Dark plasmas in the nonlinear regime: Constraints from particle-in-cell simulations
Bibliographic record
Abstract
If the dark sector possesses long-range self-interactions, these interactions can source dramatic collective instabilities even in astrophysical settings where the collisional mean free path is long. Here, we focus on the specific case of dark matter halos composed of a dark <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mrow> <a:mi>U</a:mi> <a:mo stretchy="false">(</a:mo> <a:mn>1</a:mn> <a:mo stretchy="false">)</a:mo> </a:mrow> </a:math> gauge sector undergoing a dissociative cluster merger. We study this by performing the first dedicated particle-in-cell plasma simulations of interacting dark matter streams, tracking the growth, formation, and saturation of instabilities through both the linear and nonlinear regimes. We find that these instabilities give rise to local (dark) electromagnetic inhomogeneities that serve as scattering sites, inducing an effective dynamic collisional cross section. Mapping this effective cross section onto existing results from large-scale simulations of the Bullet Cluster, we extend the limit on the dark charge-to-mass ratio by over 10 orders of magnitude. Our results serve as a simple example of the rich phenomenology that may arise in a dark sector with long-range interactions and motivate future dedicated study of such “dark plasmas.”
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".