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Record W937627311

Development and implementation of the trigger system for the INO-ICAL detector

2016· dissertation· en· W937627311 on OpenAlexaboutno aff
Sudeshna Dasgupta

Bibliographic record

VenueINFLIBNET · 2016
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsnot available
Fundersnot available
KeywordsNeutrinoPhysicsNeutrino oscillationNuclear physicsNeutrino detectorSolar neutrinoParticle physicsSolar neutrino problemObservatoryMuonMeasurements of neutrino speedAstronomy
DOInot available

Abstract

fetched live from OpenAlex

The elusive neutrino has always perplexed the scientific community. The desperate attempt by Pauli in postulating its existence, followed by experimental discovery, to save the laws of conservation of energy and momentum in nuclear -decay, bear testimony to this fact. Subse- quent experiments like, Homestake, Sudbury Neutrino Observatory (SNO), Super-Kamiokande and KamLAND, have studied neutrinos produced in the Sun, those originating from cosmic ray interactions in the Earth’s atmosphere and also those generated in nuclear reactors. Results from such pioneering experiments provide concrete evidence in support of neutrino mass through the detection of neutrino oscil- lations. This serves as the first indication of the Physics beyond the Standard Model. Neutrino has also emerged as an excellent probe in comprehending the underlying laws of nature in particle physics, nuclear physics, astronomy and cosmology. As a natural consequence, further experiments, armed with technological superiority, are being pursued world-wide to explore this particle of interest. In this context, a multi-institutional venture, called the India-based Neutrino Observatory (INO), has been initiated in India to participate in this exciting area of experimental particle physics by building a world-class underground facility for studying neutrinos. The INO collaboration has proposed to build a 50 kton magnetized Iron Calorimeter (ICAL) detector to study atmospheric neutrinos and to make precision measurements of the neutrino oscillation parame- ters. The detector will mostly look for muon neutrino induced charged current interactions using magnetized iron as the target mass and around 28 , 800 Resistive Plate Chambers (RPCs) as sensitive detector elements. A magnetic field of 1 . 3 T will be used to discriminate be- tween neutrino and anti-neutrino interactions, which equips the ICAL detector with the unique capability of determining the neutrino mass hierarchy. The detector is also envisaged as a future far detector for a neutrino factory beam. The extremely low rate of neutrino interactions necessitates the trigger scheme for such an experiment to achieve an optimization of the detection efficiency of the desired events and the chance trigger rates. It should also ensure feasibility of hardware implementation considering the vast volume of the detector. The development, vali- dation and implementation of the ICAL trigger system, which satisfy these criteria, are documented in this thesis. The design of the trigger scheme for the ICAL detector consists of a distributed and hierarchical architecture. The detector module is logically sub-divided into identical segments for the purpose of trigger generation. The segment dimensions are chosen considering the expected hit pattern of the events of interest, the associated chance trigger rates and the feasibility of implementation. Pre-trigger signals produced at the RPC level are combined together to generate a local trigger at the segment level, which in turn initiates a global trigger signal to invoke the data acquisition system to record the event data. The associated chance trigger rates have been calculated for different segment dimensions and for different sets of trigger criteria and are found to be negligible for an optimal combination of the trigger parameters. A simulation framework is developed to estimate the trigger efficiency of the scheme for the events of interest for the ICAL detector. The results ensure that substantially high detection efficiency can be obtained for the desired events under the proposed trigger scheme. The hardware implementation of the trigger scheme is initiated by designing an FPGA-based trigger module using the look-up table based technique. The module has delivered satisfactory performance in the prototype detector with negligible spurious trigger rate and trig- ger inefficiency. This ensures that such technique can be successfully and reliably employed in designing the ICAL trigger system. The overall layout for the implementation of the proposed trigger scheme for the ICAL detector has been devised and the trigger latency is estimated. A study is undertaken to ascertain the reliability of LVDS standard in transmitting the trigger signals for the ICAL detector. A technique for calibrating the delay offsets associated with the return- path of the trigger signal is proposed. The designs of the trigger boards are conceived and appropriate design components have been selected. The work reported here has thus facilitated the evolution of the ICAL trigger system from the conceptual stage up to the board-level design. The thesis is proposed to comprise six chapters. Chapter 1 contains a brief history of neutrino and its salient features. The major experi- ments that have been carried out for the detection and understanding of this fundamental particle are reviewed. The physics potential of the ICAL detector, proposed to be built by the INO collaboration, is sum- marized. Chapter 2 describes the architecture of the proposed trigger scheme for the ICAL detector and its validation results. The design of an FPGA-based trigger module for the ICAL prototype detector and its performance validation are discussed in Chapter 3 . Chapter 4 illustrates the overall layout for the hardware implementation of the trigger system for the ICAL detector. Chapter 5 deals with the con- ceptual designs of the trigger boards proposed to constitute the ICAL trigger system. The work is finally summarized and the future scope is discussed in Chapter 6 . The publications produced as the outcome of this work, which include peer-reviewed research articles, conference proceedings and technical notes, are listed in Appendix A.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.294

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 head0.018
GPT teacher head0.333
Teacher spread0.315 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

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