Readout Electronics and Data Acquisition System of the MicroBooNE Experiment Bo Yu, substituting for Hucheng Chen On behalf of the MicroBooNE Collaboration May 12th, 2009

2009 IEEE Real Time Conference Outline MicroBooNE Experiment Liquid Argon Time Projection Chamber (LArTPC) Readout Electronics & DAQ System Readout Architecture Front-end Cryogenic Electronics Online Data Reduction in FPGA DAQ System Outlook & Summary DUSEL LArTPC 2009 IEEE Real Time Conference

MicroBooNE (Booster Neutron Experiment) A 70 ton fiducial volume LAr TPC on the Booster Neutrino Beamline (BNB) at FNAL Collaboration formed in 2007 10 univ+labs/50 phys+eng. Under design phase and DOE CD-1 later this year http://www-microboone.fnal.gov Low energy phenomena and excess observed by miniBooNE Precision measurements of “golden” nm CCQE channel: Possibility of CCQE measurements from intrinsic ne Background for oscillation searches: NCpo, photonuclear events 2.5m drift @ 500V/cm 3 Readout wire planes 2 induction planes (U,V at ±60°from vertical) 1 collection plane (vertical wires, 2.5m long) 30 PMTs for T0 determination Evacuable single vessel containment 3.8m ID, 12m long Readout based on “cold” preamplifiers JFET based discrete ~10,000 channels Warm feedthroughs Bi-phase purification system 2009 IEEE Real Time Conference

2009 IEEE Real Time Conference MicroBooNE On-axis BNB 8 GeV protons on Be target Focusing horn: p+, K+ Decay channel 50m 450m dirt 2-3x1020 POT/year 3-2 years running (6x1020 POT) Proposed MicroBooNE site Off-axis NUMI 110 mrad off NUMI target 4x1020 POT/year 2009 IEEE Real Time Conference

What is Liquid Argon Time Projection Chamber? Unique detectors, true “electronic” bubble-chambers High precision measurements combined in one technology Tracking and Imaging (voxel size limited by diffusion) Precision Calorimetry Particle Identification (dE/dx meas. on the collection wire plane) 2009 IEEE Real Time Conference

Why LAr TPC detectors for neutrino and nucleon decay physics? Neutrino Oscillation Physics Significantly more sensitive (~x6) than Water Cherenkov detectors (i.e. smaller volumes for same physics reach) More powerful background reduction ne Proton Decay Search Sensitive to other decay channels (e.g. p nK) Extend sensitivity beyond Super-K limits with >5kton detectors 2009 IEEE Real Time Conference

MicroBooNE Readout Electronics Cold Preamp. Motherboard JFET discrete quad preamplifier Intermediate Amplifier Board 2009 IEEE Real Time Conference TPC Readout Board

Cryogenic Front-End based on JFET Technology mature and available as of today Reliability issues requires a careful choice of component and high-reliability design and assembly Ceramic hybrid with co-fired traces and surface mount components properly tested Several years of experience Helios-NA34: 576 preamplifiers Operations: 4 years, multiple cool-downs Failure: 1 NA48: Preamplifiers in LAr: 13,000 Operated at very high electric field Failures: ~50 because of a HV accident in 1998. Negligible failures after that Always kept at cryogenic temperature Late 80’s 2008-2009 2009 IEEE Real Time Conference

Cryogenic Electronics Setup 2009 IEEE Real Time Conference

JFET Preamplifier Noise In JFETs majority carriers in the channel are electrons CARRIER FREEZOUT: Donor levels are ~40-50mV below band conduction, so a further reduction of temperature causes more and more electrons to fall in their donor energy levels. In CMOS the conducting channel in Enhancement mode is formed by inversion (energy band bending at the Si/SiO2 interfaces) At high doping concentrations mobility increases and reaches a max., then decreases due to impurity scattering as the temperature of the lattice is reduced compared to the electron temperature Bulk mobility increases as temperature is reduced. Transconductance also. 2009 IEEE Real Time Conference

2009 IEEE Real Time Conference Online Data Reduction Dual Running Modes Beam trigger mode A total of 4.8ms (1 full drift time before and 2 after the trigger) of data are recorded without data loss Supernova mode All data undergo lossy data reduction and are buffered for one hour awaiting a potential supernova alert from other sources Large Volume of Data ~10,000 readout channels Utilize high density multiple channel ADC (AD9222 - Octal, 12-bit) Each channel is digitized individually at 16MHz ~240GBytes/s instantaneous data throughput Data Reduction Online down-sampling Shaper – 1µs peaking time 16MHz ADC data down-sampled to 2MHz Lossless data reduction – Huffman coding Lossy data reduction – Dynamic decimation 2009 IEEE Real Time Conference

