II.
Workflow overview
Reference · liveworkflow:computational-experiment-validation
Computational Experiment Validation overview
Validates computational physics experiments for reproducibility and correctness -- verifying numerical method convergence (mesh/timestep independence), checking conservation law satisfaction, comparing against analytical solutions or benchmark datasets, auditing random number generator seeding strategy, confirming parallel decomposition does not introduce non-determinism, and archiving environment snapshots for long-term reproducibility. Excludes experiment design.
Attributes
displayName
Computational Experiment Validation
workflowKind
governance
triggerType
event-driven
typicalCadence
per-experiment
complexity
single-team
description
Validates computational physics experiments for reproducibility and
correctness -- verifying numerical method convergence (mesh/timestep
independence), checking conservation law satisfaction, comparing
against analytical solutions or benchmark datasets, auditing random
number generator seeding strategy, confirming parallel decomposition
does not introduce non-determinism, and archiving environment
snapshots for long-term reproducibility. Excludes experiment design.
Outgoing edges
applies_to_domain2
- domain:physics·DomainPhysics
- domain:scientific-computing·DomainScientific Computing
involves_role3
- role:data-scientist·RoleData Scientist
- role:principal-engineer·RolePrincipal Engineer
- role:test-writer·RoleTest Writer
performed_by_org_unit2
- org-unit:research-engineering·OrgUnitResearch Engineering
- org-unit:ml-team·OrgUnitML Team
requires_skill_area2
- skill-area:python-data-pipelines·SkillAreaPython Data Pipelines
- skill-area:eval-driven-development·SkillAreaEval-Driven LLM Development
triggers_responsibility2
- responsibility:data-quality-monitoring·ResponsibilityData quality monitoring
- responsibility:review-architecture-changes·ResponsibilityReview architecture changes
Incoming edges
None.