400 likes | 402 Vues
Elementary Particle Physics Seminar Oxford, 6 November 2007. ILC vertex detector R&D: optimising the detector design for physics. Sonja Hillert (Oxford). Outline of this talk. Role of the vertex detector for extracting ILC physics
E N D
Elementary Particle Physics Seminar Oxford, 6 November 2007 ILC vertex detector R&D: optimising the detector design for physics Sonja Hillert (Oxford)
Outline of this talk • Role of the vertex detector for extracting ILC physics • Measuring quark charge: vertex charge and charge dipole procedure • Sensitivity of vertex charge reconstruction to detector design: fast MC results • LCFI Vertex Package: software tools for full MC studies • Optimising the vertex detector design • Recent results of LCFI vertex detector R&D on sensors & mechanical support
first order jet finding flavour identification reconstruction of tracks, CAL-cells energy flow objects b charged B bbar classify B as charged or neutral charge dipole, protons, charged kaons or leptons from SV, TV tune track-jet association for tracks from SV or TV contained in neighbouring jet b b-jets neutral B bbar classify D as charged or neutral c charged D c-jets cbar charged kaons or leptons neutral D c uds-jets cbar associate with parent jet in some cases gluon-jets Typical event processing at the ILC
M. Battaglia Dependence of physics reach on detector performance • Flavour tag needed for event selection and reduction of combinatoric backgrounds • Quark charge sign determination used for measurement of ALR, • angular correlations ( top polarisation) – vertex detector performance crucial • Examples: • Higgs branching ratios: • classical example of a process • relying on flavour tag • e+e- ZHH: • 4 b-jets in final state requiring • excellent tagging performance; • could profit from quark charge • sign selection
Sensitivity to deviations of extra-dimensions model from SM predicition (S. Riemann): without quark sign selection with perfect quark sign selection Processes requiring quark sign selection: e+e- b bbar • e+e- bb: indirect sensitivity to new physics, such as extra spatial dimensions, leptoquarks, • Z´, R-parity violating scalar particles (Riemann, LC-TH-2001-007, Hewett PRL 82 (1999) 4765); quark charge sign selection to large cos q needed to unfold cross section and measure ALR:
s e.g.c q’ q’ b W+ t e+ e- t W b q q e.g. s c a typical e+e- t t event Processes requiring quark sign selection: e+e- t tbar • e+e- tt demanding for vertex detector: • multijet event: final state likely to include soft jets • some of which at large polar angle • flavour tag needed to reconstruct the W bosons and top-quarks • quark charge sign selection will help to reduce • combinatoric backgrounds • top decays before it can hadronise: polarisation of top quark • can be measured from polarisation of its decay products; • best measured from angular distribution of s-jet (quark charge)
Requirements • To measure quark charge efficiently one needs: • an excellent vertex detector: • pixel-based system • few micron point resolution (< 5 mm) • small inner layer radius (~ 15 mm) • good polar angle coverage • low mass support structure (<= 0.1 % X0) • mechanical stability • appropriate high-level reconstruction software, e.g.: • topological vertex finding • flavour tagging • vertex charge reconstruction (charged hadrons) • charge dipole reconstruction (neutral B hadrons)
Vertex charge reconstruction • b-jets contain a complex decay chain, from which the charge has to be found • in the 40% of cases where b quark hadronises to charged B-hadron, • quark sign can be determined by vertex charge • need to find all stable tracks from • B decay chain: • define seed axis • cut on L/D (normalised distance • between IP and projection of track POCA • onto seed axis) • tracks that form vertices other than IP • are assigned regardless of their L/D • need vertex finding as prerequisite (definition of seed axis) • in most analyses, only calculate charge for jet of specific flavour: need flavour tagging • probability of mis-reconstructing vertex charge is small for both charged and neutral cases
SLD, NIM A 447 (2000) 90-99 Charge dipole procedure • For some neutral vertices, quark charge can be obtained from • the charge dipole formed by B- and D-decay vertex. • “ghost track” vertexing algorithm (aka ZVKIN) • developed at SLD, was shown to yield higher purity for • charge dipole than standard ZVTOP code (ZVRES, cf p12) • advantage: one-prong vertices identified by vertex finder • increased efficiency, especially at short B decay lengths • at ILC, charge dipole procedure still to be explored
Performance of charge reconstruction: leakage rates • define leakage rate l0 as probability of reconstructing neutral hadron as charged • performance strongly depends on low momentum tracks: • largest sensitivity to detector design for low jet energy, large cos q preliminary results from fast MC study (SGV)
