Target particle control of smoke simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
User control over fluid simulations is a long-standing research problem in computer graphics. Applications in games and films often require recognizable creatures or objects formed from smoke, water, or flame. This paper describes a two-layer approach to the problem, in which a bulk velocity drives a particle system towards a target distribution, while simultaneously a vortex particle simulation adds recognizable fluid motion. A bulk velocity field is obtained by distributing target particles within a mesh, then matching control particles with target particles; control particles are given a trajectory bringing them to their targets, and a field is obtained by interpolating values from the control particles. A detail velocity field is obtained by traditional vortex particle simulation. We render the final particle system using stochastic shadow mapping. We spend some effort optimizing our processes for speed, obtaining simulations at interactive or near-interactive rates: from 70 to 500 milliseconds per frame depending on the configuration.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it