Search

We identify and investigate known late M, L and T dwarfs in the Gaia second data release. This sample is being used as a training set in the Gaia data processing chain of the ultra cool dwarfs work package. We find 695 objects in the optical spectral range M8 to T6 with accurate Gaia coordinates, proper motions, and parallaxes which we combine with published spectral types and photometry from large area optical and infrared sky surveys. We find that 100 objects are in 47 multiple systems, of which 27 systems are published and 20 are new. These will be useful benchmark systems and we discuss the requirements to produce a complete catalog of multiple systems with an ultra cool dwarf component. We examine the magnitudes in the Gaia passbands and find that the GBP magnitudes are unreliable and should not be used for these objects. We examine progressively redder colour magnitude diagrams and see a notable increase in the main sequence scatter and a bivariate main sequence for old and young objects. We provide an absolute magnitude spectral sub-type calibration for G and GRP passbands along with linear fits over the range M8 L8 for other passbands., Comment: 19 pages, 24 figures, submitted to MNRAS but still time to make minor changes

Context. Ruprecht 147 is the oldest (2.5 Gyr) open cluster in the solar vicinity (< 300 pc), making it an important target for stellar evolution studies and exoplanet searches. Aims. Derive a census of members and the luminosity, mass, and spatial distributions of the cluster. Methods. We use an astro-photometric data set including all available information from the literature together with our own observations. We process the data with an updated version of an existent membership selection methodology. Results. We identify 259 high-probability candidate members, including 58 previously unreported. All these candidates cover the luminosity interval between G > 6 mag to i< 21 mag. The cluster luminosity and mass distributions are derived with an unprecedented level of details allowing us to recognize, among other features, the Wielen dip. The mass distribution in the low-mass regime drops sharply at 0.4 $M_{\odot}$ even though our data are sensitive to stellar masses down to 0.1 $M_{\odot}$, suggesting that most very-low-mass members left the cluster as the result of its dynamical evolution. In addition, the cluster is highly elongated (ellipticity $\sim$ 0.5) towards the galactic plane, and mass segregated. Conclusions. Our combined Gaia+DANCe data set allows us to obtain an extended list of cluster candidate members, and to derive luminosity, mass and projected spatial distributions in the oldest open cluster of the solar vicinity., Comment: 25 pages

Cavity optomechanics has achieved the major breakthrough of the preparation and observation of macroscopic mechanical oscillators in peculiarly quantum states. The development of reliable indicators of the oscillator properties in these conditions is important also for applications to quantum technologies. We compare two procedures to infer the oscillator occupation number, minimizing the necessity of system calibrations. The former starts from homodyne spectra, the latter is based on the measurement of the motional sidebands asymmetry in heterodyne spectra. Moreover, we describe and discuss a method to control the cavity detuning, that is a crucial parameter for the accuracy of the latter, intrinsically superior procedure.

More than half a million of the 1.69 billion sources in Gaia Data Release 2 (DR2) are published with photometric time series that exhibit light variations during the 22 months of observation. An all-sky classification of common high-amplitude pulsators (Cepheids, long-period variables, Delta Scuti / SX Phoenicis, and RR Lyrae stars) is provided for stars with brightness variations greater than 0.1 mag in G band. A semi-supervised classification approach was employed, firstly training multi-stage random forest classifiers with sources of known types in the literature, followed by a preliminary classification of the Gaia data and a second training phase that included a selection of the first classification results to improve the representation of some classes, before the improved classifiers were applied to the Gaia data. Dedicated validation classifiers were used to reduce the level of contamination in the published results. A relevant fraction of objects were not yet sufficiently sampled for reliable Fourier series decomposition, consequently classifiers were based on features derived from statistics of photometric time series in the G, BP, and RP bands, as well as from some astrometric parameters. The published classification results include 195,780 RR Lyrae stars, 150,757 long-period variables, 8550 Cepheids, and 8882 Delta Scuti / SX Phoenicis stars. All of these results represent candidates whose completeness and contamination are described as a function of variability type and classification reliability. Results are expressed in terms of class labels and classification scores, which are available in the vari_classifier_result table of the Gaia archive., Comment: 21 pages, 33 figures, with minor revisions, in press (Astronomy & Astrophysics)