250 mm 60 mm 25 mm 15 mm 8 mm e+e- BEAM 100 mm Using vertex charge for detector optimisation • Using fast MC SGV, studied dependence of leakage rate on vertex detector design: • compared detectors with different inner layer radii ( beam pipe radii) • varied amount of material per detector layer (factor 4 compared to baseline) • translated into integrated luminosityrequired to obtain physics results of same significance • for processes requiring independent quark charge measurement in 2 jets, • increase of beam pipe from 15 to 25 mm has sizeable effect (factor 1.5 – 2) preliminary results from fast MC study (SGV)
The LCFI Vertex Package • The LCFIVertex package provides, in a full MC and reconstruction framework: • vertex finder ZVTOP with branches ZVRES and ZVKIN (new in ILC environment) • flavour tagging based on neural net approach (algorithm: R. Hawkings, LC-PHSM-2000-021); includes full neural net package; flexible to allow change of inputs, network architecture • quark charge determination, currently only for jets with a charged ‘heavy flavour hadron’ • first version of the code released end of April 2007: • code, default flavour tag networks and documentation available from the ILC software portal • http://www-flc.desy.de/ilcsoft/ilcsoftware/LCFIVertex • next version planned to be released this Friday: • minor corrections, e.g. to vertex charge algorithm; further documentation • diagnostic features to check inputs and outputs • new vertex fitter based on Kalman filter to improve run-time performance
central for flavour tag: • pT-corrected vertex mass • this kinematic correction is applied • to partly account for undetected • neutral particles ZVTOP vertex finder, Pt-corrected mass • two branches: ZVRES and ZVKIN (already mentioned when discussing charge dipole) • The ZVRES algorithm (D. Jackson, NIM A 388 (1997) 247) • very general algorithm that can cope with arbitrary multi-prong decay topologies • ‘vertex function‘ calculated from Gaussian ´probability tubes´ representing tracks • iteratively search 3D-space for maxima of this function and minimise c2 of vertex fit
b c uds Flavour tagging approach • Vertex package provides flavour tag procedure developed by R. Hawkings et al • (LC-PHSM-2000-021) as default • number of vertices found determines which • NN input variables are used: • if secondary vertex found: MPt , momentum of secondary vertex, and its decay length and decay length significance • if only primary vertex found: momentum and impact parameter significance in R-f and z for the two most-significant tracks in the jet • in both cases: joint probability in R-f and z (estimator of • probability for all tracks to originate from primary vertex) • flexible: permits user to change input variables, architecture and training algorithm of NN
b c (b-bkgr) b c b c (b-bkgr) c c (b-bkgr) c c (b-bkgr) open: BRAHMS, LC-note full: MARLIN (Mokka), Si-only track cheater c open: SGV fast MC full: MARLIN, SGV-input open: SGV fast MC full: MARLIN, SGV-input b open: BRAHMS, LC-note full: MARLIN (Mokka), Si-only track cheater Identical input events Identical input events Flavour tagging performance Z-peak Z-peak 500 GeV 500 GeV
Diagnostic features • plan to make available inputs and outputs for ZVRES & flavour tag (later: vertex charge) • nearly complete: LCFIAIDAPlot – module for flavour tag diagnostics based on AIDA • input and output variables of the flavour tag neural nets, separately for b-, c-, light jets • graphs of purity vs efficiency and flavour leakage rates (i.e. efficiencies of wrong flavours) vs efficiency separately for the 1-, 2- and 3-vertex case • JAS3-macro to plot these easily • optionally: raw numbers of jets vs NN-output, AIDA tuple with flavour tag inputs written out example: inputs to flavour tag
New vertex fitter: Kalman filter • Motivation: improve run time performance by replacing the “space-holder” • Least-Squares-Minimisation (LSM) fitter of first release • Kalman filter code by S. Gorbunov, I. Kisel interfaced to Vertex Package • successfully tested: • find same flavour tagging performance • as with LSM-fitter • resulting improvement in run time performance: • overall run time of Vertex Package is • reduced to ~ 25% of the 1st-release value
Towards a realistic simulation • Current simulations are based on many approximations / oversimplifications. • The resulting error on performance is at present unknown and could be sizable, • especially when looking at particular regions in jet energy, polar angle (forward region!) • Issues to improve: • Vertex detector model: replace model with cylindrical layers by model with barrel staves • GEANT4: switched off photon conversions for time being (straightforward to correct) • hit reconstruction: using simple Gaussian smearing at present; realistic code exists only for DEPFET sensor technology, not for CPCCDs and ISIS sensors developed by LCFI • track selection: • KS and L decay tracks suppressed using MC information • tracks from hadronic interactions in the detector material discarded using MC info – only works for detector model LDC01Sc (used for code validation) at present • current default parameters of the code optimised with fast MC or old BRAHMS (GEANT3) code • default flavour tag networks were trained with fast MC
