Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2512.15904

Binarity Beyond Gaia: The case for a dedicated spectroscopic survey of binary stars

Borja Anguiano
View original source ↗Read source document ↗Export metadata ↓

Abstract

Stellar multiplicity is a fundamental ingredient of stellar astrophysics, yet binary statistics across the Galaxy remain poorly constrained. The \emph{Gaia} mission has revolutionised binary star astrophysics by delivering high-precision astrometry, photometry and global radial velocities, and by providing hundreds of thousands of non-single-star solutions in DR3. However, the RVS magnitude limit, mission time span and scanning law impose strong selection effects in period, mass ratio, inclination and semi-amplitude, leaving large regions of the binary parameter space either sparsely sampled or effectively inaccessible. In this white paper we outline the case for a dedicated, wide-field, multi-epoch spectroscopic survey explicitly optimised for binary science: deeper than the \emph{Gaia} RVS limit, with flexible cadence from hours to years, and with moderate to high spectral resolution. Using a simplified forward model of \emph{Gaia} DR5-like performance, we highlight the populations for which robust orbital solutions will be rare (ultra short period, very long period, low-amplitude and compact-object binaries), and show how a ``Binarity Beyond \emph{Gaia}'' survey would fill these gaps. Such a programme would deliver a bias correctable census of stellar multiplicity across the Milky Way and provide the spectroscopic backbone needed to exploit binary samples from \emph{Rubin}/LSST, \emph{Roman} and \emph{LISA}.

Explore related subjects

astro-ph.IMastro-ph.GAastro-ph.SR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Borja Anguiano. 2025-12-17. Binarity Beyond Gaia: The case for a dedicated spectroscopic survey of binary stars. https://arxiv.org/abs/2512.15904

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Radial Pulsations in Polaris: A Secondary Science Application of Cherenkov Telescopes via Intensity Interferometry

Ground-based Cherenkov telescopes, which are typically inoperative during moonlit nights for gamma-ray observations, offer a valuable opportunity during this time for secondary scientific applications through Intensity Interferometry (II). Recent developments and observations suggest that implementing II instrumentation on existing and planned Imaging Atmospheric Cherenkov Telescopes (IACTs) can significantly advance optical stellar measurements. Motivated by the resurgence of II efforts over the past two decades, this work presents simulations demonstrating the estimation of stellar parameters for a radially pulsating star, such as Polaris, using either a single telescope or multiple telescopes. For single-telescope simulations, we assume that the photon pixels in the camera are mapped onto four distinct regions of the aperture, generating multiple baselines and enabling enhanced observational plane coverage. These results highlight the potential of Cherenkov telescopes in India for high-resolution optical astronomy during otherwise inoperative periods and offer promising insights into the characterization of bright stellar objects with unprecedented precision.

astro-ph.IM↗
arXiv2026

Parallel adaptive reweighting importance sampling for Bayesian astrophysics

Efficient sampling from high-dimensional, multi-modal posteriors is a central challenge in Bayesian inference across the physical sciences. Gravitational-wave (GW) astronomy, where likelihood evaluations are computationally expensive and posteriors are complex, is one application motivating this work. Popular families of methods like Markov-chain Monte Carlo, nested sampling, and importance sampling all rely on proposal distributions to guide exploration. Because prior knowledge of the target is often limited, practitioners can adopt adaptive proposals that iteratively refine themselves using information gained from previously drawn samples. Traditional adaptive strategies, however, struggle in high-dimensional multi-modal settings: complex, non-linear correlations are hard to capture, and hyperparameters typically require tedious, problem-specific tuning. To address these issues, we introduce Parallel Adaptive Reweighting Importance Sampling (PARIS; descriptively, ``seed sampling''). PARIS models its proposal as a Gaussian mixture whose component centers are the existing samples and whose component weights match the current importance weights. New draws from the proposal therefore concentrate around high-weight regions, while candidate points in unexplored areas receive intentionally inflated weights. As the algorithm continuously reweights all samples up to the latest proposal, any initial over-weighting self-corrects once additional neighbor samples are collected. To enable rapid reweighting, we present an efficient update scheme and evaluate PARIS on illustrative toy problems and more realistic gravitational-wave parameter estimation tasks. PARIS achieves accurate posterior reconstruction and evidence estimation with substantially fewer function evaluations than competing approaches, highlighting its promise for widespread use in astrophysical data analysis.

astro-ph.IM↗
arXiv2026

Ising noise filter: physics-informed filtering for particle detectors

We present the Ising noise filter, a highly portable, graph-based pre-filtering algorithm for early-stage background suppression in particle accelerators and astrophysical detectors. Standard noise rejection methods relying on track fitting suffer from severe combinatorial explosion. Our method bypasses this by mapping individual detector hits to a network of binary spins and minimizing an energy functional. The interaction kernels are physics-informed, tailored to the underlying physics and geometry of the experiment. We demonstrate the efficacy of this approach in two distinct experimental regimes. Applied to the Baikal-GVD neutrino telescope the filter yields fast, standard-quality noise rejection with 96.8% recall for astrophysical neutrinos. For the SPD detector at the NICA collider the filter attains recall of 97% on a toy Monte Carlo sample. Furthermore, when combined with a Peterson--Hopfield network for track finding, our physics-informed coupling improves the TrackML score from 0.5 to 0.95.

astro-ph.IM↗