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David Bianchi

Publications and source records attributed to David Bianchi.

3 recordsLinked to original sources

SpecDis: Value added distance catalogue for 4 million stars from DESI Year-1 data

We present the SpecDis value added stellar distance catalog accompanying DESI DR1. SpecDis trains a feed-forward Neural Network (NN) with Gaia parallaxes and gets the distance estimates. To build up unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead we incorporate parallax error into the loss function. Moreover, we employ Principal Component Analysis (PCA) to reduce the noise and dimensionality of stellar spectra. Validated by independent external samples of member stars with precise distances from globular clusters (GCs), dwarf galaxies, stellar streams, combined with blue horizontal branch (BHB) stars, we demonstrate that our distance measurements show no significant bias up to 100kpc, and are much more precise than Gaia parallax beyond 7kpc. The median distance uncertainties are 23%, 19%, 11% and 7% for S/N $<$ 20, 20 $\leq$ S/N$<$ 60, 60 $\leq$ S/N $<$ 100 and S/N $\geq$ 100. Selecting stars with $\log g<3.8$ and distance uncertainties smaller than 25%, we have more than 74,000 giant candidates within 50kpc to the Galactic center and 1,500 candidates beyond this distance. Additionally, we develop a Gaussian mixture model to identify unresolvable equal-mass binaries by modeling the discrepancy between the NN-predicted and the geometric absolute magnitudes from Gaia parallaxes and identify 120,000 equal-mass binary candidates. Our final catalog provides distances and distance uncertainties for $>$ 4 million stars, offering a valuable resource for Galactic astronomy.

astro-ph.GA

Multimodal Search in Chemical Documents and Reactions

We present a multimodal search tool that facilitates retrieval of chemical reactions, molecular structures, and associated text from scientific literature. Queries may combine molecular diagrams, textual descriptions, and reaction data, allowing users to connect different representations of chemical information. To support this, the indexing process includes chemical diagram extraction and parsing, extraction of reaction data from text in tabular form, and cross-modal linking of diagrams and their mentions in text. We describe the system's architecture, key functionalities, and retrieval process, along with expert assessments of the system. This demo highlights the workflow and technical components of the search system.

cs.IR

Stellar reddening map from DESI imaging and spectroscopy

We present new Galactic dust reddening maps of the high Galactic latitude sky using DESI imaging and spectroscopy. We directly measure the reddening of 2.6 million stars by comparing the observed stellar colors in $g-r$ and $r-z$ from DESI imaging with the synthetic colors derived from DESI spectra from the first two years of the survey. The reddening in the two colors is on average consistent with the Fitzpatrick (1999) extinction curve with $R_\mathrm{V}=3.1$. We find that our reddening maps differ significantly from the commonly used Schlegel et al. (1998) (SFD) reddening map (by up to 80 mmag in $E(B-V)$), and we attribute most of this difference to systematic errors in the SFD map. To validate the reddening map, we select a galaxy sample with extinction correction based on our reddening map, and this yields significantly better uniformity than the SFD extinction correction. Finally, we discuss the potential systematic errors in the DESI reddening measurements, including the photometric calibration errors that are the limiting factor on our accuracy. The $E(g-r)$ and $E(r-z)$ maps presented in this work, and for convenience their corresponding $E(B-V)$ maps with SFD calibration, are publicly available.

astro-ph.GA