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Pulsar distances are notoriously difficult to measure, and play an important role in many fundamental physics experiments, such as pulsar timing arrays. Here, we perform a cross-match between International PTA pulsars (IPTA) and Gaia's Data Release 2 (DR2) and Data Release 3 (DR3). We then combine the IPTA pulsar’s parallax with its binary companion’s parallax, found in Gaia, to improve the distance measurement to the binary. We find seven cross-matched IPTA pulsars in Gaia DR2, and when using Gaia DR3 we find six IPTA pulsar cross-matches but with seven Gaia objects. Moving from Gaia DR2 to Gaia DR3, we find that the Gaia parallaxes for the successfully cross-matched pulsars improved by 53%, and pulsar distances improved by 29%. Finally, we find that binary companions with a <3.0σdetection are unreliable associations, setting a high bar for successful cross-matches.

 

The elemental abundances of planet host stars can shed light on the conditions of planet forming environments. We test if individual abundances of 130 known/candidate planet hosts in APOGEE are statistically different from those of a reference doppelgänger sample. The reference set comprises objects selected with the sameT_eff,$\log g$, [Fe/H], and [Mg/H] as each Kepler Object of Interest (KOI). We predict twelve individual abundances (X = C, N, O, Na, Al, Si, Ca, Ti, V, Cr, Mn, Ni) for the KOIs and their doppelgängers using a local linear model of these four parameters, training on ASPCAP abundance measurements for a sample of field stars with high-fidelity (signal-to-noise ratio > 200) APOGEE observations. We compare element prediction residuals (model–measurement) for the two samples and find them to be indistinguishable, given a high-quality sample selection. We report median intrinsic dispersions of ∼0.038 dex and ∼0.041 dex, for the KOI and doppelgänger samples, respectively, for these elements. We conclude that the individual abundances at fixedT_eff,$\log g$, [Fe/H], and [Mg/H] are unremarkable for known planet hosts. Our results establish an upper limit on the abundance precision required to uncover any chemical signatures of planet formation in planet host stars.

 

Precise Gaia measurements of positions, parallaxes, and proper motions provide an opportunity to calculate 3D positions and 2D velocities (i.e., 5D phase-space) of Milky Way stars. Where available, spectroscopic radial velocity (RV) measurements provide full 6D phase-space information, however there are now and will remain many stars without RV measurements. Without an RV it is not possible to directly calculate 3D stellar velocities; however, one can infer 3D stellar velocities by marginalizing over the missing RV dimension. In this paper, we infer the 3D velocities of stars in the Kepler field in Cartesian Galactocentric coordinates (vx, vy, vz). We directly calculate velocities for around a quarter of all Kepler targets, using RV measurements available from the Gaia, LAMOST, and APOGEE spectroscopic surveys. Using the velocity distributions of these stars as our prior, we infer velocities for the remaining three quarters of the sample by marginalizing over the RV dimension. The median uncertainties on our inferred vx, vy, and vz velocities are around 4, 18, and 4 km/s, respectively. We provide 3D velocities for a total of 148,590 stars in the Kepler field. These 3D velocities could enable kinematic age-dating, Milky Way stellar population studies, and other scientific studies using the benchmark sample of well-studied Kepler stars. Although the methodology used here is broadly applicable to targets across the sky, our prior is specifically constructed from and for the Kepler field. Care should be taken to use a suitable prior when extending this method to other parts of the Galaxy. 

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 intraday scatter of only 15–30 cm s⁻¹. 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.

 

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 Extreme-precision Spectrograph (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 radial-velocity (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.