ORAMA X

How it works?

1) Before you start

  • Browser: Use a modern browser (Chrome, Edge, Firefox, Safari). Keep a single tab active when running detections.
  • Data access: Orama X fetches light curves and metadata from MAST/SPOC and can query TESSCut and Gaia DR3.
  • Terminology: Light curve = Flux vs time; Phase folded = folded on candidate period; BLS = Box Least Squares; Vetting = checks before confirming a planet; P(planet) = AI classifier probability.

2) Detection panel overview

The main panel lets you choose a source, configure preprocessing, run a period search, and inspect candidates. Use Fetch & Detect to download data, apply filters, and search for transit signals.

3) Single-target workflow

  1. Enter target ID (TIC / EPIC / Kepler) and keep Mission = auto.
  2. Choose preprocessing: quality mask ON, outlier σ = 5, detrend = flatten.
  3. Enable centroid vetting and Gaia neighbors for contamination checks.
  4. Set thresholds (p = 0.5–0.8, centroid σ thr = 3.0, Gaia radius = 60″).
  5. Click Fetch & Detect to run the search, then inspect candidates visually.
  6. Check metrics like SNR, ΔBIC, Odd/Even Δ, Secondary?, and Centroid.
  7. Fit the transit with batman, review parameters, and export vetted results.

4) Batch workflow

Analyze multiple targets using the same settings. Paste TICs/EPICs inBulk mode, configure global parameters, run sequentially, and export results (all or vetted only).

5) Custom light curves

Upload TXT/CSV files with at least time and fluxcolumns. Configure detrending and vetting as usual, then run detection and export.

6) AI / ML tools

  • Classification: Each candidate receives a P(planet) score.
  • Explainability: “Explain prediction” highlights top contributing features (depth, duration, SNR, etc.).
  • Retraining: Upload labeled CSVs and click “Train new model” to fit a custom classifier and view metrics (F1, PR AUC, confusion matrix).

7) Gaia DR3 Neighbors panel

Shows nearby Gaia sources (sep, dx, dy, Gmag, BP−RP, RUWE). Use this to assess contamination and confirm centroid results.

8) Candidates table

Review each candidate’s period, duration, depth, power, P(planet), SNR, ΔBIC, odd/even Δ, and centroid status before confirming as a planet.

9) Export & reproducibility

Use Export CSV, Export Vetted CSV, andDownload PDF report to save your analyses. Always record mission, detrending, thresholds, and model version for reproducibility.

10) Troubleshooting & best practices

  • No candidates? Increase k peaks or relax σ clip.
  • Spurious periods? Tighten quality mask and verify by eye.
  • Centroid fails? Reduce Gaia radius and recheck neighbors.
  • AI over-confident? Raise planet threshold or review explanations.

11) Quick recipes

  • Single bright TESS target: Fetch → Detect → Fit → Verify → Export.
  • Batch analysis: Bulk mode → run → Export Vetted CSV.
  • Custom data: Upload → Detect → Fit → Explain → Export.

12) Sensible thresholds

p = 0.5 (exploratory) / 0.8 (high purity), Centroid σ thr = 3.0, Gaia radius = 60″, k peaks = 3 (quick) / 5–10 (deep search).

Final note

Orama X enables human-AI collaboration for exoplanet discovery. Always combine AI probabilities with physical vetting (centroid, Gaia neighbors, odd/even tests, ΔBIC) and visual inspection before confirming a planet.