Translate an exoplanet transit observing concept into measurable mission requirements. Estimate total samples, science data volume, observing duty, and campaign span from cadence, transit duration, target count, transit count, and data size.
Use the main result as a transparent first-order planning value. The supporting metrics expose intermediate quantities so assumptions can be checked and compared across scenarios.
The nominal span assumes a 35% usable observing duty cycle. Scheduling constraints, target visibility, calibration data, and redundancy must be budgeted separately.
For 40 stars, 3 transits each, 5 hours of coverage, and 60-second cadence, the campaign records 36,000 samples. At 2 MB each, that is 70.31 GB and 600 observing hours.
The dominant inputs are those used directly in the displayed formula. Change one input at a time to see its effect while holding the other exoplanet transit assumptions fixed.
Fields described as optional or overhead may accept zero. Physical quantities that appear in a denominator or define the mission scale must remain positive.
Only the contingency or efficiency explicitly entered is included. Add separate reserves for effects that are not represented by an input.
Detailed models include geometry, hardware modes, environmental conditions, correlated uncertainties, and organization-specific constraints that a screening calculator cannot capture.
Recompute the case with an independent tool, document every assumption and unit, test pessimistic and optimistic scenarios, and compare against subsystem or observatory requirements.
| Output | Use |
|---|---|
| Main result | Primary sizing or planning value |
| Supporting metrics | Trace the drivers behind the result |
| Interpretation | Identify what is and is not represented |