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Record W4405425610 · doi:10.1038/s41467-025-60305-3

Plasmon mode engineering with electrons on helium

2025· preprint· en· W4405425610 on OpenAlexaff
Camille A. Mikolas, N. R. Beysengulov, Austin Schleusner, D. G. Rees, C. Undershute, J. Pollanen

Bibliographic record

VenueNature Communications · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum, superfluid, helium dynamics
Canadian institutionsPQ Corporation (Canada)
FundersCollege of Engineering, Michigan State UniversityDivision of Materials ResearchMichigan State UniversityNational Science Foundation
KeywordsPlasmonHeliumElectronMode (computer interface)PhysicsAtomic physicsEngineering physicsOptoelectronicsComputer scienceNuclear physics

Abstract

fetched live from OpenAlex

An ensemble of electrons trapped above superfluid helium offers a paradigm system for investigating and controlling collective charge dynamics in low-dimensional electronic matter. Of particular interest is the ability to spatially control and engineer surface plasmons for integration with hybrid quantum systems and circuit quantum electrodynamic device architectures. Here we present experiments using an electron-on-helium microchannel device that hosts microwave-frequency plasmons, generated via local microwave excitation in an electrostatically defined central channel. By precisely varying the electron density, we demonstrate tunability of plasmon mode frequencies over several GHz. Additionally, we find that the power dependence of these modes can be used to investigate both homogeneous and inhomogeneous sources of spectral broadening. These results demonstrate the versatility of electrons on helium for probing collective excitations in low-dimensional Coulomb liquids and solids, and demonstrate a path for integrating engineered plasmons in electrons on helium with hybrid circuit quantum electrodynamic systems. Trapping electrons on a superfluid helium surface provides access to collective quantum phenomena and a platform for circuit quantum electrodynamics (cQED). Here, the authors demonstrate precision spatial and frequency engineering of plasmonic modes in a hybrid electron-on-helium system, opening the door towards integration of plasmon physics within future cQED-like devices.

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), Research integrity
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 score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.006
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 head0.007
GPT teacher head0.275
Teacher spread0.267 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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