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Remote Blind State Preparation with Weak Coherent Pulses in the Field

2019· article· en· W2971468357 on OpenAlexafffund
Yang-Fan Jiang, Kejin Wei, Liang Huang, Ke Xu, Qi-Chao Sun, Yuzhe Zhang, Weijun Zhang, Hao Li, Lixing You, Zhen Wang, Hoi‐Kwong Lo, Feihu Xu, Qiang Zhang, Jian-Wei Pan

Bibliographic record

VenuePhysical Review Letters · 2019
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaOffice of Naval ResearchNational Natural Science Foundation of ChinaCanada Foundation for InnovationOntario Research Foundation
KeywordsComputer scienceQuantum computerQubitQuantum information scienceQuantum networkQuantum teleportationQuantum error correctionQuantum entanglementPhysicsQuantumQuantum mechanics

Abstract

fetched live from OpenAlex

Quantum computing has seen tremendous progress in past years. Due to implementation complexity and cost, the future path of quantum computation is strongly believed to delegate computational tasks to powerful quantum servers on the cloud. Universal blind quantum computing (UBQC) provides the protocol for the secure delegation of arbitrary quantum computations, and it has received significant attention. However, a great challenge in UBQC is how to transmit a quantum state over a long distance securely and reliably. Here, we solve this challenge by proposing a resource-efficient remote blind qubit preparation (RBQP) protocol, with weak coherent pulses for the client to produce, using a compact and low-cost laser. We experimentally verify a key step of RBQP-quantum nondemolition measurement-in the field test over 100 km of fiber. Our experiment uses a quantum teleportation setup in the telecom wavelength and generates 1000 secure qubits with an average fidelity of (86.9±1.5)%, which exceeds the quantum no-cloning fidelity of equatorial qubit states. The results prove the feasibility of UBQC over long distances, and thus serves as a key milestone towards secure cloud quantum computing.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.234

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 head0.012
GPT teacher head0.293
Teacher spread0.281 · 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 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".

Quick stats

Citations23
Published2019
Admission routes2
Has abstractyes

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