ILC Tracking R&D at SCIPP SiD Workshop Thursday, June Bruce Schumm Santa Cruz Institute for Particle Physics

Faculty/Senior Vitaliy Fadeyev Bruce Schumm Collaborators Rich Partridge Takashi Maruyama Tom Markiewicz (SLAC) Students Alex Bogert ** Jerome Carman * London Chappel… Kelsey Collier Spencer Key Donish Khan Omar Moreno Jared Newmiller Dale Owens Sheena Schier Matt Stanton Dustin Stolp * Aaron Taylor Capella Yee The SCIPP/UCSC ILC R&D GROUP Lead Engineer: Ned Spencer Technical Staff: Max Wilder Forest Martinez-McKinney * 2010 Senior thesis (graduation requirement) !Carman thesis wins Chancellor’s Award! ** CERN will support summer 2010

OUTLINE OF SCIPP ILC R&D PROGRAM LSTFE Front-End ASIC Optimized for ILC (long ladders for barrel; high rates for forward tracking) Applicable to both SiD and ILD SiD KPIX/Double-Metal Development SiD baseline; alternative to LSTFE SCIPP has done group’s sensor testing, now beginning critical systems tests

Fundamental (“Generic”) R&D Use of charge division for longitudinal coordinate (with Rich Partridge) Solid-state noise sources SiD Simulation Projects (Not in talk) Tracking and momentum reconstruction validation Non-prompt signatures OUTLINE (Continued)

The LSTFE ASIC

1-3  s shaping time (LSTFE-I is ~1.2  s); analog measurement is Time-Over-Threshold Process: TSMC 0.25  m CMOS The LSTFE ASIC

FIFO (Leading and trailing transitions) Low Comparator Leading-Edge-Enable Domain Proposed LSTFE Back-End Architecture Clock Period  = 400 nsec Event Time 8:1 Multi- plexing (  clock = 50 ns)

LSTFE-II Prototype Optimized for 80cm ladder (ILD barrel application) Institute “analog memory cells” to improve power- cycling switch-on from 30 msec to 1 msec (problems!) Improved environmental isolation Additional amplification stage to improve S/N, control of shaping time, and channel-to-channel matching Improved control of return-to-baseline for < 4 mip signals (time-over-threshold resolution) 128 Channels (256 comparators) read out at 3 MHz, multiplexed onto 8 LVDS outputs Testing underway in SCIPP lab

LSTFE-II Performance: Time-Over- Threshold vs. Injected Charge Omar Moreno

Use of KPiX as a Tracking Chip

The SiD KPIX/Double-Metal Baseline Design 10cm 2 modules tessellate the five barrel tracking layers Traces on 2 nd (surface) metal layer to two 1024-node bump-bonding arrays

SCIPP attempting to explore whether Mounting KPiX on surface of sensor leads to digital  analog feed-through It has proved difficult to mount KPiX7 onto prototype sensors (passivation between two metal layers fails during bonding) Forest M.M.: Arranged for bonding with private firm (H&K); then cut shorted traces with laser

Connectivity After Severing Traces Pad to Pad old R(Ohms) New R(Ohms) AVdd to CLK(-) M AVdd to CLK(+) M AVdd to DVdd K Vref to AGND Vref to DGND AGND to DGND ** DVDD to CLK(-) M DVDD to CLK(+) M **This ohmic connection seems to be through the IC and is not from damage during bonding. Next step: build enclosure for assembly and begin to read out (summer)

Triggering on Minimum- Ionizing Particles

Threshold corresponding to the average pulse height for the given injected charge. 10fC injected9fC injected8fC injected 4fC injected Mean Threshold: Example channel 63

Charge in Coulombs offset gain Example Channel 63

0-Charge Input Offset (mV) by Channel (x10) Offset in mV for no input charge Gain ~4 mV/fC Next step: Interface with pulse-development simulation to confirm min-I operability

Charge Division for Silicon Strip Sensors

Final step: practical detectors are not isolated strips. Include two nearest-neighbors in simulation: Network effects lead to ~5% reduction in longitudinal resolution.

Readout Noise for Linear Collider Applications

Use of silicon strip sensors at the ILC tend towards different limits than for hadron collider or astrophysical applications:  Long shaping time  Resistive strips (narrow and/or long) But must also achieve lowest possible noise to meet ILC resolution goals. How well do we understand Si strip readout noise, particularly for resistive networks? How can we minimize noise for resistive networks?

