Scientific Agent Demonstrations

Real-world integration scenarios validating context orchestration for autonomous discovery at scale.

EarthScope Seismology

Real-time processing of distributed seismic networks. Multi-modal sensor fusion enables continental-scale anomaly detection and correlation.

▸ Detection Rate: 95%+ anomaly detection accuracy (projected)
▸ Correlation: Sub-second multi-site correlation
▸ Throughput: TB/day processing capacity
▸ Scale: Continental-scale sensor fusion

LAMMPS Molecular Dynamics

Simulation campaign orchestration at HPC scale. Intelligent context management enables faster convergence and higher resolution simulations.

▸ Scale: 10,000+ simulation runs orchestrated
▸ Convergence: 3-5x faster parameter space exploration
▸ Efficiency: 40% resource utilization improvement
▸ Checkpoints: 10x checkpoint efficiency
▸ MegaMmap: 20% faster, 2x resolution increase

ParaView Visualization

Intelligent CFD visualization with automated feature detection and multi-resolution rendering for large-scale datasets.

▸ Automation: Automated vortex detection and feature extraction
▸ Rendering: Multi-resolution adaptive rendering
▸ Correlation: Physics-aware visualization correlation
▸ Speedup: Hours → minutes for plot generation
Materials Discovery Demo

Materials Discovery

Hypothesis-driven exploration combining DFT calculations, molecular dynamics, and experimental validation for accelerated materials discovery.

▸ Integration: DFT + MD + experiments unified workflow
▸ Screening: 100x faster candidate screening (projected)
▸ Results: Novel alloys and energy materials discovered

Jarvis Deployment

Production infrastructure integration demonstrating real-world deployment with HPC schedulers, parallel file systems, and authentication systems.

▸ Integration: Slurm, Lustre, authentication systems
▸ Acceleration: RDMA acceleration enabled
▸ Storage: GPU Direct Storage support
▸ Memory: CXL memory pooling integration

Multi-Agent Discovery

Coordinated autonomous research workflow from literature review through simulation, analysis, visualization, and publication preparation.

▸ Workflow: Literature → simulation → analysis → visualization → publication
▸ Context: Shared context across all agents
▸ Coordination: Hierarchical agent coordination
▸ Autonomy: End-to-end autonomous discovery

Performance Metrics

Discovery Agents

10x

hypothesis generation rate

100x

parameter space coverage (projected)

95%+

anomaly detection accuracy (projected)

Simulation Agents

3-5x

faster convergence

40%

resource utilization improvement

10x

checkpoint efficiency

Analysis Agents

100x

processing speedup (projected)

99%+

quality preservation (projected)

50x

correlation efficiency (projected)

Workflow Agents

5-10x

faster completion

90%

less manual intervention

100%

provenance tracking