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Record W2912378491 · doi:10.3390/app9030474

Quantum Bits with Macroscopic Topologically Protected States in Semiconductor Devices

2019· article· en· W2912378491 on OpenAlexafffund
Błażej Jaworowski, Paweł Hawrylak

Bibliographic record

VenueApplied Sciences · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaNarodowe Centrum NaukiUniversity of Ottawa
KeywordsPhysicsQuantum decoherenceQuasiparticleQuantum mechanicsQubitSpin (aerodynamics)Condensed matter physicsSemiconductorSpinsQuantumSuperconductivity

Abstract

fetched live from OpenAlex

Current computers are made of semiconductors. Semiconductor technology enables realization of microscopic quantum bits based on electron spins of individual electrons localized by gates in field effect transistors. This results in very fragile quantum processors prone to decoherence. Here, we discuss an alternative approach to constructing qubits using macroscopic and topologically protected states realized in semiconductor devices. First, we discuss a synthetic spin-1 chain realized in an array of quantum dots in a semiconductor nanowire or in a field effect transitor. A synthetic spin-1 chain is characterized by two effective edge quasiparticles with spin 1 / 2 protected from decoherence by topology and Haldane gap. The spin-1 / 2 quasiparticles of Haldane phase form the basis of a macroscopic singlet-triplet qubit. We compare the spin one chain with a Kitaev chain. Its edge states are Majorana zero modes, possessing non-Abelian fractional statistics. They can be used to encode the quantum information using the braiding processes, i.e., encircling one particle by another, which do not depend on the details of the particle trajectory and thus are protected from decoherence.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.999

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)0.0020.000

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 head0.015
GPT teacher head0.246
Teacher spread0.232 · 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 designTheoretical or conceptual
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

Citations9
Published2019
Admission routes2
Has abstractyes

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