The week combines introductory lectures, hands-on challenge work, daily mentoring, and a final plenary synthesis session. The rhythm is designed to alternate between shared learning and focused team work.
Program table
Sunday 11 October — Arrival (optional)
| Time | Activity |
|---|---|
| Afternoon / Evening | Participant arrival and check-in |
| Evening | Informal welcome, logistics briefing (Jean-Zay accounts, data access policies) |
| Evening | Ice-breaker with resident artists — visual identity kick-off |
Monday 12 October — Day 1: Common Ground & Problem Setting
| Time | Activity |
|---|---|
| Morning (plenary) | Lecture 1 — Accelerators as AI systems: beam dynamics, collective effects, diagnostics, controls — where ML already works and where it fails |
| Morning (plenary) | Lecture 2 — ML methods for scientific systems: surrogates, uncertainty quantification, physics-informed learning, anomaly detection in non-stationary systems |
| Morning (plenary) | Lecture 3 — HPC & AI at scale (Jean-Zay): interactive workflows, data management, best practices |
| Afternoon | Presentation of the three challenges: datasets, metrics, baselines |
| Afternoon | Team formation — 3 groups × 2 teams (contrasting approaches) |
| Afternoon | Hands-on: environment setup, first data exploration, baseline runs |
| Evening | Poster-style session: "What we plan to try" — artists observe and sketch early concepts |
Tuesday 13 – Thursday 15 October — Days 2–4: Hackathon Core
Each day follows a common rhythm:
| Time | Activity |
|---|---|
| Morning (30–45 min) | Cross-group check-in: progress, blockers, short technical input |
| Daytime | Team work: coding, model training, diagnostics, analysis |
| Late afternoon | Mentor roundtables (accelerator physics, ML, HPC) |
| End of day | Informal wrap-up; artist interaction with teams |
Friday 16 October — Day 5: Synthesis & Confrontation
| Time | Activity |
|---|---|
| Morning | Finalization of results; preparation of presentations and demos |
| Afternoon (plenary) | Results session — for each group: scientific context, Team A vs Team B (assumptions, methodology, performance, interpretability), lessons learned |
| Closing | Cross-cutting discussion: what worked / failed, transferability to real machines |
| Closing | Outlook: publications, follow-up projects, open datasets and benchmarks |
| Closing | Presentation of artistic output — draft comic panels |
| ~16:00 |