UNCERTAINTY · ALGORITHM ARENA · 3D BIOLOGICAL OUTCOMES

Immersive Simulation Lab

Explore thousands of synthetic transport missions across five control strategies. Rotate the 3D cell atlas, inspect uncertainty envelopes, compare Pareto trade-offs, and reveal which algorithm remains resilient when faults combine.

● CHECKING AXION

Monte Carlo trials

Fault severity70%

Uncertainty distribution

Random seed

3D selected algorithm

Waiting to run0 / 0 paired trials

Each trial will be shared by every selected controller.

Run ID—

Scenarios generated0

Controller evaluations0

Throughput—

Scenario × algorithm runs0

Highest rescue probability—

Best fifth-percentile readiness—

Pareto-efficient algorithms—

Rotating 3D scRNA Cell Atlas

drag to rotate · scroll to zoom

T cellsMyeloid EpithelialStromal

Cells retained—

Cluster separation—

Stress burden—

Quality entropy—

3D Failure-Risk Landscape

drag to rotate · hover surface · cooling × bias × risk

Compare wireframe:

Low risk 0.00Guard threshold 0.55Critical ≥0.72

Peak risk—

Mean risk—

Safe operating volume—

Risk reduction vs baseline—

Run a simulation to build the risk interpretation.

3D Molecular Integrity & Gene-Evolution Twin

synthetic molecular projection · controller-linked stress trajectory

INITIAL MOLECULAR STATE

Selected controller PID counterfactualDamage / fragmentation Preserved expression

Molecular integrity—

Projected strand breaks—

RNA integrity proxy—

Transcript capture—

Move the mission timeline to inspect projected molecular degradation.

Scientific boundary: this is a controller-linked digital-twin projection—not measured DNA damage, mutation calling, RNA velocity, or clinical evidence. scRNA-seq more directly reflects RNA integrity and cell-state preservation than DNA mutations.

Monte Carlo Uncertainty Fan

median with 5–95% readiness envelope

Multi-objective Radar

normalized score

Pareto Frontier

quality ↑ · energy ↓

Failure Resilience Heatmap

rescue probability

Parallel Coordinates

every line is an algorithm

Outcome Distribution

readiness histogram · selected algorithm

Monte Carlo Convergence

running rescue probability with 95% Wilson interval

Paired-Trial Audit Stream

one fingerprint = one identical fault mission evaluated by every controller

Audit fingerprints will appear while the run executes.

Algorithm Evidence Table

Algorithm	Success	Mean readiness	P5 readiness	Energy	Recovery	Robustness

Scientific interpretation

PID reacts to current error. LQR optimizes a quadratic state/control objective. Fixed MPC predicts ahead with an unchanged model. Adaptive MPC updates process effectiveness online. Robust BioLoop adds conservative uncertainty handling and an independent safety shield.

All biological and sequencing outcomes in this browser lab are synthetic projections for algorithm exploration. Native C++ Monte Carlo evidence is generated separately by the included executable.

Common random numbers ONSuccess threshold 80% Confidence 95% WilsonRuntime — Seed —