c (b-bkgr) full LDCtracking Z-peak c b b open: VXD geometry with ladders full: VXD geometry with cylinders c (b-bkgr) c (b-bkgr) c track cheater, Z-peak b track cheater (04/07) 500 GeV open: photon conversions, uncorrected full: photon conversions off open: hadronic interaction effects full: no hadronic interactions Examples of impact of simplifications • effects of simplifications can be sizeable; • note: photon conversions and hadronic • interactions in detector material can • efficiently be corrected for • currently making initial checks needed for • implementing these corrections c
Further development of the Vertex Package • Areas of relevance for wider user community: • integration into ALCPG software framework org.lcsim: drivers under development in the US, • to be released as soon as possible (N. Graf) • consistent IP treatment, based on per-event-fit in z and on average over N events in Rf • Vertexing: • explore use of ZVKIN branch of ZVTOP for flavour tag and quark charge determination: • optimise parameters • study performance at the Z-peak and at sqrt(s) = 500 GeV • explore how best to combine output with that of ZVRES branch for flavour tag • use charge dipole procedure (based on ZVKIN) to study quark charge determination for (subset of) neutral hadrons
Improvements and extensions • Areas of relevance for wider user community contd: • Flavour tagging: explore ways to improve the tagging algorithm, e.g. through use of • different input variables and/or different set-up of neural nets that combine these • improvements to MPt calculation using calorimeter information, e.g. from high-energy p0 • vary network architecture (number of layers & nodes, node transfer function), training algorithm • explore new “data mining” and classification approaches (e.g. decision trees, … ) • Vertex charge reconstruction: • revisit reconstruction algorithm using full MC and reconstruction (optimised with fast MC) • Functionality specifically needed for vertex detector optimisation: • Correction procedure for misalignment of the detector and of the sensors will need to be • developed, adapted or interfaced (see optimisation of the detector)
Optimising the detector design • Simulations serve to estimate performance of • benchmark quantities: impact parameter resolution, flavour tag, vertex charge reconstruction • reconstruction of physics quantities obtained from study of benchmark physics processes • Vertex detector-related software cannot be developed in isolation: • vertexing, flavour tag, vertex charge rec´n performed on a jet-by-jet basis (depends onjet finder) • strong dependence on quality of input tracks (i.e. hit and track reconstruction software) • physics processes to optimise calorimeter also depend on tagging performance (e.g. ZHH) • Study of benchmark physics processes • performed in close collaboration with the two main ILC detector concept study groups: SiD and ILD (formerly GLD / LDC) • ILCSC has issued call for Letters of Intent, to be submitted 1 October 2008 • These will be followed by more detailed Engineering Design Studies to be completed by 2010
Benchmark Physics Studies • Benchmark physics processes should be typical of ILC physics and sensitive to detector design. • A Physics Benchmark Panel comprising ILC theorists and experimentalists has published • a list of recommended processes that will form the baseline for the selection of processes • to be studied in the LoI- and engineering design phases. • Following processes were highlighted as most relevant by the experts (hep-ex/0603010): particularly sensitive to vertex detector design
Parameters and aspects of design to be optimised • The Vertex Package, embedded into full MC and reconstruction frameworks, • permits the following aspects of the vertex detector design to be optimised: • Beam pipe radius • Sensor thickness, material amount at the ends of the barrel staves • Material amount and type of mechanical support (e.g. RVC, Silicon carbide foams) • Overlap of sensors: linked to sensor alignment, tolerances for sensor positions along the beam & perpendicular to it • Arrangement of barrel staves • Long barrel vs short barrel plus endcap geometry • Study of trade-offs, involving variations of more than one parameter, should be aimed at • Physics simulation results will be only one of the inputs that determine the detector • design – the more decisive input may well be provided by what is technically feasible.
