Spectroscopic Sample Research Articles

Optimizing a magnitude-limited spectroscopic training sample for photometric classification of supernovae

ABSTRACT In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-m Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching rAB ≈ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint high-redshift supernovae observed from larger spectroscopic facilities; the algorithms’ range of average area under receiver operator characteristic curve (AUC) scores over 10 runs increases from 0.547–0.628 to 0.946–0.969 and purity of the classified sample reaches 95 per cent in all runs for two of the four algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having ‘true’ faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimization of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.

Pulsational instability of pre-main sequence models from accretingprotostars I. Constraining the input physics for accretion with spectroscopic parameters and stellar pulsations

Context: The pre-main sequence evolution is often simplified by choosing classical initial models. These have large initial radii and sufficient uniform contraction to make them fully convective. Contrary to that, real stars are born as small protostellar seeds in collapsing molecular clouds and obtain their final mass by means of accretion. Aims: We aim to constrain the input physics of accretion on protostellar seeds with observed spectroscopic parameters and stellar pulsations of young stellar objects and pre-main sequence stars. Methods: We conducted a literature search for spectroscopic samples of young stellar objects and pre-main sequence stars including all previously known pulsators. The sample size of pulsating pre-main sequence stars is increased by analysing TESS observations and presenting discoveries in CoRoT data. We employ MESA and GYRE to calculate evolutionary tracks of accreting protostellar seeds in a constant accretion scenario, the subsequent pre-main sequence evolution, and their pulsation properties. The results are then compared with observations to constrain the input physics. Results: We discuss 16 formerly unknown pulsating pre-main sequence stars and candidates that are either of SPB, $\delta$ Scuti,$\gamma$ Doradus or $\delta$ Scuti - $\gamma$ Doradus hybrid type. We find that evolutionary tracks with a mass accretion rate of $5\times10^{-6} M_\odot/{\rm yr}$ and fraction of injected accretion energy of $\beta=0.1$ provide the best results in enveloping the spectroscopic parameters of pre-main sequence stars in a constant accretion scenario. The calculated instability regions constrain the atmospheric boundary conditions to Eddington Gray atmospheres; we discuss the future potential for additional constraints by instability regions that are dependent on radial order. We present a possible candidate for pulsations in M-type young stellar objects.

On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2

ABSTRACTThis paper provides a catalogue of stars, quasars, and galaxies for the Southern Photometric Local Universe Survey Data Release 2 (S-PLUS DR2) in the Stripe 82 region. We show that a 12-band filter system (5 Sloan-like and 7 narrow bands) allows better performance for object classification than the usual analysis based solely on broad bands (regardless of infrared information). Moreover, we show that our classification is robust against missing values. Using spectroscopically confirmed sources retrieved from the Sloan Digital Sky Survey DR16 and DR14Q, we train a random forest classifier with the 12 S-PLUS magnitudes + 4 morphological features. A second random forest classifier is trained with the addition of the W1 (3.4 $\mu\mathrm{m} $) and W2 (4.6 $\mu\mathrm{m} $) magnitudes from the Wide-field Infrared Survey Explorer (WISE). Forty-four per cent of our catalogue have WISE counterparts and are provided with classification from both models. We achieve 95.76 per cent (52.47 per cent) of quasar purity, 95.88 per cent (92.24 per cent) of quasar completeness, 99.44 per cent (98.17 per cent) of star purity, 98.22 per cent (78.56 per cent) of star completeness, 98.04 per cent (81.39 per cent) of galaxy purity, and 98.8 per cent (85.37 per cent) of galaxy completeness for the first (second) classifier, for which the metrics were calculated on objects with (without) WISE counterpart. A total of 2926 787 objects that are not in our spectroscopic sample were labelled, obtaining 335 956 quasars, 1347 340 stars, and 1243 391 galaxies. From those, 7.4 per cent, 76.0 per cent, and 58.4 per cent were classified with probabilities above 80 per cent. The catalogue with classification and probabilities for Stripe 82 S-PLUS DR2 is available for download.

