Search

A significant barrier to achieving the radial velocity (RV) measurement accuracy and precision required to characterize terrestrial mass exoplanets is the existence of time-variable features in the measured spectra, from both telluric absorption and stellar variability, which affect measured line shapes and can cause apparent RV shifts. Reaching the desired accuracy using traditional techniques often requires avoiding lines contaminated by stellar variability and/or changing tellurics, and thus discarding a large fraction of the spectrum, lowering precision. New data-driven methods can help achieve extremely precise and accurate RVs by enabling the use of a larger fraction of the available data. While there exist methods for modeling telluric features or the stellar variability individually, there is a need for additional tools that are capable of modeling them simultaneously at the spectral level. Here we present StellarSpectraObservationFitting.jl (SSOF), a Julia package for measuring Doppler shifts and creating data-driven models (with fast, physically-motivated Gaussian Process regularization) for the time-variable spectral features for both the telluric transmission and stellar spectrum, while accounting for the wavelength-dependent instrumental line-spread function. We demonstrate SSOF's state-of-the-art performance on data from the NEID RV spectrograph on the WIYN 3.5m Telescope for multiple stars. We show SSOF's, ability to accurately identify and characterize spectral variability and provide $\sim$2-6x smaller photon-limited errors over the NEID CCF-based pipeline and match the performance of SERVAL, a leading template-based pipeline, using only observed EPRV spectra., Comment: 47 pages, 21 figures, 7 tables. In revision for AAS Journals. Code at https://github.com/christiangil/StellarSpectraObservationFitting.jl

We present the results of Sun-as-a-star observations by the NEID Solar Telescope at WIYN Observatory, spanning January 1, 2021 through June 30, 2024. We identify 117,060 observations which are unlikely to be significantly affected by weather, hardware or major calibration issues. We describe several high-level data products being made available to the community to aid in the interpretation and inter comparisons of NEID solar observations. Solar observations demonstrate excellent performance of NEID, including radial velocity (RV) accuracy and long-term stability of better than $\simeq 0.37$ m s$^{-1}$ over $\simeq 3.5$ years, even though NEID was not originally designed or optimized for daytime observations of the Sun. Currently, intrinsic stellar variability is the primary barrier to detecting Earth-analog planets for most nearby, Sun-like stars. We present a comparison of the effectiveness of several methods proposed to mitigate the effects of solar variability on the Sun's estimated RV. We find that the Scalpels algorithm performs particularly well and substantially reduces the RMS RV of solar spectra from over 2 m s$^{-1}$ to 0.277 m s$^{-1}$. Even when training on a subset of days with NEID solar observations and testing on a held-out sample, the RMS of cleaned RV is 0.34-0.42 m s$^{-1}$. This is significantly better than previous attempts at removing solar variability and suggests that the current generation of EPRV instruments are technically capable of detecting Earth-mass planets orbiting a solar twin if provided with sufficient observing time allocations ($\sim 10^3$ nights of observations)., Comment: 25 pages, 14 figures. Submitted to AAS Journals. Data release archived at https://zenodo.org/doi/10.5281/zenodo.13363761

The Habitable Worlds Observatory (HWO) will seek to detect and characterize potentially Earth-like planets around other stars. To ensure that the mission achieves the Astro2020 Decadal's recommended goal of 25 exoEarth candidates (EECs), we must take into account the probabilistic nature of exoplanet detections and provide "science margin" to budget for astrophysical uncertainties with a reasonable level of confidence. In this study, we explore the probabilistic distributions of yields to be expected from a blind exoEarth survey conducted by such a mission. We identify and estimate the impact of all major known sources of astrophysical uncertainty on the exoEarth candidate yield. As expected, eta_Earth uncertainties dominate the uncertainty in EEC yield, but we show that sampling uncertainties inherent to a blind survey are another important source of uncertainty that should be budgeted for during mission design. We adopt the Large UV/Optical/IR Surveyor Design B (LUVOIR-B) as a baseline and modify the telescope diameter to estimate the science margin provided by a larger telescope. We then depart from the LUVOIR-B baseline design and identify six possible design changes that, when compiled, provide large gains in exoEarth candidate yield and more than an order of magnitude reduction in exposure times for the highest priority targets. We conclude that a combination of telescope diameter increase and design improvements could provide robust exoplanet science margins for HWO., Comment: 90 pages, 26 figures, 4 tables, Submitted to JATIS

