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Crombez, Nathan, El Mustapha Mouaddib, Guillaume Caron e Francois Chaumette. "Visual Servoing With Photometric Gaussian Mixtures as Dense Features". IEEE Transactions on Robotics 35, n. 1 (febbraio 2019): 49–63. http://dx.doi.org/10.1109/tro.2018.2876765.
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Hatfield, P. W., I. A. Almosallam, M. J. Jarvis, N. Adams, R. A. A. Bowler, Z. Gomes, S. J. Roberts e C. Schreiber. "Augmenting machine learning photometric redshifts with Gaussian mixture models". Monthly Notices of the Royal Astronomical Society 498, n. 4 (11 settembre 2020): 5498–510. http://dx.doi.org/10.1093/mnras/staa2741.
Abstract (sommario):
ABSTRACT Wide-area imaging surveys are one of the key ways of advancing our understanding of cosmology, galaxy formation physics, and the large-scale structure of the Universe in the coming years. These surveys typically require calculating redshifts for huge numbers (hundreds of millions to billions) of galaxies – almost all of which must be derived from photometry rather than spectroscopy. In this paper, we investigate how using statistical models to understand the populations that make up the colour–magnitude distribution of galaxies can be combined with machine learning photometric redshift codes to improve redshift estimates. In particular, we combine the use of Gaussian mixture models with the high-performing machine-learning photo-z algorithm GPz and show that modelling and accounting for the different colour–magnitude distributions of training and test data separately can give improved redshift estimates, reduce the bias on estimates by up to a half, and speed up the run-time of the algorithm. These methods are illustrated using data from deep optical and near-infrared data in two separate deep fields, where training and test data of different colour–magnitude distributions are constructed from the galaxies with known spectroscopic redshifts, derived from several heterogeneous surveys.
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Jones, Daniel M., e Alan F. Heavens. "Gaussian mixture models for blended photometric redshifts". Monthly Notices of the Royal Astronomical Society 490, n. 3 (27 settembre 2019): 3966–86. http://dx.doi.org/10.1093/mnras/stz2687.
Abstract (sommario):
ABSTRACT Future cosmological galaxy surveys such as the Large Synoptic Survey Telescope (LSST) will photometrically observe very large numbers of galaxies. Without spectroscopy, the redshifts required for the analysis of these data will need to be inferred using photometric redshift techniques that are scalable to large sample sizes. The high number density of sources will also mean that around half are blended. We present a Bayesian photometric redshift method for blended sources that uses Gaussian mixture models to learn the joint flux–redshift distribution from a set of unblended training galaxies, and Bayesian model comparison to infer the number of galaxies comprising a blended source. The use of Gaussian mixture models renders both of these applications computationally efficient and therefore suitable for upcoming galaxy surveys.
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Ansari, Zoe, Adriano Agnello e Christa Gall. "Mixture models for photometric redshifts". Astronomy & Astrophysics 650 (giugno 2021): A90. http://dx.doi.org/10.1051/0004-6361/202039675.
Abstract (sommario):
Context. Determining photometric redshifts (photo-zs) of extragalactic sources to a high accuracy is paramount to measure distances in wide-field cosmological experiments. With only photometric information at hand, photo-zs are prone to systematic uncertainties in the intervening extinction and the unknown underlying spectral-energy distribution of different astrophysical sources, leading to degeneracies in the modern machine learning algorithm that impacts the level of accuracy for photo-z estimates. Aims. Here, we aim to resolve these model degeneracies and obtain a clear separation between intrinsic physical properties of astrophysical sources and extrinsic systematics. Furthermore, we aim to have meaningful estimates of the full photo-z probability distribution, and their uncertainties. Methods. We performed a probabilistic photo-z determination using mixture density networks (MDN). The training data set is composed of optical (griz photometric bands) point-spread-function and model magnitudes and extinction measurements from the SDSS-DR15 and WISE mid-infrared (3.4 μm and 4.6 μm) model magnitudes. We used infinite Gaussian mixture models to classify the objects in our data set as stars, galaxies, or quasars, and to determine the number of MDN components to achieve optimal performance. Results. The fraction of objects that are correctly split into the main classes of stars, galaxies, and quasars is 94%. Furthermore, our method improves the bias of photometric redshift estimation (i.e., the mean Δz = (zp − zs)/(1 + zs)) by one order of magnitude compared to the SDSS photo-z, and it decreases the fraction of 3σ outliers (i.e., 3 × rms(Δz) < Δz). The relative, root-mean-square systematic uncertainty in our resulting photo-zs is down to 1.7% for benchmark samples of low-redshift galaxies (zs < 0.5). Conclusions. We have demonstrated the feasibility of machine-learning-based methods that produce full probability distributions for photo-z estimates with a performance that is competitive with state-of-the art techniques. Our method can be applied to wide-field surveys where extinction can vary significantly across the sky and with sparse spectroscopic calibration samples. The code is publicly available.
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Wagenveld, J. D., A. Saxena, K. J. Duncan, H. J. A. Röttgering e M. Zhang. "Revealing new high-redshift quasar populations through Gaussian mixture model selection". Astronomy & Astrophysics 660 (aprile 2022): A22. http://dx.doi.org/10.1051/0004-6361/202142445.