TOPoS

Context. The goal of the Turn-Off Primordial Stars survey (TOPoS) project is to find and analyse turn-off (TO) stars of extremely low metallicity. To select the targets for spectroscopic follow-up at high spectral resolution, we relied on low-resolution spectra from the Sloan Digital Sky Survey (SDSS). Aims. In this paper, we use the metallicity estimates we obtained from our analysis of the SDSS spectra to construct the metallicity distribution function (MDF) of the Milky Way, with special emphasis on its metal-weak tail. The goal is to provide the underlying distribution out of which the TOPoS sample was extracted. Methods. We made use of SDSS photometry, Gaia photometry, and distance estimates derived from the Gaia parallaxes to derive a metallicity estimate for a large sample of over 24 million TO stars. This sample was used to derive the metallicity bias of the sample for which SDSS spectra are available. Results. We determined that the spectroscopic sample is strongly biased in favour of metal-poor stars, as intended. A comparison with the unbiased photometric sample allows us to correct for the selection bias. We selected a sub-sample of stars with reliable parallaxes for which we combined the SDSS radial velocities with Gaia proper motions and parallaxes to compute actions and orbital parameters in the Galactic potential. This allowed us to characterise the stars dynamically, and in particular to select a sub-sample that belongs to the Gaia-Sausage-Enceladus (GSE) accretion event. We are thus also able to provide the MDF of GSE. Conclusions. The metal-weak tail derived in our study is very similar to that derived in the H3 survey and in the Hamburg/ESO Survey. This allows us to average the three MDFs and provide an error bar for each metallicity bin. Inasmuch as the GSE structure is representative of the progenitor galaxy that collided with the Milky Way, that galaxy appears to be strongly deficient in metal-poor stars compared to the Milky Way, suggesting that the metal-weak tail of the latter has been largely formed by accretion of low-mass galaxies rather than massive galaxies, such as the GSE progenitor.

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

ABSTRACT We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of $4699\, {\rm deg}^{2}$. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

Probing the galaxy–halo connection with total satellite luminosity

ABSTRACT We demonstrate how the total luminosity in satellite galaxies is a powerful probe of dark matter haloes around central galaxies. The method cross-correlates central galaxies in spectroscopic galaxy samples with fainter galaxies detected in photometric surveys. Using models, we show that the total galaxy luminosity, Lsat, scales linearly with host halo mass, making Lsat an excellent proxy for Mh. Lsat is also sensitive to the formation time of the halo. We demonstrate that probes of galaxy large-scale environment can break this degeneracy. Although this is an indirect probe of the halo, it yields a high signal-to-noise ratio measurement for galaxies expected to occupy haloes at <1012 M⊙, where other methods suffer from larger errors. In this paper, we focus on observational and theoretical systematics in the Lsat method. We test the robustness of our method of finding central galaxies and our methods of estimating the number of background galaxies. We implement this method on galaxies in the Sloan Digital Sky Survey (SDSS) data, with satellites identified in fainter imaging data. We find excellent agreement between our theoretical predictions and the observational measurements. Finally, we compare our Lsat measurements to weak lensing estimates of Mh for red and blue subsamples. In the stellar mass range where the measurements overlap, we find consistent results, where red galaxies live in larger haloes. However, the Lsat approach allows us to probe significantly lower mass galaxies. At these masses, the Lsat values are equivalent. This example shows the potential of Lsat as a probe of dark haloes.

Mixture models for photometric redshifts

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.

The Pristine Inner Galaxy Survey (PIGS) III: carbon-enhanced metal-poor stars in the bulge

ABSTRACT The most metal-deficient stars hold important clues about the early buildup and chemical evolution of the Milky Way, and carbon-enhanced metal-poor (CEMP) stars are of special interest. However, little is known about CEMP stars in the Galactic bulge. In this paper, we use the large spectroscopic sample of metal-poor stars from the Pristine Inner Galaxy Survey (PIGS) to identify CEMP stars ($\rm {[C/Fe]} \geqslant +0.7$) in the bulge region and to derive a CEMP fraction. We identify 96 new CEMP stars in the inner Galaxy, of which 62 are very metal-poor ($\rm {[Fe/H]} \lt -2.0$); this is more than a 10-fold increase compared to the seven previously known bulge CEMP stars. The cumulative fraction of CEMP stars in PIGS is $42^{\, +14\, }_{\, -13} {{\ \rm per\ cent}}$ for stars with $\rm {[Fe/H]} \lt -3.0$, and decreases to $16^{\, +3\, }_{\, -3} {{\ \rm per\ cent}}$ for $\rm {[Fe/H]} \lt -2.5$ and $5.7^{\, +0.6\, }_{\, -0.5} {{\ \rm per\ cent}}$ for $\rm {[Fe/H]} \lt -2.0$. The PIGS inner Galaxy CEMP fraction for $\rm {[Fe/H]} \lt -3.0$ is consistent with the halo fraction found in the literature, but at higher metallicities, the PIGS fraction is substantially lower. While this can partly be attributed to a photometric selection bias, such bias is unlikely to fully explain the low CEMP fraction at higher metallicities. Considering the typical carbon excesses and metallicity ranges for halo CEMP-s and CEMP-no stars, our results point to a possible deficiency of both CEMP-s and CEMP-no stars (especially the more metal-rich) in the inner Galaxy. The former is potentially related to a difference in the binary fraction, whereas the latter may be the result of a fast chemical enrichment in the early building blocks of the inner Galaxy.