A Case Study – BO TPC Detector Slow variation of 5MHz raw data Difference between two consecutive samples calculated More than 99% differences are within -+3. Shorter codes (1-7 bits) are assigned to differences with higher probability (in this case -3 to +3) Any differences outside +-3 use 16 bits In typical events, coding rate is ~1.5 bits/sample U(n+1)-U(n) Count Probability (P) Code No. of bits (N) P*N -4 and others 11 0.000179124 Full 16 bits word 16 0.002866 -3 45 0.00073278 111110 6 0.004396 -2 358 0.005829669 1110 4 0.023318 -1 9681 0.157645335 10 2 0.315290 40867 0.665477935 1 0.665477 +1 10145 0.165201107 110 3 0.495603 +2 298 0.00485263 11110 5 0.024263 +3 8.142E-05 1111110 7 0.000569 total 1.00 1.53 2009 IEEE Real Time Conference

Huffman Coding (Lossless Compression) U(n+1)-U(n) Code -4 and others Full 16 bits word -3 000001 -2 0001 -1 01 1 +1 001 +2 00001 +3 0000001 Huffman codes are self-punctuated, i.e., an 1 is always the code end. We pack the Huffman codes into 16-bit data words for additional fault recovery ability at the cost of reduced compression efficiency. DD=0: 5M samples/s DD=1: (5/16) M samples/s Regular ADC data when U(n+1)-U(n) is outside +-3 DD ADC value (13-bit) Reserved 1 X Huffman Coded 1 1 1 1 1 1 1 -1 +1 +2 Padding or Continue to Next Word In this example, 6 differences of the data samples are packed in the 16-bit data word. 2009 IEEE Real Time Conference

Dynamic Decimation (Lossy Compression) 5MHz raw data (5/16)MHz dyn. dec. Only small time intervals must be sampled at 5MHz Most time intervals can be sampled with lower frequency, e.g., (5/16)MHz without losing useful information. (These wire*time areas are marked with lighter color in the lower left picture) 2009 IEEE Real Time Conference

Dynamic Decimation & Huffman Coding Dynamic Decimation reduces number of samples by factor of 10. Huffman Coding reduces number of bits from raw data by factor of 10. When cascaded, the combination reduces number of bits by factor of 60. Dynamic Decimation Huffman Coding N N/10.6 N/60 N/10.7 The blocks for dynamic decimation and Huffman coding have been test designed, compiled and simulated at 250 MHz in an Altera Cyclone III FPGA device The logic element usage of these two blocks is very small compared to available resources in FPGA (217+245 out of 39600) Device: EP3C40F484C6, $129, 39600 Logic Elements Available Logic Element Usage Dynamic Decimation 217 Huffman Coding 245 2009 IEEE Real Time Conference

MicroBooNE DAQ System Architecture Inside Crate 16 Front End Modules (FEM) 1 or 2 Transmit Module (XMIT) Dataway on custom backplane Dataway The XMIT module initiates the token passing FEM receives token, passes data to the dataway FEM sends token to next one when it has no more data to transmit Dataway could run at 640MBytes/sec for deadtimeless readout SEB (sub event buffer) Off the shelf PC Data buffer, data checking, error handling etc. Optical receiver module Two 3.125Gbps optical links, can service two crates PCI Express 4 lanes plug in card, 10Gbps throughput DMA operation to send data to memory 2009 IEEE Real Time Conference

Dead Time Less Front End Module FEM Designed to take both beam trigger event and supernova data Organize ADC data as frames Data is written in time order, read in channel order to improve data reduction efficiency Grouping/processing of the frame depend on whether it is beam trigger event or not Data Flow Processed events flow to the PC in separate paths Two separate token passing dataways to separate the traffic flow Keep neutrino and supernova events flow as independent as possible 2009 IEEE Real Time Conference

Beyond MicroBooNE: DUSEL 2009 IEEE Real Time Conference

Beyond MicroBooNE: CMOS Cold Electronics R&D Operating at LAr temperatures (~90K) Multiplexed architecture Multiplexing may be performed in two steps, analog and digital, at appropriate locations within the cryostat MUX>100 With highly multiplexed readout, cost vs. channel count curve flattens Low noise, low power Performance characterization as function of T of existing processes Develop models for cryogenic operation to be used for subsequent design optimization 2009 IEEE Real Time Conference

2009 IEEE Real Time Conference Summary LArTPC is a promising detector technology for neutrino long baseline experiments and nucleon decay searches Cryogenic electronics, closed to the detector elements is critical to ease scaling issues MicroBooNE will be the first running neutrino experiment to use a specific implementation of cryogenic front-end JFET preamplifiers have been characterized in temperature and perform as expected A strong R&D program to develop a low noise, low power ASIC with high multiplexing factor is required and has just started MicroBooNE readout electronics and DAQ system Readout architecture and data flow are well defined to accommodate the different running modes Many electronics parts have been prototyped Data reduction techniques in FPGA are actively studied 2009 IEEE Real Time Conference

MicroBooNE JFET Preamplifier 2009 IEEE Real Time Conference