Abstract (sommario):
We present a novel method for identifying candidate high-redshift quasars (HzQs; z ≳ 5.5) –which are unique probes of supermassive black hole growth in the early Universe– from large-area optical and infrared photometric surveys. Using Gaussian mixture models to construct likelihoods and incorporating informed priors based on population statistics, our method uses a Bayesian framework to assign posterior probabilities that differentiate between HzQs and contaminating sources. We additionally include deep radio data to obtain informed priors. Using existing HzQ data in the literature, we set a posterior threshold that accepts ∼90% of known HzQs while rejecting > 99% of contaminants such as dwarf stars or lower redshift galaxies. Running the probability selection on test samples of simulated HzQs and contaminants, we find that the efficacy of the probability method is higher than traditional colour cuts, decreasing the fraction of accepted contaminants by 86% while retaining a similar fraction of HzQs. As a test, we apply our method to the Pan-STARRS Data Release 1 (PS1) source catalogue within the HETDEX Spring field area on the sky, covering 400 sq. deg. and coinciding with deep radio data from the LOFAR Two-metre Sky Survey Data Release 1. From an initial sample of ∼5 × 105 sources in PS1, our selection shortlists 251 candidate HzQs, which are further reduced to 63 after visual inspection. Shallow spectroscopic follow-up of 13 high-probability HzQs resulted in the confirmation of a previously undiscovered quasar at z = 5.66 with photometric colours i − z = 1.4, lying outside the typically probed regions when selecting HzQs based on colours. This discovery demonstrates the efficacy of our probabilistic HzQ selection method in selecting more complete HzQ samples, which holds promise when employed on large existing and upcoming photometric data sets.
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D’Isanto, A., e K. L. Polsterer. "Photometric redshift estimation via deep learning". Astronomy & Astrophysics 609 (gennaio 2018): A111. http://dx.doi.org/10.1051/0004-6361/201731326.
Abstract (sommario):
Context. The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application where such new methods improved the results, substantially. Up to now, the vast majority of applied redshift estimation methods have utilized photometric features. Aims. We aim to develop a method to derive probabilistic photometric redshift directly from multi-band imaging data, rendering pre-classification of objects and feature extraction obsolete. Methods. A modified version of a deep convolutional network was combined with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) were applied as performance criteria. We have adopted a feature based random forest and a plain mixture density network to compare performances on experiments with data from SDSS (DR9). Results. We show that the proposed method is able to predict redshift PDFs independently from the type of source, for example galaxies, quasars or stars. Thereby the prediction performance is better than both presented reference methods and is comparable to results from the literature. Conclusions. The presented method is extremely general and allows us to solve of any kind of probabilistic regression problems based on imaging data, for example estimating metallicity or star formation rate of galaxies. This kind of methodology is tremendously important for the next generation of surveys.
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Duncan, Kenneth J. "All-purpose, all-sky photometric redshifts for the Legacy Imaging Surveys Data Release 8". Monthly Notices of the Royal Astronomical Society 512, n. 3 (8 marzo 2022): 3662–83. http://dx.doi.org/10.1093/mnras/stac608.
Abstract (sommario):
ABSTRACT In this paper, we present photometric redshift (photo-z) estimates for the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, currently the most sensitive optical survey covering the majority of the extragalactic sky. Our photo-z methodology is based on a machine-learning approach, using sparse Gaussian processes augmented with Gaussian mixture models (GMMs) that allow regions of parameter space to be identified and trained separately in a purely data-driven way. The same GMMs are also used to calculate cost-sensitive learning weights that mitigate biases in the spectroscopic training sample. By design, this approach aims to produce reliable and unbiased predictions for all parts of the parameter space present in wide area surveys. Compared to previous literature estimates using the same underlying photometry, our photo-zs are significantly less biased and more accurate at z > 1, with negligible loss in precision or reliability for resolved galaxies at z < 1. Our photo-z estimates offer accurate predictions for rare high-value populations within the parent sample, including optically selected quasars at the highest redshifts (z > 6), as well as X-ray or radio continuum selected populations across a broad range of flux (densities) and redshift. Deriving photo-z estimates for the full Legacy Imaging Surveys Data Release 8, the catalogues provided in this work offer photo-z estimates predicted to be of high quality for ≳9 × 108 galaxies over ${\sim}19\, 400\, \text{deg}^{2}$ and spanning 0 < z ≲ 7, offering one of the most extensive samples of redshift estimates ever produced.
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Jang, J. K., Sukyoung K. Yi, Yohan Dubois, Jinsu Rhee, Christophe Pichon, Taysun Kimm, Julien Devriendt et al. "Translators of Galaxy Morphology Indicators between Observation and Simulation". Astrophysical Journal 950, n. 1 (1 giugno 2023): 4. http://dx.doi.org/10.3847/1538-4357/accd68.
