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Quantum Simulation of the Bosonic Creutz Ladder with a Parametric Cavity

2021· article· en· W3119116774 on OpenAlexafffund
Jimmy S. C. Hung, Jamal Busnaina, C. W. Sandbo Chang, A. M. Vadiraj, Ibrahim Nsanzineza, E. Solano, Hadiseh Alaeian, E. Rico, C. M. Wilson

Bibliographic record

VenuePhysical Review Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum and electron transport phenomena
Canadian institutionsUniversity of Waterloo
FundersH2020 Future and Emerging TechnologiesOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundMinisterio de Economía y CompetitividadEusko JaurlaritzaFederación Española de Enfermedades RarasBaden-Württemberg StiftungCanada Foundation for InnovationPurdue University
KeywordsQuantum simulatorPhysicsLattice (music)QuantumScalabilityHamiltonian (control theory)Parametric statisticsTopology (electrical circuits)Statistical physicsQuantum mechanicsQuantum computerComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

There has been a growing interest in realizing quantum simulators for physical systems where perturbative methods are ineffective. The scalability and flexibility of circuit quantum electrodynamics make it a promising platform for implementing various types of simulators, including lattice models of strongly coupled field theories. Here, we use a multimode superconducting parametric cavity as a hardware-efficient analog quantum simulator, realizing a lattice in synthetic dimensions with complex hopping interactions. The coupling graph, i.e., the realized model, can be programmed in situ. The complex-valued hopping interaction further allows us to simulate, for instance, gauge potentials and topological models. As a demonstration, we simulate a plaquette of the bosonic Creutz ladder. We characterize the lattice with scattering measurements, reconstructing the experimental Hamiltonian and observing important precursors of topological features including nonreciprocal transport and Aharonov-Bohm caging. This platform can be easily extended to larger lattices and different models involving other interactions.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.341

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 studies0.0000.000
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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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 designObservational
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

Citations54
Published2021
Admission routes2
Has abstractyes

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