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Record W3006451465

Design of a Real-Time Embedded Control System for Quantum Computing Experiments

2020· dissertation· en· W3006451465 on OpenAlexfundno aff
Richard Rademacher

Bibliographic record

VenueUWSpace (University of Waterloo) · 2020
Typedissertation
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsComputer scienceQuantum controlQuantum computerReal-time Control SystemControl (management)QuantumEmbedded systemPhysicsArtificial intelligenceQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

This thesis describes the design of a real-time control system for trapped ion quantum computer experiments. It is framed in the context of the QuantumIon project, a project at the University of Waterloo’s Institute for Quantum Computing that aims to provide a scalable, remote-operation ion trap for a wide variety of quantum research without the need for ‘expert’ ion-trap knowledge. The target users span the range of ion-trap researchers,algorithms researchers, performance benchmarking researchers, and quantum simulation researchers.The control system features a user programming language, remote access to a compiling server, a sub-nanosecond time sequencing engine, arbitrary waveform generation for pulse shaping, and fully adjustable internal parameters. This platform affords the user extraordinary flexibility for many research use cases without requiring physical access. High-speed precision timing is achieved through the use of FPGA technology, while internal consistency (necessary for usability by non-experts) is achieved through an abstraction layer approach. Supercomputing-grade network infrastructure is employed to meet the strict timing requirements. An extensive suite of calibration tools and results is available to monitor machine-dependent parameters of the experiment. A sophisticated symbolic algebra system is used to create powerful calculations of precision timing sequences. Extensive automation is employed to remove the need for physical access, thus providing quantum computing to a wide audience. Under this model even the lowest-level control is avail-able to support innovative new designs, while a “library” of pre-defined sequences is also available to leverage “best practice” gates for those wishing rapid results. Finally, the user language itself is designed to be portable, allowing bindings to current popular classical languages such as Matlab and Python, and can be expanded for use in quantum-specific languages such as Cirq, Quill, and QASM .Through this approach the control system for QuantumIon is a flexible, powerful, scalable, and robust platform that is expected to be in use for a long time

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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