We present an updated version of GRASS (the GRanulation And Spectrum Simulator, Palumbo et al. 2022) which now uses an expanded library of 22 solar lines to empirically model time-resolved spectral variations arising from solar granulation. We show that our synthesis model accurately reproduces disk-integrated solar line profiles and bisectors, and we quantify the intrinsic granulation-driven radial-velocity (RV) variability for each of the 22 lines studied. We show that summary statistics of bisector shape (e.g., bisector inverse slope) are strongly correlated with the measured anomalous, variability-driven RV at high pixel signal-to-noise ratio (SNR) and spectral resolution. Further, the strength of the correlations vary both line by line and with the summary statistic used. These correlations disappear for individual lines at the typical spectral resolutions and SNRs achieved by current EPRV spectrographs; so we use simulations from GRASS to demonstrate that they can, in principle, be recovered by selectively binning lines that are similarly affected by granulation. In the best-case scenario (high SNR and large number of binned lines), we find that a $\lesssim$30$\%$ reduction in the granulation-induced root mean square (RMS) RV can be achieved, but that the achievable reduction in variability is most strongly limited by the spectral resolution of the observing instrument. Based on our simulations, we predict that existing ultra-high-resolution spectrographs, namely ESPRESSO and PEPSI, should be able to resolve convective variability in other, bright stars., Comment: 20 + 16 pages, 6 + 11 figures, 4 tables; in revision for AJ

We revisit the long-studied radial velocity (RV) target HD26965 using recent observations from the NASA-NSF 'NEID' precision Doppler facility. Leveraging a suite of classical activity indicators, combined with line-by-line RV analyses, we demonstrate that the claimed 45-day signal previously identified as a planet candidate is most likely an activity-induced signal. Correlating the bulk (spectrally-averaged) RV with canonical line activity indicators confirms a multi-day 'lag' between the observed activity indicator time series and the measured RV. When accounting for this lag, we show that much of the observed RV signal can be removed by a linear detrending of the data. Investigating activity at the line-by-line level, we find a depth-dependent correlation between individual line RVs and the bulk RVs, further indicative of periodic suppression of convective blueshift causing the observed RV variability, rather than an orbiting planet. We conclude that the combined evidence of the activity correlations and depth dependence is consistent with a radial velocity signature dominated by a rotationally-modulated activity signal at a period of $\sim$42 days. We hypothesize that this activity signature is due to a combination of spots and convective blueshift suppression. The tools applied in our analysis are broadly applicable to other stars, and could help paint a more comprehensive picture of the manifestations of stellar activity in future Doppler RV surveys., Comment: 25 pages, 13 figures. Accepted in AJ

Recent discoveries of transiting giant exoplanets around M-dwarf stars (GEMS), aided by the all-sky coverage of TESS, are starting to stretch theories of planet formation through the core-accretion scenario. Recent upper limits on their occurrence suggest that they decrease with lower stellar masses, with fewer GEMS around lower-mass stars compared to solar-type. In this paper, we discuss existing GEMS both through confirmed planets, as well as protoplanetary disk observations, and a combination of tests to reconcile these with theoretical predictions. We then introduce the \textit{Searching for GEMS} survey, where we utilize multi-dimensional nonparameteric statistics to simulate hypothetical survey scenarios to predict the required sample size of transiting GEMS with mass measurements to robustly compare their bulk-density with canonical hot-Jupiters orbiting FGK stars. Our Monte-Carlo simulations predict that a robust comparison requires about 40 transiting GEMS (compared to the existing sample of $\sim$ 15) with 5-$\sigma$ mass measurements. Furthermore, we discuss the limitations of existing occurrence estimates for GEMS, and provide a brief description of our planned systematic search to improve the occurrence rate estimates for GEMS., Comment: 16 pages + references, including 7 figures. Accepted in AAS Journals

We present an analysis of Sun-as-a-star observations from four different high-resolution, stabilized spectrographs -- HARPS, HARPS-N, EXPRES, and NEID. With simultaneous observations of the Sun from four different instruments, we are able to gain insight into the radial velocity precision and accuracy delivered by each of these instruments and isolate instrumental systematics that differ from true astrophysical signals. With solar observations, we can completely characterize the expected Doppler shift contributed by orbiting Solar System bodies and remove them. This results in a data set with measured velocity variations that purely trace flows on the solar surface. Direct comparisons of the radial velocities measured by each instrument show remarkable agreement with residual intra-day scatter of only 15-30 cm/s. This shows that current ultra-stabilized instruments have broken through to a new level of measurement precision that reveals stellar variability with high fidelity and detail. We end by discussing how radial velocities from different instruments can be combined to provide powerful leverage for testing techniques to mitigate stellar signals., Comment: 17 pages, 9 figures, accepted for publication

