GRAPH — an readout ASIC for large MCP based detectors

Abstract We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

Authors

Institutions

Publication Details

Journal
Journal of Instrumentation
Published
2025-01-01
DOI
https://doi.org/10.1088/1748-0221/20/01/t01001
Citations
2
Primary Topic
Particle Detector Development and Performance
Type
article
Field-Weighted Citation Impact
3.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GRAPH — an readout ASIC for large MCP based detectors

A. Seljak, John V. Vallerga, G. Varner, Gang Liu et al.
2 citations
Journal of Instrumentation
Particle Detector Development and Performance
3.74
article

GRAPH — an readout ASIC for large MCP based detectors

A. Seljak, John V. Vallerga, G. Varner, Gang Liu, Rick Raffanti
article en
2 citations

Abstract

Abstract We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

Journal of InstrumentationVol. 20(01)
SLAC National Accelerator Laboratory (US), Jožef Stefan Institute (SI), IS Instruments (United Kingdom) (GB), University of California, Berkeley (US)
Affordable and clean energy
Openalex Percentile: Top 10%
Particle Detector Development and Performance
3.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.