Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 43 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 21 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 180 tok/s Pro
GPT OSS 120B 443 tok/s Pro
Claude Sonnet 4.5 32 tok/s Pro
2000 character limit reached

A low noise and low power cryogenic amplifier for single photoelectron sensitivity with large arrays of SiPMs (1911.06562v2)

Published 15 Nov 2019 in physics.ins-det

Abstract: This paper presents a low noise amplifier for large arrays of silicon photomultipliers (SiPMs) operated in cryogenic environments, especially liquid argon (87 K) and liquid nitrogen (77 K). The goal is for one amplifier to read out a total photosensitive surface of tens of cm$2$ while retaining the capability to resolve single photoelectron signals. Due to the large capacitance of SiPMs, typically a few nF per cm$2$, the main contributor to noise is the series (voltage) component. A silicon-germanium heterojunction bipolar transistor (HBT) was selected as the input device of the cryogenic amplifier, followed by a fully differential operational amplifier, operated in an unconventional feedback configuration. The input referred voltage noise of the circuit at 77 K is just below 0.4 nV/$\surd$Hz white (above 100 kHz) and 1 nV/$\surd$Hz at 10 kHz. The value of the base spreading resistance of the HBT at 77 K was determined from noise measurements at different bias currents. Power consumption of the full circuit is about 2.5 mW. The design gives the flexibility to optimally compensate the feedback loop for different values of the input capacitance, and obtain a gain-bandwidth product in the GHz range. The signal-to-noise ratio obtained in reading out SiPMs is discussed for the case of a 300 kHz low pass filter and compared with the upper limit that would derive from applying optimum filtering algorithms.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.