Standard Form for Readout Noise (Spieler) Series Resistance Amplifier Noise (series)Amplifier Noise (parallel) Parallel Resistance F i and F v are signal shape parameters that can be determined from average scope traces.

Expected Noise for Custom-Biased L00 Ladder Spieler formula suggests that series noise should dominate for ladders of greater than 5 or so sensors.

CDF L00 Sensor “Snake” CDF L00 “Snake” LSTFE1 chip on Readout Board

Readout Noise Results Relative to prior results, have explored “center- tapping” (reading out from center of chain rather than end. Naïve expectation Expectation with measured shape factors F i, F v Measured (end readout) Measured (center-tap)

Summary of Findings Reading out from ladder from end: Significantly less noise observed than expected (network effects ignored in formulation of expectation?) Reading out from middle (“center tap”): Noise seems further reduced (~20%) for lengths for which series noise dominates Will explore with P-SPICE simulation…

AUGUST 2010 MILESTONES  Evaluation of channel-to-channel variations in KPIX-9  Exploration of attachment of KPIX-7 to prototype sensor using cutting laser to mitigate shorts from over-glass failure  Initial characterization of LSTFE-II chip  Estimation of longitudinal resolution from resistive charge division measurement of readout noise in the series-resistance limit, including both end- and center-readout  Simulation studies supporting the design of a high-fluence electromagnetic radiation damage study of various silicon sensors  Acquisition and characterization of sensor samples to be used in damage studies  Simulation studies of SiD tracking efficiency performance in forward region

AUGUST 2011 MILESTONES  Characterization of 'analog memory' test structures and assessment of suitability for implementation of power-cycling for LSTFE  Assessment of effects of digital/analog interference effect in KPIX/double-metal assembly  PSpice simulation of series-noise readout limit and comparison with observation  Publication of charge-division results  Test-beam study of radiation damage to various silicon sensor types  Simulation studies of SiD momentum reconstruction performance in forward region

AUGUST 2012 MILESTONES  Re-optimization (for forward region) and fabrication of LSTFE ASIC.  Follow-up testbeam run to confirm radiation hardness of selected Si sensor  Determination of radial extent of sensitivity for reconstruction kinks fro stau decay in the SiD detector  KPiX/double-metal yield and reliability studies

Simulation Studies (ILC Detector Performance)

CURVATURE RECONSTRUCTION PERFORMANCE 1.Compare width of Gaussian fit to residuals with two different estimates: Error from square root of appropriate diagonal error matrix element Error from Billoir calculation ( LCDTRK program) 2.Only tracks with all DOF (5 VTX and 5 CT layers) are considered. 3.Require |cos  | < 0.5 Mixture of q/qbar at 500 and 1000 GeV, tau samples at 500 GeV; also use single muons

CURVATURE ERROR vs. CURVATURE LCDTRK calculation (no beam constraint) Gaussian fit SiD02 Detector Model

Results for Stiff, Central Tracks In terms of  p /p, comparing ,  with p=100 GeV and |cos  | < 0.5 we find   LCDTRK 0.28%0.28% Residuals 0.37%0.39% LOI Result0.33% ----  Delhi group (Kirti Ranjan et al.) looking into developing Kalman Filter fitter

SiD Forward Tracking Efficiency Start in central region (|cos  | < 0.7); establish P t cut of 2.0 GeV/c Capella Yee, Scotts Valley High School

P t > < P t < 2.0 Exploring Higher Values of cos  Note: Horizontal axis is -|cos  | (learning how to move stat box!) Capella Yee

3-Hit Tracks & Non-Prompt Signatures Probably need 5+1 layers for prompt track If we require 4 hits for non-prompt tracks, sensitive region for kinked tracks is very limited.

e.g.: Position-matching for isolated muons (mm) SCIPP algorithm for non-prompt tracks: match 3-hit seeds from tracker with stubs from calorimeter (developed by undergrads Meyer (  U. Chicago), Rice (  UC Irvine) Approximately 60% for 3-hit tracks in Z  qq events Being optimized for non-prompt recon- struction (GMSB signature) by undergraduates Stolp and Bogert. Non-Prompt Tracks and GMSB