Fundamental to our understanding of planetary bulk compositions is the relationship between their masses and radii, two properties that are often not simultaneously known for most exoplanets. However, while many previous studies have modeled the two-dimensional relationship between planetary mass and radii, this approach largely ignores the dependencies on other properties that may have influenced the formation and evolution of the planets. In this work, we extend the existing nonparametric and probabilistic framework of \texttt{MRExo} to jointly model distributions beyond two dimensions. Our updated framework can now simultaneously model up to four observables, while also incorporating asymmetric measurement uncertainties and upper limits in the data. We showcase the potential of this multi-dimensional approach to three science cases: (i) a 4-dimensional joint fit to planetary mass, radius, insolation, and stellar mass, hinting of changes in planetary bulk density across insolation and stellar mass; (ii) a 3-dimensional fit to the California Kepler Survey sample showing how the planet radius valley evolves across different stellar masses; and (iii) a 2-dimensional fit to a sample of Class-II protoplanetary disks in Lupus while incorporating the upper-limits in dust mass measurements. In addition, we employ bootstrap and Monte-Carlo sampling to quantify the impact of the finite sample size as well as measurement uncertainties on the predicted quantities. We update our existing open-source user-friendly \texttt{MRExo} \texttt{Python} package with these changes, which allows users to apply this highly flexible framework to a variety of datasets beyond what we have shown here., Comment: Accepted in ApJ. Updated MRExo package and sample scripts available here: https://github.com/shbhuk/mrexo/tree/v1.0dev. Package will be released on PyPI (pip) along with full documentation upon publication in ApJ

Exoplanets can be detected with various observational techniques. Among them, radial velocity (RV) has the key advantages of revealing the architecture of planetary systems and measuring planetary mass and orbital eccentricities. RV observations are poised to play a key role in the detection and characterization of Earth twins. However, the detection of such small planets is not yet possible due to very complex, temporally correlated instrumental and astrophysical stochastic signals. Furthermore, exploring the large parameter space of RV models exhaustively and efficiently presents difficulties. In this review, we frame RV data analysis as a problem of detection and parameter estimation in unevenly sampled, multivariate time series. The objective of this review is two-fold: to introduce the motivation, methodological challenges, and numerical challenges of RV data analysis to nonspecialists, and to unify the existing advanced approaches in order to identify areas for improvement., Comment: Published in Annual Reviews of Statistics and Its Application, contains the main text and supplemental appendix

Characterizing the masses and orbits of near-Earth-mass planets is crucial for interpreting observations from future direct imaging missions (e.g., HabEx, LUVOIR). Therefore, the Exoplanet Science Strategy report (National Academies of Sciences, Engineering, and Medicine 2018) recommended further research so future extremely precise radial velocity surveys could contribute to the discovery and/or characterization of near-Earth-mass planets in the habitable zones of nearby stars prior to the launch of these future imaging missions. Newman et al. (2021) simulated such 10-year surveys under various telescope architectures, demonstrating they can precisely measure the masses of potentially habitable Earth-mass planets in the absence of stellar variability. Here, we investigate the effect of stellar variability on the signal-to-noise ratio (SNR) of the planet mass measurements in these simulations. We find that correlated noise due to active regions has the largest effect on the observed mass SNR, reducing the SNR by a factor of $\sim$5.5 relative to the no-variability scenario -- granulation reduces by a factor of $\sim$3, while p-mode oscillations has little impact on the proposed survey strategies. We show that in the presence of correlated noise, 5-cm s$^{-1}$ instrumental precision offers little improvement over 10-cm s$^{-1}$ precision, highlighting the need to mitigate astrophysical variability. With our noise models, extending the survey to 15 years doubles the number of Earth-analogs with mass SNR $>$ 10, and reaching this threshold for any Earth-analog orbiting a star $>$ 0.76 M$_{\odot}$ in a 10-year survey would require an increase in number of observations per star from that in Newman et al. (2021)., Comment: 30 pages, 9 figures, accepted in AJ

Measured spectral shifts due to intrinsic stellar variability (e.g., pulsations, granulation) and activity (e.g., spots, plages) are the largest source of error for extreme precision radial velocity (EPRV) exoplanet detection. Several methods are designed to disentangle stellar signals from true center-of-mass shifts due to planets. The EXPRES Stellar Signals Project (ESSP) presents a self-consistent comparison of 22 different methods tested on the same extreme-precision spectroscopic data from EXPRES. Methods derived new activity indicators, constructed models for mapping an indicator to the needed RV correction, or separated out shape- and shift-driven RV components. Since no ground truth is known when using real data, relative method performance is assessed using the total and nightly scatter of returned RVs and agreement between the results of different methods. Nearly all submitted methods return a lower RV RMS than classic linear decorrelation, but no method is yet consistently reducing the RV RMS to sub-meter-per-second levels. There is a concerning lack of agreement between the RVs returned by different methods. These results suggest that continued progress in this field necessitates increased interpretability of methods, high-cadence data to capture stellar signals at all timescales, and continued tests like the ESSP using consistent data sets with more advanced metrics for method performance. Future comparisons should make use of various well-characterized data sets -- such as solar data or data with known injected planetary and/or stellar signals -- to better understand method performance and whether planetary signals are preserved., Comment: 33 pages (+12 pages of Appendix), 10 figures, 8 tables, accepted for publication in AJ

