Network Lab
Upload, analyze, visualize, and learn in one place
A structured lab workspace with gated plans, synthetic graph generation, curated datasets, and sandbox modules that bridge classical + quantum workflows.
Upload → Validate → Run
Upload CSV/GraphML, validate via Lambda, then push classical or quantum jobs with receipts.
Go →Synthetic generator
Erdős–Rényi, BA, WS, SBM, and LFR presets with safe defaults and seeded runs.
Go →Curated datasets
Research-grade, documented datasets with ready-to-run configs and schema previews.
Go →Sandbox
Single- and multi-qubit learning modules with QUBO/QAOA playgrounds and badges.
Go →Results + provenance
Job status, metrics, and artifacts with download links and (future) QTL receipts.
Go →Progress
Badges, certificates, and leaderboard-ready stats for Basic/Pro/Org plans.
Go →Plan gating
basic
basic
- Uploads
- 50 KB (≤ 1k edges)
- Sandbox
- Single-qubit sandbox
- Extras
- Classical jobs only
- Small graph generator presets
- No saved projects
pro
pro
- Uploads
- 5 MB (≤ 100k edges (pre-filtered))
- Sandbox
- Single + Multi-qubit sandbox
- Extras
- Quantum queued runs
- Private saved projects
- API tokens (coming soon)
org
org
- Uploads
- 50 MB (Priority queue, higher limits)
- Sandbox
- All sandboxes + team workspace
- Extras
- Governance exports
- Org leaderboard
- Budget controls
Generator presets
Synthetic graphs in one click
er
Erdős–Rényi
Random graphs for quick smoke tests and validator checks.
Params: n, p
ba
Barabási–Albert
Scale-free graphs for resilience and hub behavior.
Params: n, m
ws
Watts–Strogatz
Small-world graphs for community + pathfinding tests.
Params: n, k, β
sbm
Stochastic Block Model
Community-rich graphs for modularity/QUBO tuning.
Params: blocks, sizes, P matrix
lfr
LFR Benchmark
Realistic community structure for performance drills.
Params: n, τ₁, τ₂, μ, k̄