Optomechanical SiN nano-oscillators in high-finesse Fabry-Perot cavities can be used to investigate the interaction between mechanical and optical degree of freedom for ultra-sensitive metrology and fundamental quantum mechanical studies. In this work we present a nano-oscillator made of a high-stress round-shaped SiN membrane with an integrated on-chip 3D seismic filter properly designed to reduce mechanical losses. This oscillator works in the 200 kHz - 5 MHz range and features a mechanical quality factor of $Q\simeq10^7$ and a Q-frequency product in excess of $6.2 \times 10^{12}$ Hz at room temperature, fulfilling the minimum requirement for quantum ground-state cooling of the oscillator in an optomechanical cavity. The device is obtained by MEMS DRIE bulk micromachining with a two-side silicon processing on a Silicon-On-Insulator (SOI) wafer. The microfabrication process is quite flexible and additional layers could be deposited over the SiN membrane before the DRIE steps, if required for a sensing application. Therefore, such oscillator is a promising candidate for quantum sensing applications in the context of the emerging field of Quantum Technologies.

Motivation: The scratch assay is a standard experimental protocol used to characterize cell migration. It can be used to identify genes that regulate migration and evaluate the efficacy of potential drugs that inhibit cancer invasion. In these experiments, a scratch is made on a cell monolayer and recolonisation of the scratched region is imaged to quantify cell migration rates. A drawback of this methodology is the lack of its reproducibility resulting in irregular cell-free areas with crooked leading edges. Existing quantification methods deal poorly with such resulting irregularities present in the data. Results: We introduce a new quantification method that can analyse low quality experimental data. By considering in-silico and in-vitro data, we show that the method provides a more accurate statistical classification of the migration rates than two established quantification methods. The application of this method will enable the quantification of migration rates of scratch assay data previously unsuitable for analysis. Availability and Implementation: The source code and the implementation of the algorithm as a GUI along with an example dataset and user instructions, are available in https://bitbucket.org/anavictoria-ponce/local_migration_quantification_scratch_assays/src/master/. The datasets are available in https://ganymed.math.uni-heidelberg.de/~victoria/publications.shtml.

We present results from the analysis of 401 RR Lyrae stars (RRLs) belonging to the field of the Milky Way (MW). For a fraction of them multi-band ($V$, $K_{\rm s}$, $W1$) photometry, metal abundances, extinction values and pulsation periods are available in the literature and accurate trigonometric parallaxes measured by the Gaia mission alongside Gaia $G$-band time-series photometry have become available with the Gaia second data release (DR2) on 2018 April 25. Using a Bayesian fitting approach we derive new near-, mid-infrared period-absolute magnitude-metallicity ($PMZ$) relations and new absolute magnitude-metallicity relations in the visual ($M_V - {\rm [Fe/H]}$) and $G$ bands ($M_G - {\rm [Fe/H]}$), based on the Gaia DR2 parallaxes. We find the dependence of luminosity on metallicity to be higher than usually found in the literature, irrespective of the passband considered. Running the adopted Bayesian model on a simulated dataset we show that the high metallicity dependence is not caused by the method, but likely arises from the actual distribution of the data and the presence of a zero-point offset in the Gaia parallaxes. We infer a zero-point offset of $-0.057$ mas, with the Gaia DR2 parallaxes being systematically smaller. We find the RR Lyrae absolute magnitude in the $V$, $G$, $K_{\rm s}$ and $W1$ bands at metallicity of [Fe/H]=$-1.5$ dex and period of P = 0.5238 days, based on Gaia DR2 parallaxes to be $M_V = 0.66\pm0.06$ mag, $M_G = 0.63\pm0.08$ mag, $M_{K_{\rm s}} = -0.37\pm0.11$ mag and $M_{W1} = -0.41\pm0.11$ mag, respectively., Comment: 18 pages, 21 figures, 4 tables. Accepted for publication in MNRAS