The radial velocity (RV) detection of exoplanets is challenged by stellar spectroscopic variability that can mimic the presence of planets and by instrumental instability that can further obscure the detection. Both stellar and instrumental changes can distort the spectral line profiles and be misinterpreted as apparent RV shifts. We present an improved FourIEr \textit{phase} SpecTrum Analysis (FIESTA a.k.a. $\mathit{\phi}$ESTA) to disentangle apparent velocity shifts due to a line deformation from a true Doppler shift. $\mathit{\phi}$ESTA projects stellar spectrum's cross correlation function (CCF) onto a truncated set of Fourier basis functions. Using the amplitude and phase information from each Fourier mode, we can trace the line variability at different CCF width scales to robustly identify and mitigate multiple sources of RV contamination. For example, in our study of the 3 years of HARPS-N solar data, $\mathit{\phi}$ESTA reveals the solar rotational effect, the long-term trend due to solar magnetic cycle, instrumental instability and apparent solar rotation rate changes. Applying a multiple linear regression model on $\mathit{\phi}$ESTA metrics, we reduce the weighted rms noise from 1.89 m/s to 0.98 m/s. In addition, we observe a $\sim$3 days lag in the $\mathit{\phi}$ESTA metrics, similar to the findings from previous studies on BIS and FWHM.

Efforts with extreme-precision radial velocity (EPRV) instruments to detect small-amplitude planets are largely limited, on many timescales, by the effects of stellar variability and instrumental systematics. One avenue for investigating these effects is the use of small solar telescopes which direct disk-integrated sunlight to these EPRV instruments, observing the Sun at high cadence over months or years. We have designed and built a solar feed system to carry out "Sun-as-a-star" observations with NEID, a very high precision Doppler spectrometer recently commissioned at the WIYN 3.5m Telescope at Kitt Peak National Observatory. The NEID solar feed has been taking observations nearly every day since December 2020; data is publicly available at the NASA Exoplanet Science Institute (NExScI) NEID Solar Archive: \url{https://neid.ipac.caltech.edu/search_solar.php}. In this paper, we present the design of the NEID solar feed and explanations behind our design intent. We also present early radial velocity (RV) results which demonstrate NEID's RV stability on the Sun over 4 months of commissioning: 0.66~m/s RMS under good sky conditions and improving to 0.41~m/s RMS under best conditions., Comment: Accepted to AJ

Owing to recent advances in radial-velocity instrumentation and observation techniques, the detection of Earth-mass planets around Sun-like stars may soon be primarily limited by intrinsic stellar variability. Several processes contribute to this variability, including starspots, pulsations, and granulation. Although many previous studies have focused on techniques to mitigate signals from pulsations and other types of magnetic activity, granulation noise has to date only been partially addressed by empirically-motivated observation strategies and magnetohydrodynamic simulations. To address this deficit, we present the GRanulation And Spectrum Simulator ($\texttt{GRASS}$), a new tool designed to create time-series synthetic spectra with granulation-driven variability from spatially- and temporally-resolved observations of solar absorption lines. In this work, we present $\texttt{GRASS}$, detail its methodology, and validate its model against disk-integrated solar observations. As a first-of-its-kind empirical model for spectral variability due to granulation in a star with perfectly known center-of-mass radial-velocity behavior, $\texttt{GRASS}$ is an important tool for testing new methods of disentangling granular line-shape changes from true Doppler shifts., Comment: 18 pages, 7 figures, 2 tables, accepted for publication in The Astronomical Journal