Abstract (sommario):
Abstract Based on the recent advancements in numerical simulations of galaxy formation, we anticipate the achievement of realistic models of galaxies in the near future. Morphology is the most basic and fundamental property of galaxies, yet observations and simulations still use different methods to determine galaxy morphology, making it difficult to compare them. We hereby perform a test on the recent NewHorizon simulation, which has spatial and mass resolutions that are remarkably high for a large-volume simulation, to resolve the situation. We generate mock images for the simulated galaxies using SKIRT, which calculates complex radiative transfer processes in each galaxy. We measure morphological and kinematic indicators using photometric and spectroscopic methods following observers’ techniques. We also measure the kinematic disk-to-total ratios using the Gaussian mixture model and assume that they represent the true structural composition of galaxies. We found that spectroscopic indicators such as V/σ and λ R closely trace the kinematic disk-to-total ratios. In contrast, photometric disk-to-total ratios based on the radial profile fitting method often fail to recover the true kinematic structure of galaxies, especially small ones. We provide translating equations between various morphological indicators.
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Escudero, Carlos G., Arianna Cortesi, Favio R. Faifer, Leandro A. Sesto, Analía V. Smith Castelli, Evelyn J. Johnston, Victoria Reynaldi et al. "The complex globular cluster system of the S0 galaxy NGC 4382 in the outskirts of the Virgo Cluster". Monthly Notices of the Royal Astronomical Society 511, n. 1 (8 gennaio 2022): 393–412. http://dx.doi.org/10.1093/mnras/stac021.
Abstract (sommario):
ABSTRACT NGC 4382 is a merger-remnant galaxy that has been classified as morphological type E2, S0, and even Sa. In this work, we performed a photometric and spectroscopic analysis of the globular cluster (GC) system of this peculiar galaxy in order to provide additional information about its history. We used a combination of photometric data in different filters, and multiobject and long-slit spectroscopic data obtained using the Gemini/GMOS instrument. The photometric analysis of the GC system, using the Gaussian Mixture Model algorithm in the colour plane, reveals a complex colour distribution within Rgal < 5 arcmin (26.1 kpc), showing four different groups: the typical blue and red subpopulations, a group with intermediate colours, and the fourth group towards even redder colours. From the spectroscopic analysis of 47 GCs, confirmed members of NGC 4382 based on radial velocities, we verified 3 of the 4 photometric groups from the analysis of their stellar populations using the ULySS code. NGC 4382 presents the classic blue (10.4 ± 2.8 Gyr, [Fe/H] = −1.48 ± 0.18 dex), and red (12.1 ± 2.3 Gyr, [Fe/H] = −0.64 ± 0.26 dex) GCs formed earlier in the lifetime of the galaxy, and a third group of young GCs (2.2 ± 0.9 Gyr; [Fe/H] = −0.05 ± 0.28 dex). Finally, analysis of long-slit data of the galaxy reveals a luminosity-weighted mean age for the stellar population of ∼2.7 Gyr, and an increasing metallicity from [Fe/H] = −0.1 to +0.2 dex in Rgal < 10 arcsec (0.87 kpc). These values, and other morphological signatures in the galaxy, are in good agreement with the younger group of GCs, indicating a common origin as a result of a recent merger.
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Tardugno Poleo, Valentina, Steven L. Finkelstein, Gene Leung, Erin Mentuch Cooper, Karl Gebhardt, Daniel J. Farrow, Eric Gawiser et al. "Identifying Active Galactic Nuclei at z ∼ 3 from the HETDEX Survey Using Machine Learning". Astronomical Journal 165, n. 4 (10 marzo 2023): 153. http://dx.doi.org/10.3847/1538-3881/acba92.
Abstract (sommario):
Abstract We used data from the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) to study the incidence of AGN in continuum-selected galaxies at z ∼ 3. From optical and infrared imaging in the 24 deg2 Spitzer HETDEX Exploratory Large Area survey, we constructed a sample of photometric-redshift selected z ∼ 3 galaxies. We extracted HETDEX spectra at the position of 716 of these sources and used machine-learning methods to identify those which exhibited AGN-like features. The dimensionality of the spectra was reduced using an autoencoder, and the latent space was visualized through t-distributed stochastic neighbor embedding. Gaussian mixture models were employed to cluster the encoded data and a labeled data set was used to label each cluster as either AGN, stars, high-redshift galaxies, or low-redshift galaxies. Our photometric redshift (photoz) sample was labeled with an estimated 92% overall accuracy, an AGN accuracy of 83%, and an AGN contamination of 5%. The number of identified AGN was used to measure an AGN fraction for different magnitude bins. The ultraviolet (UV) absolute magnitude where the AGN fraction reaches 50% is M UV = −23.8. When combined with results in the literature, our measurements of AGN fraction imply that the bright end of the galaxy luminosity function exhibits a power law rather than exponential decline, with a relatively shallow faint-end slope for the z ∼ 3 AGN luminosity function.
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Jadhav, Vikrant V., Clara M. Pennock, Annapurni Subramaniam, Ram Sagar e Prasanta Kumar Nayak. "UOCS – III. UVIT catalogue of open clusters with machine learning-based membership using Gaia EDR3 astrometry". Monthly Notices of the Royal Astronomical Society 503, n. 1 (27 gennaio 2021): 236–53. http://dx.doi.org/10.1093/mnras/stab213.
