DIAmante TESS AutoRegressive Planet Search (DTARPS): III. Understanding the DTARPS Candidate Transiting Planet Catalogs

Melton, Elizabeth J.; Feigelson, E. D.; Montalto, M.; Caceres, Gabriel; Rosenswie, Andrew W.; Abelson, Cullen S.

doi:10.48550/arxiv.2302.06744

Cited by 2 publications

(3 citation statements)

References 69 publications

(115 reference statements)

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“…The latter is now often used with the LSP (Baluev 2008;Süveges 2014). Section 5 of Caceres et al (2019b) and Figure 16 of Melton et al (2023c) show that transit planet candidates derived from the ARIMA + TCF combination are often smaller than confirmed planets derived from BLS-based procedures, and thus the findings of this paper. Our study explains some of the problems with the BLS periodogram described by Ofir (2014).…”

Section: Discussionsupporting

confidence: 56%

“…To complement our comparison of the BLS and TCF periodograms in simulated light curves (Sections 2-4), we apply the procedures to four TESS FFI light curves drawn from the DTARPS-S survey (Melton et al 2023a(Melton et al , 2023b(Melton et al , 2023c) that contain true known small exoplanets. Trends in these light curves have been removed using splines; however, we still preprocess the light curve using Gaussian process regression to maintain an analysis procedure similar to our simulations above.…”

Section: Application To Tess Light Curvesmentioning

confidence: 99%

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A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets

Gondhalekar,

Feigelson,

Caceres

et al. 2023

ApJL

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The sensitivities of two periodograms are compared for weak signal planet detection in transit surveys: the widely used Box Least Squares (BLS) algorithm following light curve detrending and the Transit Comb Filter (TCF) algorithm following autoregressive ARIMA modeling. Small depth transits are injected into light curves with different simulated noise characteristics. Two measures of spectral peak significance are examined: the periodogram signal-to-noise ratio (S/N) and a false alarm probability (FAP) based on the generalized extreme value distribution. The relative performance of the BLS and TCF algorithms for small planet detection is examined for a range of light curve characteristics, including orbital period, transit duration, depth, number of transits, and type of noise. We find that the TCF periodogram applied to ARIMA fit residuals with the S/N detection metric is preferred when short-memory autocorrelation is present in the detrended light curve and even when the light curve noise had white Gaussian noise. BLS is more sensitive to small planets only under limited circumstances with the FAP metric. BLS periodogram characteristics are inferior when autocorrelated noise is present due to heteroscedastic noise and false period detection. Application of these methods to TESS light curves with known small exoplanets confirms our simulation results. The study ends with a decision tree that advises transit survey scientists on procedures to detect small planets most efficiently. The use of ARIMA detrending and TCF periodograms can significantly improve the sensitivity of any transit survey with regularly spaced cadence.

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Section: Discussionsupporting

confidence: 56%

Section: Application To Tess Light Curvesmentioning

confidence: 99%

A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets

Gondhalekar,

Feigelson,

Caceres

et al. 2023

ApJL

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show abstract

“…These USP Jupiters are rare. Based on a survey of 1 million stars with the TESS satellite (Melton et al 2023), we roughly expect ∼10 such systems to be present in this LSST microsurvey. It is possible they will suffer strong contamination by unequal-mass stellar binaries.…”

Section: Usp Exoplanetsmentioning

confidence: 99%

An Evenly Spaced LSST Cadence for Rapidly Variable Stars

Feigelson,

Bianco,

Bonito

2023

ApJS

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Stars exhibit a bewildering variety of rapidly variable behaviors ranging from explosive magnetic flares to stochastically changing accretion to periodic pulsations or rotation. The principal Rubin Observatory Legacy Survey of Space and Time (LSST) surveys will have cadences too sparse and irregular to capture many of these phenomena. We propose here an LSST microsurvey to observe a single Galactic field, rich in unobscured stars, in a continuous sequence of 30 s exposures for one long winter night in a single photometric band. The result will be a unique data set of ∼1 million regularly spaced stellar light curves. The light curves will constitute a comprehensive collection of late-type stellar flaring, but also other classes like short-period binary systems and cataclysmic variables, young stellar objects, and ultrashort-period exoplanets. An unknown variety of anomalous solar system, Galactic, and extragalactic variables and transients may also be present. A powerful array of statistical procedures can be applied to individual light curves from the long-standing fields of time series analysis, signal processing, and econometrics. Dozens of “features” describing the variability can be extracted and the ensemble of light curves can be subject to advanced machine-learning clustering procedures. This will give a unique, authoritative, objective taxonomy of the rapidly variable sky derived from identically cadenced light curves. This microsurvey is best performed early in the Rubin Observatory program, and the results can inform the wider community on the best approaches to variable star identification and classification from the sparse, irregular cadences that dominate the planned surveys.

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DIAmante TESS AutoRegressive Planet Search (DTARPS): III. Understanding the DTARPS Candidate Transiting Planet Catalogs

Cited by 2 publications

References 69 publications

A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets

A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets

An Evenly Spaced LSST Cadence for Rapidly Variable Stars

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