Precise mass measurements of exoplanets discovered by the direct imaging or transit technique are required to determine planet bulk properties and potential habitability. Furthermore, it is generally acknowledged that, for the foreseeable future, the Extreme Precision Radial Velocity (EPRV) measurement technique is the only method potentially capable of detecting and measuring the masses and orbits of habitable-zone Earths orbiting nearby F, G, and K spectral-type stars from the ground. In particular, EPRV measurements with a precision of better than approximately 10 cm/s (with a few cm/s stability over many years) are required. Unfortunately, for nearly a decade, PRV instruments and surveys have been unable to routinely reach RV accuracies of less than roughly 1 m/s. Making EPRV science and technology development a critical component of both NASA and NSF program plans is crucial for reaching the goal of detecting potentially habitable Earthlike planets and supporting potential future exoplanet direct imaging missions such as the Habitable Exoplanet Observatory (HabEx) or the Large Ultraviolet Optical Infrared Surveyor (LUVOIR). In recognition of these facts, the 2018 National Academy of Sciences (NAS) Exoplanet Science Strategy (ESS) report recommended the development of EPRV measurements as a critical step toward the detection and characterization of habitable, Earth-analog planets. In response to the NAS-ESS recommendation, NASA and NSF commissioned the EPRV Working Group to recommend a ground-based program architecture and implementation plan to achieve the goal intended by the NAS. This report documents the activities, findings, and recommendations of the EPRV Working Group., Comment: Full report: 103 pages. Executive summary: 7 pages. More information about the NASA-NSF Exoplanet Observational Research (NN-EXPLORE) program, including the NASA-NSF Extreme Precision Radial Velocity Initiative, can be found here: https://exoplanets.nasa.gov/exep/NNExplore/

In the search for planets orbiting distant stars the presence of stellar activity in the atmospheres of observed stars can obscure the radial velocity signal used to detect such planets. Furthermore, this stellar activity contamination is set by the star itself and cannot simply be avoided with better instrumentation. Various stellar activity indicators have been developed that may correlate with this contamination. We introduce a new stellar activity indicator called the Stellar Activity F-statistic for Exoplanet surveys (SAFE) that has higher statistical power (i.e., probability of detecting a true stellar activity signal) than many traditional stellar activity indicators in a simulation study of an active region on a Sun-like star with moderate to high signal-to-noise. Also through simulation, the SAFE is demonstrated to be associated with the projected area on the visible side of the star covered by active regions. We also demonstrate that the SAFE detects statistically significant stellar activity in most of the spectra for HD 22049, a star known to have high stellar variability. Additionally, the SAFE is calculated for recent observations of the three low-variability stars HD 34411, HD 10700, and HD 3651, the latter of which is known to have a planetary companion. As expected, the SAFE for these three only occasionally detects activity. Furthermore, initial exploration appears to indicate that the SAFE may be useful for disentangling stellar activity signals from planet-induced Doppler shifts., Comment: 20 pages, 12 figures, accepted for publication in The Astronomical Journal

The Habitable zone Planet Finder (HPF) is a fiber fed precise radial velocity spectrograph at the 10 m Hobby Eberly Telescope (HET). Due to its fixed altitude design, the HET pupil changes appreciably across a track, leading to significant changes of the fiber far-field illumination. HPF's fiber scrambler is designed to suppress the impact of these illumination changes on the radial velocities -- but the residual impact on the radial velocity measurements has yet to be probed on sky. We use GJ 411, a bright early type (M2) M dwarf to probe the effects of far-field input trends due to these pupil variations on HPF radial velocities (RVs). These large changes ($\sim$ 2x) in pupil area and centroid present a harsh test of HPF's far-field scrambling. Our results show that the RVs are effectively decoupled from these extreme far-field input changes due to pupil centroid offsets, attesting to the effectiveness of the scrambler design. This experiment allows us to test the impact of these changes with large pupil variation on-sky, something we would not easily be able to do at a conventional optical telescope. While the pupil and illumination changes expected at these other telescopes are small, scaling from our results enables us to estimate and bound these effects, and show that they are controllable even for the new and next generation of RV instruments in their quest to beat down instrumental noise sources towards the goal of a few cm/s., Comment: 16 pages. Published in The Astrophysical Journal

NEID is a high-resolution optical spectrograph on the WIYN 3.5-m telescope at Kitt Peak National Observatory and will soon join the new generation of extreme precision radial velocity instruments in operation around the world. We plan to use the instrument to conduct the NEID Earth Twin Survey (NETS) over the course of the next 5 years, collecting hundreds of observations of some of the nearest and brightest stars in an effort to probe the regime of Earth-mass exoplanets. Even if we take advantage of the extreme instrumental precision conferred by NEID, it will remain difficult to disentangle the weak (~10 cm s$^{-1}$) signals induced by such low-mass, long-period exoplanets from stellar noise for all but the quietest host stars. In this work, we present a set of quantitative selection metrics which we use to identify an initial NETS target list consisting of stars conducive to the detection of exoplanets in the regime of interest. We also outline a set of observing strategies with which we aim to mitigate uncertainty contributions from intrinsic stellar variability and other sources of noise., Comment: 19 pages, 10 figures, 1 table