Abstract (sommario):
ABSTRACT We present a study of six open clusters (Berkeley 67, King 2, NGC 2420, NGC 2477, NGC 2682, and NGC 6940), using the Ultra Violet Imaging Telescope (UVIT) aboard ASTROSAT and Gaia EDR3. We used combinations of astrometric, photometric, and systematic parameters to train and supervise a machine-learning algorithm along with a Gaussian mixture model for the determination of cluster membership. This technique is robust, reproducible, and versatile in various cluster environments. In this study, the Gaia EDR3 membership catalogues are provided along with classification of the stars as members, candidates, and field in the six clusters. We could detect 200–2500 additional members using our method with respect to previous studies, which helped estimate mean space velocities, distances, number of members and core radii. UVIT photometric catalogues, which include blue stragglers, main-sequence, and red giants are also provided. From UV–Optical colour–magnitude diagrams, we found that majority of the sources in NGC 2682 and a few in NGC 2420, NGC 2477, and NGC 6940 showed excess UV flux. NGC 2682 images have 10 white dwarf detection in far-UV. The far-UV and near-UV images of the massive cluster NGC 2477 have 92 and 576 members, respectively, which will be useful to study the UV properties of stars in the extended turn-off and in various evolutionary stages from main sequence to red clump. Future studies will carry out panchromatic and spectroscopic analysis of noteworthy members detected in this study.
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Reinhold, Timo, e Saskia Hekker. "Stellar rotation periods from K2 Campaigns 0–18". Astronomy & Astrophysics 635 (marzo 2020): A43. http://dx.doi.org/10.1051/0004-6361/201936887.
Abstract (sommario):
Context. Rotation period measurements of stars observed with the Kepler mission have revealed a lack of stars at intermediate rotation periods, accompanied by a decrease of photometric variability. Whether this so-called dearth region is a peculiarity of stars in the Kepler field, or reflects a general manifestation of stellar magnetic activity, is still under debate. The K2 mission has the potential to unravel this mystery by measuring stellar rotation and photometric variability along different fields in the sky. Aims. Our goal is to measure stellar rotation periods and photometric variabilities for tens of thousands of K2 stars, located in different fields along the ecliptic plane, to shed light on the relation between stellar rotation and photometric variability. Methods. We use Lomb–Scargle periodograms, auto-correlation and wavelet functions to determine consistent rotation periods. Stellar brightness variability is assessed by computing the variability range, Rvar, from the light curve. We further apply Gaussian mixture models to search for bimodality in the rotation period distribution. Results. Combining measurements from all K2 campaigns, we detect rotation periods in 29 860 stars. The reliability of these periods was estimated from stars observed more than once. We find that 75–90% of the stars show period deviation smaller than 20% between different campaigns, depending on the peak height threshold in the periodograms. For effective temperatures below 6000 K, the variability range shows a local minimum at different periods, consistent with an isochrone age of ∼750 Myr. Additionally, the rotation period distribution shows evidence for bimodality, although the dearth region in the K2 data is less pronounced compared to the Kepler field. The period at the dip of the bimodal distribution shows good agreement with the period at the local variability minimum. Conclusions. We conclude that the rotation period bimodality is present in different fields of the sky, and is hence a general manifestation of stellar magnetic activity. The reduced variability in the dearth region is interpreted as a cancelation between dark spots and bright faculae. Our results strongly advocate that the role of faculae has been underestimated so far, suggesting a more complex dependence of the brightness variability on the rotation period.
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Peña Ramírez, K., C. González-Fernández, A.-N. Chené e S. Ramírez Alegría. "The VVV open cluster project. Near-infrared sequences of NGC 6067, NGC 6259, NGC 4815, Pismis 18, Trumpler 23, and Trumpler 20". Monthly Notices of the Royal Astronomical Society 503, n. 2 (4 marzo 2021): 1864–76. http://dx.doi.org/10.1093/mnras/stab328.
Abstract (sommario):
ABSTRACT Open clusters are central elements of our understanding of the Galactic disc evolution, as an accurate determination of their parameters leads to an unbiased picture of our Galaxy’s structure. Extending the analysis towards fainter magnitudes in cluster sequences has a significant impact on the derived fundamental parameters, such as extinction and total mass. We perform a homogeneous analysis of six open stellar clusters in the Galactic disc using kinematic and photometric information from the Gaia DR2 and VVV surveys: NGC 6067, NGC 6259, NGC 4815, Pismis 18, Trumpler 23, and Trumpler 20. We implement two coarse-to-fine characterization methods: first, we employ Gaussian mixture models to tag fields around each open cluster in the proper motion space, and then we apply an unsupervised machine learning method to make the membership assignment to each cluster. For the studied clusters, with ages in the ∼120–1900 Myr range, we report an increase of ∼45 per cent new member candidates on average in our sample. The data-driven selection approach of cluster members makes our catalogue a valuable resource for testing stellar evolutionary models and for assessing the cluster low-to-intermediate mass populations. This study is the first of a series intended to homogeneously reveal open cluster near-infrared sequences.
