evidence
Research
Researching Hidden Computational Instability.
Convia combines systems research, reproducible validation, runtime metrics, and mathematical programs to study how structural instability emerges — and how computational order can be restored.
Research areas
Scientific, experimental, reproducible.
Structural Runtime Research
- Structural Instability
- Execution Variability
- Recomputation Analysis
Coordination & Stabilization
- Distributed Coordination
- Execution Control Architecture
- Computational Order Restoration
Validation
The research page shows actual validation surfaces.
The public Argus validation protocol records concrete runtime metrics and execution context rather than relying on philosophical claims alone.
Benchmark protocol
seed, steps, repeat count, warmup steps, workload nodes, requests per step
Argus config example
Runtime environment checks
cpu_load_percent, memory_usage_percent, gpu_temperature, gpu_utilization
Argus reliability checks
Observation record
metrics.json, report.md, run_meta.json, and optional sanitized execution exports
Argus output package
Validation evidence
Observing execution variance across repeated runs.
By tracking identical workloads across multiple runs, Argus reveals the underlying environmental noise, migration propagation, and structural instability that raw performance metrics obscure.
repeated-run variance plotmigration propagation heatmap
run 01
run 02
run 03
run 04
evidence
Migration propagation
evidence
Runtime fluctuation
Metrics
Benchmark dimensions are explicit.
Execution VarianceRetry AmplificationRecomputation RatioStructural Stability ScoreMigration PropagationP95 latencyP99 latencyThroughputMigration countRetry countInvalidation countError rateOOM countDeadlock countCrash countPeak memoryAverage memory
argus_config.yaml
seed: 42
steps: 500
repeat_count: 5
warmup_steps: 20
ricci: [off, on]
workload:
nodes: 8
requests_per_step: 128Papers
Mathematical program records.
Convia Mathematical Program explores mathematical approaches to structure, instability, regularization, and computational order.
Convia Mathematical Program I
Ricci–Schrödinger Correspondence (RSC) and the Hodge Problem
Programmatic research exploring flow-based structural regularization and instability reduction through coupled geometric systems.
Record: 10.5281/zenodo.17575221
Convia Mathematical Program II
High-Probability Region Restriction for Cost Reduction
Research exploring probabilistic restriction methods for reducing structural computational overhead under uncertainty.
Record: zenodo.org/records/17932569
Source