Synopsis
The search for extraterrestrial intelligence (SETI) seeks evidence of technology created by intelligent life beyond Earth. One approach is to look for narrowband radio signals that exhibit a frequency drift over time, known as a “drift rate”. These can arise when a transmitter on an exoplanet moves radially relative to a receiver on Earth. Accounting for drift rates can help SETI researchers determine which frequency ranges to search and judge the validity of signal candidates by comparing to expected drift rates.
In this paper, Li et al model drift rate distributions for exoplanets to inform SETI searches. They calculate drift rates for over 5300 confirmed exoplanets using orbital parameters from the NASA Exoplanet Archive. Factoring in effects like exoplanet orbits and rotations and Earth’s motion, they find 99% of drift rates fall within ±53 nHz. This distribution-informed limit is about 4 times lower than a previous 200 nHz upper bound, implying a significant reduction in search ranges for higher efficiency.
However, the known exoplanet sample has observational biases. The transit and radial velocity discovery methods preferentially detect short-period and edge-on orbits, which produce higher drift rates. To mitigate this, the authors simulate a more representative exoplanet population using parameters drawn from theoretical models. For example, they use uniform inclination distributions rather than assuming edge-on orbits.
With the simulated population, the 99% drift rate containment falls to just ±0.44 nHz. This huge drop partially stems from including a wider range of inclinations. It also results from removing the bias toward short orbital periods in the known sample. These findings suggest SETI searches around stars without known planets could use much smaller drift rate ranges than thought previously.
In summary, modeling drift rate distributions for exoplanets can inform SETI search parameters to improve efficiency. While known exoplanets exhibit drifts up to ~50 nHz, a simulated population points to maxima below 1 nHz. Such narrower ranges will significantly reduce computational costs and observation time needed for sensitive radio technosignature searches in the future.