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Escudero, Carlos G., Favio R. Faifer, Analía V. Smith Castelli, Mark A. Norris e Juan C. Forte. "Field/isolated lenticular galaxies with high SN values: the case of NGC 4546 and its globular cluster system". Monthly Notices of the Royal Astronomical Society 493, n. 2 (10 febbraio 2020): 2253–70. http://dx.doi.org/10.1093/mnras/staa392.
Abstract (sommario):
ABSTRACT We present a photometric study of the field lenticular galaxy NGC 4546 using Gemini/GMOS imaging in g′r′i′z′. We perform a 2D image decomposition of the surface brightness distribution of the galaxy using galfit, finding that four components adequately describe it. The subtraction of this model from our images and the construction of a colour map allow us to examine in great detail the asymmetric dust structures around the galactic centre. In addition, we perform a detailed analysis of the globular cluster (GC) system of NGC 4546. Using a Gaussian Mixture Model algorithm in the colour–colour plane, we detected hints of multiple groups of GC candidates: the classic blue and red subpopulations, a group with intermediate colours that present a concentrated spatial distribution towards the galaxy, and an additional group towards the red end of the colour distribution. We estimate a total GC population for NGC 4546 of 390 ± 60 members and specific frequency SN = 3.3 ± 0.7, which is relatively high compared to the typical value for galaxies of similar masses and environment. We suggest that the unusual GC population substructures were possibly formed during the interaction that led to the formation of the young ultra-compact dwarf (NGC 4546-UCD1) found in this system. Finally, we estimate the distance modulus of NGC 4546 by analysing its luminosity function, resulting in (m − M) = 30.75 ± 0.12 mag (14.1 Mpc).
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Davis, Brian D., Howard E. Bond, Michael H. Siegel e Robin Ciardullo. "A Census of Above-horizontal-branch Stars in Galactic Globular Clusters*". Astrophysical Journal 926, n. 1 (1 febbraio 2022): 99. http://dx.doi.org/10.3847/1538-4357/ac4224.
Abstract (sommario):
Abstract We have carried out a search for above-horizontal-branch (AHB) stars—objects lying above the horizontal branch (HB) and blueward of the asymptotic giant branch (AGB) in the color–magnitude diagram—in 97 Galactic and seven Magellanic Cloud globular clusters (GCs). We selected AHB candidates based on photometry in the uBVI system, which is optimized for detection of low-surface-gravity stars with large Balmer jumps, in the color range −0.05 ≤ (B − V)0 ≤1.0. We then used Gaia astrometry and Gaussian-mixture modeling to confirm cluster membership and remove field interlopers. Our final catalog contains 438 AHB stars, classified and interpreted in the context of post-HB evolution as follows: (1) AHB1: 280 stars fainter than M V = −0.8, evolving redward from the blue HB (BHB) toward the base of the AGB. (2) Post-AGB (PAGB): 13 stars brighter than M V ≃ −2.75, departing from the top of the AGB and evolving rapidly blueward. (3) AHB2: 145 stars, with absolute magnitudes between those of the AHB1 and PAGB groups. This last category includes a mixture of objects leaving the extreme BHB and evolving toward the AGB, and brighter ones moving back from the AGB toward higher temperatures. Among the AHB1 stars are 59 RR Lyrae interlopers, observed by chance in our survey near maximum light. PAGB and AHB2 stars (including W Virginis Cepheids) overwhelmingly belong to GCs containing BHB stars, in accordance with predictions of post-HB evolutionary tracks. We suggest that most W Vir variables are evolving toward lower temperatures and are in their first crossings of the instability strip. Nonvariable yellow PAGB stars show promise as a Population II standard candle for distance measurement.
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Johnson, Christian I., Robert Michael Rich, Michael D. Young, Iulia T. Simion, William I. Clarkson, Catherine A. Pilachowski, Scott Michael, Andrea Kunder, Andreas Koch e Anna Katherina Vivas. "Blanco DECam Bulge Survey (BDBS) II: project performance, data analysis, and early science results". Monthly Notices of the Royal Astronomical Society 499, n. 2 (3 settembre 2020): 2357–79. http://dx.doi.org/10.1093/mnras/staa2393.
Abstract (sommario):
ABSTRACT The Blanco DECam Bulge Survey (BDBS) imaged more than 200 sq deg of the Southern Galactic bulge using the ugrizY filters of the Dark Energy Camera, and produced point spread function photometry of approximately 250 million unique sources. In this paper, we present details regarding the construction and collation of survey catalogues, and also discuss the adopted calibration and dereddening procedures. Early science results are presented with a particular emphasis on the bulge metallicity distribution function and globular clusters. A key result is the strong correlation (σ ∼ 0.2 dex) between (u − i)o and [Fe/H] for bulge red clump giants. We utilized this relation to find that interior bulge fields may be well described by simple closed box enrichment models, but fields exterior to b ∼ −6° seem to require a secondary metal-poor component. Applying scaled versions of the closed box model to the outer bulge fields is shown to significantly reduce the strengths of any additional metal-poor components when compared to Gaussian mixture models. Additional results include: a confirmation that the u band splits the subgiant branch in M22 as a function of metallicity, the detection of possible extratidal stars along the orbits of M 22 and FSR 1758, and additional evidence that NGC 6569 may have a small but discrete He spread, as evidenced by red clump luminosity variations in the reddest bands. We do not confirm previous claims that FSR 1758 is part of a larger extended structure.
