CamCEAD at the University of Cambridge Institute of Astronomy supports PLATO WP36 and EAS data-flow operations, coordinating infrastructure, backend services, pipelines, databases, and distributed computing for the ESA PLATO exoplanet mission.
The Cambridge Centre for Environmental and Astronomical Data flow (CamCEAD) at the Institute of Astronomy drives the development and runtime architecture for the PLATO Exoplanet Analysis System (EAS), targeting Work Package 36 (WP36) for exoplanetary discovery and characterisation. CamCEAD coordinates infrastructure, backend services, pipelines, databases, and distributed computing for the mission.
The WP36 End-to-End EAS Data Flow
CamCEAD holds primary responsibility for the WP36 framework and EAS operations nodes in the end-to-end data pipeline — from raw spacecraft photometry through to catalogued planetary systems delivered to the science community.
WP36 Architecture
Managing systems critical to implementing data flow models for exoplanet light-curve verification and parameter space searches:
- Framework Operations: Overseeing dedicated exoplanet pipeline codebases deployed within Cambridge's operational nodes.
- EAS Infrastructure: Synchronising software versioning, component packages, and operational models across analysis branches.
- Pipeline Modularisation: Structuring algorithms for automated verification, multi-transit detection, and false-positive vetting.
EAS Code Development
Delivering foundational exoplanet analysis system modules within the WP36 framework:
- Module Calibration: Optimising transit modelling arrays and planet-star blending identification modules.
- Data Stream Handlers: Structuring pipelines to ingest corrected light-curves into memory-centric query loops.
- Validation Controls: Deploying regression tests and pipeline verification benches across production baselines.
Operational Management
Ensuring processing workflows remain robust and stable against mission telemetry workloads:
- Operational Readiness: Running scale-up tests on simulated planetary transit streams ahead of real-time flight telemetry.
- Quality Controls: Continuous regression testing and performance benchmarking across pipeline production baselines.
- EAS Lifecycle: Coordinating software release cycles aligned with ESA mission milestones.
CETRA — Cambridge Exoplanet Transit Recovery Algorithm
CETRA represents a major leap forward for exoplanetary discovery pipelines within the EAS framework. Optimised for NVIDIA GPUs using the CUDA platform, CETRA splits transit verification into linear time-space searches followed by physically motivated phase-folding profiles.
- Superior Sensitivity: Outperforms BLS and TLS, recovering 20%+ more low-SNR and long-period transits.
- GPU Acceleration: Drastically reduces pipeline crunch-time on high-cadence star-field light curves.
- Proven Validation: Enhanced statistical significance in real datasets, pushing faint candidates to validation thresholds.
- Open Ecosystem: Python-ready core infrastructure integrated onto PyPI and GitHub repositories.
The IRIS Ecosystem for PLATO EAS
CamCEAD leverages the IRIS National Facility to deliver scalable distributed cloud computing allocations required for high-throughput PLATO WP36 data runs.
Kubernetes Clusters
Providing distributed, resilient dynamic orchestration for exoplanet detection algorithms and data pipeline nodes across containerised layers, enabling elastic scaling with mission data volume.
Docker & Python Runtime
Deploying modular Python pipeline jobs encapsulated inside secure Docker containers to enforce software predictability, reproducibility, and swift scalability across IRIS compute nodes.
Related Links
CamCEAD Collaborators
Research Associate
Research Professor
Assistant Research Professor
Assistant Research Professor
Research Associate
Assistant Research Professor
Research Professor
Research Associate
Research Assistant Professor
Senior Research Associate
Research Associate
Senior Research Associate
