A linearized approach to radial velocity extraction

High-precision radial velocity (RV) measurements are crucial for exoplanet detection and characterisation. Efforts to achieve ~10 cm/s precision have been made over the recent decades, with significant advancements in instrumentation, data reduction techniques, and statistical inference methods. However, despite these efforts, RV precision is currently limited to ~50 cm/s. This value exceeds state-of-the-art spectrographs' expected instrumental noise floor and is mainly attributed to RV signals induced by stellar variability. In this work, we propose a factorisation method to overcome this limitation. The factorisation is particularly suitable for controlling the effect of localised changes in the stellar emission profile, assuming some smooth function of a few astrophysical parameters governs them. We use short-time Fourier transforms (STFT) to infer the RV in a procedure equivalent to least-squares minimisation in the wavelength domain and demonstrate the effectiveness of our method in treating arbitrary temperature fluctuations on the star's surface. The proposed prescription can be naturally generalised to account for other effects, either intrinsic to the star, such as magnetic fields, or extrinsic to it, such as telluric contamination. As a proof-of-concept, we empirically derive a set of factorisation terms describing the Solar centre-to-limb variation and apply them to a set of realistic SOAP-GPU spectral simulations. We discuss the method's capability to mitigate variability-induced RV signals and its potential extensions to serve as a tomographic tool.Comment: 14 pages, 9 figures. Accepted for publication in MNRA

USuRPER: Unit-Sphere Representation PERiodogram for full spectra

We introduce an extension of the periodogram concept to time-resolved spectroscopy. USuRPER -- Unit Sphere Representation PERiodogram -- is a novel technique which opens new horizons in the analysis of astronomical spectra. It can be used to detect a wide range of periodic variability of the spectrum shape. Essentially, the technique is based on representing spectra as unit vectors in a multidimensional hyperspace, hence its name. It is an extension of the phase-distance correlation (PDC) periodogram we had introduced in previous papers, to very high-dimensional data like spectra. USuRPER takes into account the overall shape of the spectrum, sparing the need to reduce it into a single quantity like radial velocity or temperature. Through simulations we demonstrate its performance in various types of spectroscopic variability -- single-lined and double-lined spectroscopic binary stars and pulsating stars. We also show its performance on actual data of a rapidly oscillating Ap (roAp) star. USuRPER is a new tool to explore large time-resolved spectroscopic databases, e.g. APOGEE, LAMOST and the RVS spectra of Gaia. We have made available to the community a public GitHub repository with a Python implementation of USuRPER, to experiment with it and apply it to a wide range of spectroscopic time series.Comment: 7 pages, 10 figures. A&A accepted. The code is available at: https://github.com/SPARTA-dev/SPART

Model Independent Periodogram for Scanning Astrometry

We present a new periodogram for periodicity detection in one-dimensional time-series data from scanning astrometry space missions, like Hipparcos or Gaia. The periodogram is non-parametric and does not rely on a full or approximate orbital solution. Since no specific properties of the periodic signal are assumed, the method is expected to be suitable for the detection of various types of periodic phenomena, from highly eccentric orbits to periodic variability-induced movers. The periodogram is an extension of the phase-distance correlation periodogram (PDC) we introduced in previous papers based on the statistical concept of distance correlation. We demonstrate the performance of the periodogram using publicly available Hipparcos data, as well as simulated data. We also discuss its applicability for Gaia epoch astrometry, to be published in the future data release 4 (DR4).Comment: 7 pages, 4 figures. A&A accepte

Triage of the Gaia astrometric orbits. I. A sample of binaries with probable compact companions

In preparation for the release of the astrometric orbits of Gaia, Shahaf et al. (2019) proposed a triage technique to identify astrometric binaries with compact companions based on their astrometric semi-major axis, parallax, and primary mass. The technique requires the knowledge of the appropriate mass-luminosity relation to rule out single or close-binary main-sequence companions. The recent publication of the Gaia DR3 astrometric orbits used a schematic version of this approach, identifying 735 astrometric binaries that might have compact companions. In this communication, we return to the triage of the DR3 astrometric binaries with more careful analysis, estimating the probability for its astrometric secondary to be a compact object or a main-sequence close binary. We compile a sample of 177 systems with highly-probable non-luminous massive companions, which is smaller but cleaner than the sample reported in Gaia DR3. The new sample includes 8 candidates to be black-hole systems with compact-object masses larger than 2.4 $M_\odot$. The orbital-eccentricity$-$secondary-mass diagram of the other 169 systems suggests a tentative separation between the white-dwarf and the neutron-star binaries. Most white-dwarf binaries are characterized by small eccentricities of about 0.1 and masses of 0.6 $M_\odot$, while the neutron star binaries display typical eccentricities of 0.4 and masses of 1.3 $M_\odot$.Comment: Submitted to MNRAS; 12 pages, 13 figure