LCFI sensor development: introduction • LCFI pursuing development of two sensor technologies for ILC vertex detector: • Column Parallel CCD (CPCCD) • CPC1 (first CPCCD) • CPC2 – second generation, large area device • In-situ Storage Image Sensor (ISIS) • proof-of-principle device (ISIS1) • effort towards ISIS2 CPC1 CPC2 ISIS1
M M N N “Classic CCD” Readout time NM/fout Column Parallel CCD Readout time = N/fout Column Parallel CCD: principle • Main sensor technology developed by LCFI • Every column has its own amplifier and ADC • Readout time shortened by ~3 orders of magnitude compared to “classic” CCD • All of the image area is clocked, complicated by the large gate capacitance • Optimised for low voltage clocks to reduce power dissipation
CPC2 devices ISIS1 Busline-free CPC2 CPC2-70 104 mm CPC2-40 CPC2-10 • Three device sizes: 10, 40 and 70 mm length (requirement for inner layer device: 100 mm) • Some devices designed to reach high speed (up to 50 MHz operation): • 2-level metallisation permits using whole image area as distributed bus line • Charge to voltage conversion can happen on CCD (50% channels) or on readout chip (other 50%)
CPC2 test results 20 MHz System noise = 110 e- RMS 10 MHz System noise = 75 e- RMS • short (CPC2-10) device, high-speed design, tested with 55Fe signal(1620 e-, MIP-like) • X-ray hits seen up to 45 MHz: important milestone • CPC2 works with clock amplitude down to 1.35 Vpp • in standalone tests (w/o readout chip, using 2-stage source follower outputs): at 10 MHz achieve noise level of 75 e- RMS (CMOS driver chip) • tests continuing
Readout chips: CPR1 and CPR2 Voltage and charge amplifiers 125 channels each Analogue test I/O Digital test I/O 5-bit flash ADCs on 20 μm pitch Cluster finding logic (22 kernel) Sparse readout circuitry FIFO Bump bond pads CPR1 CPR2 • both chips made on 0.25 μm CMOS process (IBM) • front-end amplifiers matched to the CCD outputs • additional test features in CPR2 • CPR2 includes data sparsification Wire/Bump bond pads
Cluster finding with X-ray signals Sparsified output Readout chips: results CPR1, 1 MHz: CPR2: sparsification Voltage outputs • non-inverting (negative signals) Charge outputs • inverting (positive signals) • CPR1: in charge channels expected gain observed, constant over device; • in voltage channels gain drops from edge to the centre of the device (not understood) • CPR2: same gain drop in voltage channels as in CPR1, charge channels don’t work; • errors in sparsification for cluster distances < 60 – 100 pixels: extensive tests with measured • and simulated input led to major re-design of next generation chip CPR2A
Clock driver for CPCCD • Challenge: providing 2 Vpp clocks at 50 MHz for • CPCCD (capacitance 40 nF / phase): 20 A peak current • Further requirements: • low power dissipation • must be close to CCD (to reduce parasitic inductance) • must not add too much to material budget • may have to work at low temperature (down to -100 oC) • 2 approaches: transformer (fallback), custom ASIC (baseline) • performed tests with 16:1 transformer integrated into PCB (above) • and with first version of driver chip CPD1 (right): • 1 chip drives 2 phases, up to 3.3 V clock swing • 0.35 mm CMOS process, chip size 3 x 8 mm2 • 8 independent clock sections • careful layout on- and off-chip to cancel inductance • bump-bondable
CPD1 CPC2-40 CPR2 Integration of CPC, CPR and CPD • a lot more work needed to arrive at ladders • (design of ladder end: left) • but an integrated system of CPC, CPR and CPD • exists and works up to frequency of 9 MHz • (speed limited by CPR2)
LCFI Mechanical Studies • LCFI mechanical work comprises: • support structure prototyping • (RVC-, SiC foam, carbon fibre, shells) • cooling studies • conceptual design example design of a foam ladder (cross section) SiC, samples of 8% and 6% relative density obtained Plot: deviation under temperature cycling