The radial velocity method is one of the most successful techniques for the discovery and characterization of exoplanets. Modern spectrographs promise measurement precision of ~0.2-0.5 m/s for an ideal target star. However, the intrinsic variability of stellar spectra can mimic and obscure true planet signals at these levels. Rajpaul et al. (2015) and Jones et al. (2017) proposed applying a physically motivated, multivariate Gaussian process (GP) to jointly model the apparent Doppler shift and multiple indicators of stellar activity as a function of time, so as to separate the planetary signal from various forms of stellar variability. These methods are promising, but performing the necessary calculations can be computationally intensive and algebraically tedious. In this work, we present a flexible and computationally efficient software package, GPLinearOdeMaker.jl, for modeling multivariate time series using a linear combination of univariate GPs and their derivatives. The package allows users to easily and efficiently apply various multivariate GP models and different covariance kernel functions. We demonstrate GPLinearOdeMaker.jl by applying the Jones et al. (2017) model to fit measurements of the apparent Doppler shift and activity indicators derived from simulated active solar spectra time series affected by many evolving star spots. We show how GPLinearOdeMaker.jl makes it easy to explore the effect of different choices for the GP kernel. We find that local kernels could significantly increase the sensitivity and precision of Doppler planet searches relative to the widely used quasi-periodic kernel., Comment: 19 pages, 4 figures, published in ApJ

Recent and upcoming stabilized spectrographs are pushing the frontier for Doppler spectroscopy to detect and characterize low-mass planets. Specifications for these instruments are so impressive that intrinsic stellar variability is expected to limit their Doppler precision for most target stars (Fischer et al. 2016). To realize their full potential, astronomers must develop new strategies for distinguishing true Doppler shifts from intrinsic stellar variability. Stellar variability due to star spots, faculae and other rotationally-linked variability are particularly concerning, as the stellar rotation period is often included in the range of potential planet orbital periods. To robustly detect and accurately characterize low-mass planets via Doppler planet surveys, the exoplanet community must develop statistical models capable of jointly modeling planetary perturbations and intrinsic stellar variability. Towards this effort, this note presents simulations of extremely high resolution, solar-like spectra created with SOAP 2.0 (arXiv:1409.3594) that includes multiple evolving star spots. We anticipate this data set will contribute to future studies developing, testing, and comparing statistical methods for measuring physical radial velocities amid contamination by stellar variability., Comment: 3 pages, 1 figure, published in RNAAS

We validate the discovery of a 2 Earth radii sub-Neptune-size planet around the nearby high proper motion M2.5-dwarf G 9-40 (EPIC 212048748), using high-precision near-infrared (NIR) radial velocity (RV) observations with the Habitable-zone Planet Finder (HPF), precision diffuser-assisted ground-based photometry with a custom narrow-band photometric filter, and adaptive optics imaging. At a distance of $d=27.9\mathrm{pc}$, G 9-40b is the second closest transiting planet discovered by K2 to date. The planet's large transit depth ($\sim$3500ppm), combined with the proximity and brightness of the host star at NIR wavelengths (J=10, K=9.2) makes G 9-40b one of the most favorable sub-Neptune-sized planet orbiting an M-dwarf for transmission spectroscopy with JWST, ARIEL, and the upcoming Extremely Large Telescopes. The star is relatively inactive with a rotation period of $\sim$29 days determined from the K2 photometry. To estimate spectroscopic stellar parameters, we describe our implementation of an empirical spectral matching algorithm using the high-resolution NIR HPF spectra. Using this algorithm, we obtain an effective temperature of $T_{\mathrm{eff}}=3404\pm73$K, and metallicity of $\mathrm{[Fe/H]}=-0.08\pm0.13$. Our RVs, when coupled with the orbital parameters derived from the transit photometry, exclude planet masses above $11.7 M_\oplus$ with 99.7% confidence assuming a circular orbit. From its radius, we predict a mass of $M=5.0^{+3.8}_{-1.9} M_\oplus$ and an RV semi-amplitude of $K=4.1^{+3.1}_{-1.6}\mathrm{m\:s^{-1}}$, making its mass measurable with current RV facilities. We urge further RV follow-up observations to precisely measure its mass, to enable precise transmission spectroscopic measurements in the future., Comment: Accepted for publication in AJ, 22 pages, 15 figures

This Astro2020 State of the Profession Consideration White Paper highlights the growth of astrostatistics and astroinformatics in astronomy, identifies key issues hampering the maturation of these new subfields, and makes recommendations for structural improvements at different levels that, if acted upon, will make significant positive impacts across astronomy., Comment: 14 pages, 1 figure; submitted to the Decadal Survey on Astronomy and Astrophysics (Astro2020) on 10 July 2019; see https://sites.nationalacademies.org/DEPS/Astro2020/DEPS_192906

