Related papers: Stellar Populations With Optical Spectra: Deep Lea…
Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…
We explore the ability of four different inverse population synthesis codes to recover the physical properties of galaxies from their spectra by SED fitting. Three codes, DynBaS, TGASPEX, and GASPEX, have been implemented by the authors and…
A recent paper by Ge et al. performs a series of experiments with two full spectral fitting codes, pPXF and starlight, finding that the two yield consistent results when the input spectrum is not heavily reddened. For E(B-V) > 0.2, however,…
We firstly derive the stellar population properties: age and metallicity for $\sim$ 43,000 low redshift galaxies in the seventh data release (DR7) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey, which have…
We present a machine learning (ML) pipeline to identify star clusters in the multi{color images of nearby galaxies, from observations obtained with the Hubble Space Telescope as part of the Treasury Project LEGUS (Legacy ExtraGalactic…
We investigated the use of a U-Net convolutional neural network for denoising simulated medium-resolution spectroscopic observations of stars. Simulated spectra were generated under realistic observational conditions resembling the Subaru…
We present new, high-to-intermediate spectral resolution stellar population models, based on four popular libraries of empirical stellar spectra, namely Pickles, ELODIE, STELIB and MILES. These new models are the same as our previous…
In the era of exploding survey volumes, traditional methods of spectroscopic analysis are being pushed to their limits. In response, we develop deep-REMAP, a novel deep learning framework that utilizes a regularized, multi-task approach to…
Populations of massive stars are directly reflective of the physics of stellar evolution. Counting subtypes of massive stars and ratios of massive stars in different evolutionary states have been used ubiquitously as diagnostics of age and…
Spectroscopy represents the ideal observational method to maximally extract information from galaxies regarding their star formation and chemical enrichment histories. However, absorption spectra of galaxies prove rather challenging at high…
We present a detailed stellar population analysis of 11 bright ($H<26.6$) galaxies at $z=9-11$ (three spectroscopically confirmed) to constrain the chemical enrichment and growth of stellar mass of early galaxies. We use the flexible…
We present a new spectral fitting code, Firefly, for deriving the stellar population properties of stellar systems. Firefly is a chi-squared minimisation fitting code that fits combinations of single-burst stellar population models to…
Understanding the star-formation properties of galaxies as a function of cosmic epoch is a critical exercise in studies of galaxy evolution. Traditionally, stellar population synthesis models have been used to obtain best fit parameters…
We performed a near-infrared (NIR, $\sim$1.0$\mu$m-2.4$\mu$m) stellar population study in a sample of early type galaxies. The synthesis was performed using five different evolutionary population synthesis libraries of models. Our main…
Machine learning has been widely applied to clearly defined problems of astronomy and astrophysics. However, deep learning and its conceptual differences to classical machine learning have been largely overlooked in these fields. The broad…
We present an evolutionary stellar population synthesis model which predicts SED's for simple stellar populations, SSP's, at ~2A resolution in the visible. The input database is composed of ~550 stars, selected from the spectral library of…
We present a new model for computing the spectral evolution of stellar populations at ages between 100,000 yr and 20 Gyr at a resolution of 3 A across the whole wavelength range from 3200 to 9500 A for a wide range of metallicities. These…
We are presenting a novel, Deep Learning based approach to estimate the normalized broadband spectral energy distribution (SED) of different stellar populations in synthetic galaxies. In contrast to the non-parametric multiband source…
High spectral resolution evolutionary synthesis models have become a routinely used ingredient in extragalactic work, and as such deserve thorough testing. Star clusters are ideal laboratories for such tests. This paper applies the spectral…
With current and upcoming experiments such as WFIRST, Euclid and LSST, we can observe up to billions of galaxies. While such surveys cannot obtain spectra for all observed galaxies, they produce galaxy magnitudes in color filters. This data…