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Searching for codes credited to 'Hattori, Soichiro'

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Found 3 codes.

[ascl:2504.028] jaxoplanet: Astronomical time series analysis with JAX
Hattori, Soichiro; Garcia, Lionel; Murray, Catriona; Dong, Jiayin; Dholakia, Shashank; Degen, David; Foreman-Mackey, Daniel
jaxoplanet is a functional-programming-forward implementation of many features from the exoplanet and starry packages built on top of JAX (ascl:2111.002). It includes fast and robust implementations of many exoplanet-specific operations, including solving Kepler’s equation, and computing limb-darkened light curves. jaxoplanet has first-class support for hardware acceleration using GPUs and TPUs, and integrates seamlessly with modeling tools such as NumPyro (ascl:2505.005) and Flax (ascl:2504.026).
[ascl:2502.006] Giants: Pipeline to search for exoplanets around evolved stars
Saunders, Nicholas; Grunblatt, Samuel K.; Huber, Daniel; Collins, Karen A.; Jensen, Eric L. N.; Vanderburg, Andrew; Brahm, Rafael; Jordán, Andrés; Espinoza, Néstor; Henning, Thomas; Hobson, Melissa J.; Quinn, Samuel N.; Zhou, George; Butler, R. Paul; Crause, Lisa; Kuhn, Rudi B.; Moses Mogotsi, K.; Hellier, Coel; Angus, Ruth; Hattori, Soichiro; Chontos, Ashley; Ricker, George R.; Jenkins, Jon M.; Tenenbaum, Peter; Latham, David W.; Seager, Sara; Vanderspek, Roland K.; Winn, Joshua N.; Stockdale, Chris; Cloutier, Ryan
The Giants pipeline accesses TESS data, produces noise-corrected light curves, and searches for planets transiting evolved stars. Built with Lightkurve (ascl:1812.013) and written in Python, its emphasis is on finding giant planets around subgiant and RGB stars in TESS Full Frame Images (FFIs). Giants produces a one-page PDF summary for each target.
[ascl:2109.015] unpopular: Using CPM detrending to obtain TESS light curves
Hattori, Soichiro; Foreman-Mackey, Daniel; Hogg, David W.; Montet, Benjamin T.; Angus, Ruth; Pritchard, T. A.; Curtis, Jason L.; Schölkopf, Bernhard
unpopular is an implementation of the Causal Pixel Model (CPM) de-trending method to obtain TESS Full-Frame Image (FFI) light curves. The code, written in Python, models the systematics in the light curves of individual pixels as a linear combination of light curves from many other distant pixels and removes shared flux variations. unpopular is able to preserve sector-length astrophysical signals, allowing for the extraction of multi-sector light curves from the FFI data.