The LOFAR Two-meter Sky Survey: Deep Fields Data Release 1

The Low Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) is a sensitive, high-resolution 120-168 MHz survey split across multiple tiers over the northern sky. The first LoTSS Deep Fields data release consists of deep radio continuum imaging at 150 MHz of the Boötes, European Large Area Infrared Space Observatory Survey-North 1, and Lockman Hole fields, down to rms sensitivities of ~32, 20, and 22 μJy beam−1, respectively. In this paper we present consistent photometric redshift (photo-z) estimates for the optical source catalogues in all three fields – totalling over 7 million sources (~5 million after limiting to regions with the best photometric coverage). Our photo-z estimation uses a hybrid methodology that combines template fitting and machine learning and is optimised to produce the best possible performance for the radio continuum selected sources and the wider optical source population. Comparing our results with spectroscopic redshift samples, we find a robust scatter ranging from 1.6 to 2% for galaxies and 6.4 to 7% for identified optical, infrared, or X-ray selected active galactic nuclei. Our estimated outlier fractions (|zphot−zspec|/(1+zspec)>0.15) for the corresponding subsets range from 1.5 to 1.8% and 18 to 22%, respectively. Replicating trends seen in analyses of previous wide-area radio surveys, we find no strong trend in photo-z quality as a function of radio luminosity for a fixed redshift. We exploit the broad wavelength coverage available within each field to produce galaxy stellar mass estimates for all optical sources at z < 1.5. Stellar mass functions derived for each field are used to validate our mass estimates, with the resulting estimates in good agreement between each field and with published results from the literature.

Quasars at intermediate redshift are not special; but they are often satellites

ABSTRACT Understanding the links between the activity of supermassive black holes (SMBHs) at the centres of galaxies and their host dark matter haloes is a key question in modern astrophysics. The final data release of the SDSS-IV eBOSS provides the largest contemporary spectroscopic sample of galaxies and quasi-stellar objects (QSOs). Using this sample and covering the redshift interval z = 0.7–1.1, we have measured the clustering properties of the eBOSS QSOs, emission-line galaxies (ELGs), and luminous red galaxies (LRGs). We have also measured the fraction of QSOs as a function of the overdensity defined by the galaxy population. Using these measurements, we investigate how QSOs populate and sample the galaxy population, and how the host dark-matter haloes of QSOs sample the underlying halo distribution. We find that the probability of a galaxy hosting a QSO is independent of the host dark matter halo mass of the galaxy. We also find that about 60 per cent of eBOSS QSOs are hosted by LRGs and about 20–40 per cent of QSOs are hosted by satellite galaxies. We find a slight preference for QSOs to populate satellite galaxies over central galaxies. This is connected to the host halo mass distribution of different types of galaxies. Based on our analysis, QSOs should be hosted by a very broad distribution of haloes, and their occurrence should be modulated only by the efficiency of galaxy formation processes.

Euclid preparation

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate knowledge of the galaxy mean redshift ⟨z⟩. We investigate the possibility of measuring ⟨z⟩ with an accuracy better than 0.002 (1 + z) in ten tomographic bins spanning the redshift interval 0.2 < z < 2.2, the requirements for the cosmic shear analysis of Euclid. We implement a sufficiently realistic simulation in order to understand the advantages and complementarity, as well as the shortcomings, of two standard approaches: the direct calibration of ⟨z⟩ with a dedicated spectroscopic sample and the combination of the photometric redshift probability distribution functions (zPDFs) of individual galaxies. We base our study on the Horizon-AGN hydrodynamical simulation, which we analyse with a standard galaxy spectral energy distribution template-fitting code. Such a procedure produces photometric redshifts with realistic biases, precisions, and failure rates. We find that the current Euclid design for direct calibration is sufficiently robust to reach the requirement on the mean redshift, provided that the purity level of the spectroscopic sample is maintained at an extremely high level of > 99.8%. The zPDF approach can also be successful if the zPDF is de-biased using a spectroscopic training sample. This approach requires deep imaging data but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the de-biasing method and confirm our finding by applying it to real-world weak-lensing datasets (COSMOS and KiDS+VIKING-450).