The 2020s will be the most data-rich decade of astronomy in history. As the scale and complexity of our surveys increase, the problem of scheduling becomes more critical. We must develop high-quality scheduling approaches, implement them as open-source software, and begin linking the typically separate stages of observation and data analysis., Comment: 10 pages; Astro2020 APC White Paper

Transit timing variations (TTVs) are a valuable tool to determine the masses and orbits of transiting planets in multi-planet systems. TTVs can be readily modeled given knowledge of the interacting planets' orbital configurations and planet-star mass ratios, but such models are highly nonlinear and difficult to invert. Markov chain Monte Carlo (MCMC) methods are often used to explore the posterior distribution for model parameters, but, due to the high correlations between parameters, nonlinearity, and potential multi-modality in the posterior, many samplers perform very inefficiently. Therefore, we assess the performance of several MCMC samplers that use varying degrees of geometric information about the target distribution. We generate synthetic datasets from multiple models, including the TTVFaster model and a simple sinusoidal model, and test the efficiencies of various MCMC samplers. We find that sampling efficiency can be greatly improved for all models by sampling from a parameter space transformed using an estimate of the covariance and means of the target distribution. No one sampler performs the best for all datasets, but several samplers, such as Differential Evolution Monte Carlo and Geometric adaptive Monte Carlo, have consistently efficient performance. For datasets with near Gaussian posteriors, Hamiltonian Monte Carlo samplers with 2 or 3 leapfrog steps obtained the highest efficiencies. Based on differences in effective sample sizes per time, we show that the right choice of sampler can improve sampling efficiencies by several orders of magnitude.

We present results from a data challenge posed to the radial velocity (RV) community: namely, to quantify the Bayesian "evidence" for n={0,1,2,3} planets in a set of synthetically generated RV datasets containing a range of planet signals. Participating teams were provided the same likelihood function and set of priors to use in their analysis. They applied a variety of methods to estimate Z, the marginal likelihood for each n-planet model, including cross-validation, the Laplace approximation, importance sampling, and nested sampling. We found the dispersion in Z across different methods grew with increasing n-planet models: ~3 for 0-planets, ~10 for 1-planet, ~100-1000 for 2-planets, and >10,000 for 3-planets. Most internal estimates of uncertainty in Z for individual methods significantly underestimated the observed dispersion across all methods. Methods that adopted a Monte Carlo approach by comparing estimates from multiple runs yielded plausible uncertainties. Finally, two classes of numerical algorithms (those based on importance and nested samplers) arrived at similar conclusions regarding the ratio of Zs for n and (n+1)-planet models. One analytic method (the Laplace approximation) demonstrated comparable performance. We express both optimism and caution: we demonstrate that it is practical to perform rigorous Bayesian model comparison for <=3-planet models, yet robust planet discoveries require researchers to better understand the uncertainty in Z and its connections to model selection., Comment: Accepted in AJ. 33 pages, 8 figures, 4 tables. Evidence Challenge repository can be found at https://github.com/EPRV3EvidenceChallenge/Inputs

We outline the important role that ground-based, Doppler monitoring of exoplanetary systems will play in advancing our theories of planet formation and dynamical evolution. A census of planetary systems requires a well designed survey to be executed over the course of a decade or longer. A coordinated survey to monitor several thousand targets each at ~1000 epochs (~3-5 million new observations) will require roughly 40 dedicated spectrographs. We advocate for improvements in data management, data sharing, analysis techniques, and software testing, as well as possible changes to the funding structures for exoplanet science., Comment: White Paper submitted to NAS Exoplanet Strategy Committee

The radial velocity method is one of the most successful techniques for detecting exoplanets. It works by detecting the velocity of a host star induced by the gravitational effect of an orbiting planet, specifically the velocity along our line of sight, which is called the radial velocity of the star. Low-mass planets typically cause their host star to move with radial velocities of 1 m/s or less. By analyzing a time series of stellar spectra from a host star, modern astronomical instruments can in theory detect such planets. However, in practice, intrinsic stellar variability (e.g., star spots, convective motion, pulsations) affects the spectra and often mimics a radial velocity signal. This signal contamination makes it difficult to reliably detect low-mass planets. A principled approach to recovering planet radial velocity signals in the presence of stellar activity was proposed by Rajpaul et al. (2015). It uses a multivariate Gaussian process model to jointly capture time series of the apparent radial velocity and multiple indicators of stellar activity. We build on this work in two ways: (i) we propose using dimension reduction techniques to construct new high-information stellar activity indicators; and (ii) we extend the Rajpaul et al. (2015) model to a larger class of models and use a power-based model comparison procedure to select the best model. Despite significant interest in exoplanets, previous efforts have not performed large-scale stellar activity model selection or attempted to evaluate models based on planet detection power. In the case of main sequence G2V stars, we find that our method substantially improves planet detection power compared to previous state-of-the-art approaches., Comment: 37 pages, 7 figures