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Bailer-Jones, Coryn A. L., Morgan Fouesneau e Rene Andrae. "Quasar and galaxy classification in Gaia Data Release 2". Monthly Notices of the Royal Astronomical Society 490, n. 4 (21 ottobre 2019): 5615–33. http://dx.doi.org/10.1093/mnras/stz2947.
Abstract (sommario):
ABSTRACT We construct a supervised classifier based on Gaussian Mixture Models to probabilistically classify objects in Gaia data release 2 (GDR2) using only photometric and astrometric data in that release. The model is trained empirically to classify objects into three classes – star, quasar, galaxy – for G ≥ 14.5 mag down to the Gaia magnitude limit of G = 21.0 mag. Galaxies and quasars are identified for the training set by a cross-match to objects with spectroscopic classifications from the Sloan Digital Sky Survey. Stars are defined directly from GDR2. When allowing for the expectation that quasars are 500 times rarer than stars, and galaxies 7500 times rarer than stars (the class imbalance problem), samples classified with a threshold probability of 0.5 are predicted to have purities of 0.43 for quasars and 0.28 for galaxies, and completenesses of 0.58 and 0.72, respectively. The purities can be increased up to 0.60 by adopting a higher threshold. Not accounting for this expected low frequency of extragalactic objects (the class prior) would give both erroneously optimistic performance predictions and severely impure samples. Applying our model to all 1.20 billion objects in GDR2 with the required features, we classify 2.3 million objects as quasars and 0.37 million objects as galaxies (with individual probabilities above 0.5). The small number of galaxies is due to the strong bias of the satellite detection algorithm and on-ground data selection against extended objects. We infer the true number of quasars and galaxies – as these classes are defined by our training set – to be 690 000 and 110 000, respectively (±50 per cent). The aim of this work is to see how well extragalactic objects can be classified using only GDR2 data. Better classifications should be possible with the low resolution spectroscopy (BP/RP) planned for GDR3.
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Black, William K., e August E. Evrard. "Cosmic Dragons: A Two-Component Mixture Model of COSMOS Galaxies". Open Journal of Astrophysics 7 (4 aprile 2024). http://dx.doi.org/10.33232/001c.116171.
Abstract (sommario):
Using the photometric population prediction method {}, we characterize the Red Sequence (RS) and Blue Cloud (BC) of DES galaxies in the COSMOS field. Red Dragon (RD) uses a redshift-evolving, error-corrected Gaussian mixture model to detail the distribution of photometric colors, smoothly parameterizing the two populations with relative weights, mean colors, intrinsic scatters, and inter-color correlations. This resulting fit of RS and BC yields RS membership probabilities for each galaxy. Even when training on only DES main bands griz, RD selects the quiescent population (defined here as galaxies with ) with ≳90% balanced accuracy out to z=2; augmenting with extended photometry from VIRCAM improves this accuracy to ∼95% out to z=3. We measure redshift evolution of sSFR and galactic age in several stellar mass bins, finding that the BC is consistently more star-forming (by ) and typically younger (by ) than the RS (up to z∼1.4). This characterization of both RS and BC as functions of redshift and stellar mass improves our understanding of both populations and opens the door to more precise galaxy population characterization in future deep optical and IR systems.
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Liu, Wei, Yude Bu, Xiaoming Kong, Zhenping Yi e Meng Liu. "Identifying hot subdwarf stars from photometric data using a Gaussian mixture model and graph neural network". Publications of the Astronomical Society of Japan, 9 aprile 2024. http://dx.doi.org/10.1093/pasj/psae013.
Abstract (sommario):
Abstract Hot subdwarf stars are very important for understanding stellar evolution, stellar astrophysics, and binary star systems. Identifying more such stars can help us better understand their statistical distribution, properties, and evolution. In this paper, we present a new method to search for hot subdwarf stars in photometric data (BP, RP, G, g, r, i, z, y) using a machine-learning algorithm, a graph neural network, and a Gaussian mixture model. We use a Gaussian mixture model and Markov distance to build the graph structure, and on the graph structure we use a graph neural network to identify hot subdwarf stars from a dataset containing 31838 stars, with the recall, precision, and F1 score maximized on the original, weight, and synthetic minority oversampling technique datasets. Finally, to validate the model, we selected about 2116 hot subdwarf candidates from the Gaia Data Release 3 database and compared them with the studies by Culpan et al. (2022, A&A, 662, A40) and Geier et al. (2019, A&A, 621, A38).
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Garcia, Jonathan Cabrera, Timothy C. Beers, Yang Huang, Xin-Yi Li, Gaochao Liu, Huawei Zhang, Jihye Hong et al. "Probing the Galactic halo with RR Lyrae stars – V. Chemistry, kinematics, and dynamically tagged groups". Monthly Notices of the Royal Astronomical Society, 5 dicembre 2023. http://dx.doi.org/10.1093/mnras/stad3674.
