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A 3D Photon-to-Digital Converter Readout for Low-Power and Large-Area Applications

2024· preprint· en· W4398132881 on OpenAlexaff
T. Rossignol, N. Roy, Samuel Parent, Serge A. Charlebois, J.‐F. Pratte

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsPower (physics)PhotonAnalog-to-digital converterUltra low powerPhysicsComputer scienceElectrical engineeringElectronic engineeringOpticsEngineeringPower consumptionVoltage

Abstract

fetched live from OpenAlex

The new trend in large area noble liquid experiments is to measure the scintillation light with photodetectors and their electronics inside the active volume. Compared to the typical approach of using silicon photomultipliers (SiPM) with the analog readout chain to an analog-todigital converter, this paper presents a new 3D photon-to-digital converter (PDC) readout that takes advantage of the binary nature of the single-photon avalanche diode. The readout contains 4096 pixels over 25 mm 2 , each including a 3D bonding pad and a quenching circuit. The readout features three different outputs : a fast flag to get the timestamp of each event from an external time-to-digital converter, a digital sum to retrieve the number of pixels triggered during an event and an analog monitor to generate an analog SiPM-like output. The analog monitor is also used to validate the two former digital outputs. The readout also includes 61 2D CMOS SPADs for validation purpose prior to the final 3D integration with a Teledyne DALSA custom SPAD array. As a first system integration toward large-area detector applications, a mini-tile of 2 × 2 readouts has been developed to test all the functionalities. The measured single-photon timing resolution ranges from 72 to 93 ps FWHM across the mini-tile SPAD channels population (i.e. 4 × 61 channels). The flag timing resolution is below 95 ps RMS, which includes the contribution of the optimized flag H-tree with an additional trigger tree to replace the 3D SPAD array for 2D testing. Once bonded with the 3D SPADs, the trigger tree won't be required to measure the flag timing resolution. With the removed contribution of the trigger tree, the estimated flag timing resolution should be below 45 ps RMS. The benefits of the digital sum output depend on the application, and this paper focuses on two cases. First, a low-power coincidence scheme for the nEXO liquid xenon experiment, leading to a power consumption as low as 140 µW per PDC. On the other hand, with a finer sampling mode of the scintillation light for pulse shape discrimination in liquid argon, the power consumption remains below 100 µW per PDC. Overall, this readout is designed as a replacement for a typical analog SiPM chain, without any compromise on the performances.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.225
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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