What's in Your Transit? Towards Reliably Getting $5\times$ More Science from Exoplanet Transit Data
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arXiv
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| Natura: | Preprint |
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2025
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| _version_ | 1866914069219377152 |
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| author | Mercier, Samson J. de Wit, Julien Rackham, Benjamin V. |
| author_facet | Mercier, Samson J. de Wit, Julien Rackham, Benjamin V. |
| contents | Exoplanetary science heavily relies on transit depth ($D$) measurements. Yet, as instrumental precision increases, the uncertainty on $D$ appears to increasingly drift from expectations driven solely by photon-noise. Here we characterize this shortfall (the Transit-Depth Precision Problem, TDPP), by defining an amplification factor, $A$, quantifying the discrepancy between the measured transit-depth uncertainty and the measured baseline scatter on a same time bin size. While in theory $A$ should be $\sim\sqrt{3}$, we find that it can reach values $\gtrsim$10 notably due to correlations between $D$ and the limb-darkening coefficients (LDCs). This means that (1) the performance of transit-based exoplanet studies (e.g., atmospheric studies) can be substantially improved with reliable priors on LDCs and (2) low-fidelity priors on the LDCs can yield substantial biases on $D$--potentially affecting atmospheric studies due to the wavelength-dependence of such biases. For the same reason, biases may emerge on stellar-density and planet-shape/limb-asymmetry measurements. With current photometric precisions, we recommend using a 3$^{\rm rd}$-order polynomial law and a 4$^{\rm th}$-order non-linear law, as they provide an optimal compromise between bias and $A$, while testing the fidelity for each parametrization. While their use combined with existing LDC priors (10-20% uncertainty) currently implies $A\sim10$, we show that targeted improvements to limb-darkening models can bring $A$ down to $\sim2$. Improving stellar models and transit-fitting practices is thus essential to fully exploit transit datasets, and reliably increasing their scientific yield by $5\times$, thereby enabling the same science with up to $25\times$ fewer transits. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_00124 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | What's in Your Transit? Towards Reliably Getting $5\times$ More Science from Exoplanet Transit Data Mercier, Samson J. de Wit, Julien Rackham, Benjamin V. Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics Exoplanetary science heavily relies on transit depth ($D$) measurements. Yet, as instrumental precision increases, the uncertainty on $D$ appears to increasingly drift from expectations driven solely by photon-noise. Here we characterize this shortfall (the Transit-Depth Precision Problem, TDPP), by defining an amplification factor, $A$, quantifying the discrepancy between the measured transit-depth uncertainty and the measured baseline scatter on a same time bin size. While in theory $A$ should be $\sim\sqrt{3}$, we find that it can reach values $\gtrsim$10 notably due to correlations between $D$ and the limb-darkening coefficients (LDCs). This means that (1) the performance of transit-based exoplanet studies (e.g., atmospheric studies) can be substantially improved with reliable priors on LDCs and (2) low-fidelity priors on the LDCs can yield substantial biases on $D$--potentially affecting atmospheric studies due to the wavelength-dependence of such biases. For the same reason, biases may emerge on stellar-density and planet-shape/limb-asymmetry measurements. With current photometric precisions, we recommend using a 3$^{\rm rd}$-order polynomial law and a 4$^{\rm th}$-order non-linear law, as they provide an optimal compromise between bias and $A$, while testing the fidelity for each parametrization. While their use combined with existing LDC priors (10-20% uncertainty) currently implies $A\sim10$, we show that targeted improvements to limb-darkening models can bring $A$ down to $\sim2$. Improving stellar models and transit-fitting practices is thus essential to fully exploit transit datasets, and reliably increasing their scientific yield by $5\times$, thereby enabling the same science with up to $25\times$ fewer transits. |
| title | What's in Your Transit? Towards Reliably Getting $5\times$ More Science from Exoplanet Transit Data |
| topic | Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2510.00124 |