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Record W3045694437 · doi:10.3847/1538-4357/ac0627

Revisiting Dynamical Friction: The Role of Global Modes and Local Wakes

2021· article· en· W3045694437 on OpenAlexaff
Tomas Tamfal, Lucio Mayer, Thomas Quinn, Pedro R. Capelo, Stelios Kazantzidis, Arif Babul, D. Potter

Bibliographic record

VenueThe Astrophysical Journal · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsDynamical frictionAstrophysicsGalaxyGlobular clusterDark matterAstronomyDwarf galaxyMilky WayOrbital decayLocal GroupDark matter haloHaloDragGalaxy formation and evolutionSatellite

Abstract

fetched live from OpenAlex

Abstract The orbital decay of a perturber within a larger system plays a key role in the dynamics of many astrophysical systems—from nuclear star clusters or globular clusters in galaxies, to massive black holes in galactic nuclei, to dwarf galaxy satellites within the dark matter halos of more massive galaxies. For many decades, there have been various attempts to determine the underlying physics and timescales of the drag mechanism, ranging from the local dynamical friction approach to descriptions based on the back-reaction of global modes induced in the background system. We present ultra-high-resolution N-body simulations of massive satellites orbiting a Milky Way-like galaxy (with > 108 particles), that appear to capture both the local “wake” and the global “mode” induced in the primary halo. We address directly the mechanism of orbital decay from the combined action of local and global perturbations and specifically analyze where the bulk of the torque originates.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.202
Teacher spread0.198 · 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 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

Citations30
Published2021
Admission routes1
Has abstractyes

Explore more

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