Abstract (sommario):
Abstract We employ a sample of 135,873 RR Lyrae stars (RRLs) with precise photometric-metallicity and distance estimates from the newly calibrated P–φ31–R21–[Fe/H] and Gaia G-band P–R21–[Fe/H] absolute magnitude-metallicity relations of Li et al., combined with available proper motions from Gaia EDR3, and 6955 systemic radial velocities from Gaia DR3 and other sources, in order to explore the chemistry and kinematics of the halo of the Milky Way (MW). This sample is ideally suited for characterization of the inner- and outer-halo populations of the stellar halo, free from the bias associated with spectroscopically selected probes, and for estimation of their relative contributions as a function of Galactocentric distance. The results of a Gaussian Mixture-Model analysis of these contributions are broadly consistent with other observational studies of the halo, and with expectations from recent MW simulation studies. We apply the HDBSCAN clustering method to the specific energies and cylindrical actions (E, Jr, Jφ, Jz), identifying 97 Dynamically Tagged Groups (DTGs) of RRLs, and explore their associations with recognized substructures of the MW. The precise photometric-distance determinations (relative distance errors on the order of 5 % or better), and the resulting high-quality determination of dynamical parameters, yield highly statistically significant (low) dispersions of [Fe/H] for the stellar members of the DTGs compared to random draws from the full sample, indicating that they share common star-formation and chemical histories, influenced by their birth environments.
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Ramírez, K. Peña, L. C. Smith, S. Ramírez Alegría, A.-N. Chené, C. González-Fernández, P. W. Lucas e D. Minniti. "The VVV open cluster project II. Near-infrared sequences of 37 open clusters on eight-dimensional parameter space". Monthly Notices of the Royal Astronomical Society, 11 maggio 2022. http://dx.doi.org/10.1093/mnras/stac1296.
Abstract (sommario):
Abstract Open clusters are key coeval structures that help us understand star formation stellar evolution and trace the physical properties of our Galaxy. In the past years, the isolation of open clusters from the field has been heavily alleviated by the access to accurate large-scale stellar parallaxes and proper motions along a determined line of sight. Still, there are limitations regarding their completeness since large-scale studies rely on optical wavelengths. Here we extend the open clusters sequences towards fainter magnitudes complementing the Gaia photometric and astrometric information with near-infrared data from the VVV survey. We performed a homogeneous analysis on 37 open clusters implementing two coarse-to-fine characterization methods: extreme deconvolution Gaussian mixture models coupled with an unsupervised machine learning method on 8-dimensional parameter space. The process allowed us to separate the clusters from the field at near-infrared wavelengths. We report an increase of ∼47 per cent new member candidates on average in our sample (considering only sources with high membership probability p≧0.9). This study is the second in a series intended to reveal open cluster near-infrared sequences homogeneously.
22
Fraser, T. S., R. Tojeiro e H. G. Chittenden. "Applying unsupervised learning to resolve evolutionary histories and explore the galaxy-halo connection in IllustrisTNG". Monthly Notices of the Royal Astronomical Society, 11 gennaio 2023. http://dx.doi.org/10.1093/mnras/stad015.
Abstract (sommario):
Abstract We examine the effectiveness of identifying distinct evolutionary histories in IllustrisTNG-100 galaxies using unsupervised machine learning with Gaussian Mixture Models. We focus on how clustering compressed metallicity histories and star formation histories produces subpopulations of galaxies with distinct evolutionary properties (for both halo mass assembly and merger histories). By contrast, clustering with photometric colours fail to resolve such histories. We identify several populations of interest that reflect a variety of evolutionary scenarios supported by the literature. Notably, we identify a population of galaxies inhabiting the upper-red sequence, M* > 1010M⊙ that has a significantly higher ex-situ merger mass fraction present at fixed masses, and a star formation history that has yet to fully quench, in contrast to an overlapping, satellite-dominated population along the red sequence, which is distinctly quiescent. Extending the clustering to study four clusters instead of three further divides quiescent galaxies, while star forming ones are mostly contained in a single cluster, demonstrating a variety of supported pathways to quenching. In addition to these populations, we identify a handful of populations from our other clusters that are readily applicable to observational surveys, including a population related to post starburst (PSB) galaxies, allowing for possible extensions of this work in an observational context, and to corroborate results within the IllustrisTNG ecosystem.
23
Nanni, Riccardo, Joseph F. Hennawi, Feige Wang, Jinyi Yang, Jan-Torge Schindler e Xiaohui Fan. "Paving the way for euclid and JWST via probabilistic selection of high-redshift quasars". Monthly Notices of the Royal Astronomical Society, 23 luglio 2022. http://dx.doi.org/10.1093/mnras/stac1944.
