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Record W4395444214 · doi:10.1126/science.ado8069

Squeezing the quantum noise of a gravitational-wave detector below the standard quantum limit

2024· preprint· en· W4395444214 on OpenAlexaff
Wenxuan Jia, Victoria Xu, K. Kuns, Masayuki Nakano, L. Barsotti, M. Evans, N. Mavalvala, Rich Abbott, I. Abouelfettouh, R. X. Adhikari, A. Ananyeva, Stephen Appert, K. Arai, N. Aritomi, Stuart Aston, M. Ball, S. Ballmer, David Barker, B. K. Berger, J. Betzwieser, D. Bhattacharjee, G. Billingsley, N. Bode, E. Bonilla, V. Bossilkov, A. Branch, A. F. Brooks, Daniel D. Brown, John Bryant, C. Cahillane, Huy-tuong Cao, E. Capote, Yanbei Chen, F. Clara, Josh N. Collins, C. M. Compton, R. Cottingham, D. C. Coyne, Ryan Crouch, J. Csizmazia, L. P. Dartez, Nicholas Demos, E. Dohmen, Jenne C. Driggers, S. E. Dwyer, A. Effler, A. Ejlli, T. Etzel, J. Feicht, Raymond Frey, W. Frischhertz, P. Fritschel, Valery Frolov, P. Fulda, M. Fyffe, D. Ganapathy, Bubba Gateley, Joe Giaime, Dwayne Giardina, Jane Glanzer, E. Goetz, A. W. Jones, Slawomir Gras, Corey Gray, D. Griffith, H. Grote, T. Guidry, E. D. Hall, Jonathan Hanks, J. Hanson, M. C. Heintze, A. F. Helmling-Cornell, H. Y. Huang, Yuki Inoue, A. L. James, A. Jennings, Srinath Karat, M. Kasprzack, K. Kawabe, N. Kijbunchoo, J. S. Kissel, A. Kontos, R. Kumar, M. Landry, B. Lantz, M. Laxen, H. K. Lee, M. Lesovsky, F. Llamas, Marc Lormand, Hudson A. Loughlin, R. Macas, M. MacInnis, B. Mannix, G. L. Mansell, R. M. Martin, Nyath Maxwell, G. McCarrol, R. McCarthy, D. E. McClelland, Scott McCormick, L. McCuller, T. McRae, F. Mera, E. L. Merilh, F. Meylahn, R. Mittleman, D. Moraru, Gerardo Moreno, Matthew Mould, A. Mullavey, T. J. N. Nelson, A. Neunzert, J. Oberling, T. O’Hanlon, C. Osthelder, D. J. Ottaway, H. Overmier, W. Parker, A. Pele, Huyên Pham, M. Pirello, V. Quetschke, K. E. Ramirez, Jonathan Reyes, J. W. Richardson, Mitchell B. Robinson, J. G. Rollins, Janeen H. Romie, M. P. Ross, Travis Sadecki, Anthony Sanchez, Eduardo Sanchez, Luis Sanchez, R. L. Savage, D. Schaetzl, M. G. Schiworski, Roman Schnabel, Robert Schofield, E. Schwartz, Danny Sellers, Thomas Shaffer, Ryan Short, D. Sigg, B. J. J. Slagmolen, S. Soni, L. Sun, D. B. Tanner, M. Thomas, P. Thomas, K. Thorne, Calum Torrie, G. Traylor, G. Vajente, J. Vanosky, A. Vecchio, P. J. Veitch, A. Vibhute, J. Warner, B. Weaver, C. Whittle, B. Willke, Christopher Wipf, Hiro Yamamoto, Haocun Yu, Liyuan Zhang, M. E. Zucker

Bibliographic record

VenueScience · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of British Columbia
FundersScience and Technology Facilities Council
KeywordsLIGOPhysicsQuantum limitGravitational waveNoise (video)DetectorQuantum noiseQuantumQuantum sensorUncertainty principleQuantum mechanicsQuantum technologyOpticsOpen quantum systemComputer science

Abstract

fetched live from OpenAlex

The Heisenberg uncertainty principle dictates that the position and momentum of an object cannot be simultaneously measured with arbitrary precision, giving rise to an apparent limitation known as the standard quantum limit (SQL). Gravitational-wave detectors use photons to continuously measure the positions of freely falling mirrors and so are affected by the SQL. We investigated the performance of the Laser Interferometer Gravitational-Wave Observatory (LIGO) after the experimental realization of frequency-dependent squeezing designed to surpass the SQL. For the LIGO Livingston detector, we found that the upgrade reduces quantum noise below the SQL by a maximum of three decibels between 35 and 75 hertz while achieving a broadband sensitivity improvement, increasing the overall detector sensitivity during astrophysical observations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.031
GPT teacher head0.347
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations76
Published2024
Admission routes1
Has abstractyes

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