Gaia DR2 provides a unique all-sky catalogue of 550'737 variable stars, of which 151'761 are long-period variable (LPV) candidates with G variability amplitudes larger than 0.2 mag (5-95% quantile range). About one-fifth of the LPV candidates are Mira candidates, the majority of the rest are semi-regular variable candidates. For each source, G, BP , and RP photometric time-series are published, together with some LPV-specific attributes for the subset of 89'617 candidates with periods in G longer than 60 days. We describe this first Gaia catalogue of LPV candidates, and present various validation checks. Various samples of LPVs were used to validate the catalogue: a sample of well-studied very bright LPVs with light curves from the AAVSO that are partly contemporaneous with Gaia light curves, a sample of Gaia LPV candidates with good parallaxes, the ASAS_SN catalogue of LPVs, and the OGLE catalogues of LPVs towards the Magellanic Clouds and the Galactic bulge. The analyses of these samples show a good agreement between Gaia DR2 and literature periods. The same is globally true for bolometric corrections of M-type stars. The main contaminant of our DR2 catalogue comes from young stellar objects (YSOs) in the solar vicinity (within ~1 kpc), although their number in the whole catalogue is only at the percent level. A cautionary note is provided about parallax-dependent LPV attributes published in the catalogue. This first Gaia catalogue of LPVs approximately doubles the number of known LPVs with amplitudes larger than 0.2 mag, despite the conservative candidate selection criteria that prioritise low contamination over high completeness, and despite the limited DR2 time coverage compared to the long periods characteristic of LPVs. It also contains a small set of YSO candidates, which offers the serendipitous opportunity to study these objects at an early stage of the Gaia data releases., Comment: Accepted for publication in A&A. 29 pages, 52 figures

The Gaia second Data Release (DR2) presents a first mapping of full-sky RR Lyrae stars and Cepheids observed by the spacecraft during the initial 22 months of science operations. The Specific Object Study (SOS) pipeline, developed to validate and fully characterise Cepheids and RR Lyrae stars (SOS Cep&RRL) observed by Gaia, has been presented in the documentation and papers accompanying the Gaia first Data Release. Here we describe how the SOS pipeline was modified to allow for processing the Gaia multiband (G, G_BP and G_RP) time series photometry of all-sky candidate variables and produce specific results for confirmed RR Lyrae stars and Cepheids that are published in the DR2 catalogue. The SOS Cep&RRL processing uses tools such as the period-amplitude and the period-luminosity relations in the G band. For the analysis of the Gaia DR2 candidates we also used tools based on the G_BP and G_RP photometry, such as the period-Wesenheit relation in (G,G_RP). Multiband time series photometry and characterisation by the SOS Cep&RRL pipeline are published in Gaia DR2 for 150,359 such variables (9,575 classified as Cepheids and 140,784 as RR Lyrae stars) distributed all over the sky. The sample includes variables in 87 globular clusters and 14 dwarf galaxies. To the best of our knowledge, as of 25 April 2018, variability of 50,570 of these sources (350 Cepheids and 50,220 RR Lyrae stars) is not known in the literature, hence likely they are new discoveries by Gaia. An estimate of the interstellar absorption is published for 54,272 fundamental-mode RR Lyrae stars from a relation based on the G-band amplitude and the pulsation period. Metallicities derived from the Fourier parameters of the light curves are also released for 64,932 RR Lyrae stars and 3,738 fundamental-mode classical Cepheids with period shorter than 6.3 days., Comment: 46 pages, 46 figures, 5 tables. Accepted for publication in Astronomy & Astrophysics