The Second Workshop on Extreme Precision Radial Velocities defined circa 2015 the state of the art Doppler precision and identified the critical path challenges for reaching 10 cm/s measurement precision. The presentations and discussion of key issues for instrumentation and data analysis and the workshop recommendations for achieving this precision are summarized here. Beginning with the HARPS spectrograph, technological advances for precision radial velocity measurements have focused on building extremely stable instruments. To reach still higher precision, future spectrometers will need to produce even higher fidelity spectra. This should be possible with improved environmental control, greater stability in the illumination of the spectrometer optics, better detectors, more precise wavelength calibration, and broader bandwidth spectra. Key data analysis challenges for the precision radial velocity community include distinguishing center of mass Keplerian motion from photospheric velocities, and the proper treatment of telluric contamination. Success here is coupled to the instrument design, but also requires the implementation of robust statistical and modeling techniques. Center of mass velocities produce Doppler shifts that affect every line identically, while photospheric velocities produce line profile asymmetries with wavelength and temporal dependencies that are different from Keplerian signals. Exoplanets are an important subfield of astronomy and there has been an impressive rate of discovery over the past two decades. Higher precision radial velocity measurements are required to serve as a discovery technique for potentially habitable worlds and to characterize detections from transit missions. The future of exoplanet science has very different trajectories depending on the precision that can ultimately be achieved with Doppler measurements., Comment: 45 pages, 23 Figures, workshop summary proceedings

We present Swarm-NG, a C++ library for the efficient direct integration of many n-body systems using highly-parallel Graphics Processing Unit (GPU), such as NVIDIA's Tesla T10 and M2070 GPUs. While previous studies have demonstrated the benefit of GPUs for n-body simulations with thousands to millions of bodies, Swarm-NG focuses on many few-body systems, e.g., thousands of systems with 3...15 bodies each, as is typical for the study of planetary systems. Swarm-NG parallelizes the simulation, including both the numerical integration of the equations of motion and the evaluation of forces using NVIDIA's "Compute Unified Device Architecture" (CUDA) on the GPU. Swarm-NG includes optimized implementations of 4th order time-symmetrized Hermite integration and mixed variable symplectic integration, as well as several sample codes for other algorithms to illustrate how non-CUDA-savvy users may themselves introduce customized integrators into the Swarm-NG framework. To optimize performance, we analyze the effect of GPU-specific parameters on performance under double precision. Applications of Swarm-NG include studying the late stages of planet formation, testing the stability of planetary systems and evaluating the goodness-of-fit between many planetary system models and observations of extrasolar planet host stars (e.g., radial velocity, astrometry, transit timing). While Swarm-NG focuses on the parallel integration of many planetary systems,the underlying integrators could be applied to a wide variety of problems that require repeatedly integrating a set of ordinary differential equations many times using different initial conditions and/or parameter values., Comment: Submitted to New Astronomy

We present a Bayesian surrogate model for the analysis of periodic or quasi-periodic time series data. We describe a computationally efficient implementation that enables Bayesian model comparison. We apply this model to simulated and real exoplanet observations. We discuss the results and demonstrate some of the challenges for applying our surrogate model to realistic exoplanet data sets. In particular, we find that analyses of real world data should pay careful attention to the effects of uneven spacing of observations and the choice of prior for the "jitter" parameter., Comment: 25 pages, 4 figures, accepted to Bayesian Analysis , special issue for Ninth Valencia International Conference on Bayesian Statistics

If the two planets in the HAT-P-13 system are coplanar, the orbital states provide a probe of the internal planetary structure. Previous analyses of radial velocity and transit timing data of the system suggested that the observational constraints on the orbital states were rather small. We reanalyze the available data, treating the jitter as an unknown MCMC parameter, and find that a wide range of jitter values are plausible, hence the system parameters are less well constrained than previously suggested. For slightly increased levels of jitter ($\sim 4.5\,m\,s^{-1}$) the eccentricity of the inner planet can be in the range $0

Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z<0.7 and at z~2.5. SEGUE-2, which is now completed, measured medium-resolution (R=1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE will obtain high-resolution (R~30,000), high signal-to-noise (S/N>100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged), Comment: Revised to version published in The Astronomical Journal

We ask if Earth-like planets (terrestrial mass and habitable-zone orbit) can be detected in multi-planet systems, using astrometric and radial velocity observations. We report here the preliminary results of double-blind calculations designed to answer this question., Comment: 10 pages, 0 figures