Abstract (sommario):
Abstract We introduce a probabilistic approach to select 6 ≤ z ≤ 8 quasar candidates for spectroscopic follow-up, which is based on density estimation in the high-dimensional space inhabited by the optical and near-infrared photometry. Densities are modeled as Gaussian mixtures with principled accounting of errors using the extreme deconvolution (XD) technique, generalizing an approach successfully used to select lower redshift (z ≤ 3) quasars. We train the probability density of contaminants on 1,902,071 7-d flux measurements from the 1076 deg2 overlapping area from the DECaLS (z), VIKING (YJHKs), and unWISE (W1W2) imaging surveys, after requiring they dropout of DECaLS g and r, whereas the distribution of high-z quasars are trained on synthetic model photometry. Extensive simulations based on these density distributions and current estimates of the quasar luminosity function indicate that this method achieves a completeness of $\ge 56{{\%}}$ and an efficiency of $\ge 5{{\%}}$ for selecting quasars at 6 < z < 8 with JAB < 21.5. Among the classified sources are 8 known 6 < z < 7 quasars, of which 2/8 are selected suggesting a completeness $\simeq 25{{\%}}$, whereas classifying the 6 known (JAB < 21.5) quasars at z > 7 from the entire sky, we select 5/6 or a completeness of $\simeq 80{{\%}}$. The failure to select the majority of 6 < z < 7 quasars arises because our quasar density model is based on an empirical quasar spectral energy distribution model that underestimates the scatter in the distribution of fluxes. This new approach to quasar selection paves the way for efficient spectroscopic follow-up of Euclid quasar candidates with ground based telescopes and JWST.
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Ortega-Martinez, Sara, Aura Obreja, Rosa Dominguez-Tenreiro, Susana E. Pedrosa, Yetli Rosas-Guevara e Patricia B. Tissera. "Milky Way-like galaxies: Stellar population properties of dynamically defined disks, bulges and stellar haloes". Monthly Notices of the Royal Astronomical Society, 23 luglio 2022. http://dx.doi.org/10.1093/mnras/stac2033.
Abstract (sommario):
Abstract The formation of galaxies can be understood in terms of the assembly patterns of each type of galactic component. To perform this kind of analysis, is necessary to define some criteria to separate those components. Decomposition methods based on dynamical properties are more physically motivated than photometry-based ones. We use the unsupervised Gaussian Mixture model of galactic structure finder to extract the components of a sub-sample of galaxies with Milky Way-like masses from the EAGLE simulations. A clustering in the space of first and second order dynamical moments of all identified substructures reveals five types of galaxy components: thin and thick disks, stellar haloes, bulges and spheroids. We analyse the dynamical, morphological and stellar population properties of these five component types, exploring to what extent these properties correlate with each other, and how much they depend on the total galaxy stellar and dark matter halo masses. All galaxies contain a bulge, a stellar halo and a disk. 60 per cent of objects host two disks (thin and thick), and 68 per cent host also a spheroid. The dynamical disk-to-total ratio does not depend on stellar mass, but the median rotational velocities of the two disks do. Thin disks are well separated in stellar ages, [Fe/H] and α-enhancement from the three dispersion-dominated components, while thick disks are in between. Except for thin disks, all components show correlations among their stellar population properties: older ages mean lower metallicities and larger α-enhancement. Finally, we quantify the weak dependence of stellar population properties on each component’s dynamics.
25
Fukushima, Tetsuya, Masashi Chiba, Mikito Tanaka, Kohei Hayashi, Daisuke Homma, Sakurako Okamoto, Yutaka Komiyama, Masayuki Tanaka, Nobuo Arimoto e Tadafumi Matsuno. "The stellar halo of the Milky Way traced by blue horizontal-branch stars in the Subaru Hyper Suprime-Cam Survey". Publications of the Astronomical Society of Japan 71, n. 4 (13 giugno 2019). http://dx.doi.org/10.1093/pasj/psz052.
Abstract (sommario):
Abstract We report on the global structure of the Milky Way (MW) stellar halo up to its outer boundary based on the analysis of blue horizontal-branch stars (BHBs). These halo tracers are extracted from the (g, r, i, z)-band multi-photometry in the internal data release of the ongoing Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) surveyed over a ∼550 deg2 area. In order to select the most likely BHBs by removing blue straggler stars (BSs) and other contamination in a statistically significant manner, we have developed and applied an extensive Bayesian method, instead of the simple color cuts adopted in our previous work, where each of the template BHBs and non-BHBs obtained from the available catalogs are represented as a mixture of multiple Gaussian distributions in the color–color diagrams. We found from the candidate BHBs in the range of 18.5 < g < 23.5 mag that the radial density distribution over a Galactocentric radius of r = 36–360 kpc can be approximated as a single power-law profile with an index of $\alpha =3.74^{+0.21}_{-0.22}$ or a broken power-law profile with an index of $\alpha _{\rm in}=2.92^{+0.33}_{-0.33}$ at r below a broken radius of $r_{\rm b}=160^{+18}_{-19}\:$kpc and a very steep slope of $\alpha _{\rm out}=15.0^{+3.7}_{-4.5}$ at r > rb. The latter profile with a prolate shape having an axial ratio of $q=1.72^{+0.44}_{-0.28}$ is most likely and this halo may hold a rather sharp boundary at r ≃ 160 kpc. The slopes of the halo density profiles are compared with those from the suite of hydrodynamical simulations for the formation of stellar halos. This comparison suggests that the MW stellar halo may consist of the two overlapping components: the in situ inner halo as probed by RR Lyrae stars showing a relatively steep radial density profile and the ex situ outer halo with a shallow profile probed by BHBs here, which is made by accretion of small stellar systems.