We highlight the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD). Gaia allows us to present many different HRDs, depending in particular on stellar population selections. We do not aim here for completeness in terms of types of stars or stellar evolutionary aspects. Instead, we have chosen several illustrative examples. We describe some of the selections that can be made in Gaia DR2 to highlight the main structures of the Gaia HRDs. We select both field and cluster (open and globular) stars, compare the observations with previous classifications and with stellar evolutionary tracks, and we present variations of the Gaia HRD with age, metallicity, and kinematics. Late stages of stellar evolution such as hot subdwarfs, post-AGB stars, planetary nebulae, and white dwarfs are also analysed, as well as low-mass brown dwarf objects. The Gaia HRDs are unprecedented in both precision and coverage of the various Milky Way stellar populations and stellar evolutionary phases. Many fine structures of the HRDs are presented. The clear split of the white dwarf sequence into hydrogen and helium white dwarfs is presented for the first time in an HRD. The relation between kinematics and the HRD is nicely illustrated. Two different populations in a classical kinematic selection of the halo are unambiguously identified in the HRD. Membership and mean parameters for a selected list of open clusters are provided. They allow drawing very detailed cluster sequences, highlighting fine structures, and providing extremely precise empirical isochrones that will lead to more insight in stellar physics. Gaia DR2 demonstrates the potential of combining precise astrometry and photometry for large samples for studies in stellar evolution and stellar population and opens an entire new area for HRD-based studies., Comment: Published in the A&A Gaia Data Release 2 special issue. Tables 2 and A.4 corrected. Tables available at http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/616/A10

The second Gaia data release (GDR2) provides precise five-parameter astrometric data (positions, proper motions and parallaxes) for an unprecedented amount of sources (more than $1.3$ billion, mostly stars). The use of this wealth of astrometric data comes with a specific challenge: how does one properly infer from these data the astrophysical parameters of interest? The main - but not only - focus of this paper is the issue of the estimation of distances from parallaxes, possibly combined with other information. We start with a critical review of the methods traditionally used to obtain distances from parallaxes and their shortcomings. Then we provide guidelines on how to use parallaxes more efficiently to estimate distances by using Bayesian methods. In particular also we show that negative parallaxes, or parallaxes with relatively larger uncertainties still contain valuable information. Finally, we provide examples that show more generally how to use astrometric data for parameter estimation, including the combination of proper motions and parallaxes and the handling of covariances in the uncertainties. The paper contains examples based on simulated Gaia data to illustrate the problems and the solutions proposed. Furthermore, the developments and methods proposed in the paper are linked to a set of tutorials included in the Gaia archive documentation that provide practical examples and a good starting point for the application of the recommendations to actual problems. In all cases the source code for the analysis methods is provided. Our main recommendation is to always treat the derivation of (astro-) physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach., Comment: Accepted for publication in the special issue "Gaia data release 2" of Astronomy & Astrophysics

The Gaia Data Release 2 (DR2): we summarise the processing and results of the identification of variable source candidates of RR Lyrae stars, Cepheids, long period variables (LPVs), rotation modulation (BY Dra-type) stars, delta Scuti & SX Phoenicis stars, and short-timescale variables. In this release we aim to provide useful but not necessarily complete samples of candidates. The processed Gaia data consist of the G, BP, and RP photometry during the first 22 months of operations as well as positions and parallaxes. Various methods from classical statistics, data mining and time series analysis were applied and tailored to the specific properties of Gaia data, as well as various visualisation tools. The DR2 variability release contains: 228'904 RR Lyrae stars, 11'438 Cepheids, 151'761 LPVs, 147'535 stars with rotation modulation, 8'882 delta Scuti & SX Phoenicis stars, and 3'018 short-timescale variables. These results are distributed over a classification and various Specific Object Studies (SOS) tables in the Gaia archive, along with the three-band time series and associated statistics for the underlying 550'737 unique sources. We estimate that about half of them are newly identified variables. The variability type completeness varies strongly as function of sky position due to the non-uniform sky coverage and intermediate calibration level of this data. The probabilistic and automated nature of this work implies certain completeness and contamination rates which are quantified so that users can anticipate their effects. This means that even well-known variable sources can be missed or misidentified in the published data. The DR2 variability release only represents a small subset of the processed data. Future releases will include more variable sources and data products; however, DR2 shows the (already) very high quality of the data and great promise for variability studies., Comment: 21 pages, 10 figures, 5 tables, accepted by Astronomy & Astrophysics, added several language corrections, and expanded Gaia archive query examples