Summary • ILC physics will require an excellent vertex detector as well as adequate reconstruction software. • Studies of the performance of vertexing, flavour tagging, quark charge reconstruction, • and studies of benchmark physics processes are used to optimise the vertex detector design. • The LCFI Vertex Package provides software tools to perform such optimisation using • GEANT4-based simulation and full reconstruction software (including e.g. pattern recognition). • Further development of these tools is needed for realistic detector assessment and comparison. • The development of CPCCD-sensors, CPR readout chips and CPD drivers within the • LCFI collaboration is far advanced. In parallel, mechanical work is progressing well. • In lab tests, CCDs were driven with amplitudes as low as 1.35 Vpp (design spec: 2 Vpp) • and signals observed up to frequencies of 45 MHz (design spec: 50 MHz) • A combined system of CPC2-CPR2-CPD1 was successfully operated up to 9 MHz.
D. Jackson, NIM A 388 (1997) 247 The ZVTOP vertex finder • two branches: ZVRES and ZVKIN (also known as ghost track algorithm) • The ZVRES algorithm: very general algorithm • that can cope with arbitrary multi-prong decay topologies • ‘vertex function‘ calculated from Gaussian • ´probability tubes´ representing tracks • iteratively search 3D-space for maxima of this function • and minimise c2 of vertex fit • ZVKIN:more specialised algorithm to extend coverage to b-jets with • 1-pronged vertices and / or a short-lived B-hadron not resolved from the IP • additional kinematic information • (IP-, B-, D-decay vertex approximately • lie on a straight line) used to find • vertices • should improve flavour tag efficiency and determination of vertex charge
CPC2 Clock Driving Φ1 Φ2 Φ2 Φ1 To multiple wire bonds Φ1 Φ2 Φ2 Φ1 To multiple wire bonds Level 1 metal Polyimide Level 2 metal • CPC1 did not have optimal drive conditions due to the single level metal • Novel idea from LCFI for high-speed clock propagation: “busline-free” CCD: • 50 MHz achievable with suitable driver in CPC2-10 and CPC2-40 (L1 device) • Transformer or ASIC driver 1 mm
In-situ Storage Image Sensor (ISIS) • Operating principles of the ISIS: • Charge collected under a photogate; • Charge is transferred to 20-cell storage CCD in situ, 20 times during the 1 ms-long train; • Conversion to voltage and readout in the 200 ms-long quiet period after the train (insensitive to beam-related RF pickup); • 1 MHz column-parallel readout is sufficient;
In-situ Storage Image Sensor (ISIS) 5 μm Global Photogate and Transfer gate • The ISIS offers significant advantages: • Easy to drivebecause of the low clock frequency: 20 kHz during capture, 1 MHz during readout • ~100 times more radiation hard than CCDs (less charge transfers) • Very robust to beam-induced RF pickup • ISIS combines CCDs, active pixel transistors and edge electronics in one device: non-standard process • Presently discussing with 3 vendors for the ISIS2 development: • Looking at modified 0.18 μm CMOS process with additional buried channel and deep p+ implants • Proof-of-principle device (ISIS1) designed and manufactured by e2V Technologies ROW 1: CCD clocks ROW 2: CCD clocks On-chip switches On-chip logic ROW 3: CCD clocks ROW 1: RSEL Global RG, RD, OD RG RD OD RSEL Column transistor
Tests of ISIS1 • Tests with 55Fe X-ray source: • ISIS1 without p-well tested first and works OK: • Correct charge storage in 5 time slices and consequent readout • Successfully demonstrated the principle • New ISIS1 chips with p-well have been received, now under tests • ISIS1 without p-well is now in a test beam in DESY