scholarly journals Using a Neural Network Classifier to Select Galaxies with the Most Accurate Photometric Redshifts

2021 ◽  
Vol 922 (2) ◽  
pp. 153
Author(s):  
Adam Broussard ◽  
Eric Gawiser
Keyword(s):  
Neural Network ◽  
Galaxy Evolution ◽  
Data Augmentation ◽  
Power Spectra ◽  
Neural Network Classifier ◽  
Photometric Redshifts ◽  
The Galaxy ◽  
Galaxy Sample ◽  
Strategic Program ◽  
Using Data

Abstract The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will produce several billion photometric redshifts (photo-z's), enabling cosmological analyses to select a subset of galaxies with the most accurate photo-z. We perform initial redshift fits on Subaru Strategic Program galaxies with deep grizy photometry using Trees for Photo-Z (TPZ) before applying a custom neural network classifier (NNC) tuned to select galaxies with (z phot − z spec)/(1 + z spec) < 0.10. We consider four cases of training and test sets ranging from an idealized case to using data augmentation to increase the representation of dim galaxies in the training set. Selections made using the NNC yield significant further improvements in outlier fraction and photo-z scatter (σ z ) over those made with typical photo-z uncertainties. As an example, when selecting the best third of the galaxy sample, the NNC achieves a 35% improvement in outlier rate and a 23% improvement in σ z compared to using uncertainties from TPZ. For cosmology and galaxy evolution studies, this method can be tuned to retain a particular sample size or to achieve a desired photo-z accuracy; our results show that it is possible to retain more than a third of an LSST-like galaxy sample while reducing σ z by a factor of 2 compared to the full sample, with one-fifth as many photo-z outliers. For surveys like LSST that are not limited by shot noise, this method enables a larger number of tomographic redshift bins and hence a significant increase in the total signal to noise of galaxy angular power spectra.

scholarly journals Large scale profiles of galaxies at z=0-2 studied by stacking the HSC SSP survey data

2016 ◽  
Vol 11 (S321) ◽  
pp. 318-320
Author(s):  
Mariko Kubo ◽  
Masami Ouchi ◽  
Takatoshi Shibuya
Keyword(s):  
Survey Data ◽  
Surface Brightness ◽  
Large Scale ◽  
High Redshift ◽  
Photometric Redshifts ◽  
Early Formation ◽  
The Galaxy ◽  
Strategic Program ◽  
Galaxy Populations ◽  
Using Data

AbstractWe are carrying out the study of the evolution of radial surface brightness profiles of galaxies from z = 0 to 2 by stacking analysis using data corrected by the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP). This will allow us to constrain the large scale average profiles of various galaxy populations at high redshift. From the stacking analysis of galaxies selected based on their photometric redshifts, we successfully detected the outer components of galaxies at z > 1 extending to at least ~80 kpc, which imply an early formation for the galaxy outskirts.

scholarly journals Quasar Sightline and Galaxy Evolution (QSAGE) survey – I. The galaxy environment of O vi absorbers up to z = 1.4 around PKS 0232−04

2019 ◽  
Vol 486 (1) ◽  
pp. 21-41 ◽  
Author(s):  
R M Bielby ◽  
J P Stott ◽  
F Cullen ◽  
T M Tripp ◽  
J N Burchett ◽  
...  
Keyword(s):  
Galaxy Evolution ◽  
Near Infrared ◽  
Hubble Space Telescope ◽  
High Redshift ◽  
Star Forming ◽  
The Galaxy ◽  
Circumgalactic Medium ◽  
Galaxy Environment ◽  
Using Data ◽  
Galaxy Population

ABSTRACT We present the first results from a study of O vi absorption around galaxies at z &lt; 1.44 using data from a near-infrared grism spectroscopic Hubble Space Telescope Large Programme, the Quasar Sightline and Galaxy Evolution (QSAGE) survey. QSAGE is the first grism galaxy survey to focus on the circumgalactic medium at z ∼ 1, providing a blind survey of the galaxy population. The galaxy sample is H α flux limited (f(H α) &gt; 2 × 10−17 erg s−1 cm−2) at 0.68 &lt; z &lt; 1.44, corresponding to ≳0.2–0.8 M⊙ yr−1. In this first of 12 fields, we combine the galaxy data with high-resolution STIS and COS spectroscopy of the background quasar to study O vi in the circumgalactic medium. At z ∼ 1, we find O vi absorption systems up to b ∼ 350 kpc (∼4Rvir) from the nearest detected galaxy. Further, we find ${\sim }50{{\ \rm per\ cent}}$ of ≳1 M⊙ yr−1 star-forming galaxies within 2Rvir show no associated O vi absorption to a limit of at least N(O vi) = 1013.9 cm−2. That we detect O vi at such large distances from galaxies and that a significant fraction of star-forming galaxies show no detectable O vi absorption disfavours outflows from ongoing star formation as the primary medium traced by these absorbers. Instead, by combining our own low- and high-redshift data with existing samples, we find tentative evidence for many strong (N(O vi) &gt; 1014 cm−2) O vi absorption systems to be associated with M⋆ ∼ 109.5–10 M⊙ mass galaxies (Mhalo ∼ 1011.5–12 M⊙ dark matter haloes), and infer that they may be tracing predominantly collisionally ionized gas within the haloes of such galaxies.