Aims. We develop, test and characterise of a new statistical tool (intelligent system) for the sifting and analysis of nearby young open cluster (NYOC) populations. Methods. Using a Bayesian formalism, this statistical tool is able to obtain the posterior distributions of parameters governing the cluster model. It also uses hierarchical bayesian models to establish weakly informative priors, and incorporates the treatment of missing values and non-homogeneous (heteroscedastic) observational uncertainties. Results. From simulations, we estimate that this statistical tool renders kinematic (proper motion) and photometric (luminosity) distributions of the cluster population with a contamination rate of $5.8 \pm 0.2$ %. The luminosity distributions and present day mass function agree with the ones found by Bouy et al. (2015b) on the completeness interval of the survey. At the probability threshold of maximum accuracy, the classifier recovers $\sim$ 90% of Bouy et al. (2015b) candidate members and finds 10% of new ones. Conclusions. A new statistical tool for the analysis of NYOC is introduced, tested and characterised. Its comprehensive modelling of the data properties allows it to get rid of the biases present in previous works. In particular, those resulting from the use of only completely observed (non-missing) data and the assumption of homoskedastic uncertainties. Also, its Bayesian framework allows it to properly propagate observational uncertainties into membership probabilities and cluster velocity and luminosity distributions. Our results are in a general agreement with those from the literature, although we provide the most up-to-date and extended list of candidate members of the Pleiades cluster., Comment: 30 pages, 21 figures, 1 online table

The second Gaia data release is expected to contain data products from about 22 months of observation. Based on these data, we aim to provide an advance publication of a full-sky Gaia map of RR Lyrae stars. Although comprehensive, these data still contain a significant fraction of sources which are insufficiently sampled for Fourier series decomposition of the periodic light variations. The challenges in the identification of RR Lyrae candidates with (much) fewer than 20 field-of-view transits are described. General considerations of the results, their limitations, and interpretation are presented together with prospects for improvement in subsequent Gaia data releases., Comment: 5 pages, 1 figure, Proceedings of the RR Lyrae 2017 Conference (Revival of the Classical Pulsators: from Galactic Structure to Stellar Interior Diagnostics), to be published in the Proceedings of the Polish Astronomical Society

Aims. We aim at creating a Bayesian model to infer the coefficients of PL or PLZ relations that propagates uncertainties in the observables in a rigorous and well founded way. Methods. We propose a directed acyclic graph to encode the conditional probabilities of the inference model that will allow us to infer probability distributions for the PL and PL(Z) relations. We evaluate the model with several semi-synthetic data sets and apply it to a sample of 200 fundamental mode and first overtone mode RR Lyrae stars for which Gaia DR1 parallaxes and literature Ks-band mean magnitudes are available. We define and test several hyperprior probabilities to verify their adequacy and check the sensitivity of the solution with respect to the prior choice. Results. The main conclusion of this work is the absolute necessity of incorporating the existing correlations between the observed variables (periods, metallicities and parallaxes) in the form of model priors in order to avoid systematically biased results, especially in the case of non-negligible uncertainties in the parallaxes. The tests with the semi-synthetic data based on the data set used in Gaia Collaboration et al. (2017) reveal the significant impact that the existing correlations between parallax, metallicity and periods have on the inferred parameters. The relation coefficients obtained here have been superseded by those presented in Muraveva et al. (2018a), that incorporates the findings of this work and the more recent Gaia DR2 measurements., Comment: 14 pages, 12 figures. Submitted to A&A