The Lyman Alpha Spectral Database (LASD)

Lymanα (Lyα) emission from star-forming galaxies is an important tool to study a large range of astrophysical questions: it has the potential to carry information about the source galaxy, its nearby circumgalactic medium, and also the surrounding intergalactic medium. Substantial observational and theoretical work has therefore focused on understanding the details of this emission line. These efforts have been hampered, however, by an absence of spectroscopic reference samples that can be used both as comparisons for observational studies and as critical tests for theoretical work. For this reason, we have compiled a large sample of Lyα spectra, at both low and high redshift, and created a publicly available online database, at lasd.lyman-alpha.com. The Lyman Alpha Spectral Database (LASD) hosts these spectra, as well as a large set of spectral and kinematic quantities that have been homogeneously measured for the entire sample. As part of this we have developed an automated redshift determination algorithm which we show is accurate to within less than ±180 kms−1 on average, across many different Lyα profiles. The measurements can conveniently be viewed online and downloaded in tabular form. The LASD has the capacity for users to easily upload their own Lyα spectra, and all the same spectral measurements will be made, reported, and ingested into the database. We actively invite the community to do so, and the LASD is intended to be a long-term community resource. In this paper we present the design of the database as well as descriptions of the underlying algorithms and the initial Lyα emitter samples that are in the database.

A machine learning approach to measuring the quenched fraction of low-mass satellites beyond the Local Group

ABSTRACT Observations suggest that satellite quenching plays a major role in the build-up of passive, low-mass galaxies at late cosmic times. Studies of low-mass satellites, however, are limited by the ability to robustly characterize the local environment and star formation activity of faint systems. In an effort to overcome the limitations of existing data sets, we utilize deep photometry in Stripe 82 of the Sloan Digital Sky Survey, in conjunction with a neural network classification scheme, to study the suppression of star formation in low-mass satellite galaxies in the local Universe. Using a statistically driven approach, we are able to push beyond the limits of existing spectroscopic data sets, measuring the satellite quenched fraction down to satellite stellar masses of ∼107 M⊙ in group environments (Mhalo = 1013−14 h−1 M⊙). At high satellite stellar masses (≳1010 M⊙), our analysis successfully reproduces existing measurements of the quenched fraction based on spectroscopic samples. Pushing to lower masses, we find that the fraction of passive satellites increases, potentially signalling a change in the dominant quenching mechanism at M⋆ ∼ 109 M⊙. Similar to the results of previous studies of the Local Group, this increase in the quenched fraction at low satellite masses may correspond to an increase in the efficacy of ram-pressure stripping as a quenching mechanism in groups.

Baryon acoustic oscillations in the projected cross-correlation function between the eBOSS DR16 quasars and photometric galaxies from the DESI Legacy Imaging Surveys

ABSTRACT We search for the baryon acoustic oscillations in the projected cross-correlation function binned into transverse comoving radius between the SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected from the DESI Legacy Imaging Surveys. We estimate the density of the photometric sample of galaxies in this redshift range to be about 2900 deg−2, which is deeper than the official DESI emission line galaxy selection, and the density of the spectroscopic sample is about 20 deg−2. In order to mitigate the systematics related to the use of different imaging surveys close to the detection limit, we use a neural network approach that accounts for complex dependences between the imaging attributes and the observed galaxy density. We find that we are limited by the depth of the imaging surveys that affects the density and purity of the photometric sample and its overlap in redshift with the quasar sample, which thus affects the performance of the method. When cross-correlating the photometric galaxies with quasars in the range 0.6 ≤ z ≤ 1.2, the cross-correlation function can provide better constraints on the comoving angular distance DM (6 per cent precision) compared to the constraint on the spherically averaged distance DV (9 per cent precision) obtained from the autocorrelation. Although not yet competitive, this technique will benefit from the arrival of deeper photometric data from upcoming surveys that will enable it to go beyond the current limitations we have identified in this work.

