements Models: MSUGRA, MSSM, GMSB, AMB The workhorses: • Mass spectrum generated by SUSPECT (new version interfaced) or SOFTSUSY • Branching ratios by MSMLIB • NLO cross sections by Prospino 2. 0 • MINUIT The Technique: • GRID (multidimensional to find a non-biased seed, configurable) • subsequent FIT Other approaches: • Fittino (P. Bechtle, K. Desch, P. Wienemann) • Interpolation (Polesello) • Analytical calculations (Kneur et al, Kalinowski et al) • Hybrid (Porod) Beenakker et al

Results for MSUGRA Once a certain number of measurements are available, start with the most constrained model Start SPS 1 a LHC ILC LHC+ILC SPS 1 a ΔLHC m 0 100 1 Te. V m 1/2 250 1 Te. V tanβ 10 50 50 50 A 0 Two separate questions: • do we find the right point? • need and unbiased starting point • what are the errors? -100 0 Ge. V ΔILC ΔLHC+ILC m 0 100 3. 9 0. 08 m 1/2 250 1. 7 0. 13 0. 11 tanβ 10 1. 1 0. 12 A 0 -100 33 4. 8 4. 3 Sign(μ) fixed • Convergence to central point • errors from LHC % • errors from ILC 0. 1% • LHC+ILC: slight improvement • low mass scalars dominate m 0

Masses versus Edges SPS 1 a ΔLHC masses ΔLHC edges m 0 100 3. 9 1. 2 m 1/2 250 1. 7 1. 0 tanβ 10 1. 1 0. 9 A 0 -100 33 20 Sign(μ) fixed • use of masses improves parameter determination! • edges to masses is not a simple “coordinate” transformation: Δm 0 1 Ge. V Effect on mℓR Effect on mℓℓ 0. 7/5=0. 14 0. 4/0. 08=5 Similar effect for m 1/2 need correlations to obtain the ultimate precision from masses….

Total Error and down/up effect Theoretical errors (mixture of c 2 c and educated guess): Higgs sleptons 3 Ge. V Squarks, gluinos 1% Neutralinos, charginos 3% 1% Higgs error: Sven Heinemeyer et al. SPS 1 a ΔLHC+ ILCexp ΔLH+ ILCth Soft. SUSYup 100 0. 08 1. 2 m 1/2 250 0. 11 0. 7 10 0. 12 0. 7 A 0 SPS 1 a m 0 tanβ Including theory errors reduces sensitivity by an order of magnitude -100 4. 3 17 ΔLHC+LC m 0 100 95. 2 1. 1 m 1/2 250 249. 8 0. 5 tanβ 10 9. 82 0. 5 A 0 -100 -97 10 Running down/up • spectrum generated by SUSPECT • fit with SOFTSUSY (B. Allanach) • central values shifted (natural) • m 0 not compatible

Between MSUGRA and the MSSM Start with MSUGRA, then loosen the unification criteria, less restricted model defined at the GUT scale: • tanβ, A 0, m 1/2 , m 0 sleptons, m 0 squarks, m. H 2 , μ Sfitter-team and Sabine Kraml • experimental errors only SPS 1 a LHC ΔLHC m 0 sleptons 100 4. 6 m 0 squarks 100 50 m. H 2 10000 9932 42000 m 1/2 250 3. 5 tanβ 10 9. 82 4. 3 A 0 -100 181 • Higgs sector undetermined • only h (m. Z) seen • slepton sector the same as MSUGRA • light scalars dominate determination of m 0 • smaller degradation in other parameters, but still % precision The highest mass states do not contain the maximum information in the scalar sector, but they do in the Higgs sector!

MSSM With more measurements available: fit the low energy parameters LHC ILC LHC+ILC MSSM fit: bottom-up approach 24 parameters at the EW scale LHC or ILC alone: • certains parameters must be fixed LHC+ILC: • all parameters fitted • several parameters improved Caveat: • LHC errors ~ theory errors • ILC errors << theory errors ÞSPA project: improvement of theory predictions and standardisation

Higgs mass from γγ Impact of Te. Vatron Data? With Volker Buescher (Uni Freiburg): • 2008 too early for Higgs to γγ with 10 fb-1 at LHC • only central cascade SUSY measurements are ~ ~ available: χ1, χ2, q. L, ℓR • Higgs is sitting on the edge of LEP exclusion • WH+ZH 6 events per fb-1 and experiment at Te. Vatron • end of Run: Δmh = ± 2 Ge. V • adding background: Δmh = ± 4 -5 Ge. V No Higgs, edges from the LHC: m 0 = 100 ± 14 Ge. V m 1/2 = 250 ± 10 Ge. V tanβ = 10 ± 144 A 0 = -100. 37 ± 2400 Ge. V Higgs hint plus edges from the LHC: m 0 = 100 ± 9 Ge. V m 1/2 = 250 ± 9 Ge. V tanβ = 10 ± 31 A 0 = -100 ± 685 Ge. V • A hint of Higgs from the Te. Vatron would help the LHC at least the first year! • mtop from Te. Vatron with 2 Ge. V precision makes impact on fit negligible

And the Egret point? Wim de Boer: astro-ph/0408272 EGRET: on Compton gamma ray observatory, measured high energy gamma ray flux. Compatible with Standard Model, but also SUSY: m 0 =1400 Ge. V m 1/2 = 180 Ge. V A 0=700 Ge. V tanβ = 51 μ > 0 Stau coannihilation 0 ce m. A n sona re Stau LSP Incomp. with EGRET data Dominant Processes at the LHC: Tri-lepton signal promissing WMAP Bulk No EWSB EGRET Les Houches 2005: P. Gris, L. Serin, L. Tompkins, D. Z. Measurements: • Higgs masses h, H, A • mass difference χ2 -χ1 ~ • mass difference g- χ2 Sufficient for MSUGRA m 0 =1400 ± (50 – 530)Ge. V m 1/2 = 180 ± (2 -12) Ge. V A 0 =700 ± (181 -350) Ge. V tanβ= 51 ± (0. 33 -2) Uncertainties: • b quark mass • t quark mass • Higgs mass prediction

Conclusions • Construction of ATLAS-EM calorimeter modules finished • Testbeam studies have driven the improvement of the understanding of the combined optimisation of linearity and resolution of the calorimeter • EM calibration under control • electron (and photon identification) are at the required level with multivariate approaches under study • SFitter (and Fittino) will be essential to determine SUSY’s fundamental parameters • mass differences, edges and thresholds are more sensitive than masses • the LHC will be able to measure the parameters at the level % • LC will improve by a factor 10 • LHC+LC reduces the model dependence • EGRET: in MSUGRA, LHC has enough potential measurements to confront the hypothesis Many thanks to Laurent Serin for his help in the preparation of the talk!