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Record W3010517341 · doi:10.1109/tns.2020.3043671

ADC Nonlinearity Correction for the Majorana Demonstrator

2020· article· en· W3010517341 on OpenAlexaff
N. Abgrall, J. M. Allmond, I. J. Arnquist, F. T. Avignone, A. S. Barabash, C. J. Barton, F. E. Bertrand, B. Bos, M. Busch, M. Buuck, T. S. Caldwell, C. M. Campbell, Y-D. Chan, C. D. Christofferson, P.-H. Chu, Michael Clark, H. L. Crawford, C. Cuesta, J. A. Detwiler, A. Drobizhev, D. W. Edwins, Yu. Efremenko, H. Ejiri, S. R. Elliott, T. Gilliss, G. K. Giovanetti, M. P. Green, J. Gruszko, I. S. Guinn, V. E. Guiseppe, C. R. Haufe, R. J. Hegedus, R. Henning, D. Hervas Aguilar, E. W. Hoppe, A. Hostiuc, M. F. Kidd, I. Kim, R. T. Kouzes, A.M. Lopez, J. M. López-Castaño, E. L. Martín, R. D. Martin, R. Massarczyk, S. J. Meijer, S. Mertens, J. Myslik, T. K. Oli, G. Othman, W. Pettus, A. W. P. Poon, D. C. Radford, J. Rager, A. L. Reine, K. Rielage, N. W. Ruof, M. J. Stortini, D. Tedeschi, R. L. Varner, S. Vasilyev, B. R. White, J. F. Wilkerson, C. Wiseman, W. Xu, C.-H. Yu, B. X. Zhu, B. Shanks

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMAJORANADigitizationWaveformPhysicsDynamic rangeSIGNAL (programming language)Flash ADCRange (aeronautics)Integral nonlinearityNonlinear systemComputer scienceElectronic engineeringNuclear physicsOpticsConvertersEngineeringNeutrinoVoltageQuantum mechanicsTelecommunications

Abstract

fetched live from OpenAlex

Imperfections in analog-to-digital conversion (ADC) cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the Majorana Demonstrator <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">76</sup> Ge neutrinoless double-beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearities. A simple measurement protocol was developed that did not require sophisticated equipment or lengthy data-taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearities by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.033
GPT teacher head0.294
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

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