A new determination of the primordial helium abundance using the analyses of H ii region spectra from SDSS

ABSTRACT The precision measurement of the primordial helium abundance Yp is a powerful probe of the early Universe. The most common way to determine Yp is the analyses of observations of metal-poor H ii regions found in blue compact dwarf galaxies. We present the spectroscopic sample of 100 H ii regions collected from the Sloan Digital Sky Survey. The final analysed sample consists of our sample and HeBCD data base from Izotov et al. (2007). We use a self-consistent procedure to determine physical conditions, current helium abundances, and metallicities of the H ii regions. From a regression to zero metallicity, we have obtained Yp = 0.2462 ± 0.0022, which is one of the most stringent constraints obtained with such methods up to date and is in a good agreement with the Planck result $Y_{\rm p}^{\it {\mathrm{ Planck}}} = 0.2471 \pm 0.0003$. Using the determined value of Yp and the primordial deuterium abundance taken from Particle Data Group (Zyla et al. 2020) we put a constraint on the effective number of neutrino species Neff = 2.95 ± 0.16, which is consistent with the Planck one Neff = 2.99 ± 0.17. Further increase of statistics potentially allows us to achieve Planck accuracy, which in turn will become a powerful tool for studying the self-consistency of the standard cosmological model and/or physics beyond.

The PAU Survey: an improved photo-zsample in the COSMOS field

ABSTRACTWe present – and make publicly available – accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with iAB ≤ 23. The redshifts are computed using a combination of narrow-band photometry from PAUS, a survey with 40 narrow bands spaced at $100\,\mathring{\rm A}$ intervals covering the range from 4500 to $8500\,\mathring{\rm A}$, and 26 broad, intermediate, and narrow bands covering the UV, visible and near-infrared spectrum from the COSMOS2015 catalogue. We introduce a new method that models the spectral energy distributions as a linear combination of continuum and emission-line templates and computes its Bayes evidence, integrating over the linear combinations. The correlation between the UV luminosity and the O ii line is measured using the 66 available bands with the zCOSMOS spectroscopic sample, and used as a prior which constrains the relative flux between continuum and emission-line templates. The flux ratios between the O ii line and Hα, Hβ and $\mathrm{O\,{\small III}}$ are similarly measured and used to generate the emission-line templates. Comparing to public spectroscopic surveys via the quantity Δz ≡ (zphoto − zspec)/(1 + zspec), we find the photometric redshifts to be more precise than previous estimates, with σ68(Δz) ≈ (0.003, 0.009) for galaxies at magnitude iAB ∼ 18 and iAB ∼ 23, respectively, which is three times and 1.66 times tighter than COSMOS2015. Additionally, we find the redshifts to be very accurate on average, yielding a median of the Δz distribution compatible with |median(Δz)| ≤ 0.001 at all redshifts and magnitudes considered. Both the added PAUS data and new methodology contribute significantly to the improved results. The catalogue produced with the technique presented here is expected to provide a robust redshift calibration for current and future lensing surveys, and allows one to probe galaxy formation physics in an unexplored luminosity-redshift regime, thanks to its combination of depth, completeness, and excellent redshift precision and accuracy.

A model for spectroscopic food sample analysis using data sonification

In this paper, we propose a method to generate an audio output based on spectroscopy data in order to discriminate two classes of data, based on the features of our spectral dataset. To do this, we first perform spectral pre-processing, and then extract features, followed by machine learning, for dimensionality reduction. The features are then mapped to the parameters of a sound synthesiser, as part of the audio processing, so as to generate audio samples in order to compute statistical results and identify important descriptors for the classification of the dataset. To optimise the process, we compare Amplitude Modulation (AM) and Frequency Modulation (FM) synthesis, as applied to two real-life datasets to evaluate the performance of sonification as a method for discriminating data. FM synthesis provides a higher subjective classification accuracy as compared with to AM synthesis. We then further compare the dimensionality reduction method of Principal Component Analysis (PCA) and Linear Discriminant Analysis in order to optimise our sonification algorithm. The results of classification accuracy using FM synthesis as the sound synthesiser and PCA as the dimensionality reduction method yields a mean classification accuracies of 93.81% and 88.57% for the coffee dataset and the fruit puree dataset respectively, and indicate that this spectroscopic analysis model is able to provide relevant information on the spectral data, and most importantly, is able to discriminate accurately between the two spectra and thus provides a complementary tool to supplement current methods.

