DYNAMICS LAB · ENGINE01
DME-003
Across 500 simulations, local consensus among 50 agents reduced mean velocity dispersion from 4.86 in the noisy case (B) to 0.29 in scenario C. Removing observations in scenario D lowered coverage to 69.8% while leaving the underlying trajectories unchanged relative to B.
Study limits. These are results in abstract units produced by the simulator’s rules. They describe the tested assumptions rather than the behavior of real drones.
DME-003 · SIMULATED DATA
Computed 2026-11-06T10:26:06.753926+00:00 · reproducible scientific prototype
Measure scaling, collective statistics and reproducibility of an abstract stochastic multi-agent system.
{
"main_simulations": 500,
"robustness_simulations": 15,
"reproducibility_recalculations": 1,
"maximum_agents": 50,
"steps_per_main_run": 200,
"seed_replicates_per_configuration": 20
}| scenario | agents | replicates | velocity_dispersion_mean | observation_coverage | terminal_displacement_mean | centroid_displacement | observation_rmse |
|---|---|---|---|---|---|---|---|
| A | 1 | 20 | 0.0 | 1.0 | 41.870487 | 41.870487 | 1.411106 |
| A | 5 | 20 | 3.765396 | 1.0 | 50.675299 | 16.59906 | 1.410445 |
| A | 10 | 20 | 3.341888 | 1.0 | 47.478487 | 14.105822 | 1.415085 |
| A | 20 | 20 | 4.016579 | 1.0 | 50.073858 | 11.984433 | 1.415531 |
| A | 50 | 20 | 3.909306 | 1.0 | 49.413596 | 8.146317 | 1.416274 |
| B | 1 | 20 | 0.0 | 1.0 | 48.822249 | 48.822249 | 1.411106 |
| B | 5 | 20 | 4.386093 | 1.0 | 52.524302 | 19.085683 | 1.410445 |
| B | 10 | 20 | 4.079807 | 1.0 | 50.651062 | 16.383918 | 1.415085 |
| B | 20 | 20 | 4.981916 | 1.0 | 53.471046 | 12.565007 | 1.415531 |
| B | 50 | 20 | 4.855011 | 1.0 | 52.943239 | 8.968647 | 1.416274 |
| C | 1 | 20 | 0.0 | 1.0 | 48.822249 | 48.822249 | 1.411106 |
| C | 5 | 20 | 2.277782 | 1.0 | 38.626312 | 19.852833 | 1.410445 |
| C | 10 | 20 | 0.950429 | 1.0 | 25.781581 | 16.916832 | 1.415085 |
| C | 20 | 20 | 0.668383 | 1.0 | 20.777772 | 12.795076 | 1.415531 |
| C | 50 | 20 | 0.287159 | 1.0 | 12.081143 | 9.212947 | 1.416274 |
| D | 1 | 20 | 0.0 | 0.688806 | 48.822249 | 48.822249 | 1.40881 |
| D | 5 | 20 | 4.386093 | 0.694378 | 52.524302 | 19.085683 | 1.410351 |
| D | 10 | 20 | 4.079807 | 0.700224 | 50.651062 | 16.383918 | 1.41396 |
| D | 20 | 20 | 4.981916 | 0.700398 | 53.471046 | 12.565007 | 1.417139 |
| D | 50 | 20 | 4.855011 | 0.697881 | 52.943239 | 8.968647 | 1.416109 |
| E | 1 | 20 | 0.0 | 1.0 | 48.822249 | 48.822249 | 1.411106 |
| E | 5 | 20 | 3.082943 | 1.0 | 36.563589 | 15.73776 | 1.410445 |
| E | 10 | 20 | 2.32764 | 1.0 | 32.069244 | 11.548876 | 1.415085 |
| E | 20 | 20 | 2.64923 | 1.0 | 32.891587 | 9.192158 | 1.415531 |
| E | 50 | 20 | 2.681613 | 1.0 | 32.69384 | 6.955912 | 1.416274 |
# DME-003 — method
Kind: SIMULATED DATA. Algorithm: dme-simulation-1.0.
Five synthetic scenarios Aindependent/Bstochastic/Clocal velocity consensus/Dpartial observations/Eheterogeneous CV+CRW; N1/5/10/20/50×20seeds=500main runs. dt=.1s,200steps, q=noise²=.09, radius12abstract units, coupling.8, observationσ1, Dmissing.3. Synchronous consensus dv_i=κ(mean_neighbor(v)−v_i)dt; reflecting box±100, no targets or geography. Three separate RNG streams for process/measurement/missingness. Bootstrap resamples independent seeds. Sensitivity dt .05/.1/.2 at equal20s, noise .1/.3/.8, coupling0/.8/1.6, missing0/.3/.6. Observation cadence1/2/5 supplemental after first pilot. Same-seed replay byte checks strict scientific JSON. Timing excludes no work silently; run timing includes state recording/result assembly. Abstract results are not validated drone aerodynamics.
## Limits
- All values are synthetic abstract-system results, not real flights.
- Local velocity consensus and a reflecting box are defined mathematical rules, not validated aerodynamics.
- Different timesteps use equal physical duration but different stochastic discretizations; sensitivity is not a common-Brownian-path strong-convergence proof.
- Bootstrap intervals here resample independent simulation seeds, unlike temporal observations within real flights.
## Source
{
"source": "Dynamics mathematical/simulation core",
"license": "Apache-2.0 original generated synthetic data; no measured flights",
"actual_flight_data": false
}
# Reproduce DME-003
Use Python3.12 and the pinned lock. From the distribution root:
python -m dynamics.cli run DME-003 --data /your/local/dynamics-data
python -m dynamics.cli reproduce JOB_UUID --data /your/local/dynamics-data
The second command rehashes every acquired source object, reparses original selected ZIP bytes and recomputes mathematical results offline, with the original manifest parameters. Missing or altered cached bytes fail explicitly; a new download is a new acquisition, not substitution for an old vintage. The results_sha256 excludes measured execution timing but includes all scientific results and source identities. Public source packages do not contain multi-GB third-party archives. Dataset source availability may change. All seeds/parameters/dependency versions and source hashes are in the manifest.
Scientific result SHA-256: f154ddcdb4aebdec0a278e478fae39a500f3ee9383c4bfdcd1c20b63a9441a67. Numerical correctness is evaluated with independent controls and source replay; scientific validity remains bounded by source quality and model assumptions.
{
"source": "Dynamics mathematical/simulation core",
"license": "Apache-2.0 original generated synthetic data; no measured flights",
"actual_flight_data": false
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