SQuIGG E Survey: Massive z ∼ 0.6 Post-starburst Galaxies Exhibit Flat Age Gradients

Abstract We present Gemini Multi-Object Spectrograph (GMOS) integral field unit (IFU) observations of six massive (M ⋆ ≥ 1011 M ⊙) A-star dominated post-starburst galaxies at z ∼ 0.6. These galaxies are a subsample of the Survey, which selects intermediate-redshift post-starbursts from the Sloan Digital Sky Survey spectroscopic sample (DR14) with spectral shapes that indicate they have recently shut off their primary epoch of star formation. Using Hδ A absorption as a proxy for stellar age, we constrain five of the galaxies to have young (∼600 Myr) light-weighted ages at all radii and find that the sample on average has flat age gradients. We examine the spatial distribution of mass-weighted properties by fitting our profiles with a toy model including a young, centrally concentrated burst superimposed on an older, extended population. We find that galaxies with flat Hδ A profiles are inconsistent with formation via a central secondary starburst. This implies that the mechanism responsible for shutting off this dominant episode of star formation must have done so uniformly throughout the galaxy.

The First Extensive Spectroscopic Study of Young Stars in the North America and Pelican Nebulae

Abstract We present a spectroscopic survey of over 3400 potential members in the North America and Pelican Nebulae (NAP) using several low-resolution (R ≈ 1300–2000) spectrographs: Palomar/Norris, WIYN/Hydra, Keck/DEep Imaging Multi-Object Spectrograph (DEIMOS), and the Multiple Mirror Telescope (MMT)/Hectospec. We identify 580 young stars as likely members of the NAP region based on criteria involving infrared excess, Li I 6708 Å absorption, X-ray emission, parallax, and proper motions. The spectral types of individual spectra are derived by fitting them with templates that are either empirical spectra of pre-main-sequence stars or model atmospheres. The templates are artificially veiled, and a best-fit combination of spectral type and veiling parameter is derived for each star. We use the spectral types with archival photometry to derive V-band extinction and stellar luminosity. From the Hertzsprung–Russell diagram, the median age of the young stars is about 1 Myr, with a luminosity dispersion of ∼0.3–0.4 dex. We investigate the photometric variability of the spectroscopic member sample using Zwicky Transient Facility data and conclude that photometric variability, while present, does not significantly contribute to the luminosity dispersion. While larger than the formal errors, the luminosity dispersion is smaller than if veiling were not taken into account in our spectral typing process. The measured ages of the stellar kinematic groups, combined with the inferred ages for embedded stellar populations revealed by Spitzer, suggest a sequential history of star formation in the NAP region.

A comparative study of satellite galaxies in Milky Way-like galaxies from HSC, DECaLS, and SDSS

ABSTRACT We conduct a comprehensive and statistical study of the luminosity functions (LFs) for satellite galaxies, by counting photometric galaxies from HSC, DECaLS, and SDSS around isolated central galaxies (ICGs) and paired galaxies from the SDSS/DR7 spectroscopic sample. Results of different surveys show very good agreement. The satellite LFs can be measured down to MV ∼ −10, and for central primary galaxies as small as 8.5 < log10M*/M⊙ < 9.2 and 9.2 < log10M*/M⊙ < 9.9, which implies there are on average 3–8 satellites with MV < −10 around LMC-mass ICGs. The bright end cutoff of satellite LFs and the satellite abundance are both sensitive to the magnitude gap between the primary and its companions, indicating galaxy systems with larger magnitude gaps are on average hosted by less massive dark matter haloes. By selecting primaries with stellar mass similar to our Milky Way (MW), we discovered that (i) the averaged satellite LFs of ICGs with different magnitude gaps to their companions and of galaxy pairs with different colour or colour combinations all show steeper slopes than the MW satellite LF; (ii) there are on average more satellites with −15 < MV < −10 than those in our MW; (iii) there are on average 1.5 to 2.5 satellites with MV < −16 around ICGs, consistent with our MW; (iv) even after accounting for the large scatter predicted by numerical simulations, the MW satellite LF is uncommon at MV > −12. Hence, the MW and its satellite system are statistically atypical of our sample of MW-mass systems. In consequence, our MW is not a good representative of other MW-mass galaxies. Strong cosmological implications based on only MW satellites await additional discoveries of fainter satellites in extra-galactic systems. Interestingly, the MW satellite LF is typical among other MW-mass systems within 40 Mpc in the local Universe, perhaps implying the Local Volume is an underdense region.