scholarly journals Compact galaxies and the size–mass galaxy distribution from a colour-selected sample at 0.04 < z < 0.15 supplemented by ugrizYJHK photometric redshifts

2020 ◽  
Vol 500 (2) ◽  
pp. 1557-1574
Author(s):  
Ivan K Baldry ◽  
Tricia Sullivan ◽  
Raffaele Rani ◽  
Sebastian Turner
Keyword(s):  
Galaxy Evolution ◽  
High Redshift ◽  
Sample Selection ◽  
Distribution Functions ◽  
Sloan Digital Sky Survey ◽  
Photometric Redshifts ◽  
Galaxy Distribution ◽  
Sky Survey ◽  
Galaxy Sample ◽  
Compact Galaxies

ABSTRACT The size–mass galaxy distribution is a key diagnostic for galaxy evolution. Massive compact galaxies are potential surviving relics of a high-redshift phase of star formation. Some of these could be nearly unresolved in Sloan Digital Sky Survey (SDSS) imaging and thus not included in galaxy samples. To overcome this, a sample was selected from the combination of SDSS and UKIRT Infrared Deep Sky Survey (UKIDSS) photometry to r &lt; 17.8. This was done using colour–colour selection, and then by obtaining accurate photometric redshifts (photo-z) using scaled flux matching (SFM). Compared to spectroscopic redshifts (spec-z), SFM obtained a 1σ scatter of 0.0125 with only 0.3 per cent outliers (|Δln (1 + z)| &gt; 0.06). A sample of 163 186 galaxies was obtained with 0.04 &lt; z &lt; 0.15 over $2300\, {\rm deg}^2$ using a combination of spec-z and photo-z. Following Barro et al. log Σ1.5 = log M* − 1.5log r50, maj was used to define compactness. The spectroscopic completeness was 76 per cent for compact galaxies (log Σ1.5 &gt; 10.5) compared to 92 per cent for normal-sized galaxies. This difference is primarily attributed to SDSS ‘fibre collisions’ and not the completeness of the main galaxy sample selection. Using environmental overdensities, this confirms that compact quiescent galaxies are significantly more likely to be found in high-density environments compared to normal-sized galaxies. By comparison with a high-redshift sample from 3D-HST, log Σ1.5 distribution functions show significant evolution, with this being a compelling way to compare with simulations such as EAGLE. The number density of compact quiescent galaxies drops by a factor of about 30 from z ∼ 2 to log (n/Mpc−3) = − 5.3 ± 0.4 in the SDSS–UKIDSS sample. The uncertainty is dominated by the steep cut off in log Σ1.5, which is demonstrated conclusively using this complete sample.

scholarly journals Photometric redshifts from SDSS images using a convolutional neural network

2018 ◽  
Vol 621 ◽  
pp. A26 ◽  
Author(s):  
Johanna Pasquet ◽  
E. Bertin ◽  
M. Treyer ◽  
S. Arnouts ◽  
D. Fouchez
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Signal To Noise Ratio ◽  
Distribution Functions ◽  
Sloan Digital Sky Survey ◽  
Photometric Redshifts ◽  
Photometric Redshift ◽  
Probability Distribution Functions ◽  
Sky Survey ◽  
Galaxy Sample

We developed a deep convolutional neural network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies in the Main Galaxy Sample of the Sloan Digital Sky Survey at z <  0.4. Our method exploits all the information present in the images without any feature extraction. The input data consist of 64 × 64 pixel ugriz images centered on the spectroscopic targets, plus the galactic reddening value on the line-of-sight. For training sets of 100k objects or more (≥20% of the database), we reach a dispersion σMAD <  0.01, significantly lower than the current best one obtained from another machine learning technique on the same sample. The bias is lower than 10−4, independent of photometric redshift. The PDFs are shown to have very good predictive power. We also find that the CNN redshifts are unbiased with respect to galaxy inclination, and that σMAD decreases with the signal-to-noise ratio (S/N), achieving values below 0.007 for S/N >  100, as in the deep stacked region of Stripe 82. We argue that for most galaxies the precision is limited by the S/N of SDSS images rather than by the method. The success of this experiment at low redshift opens promising perspectives for upcoming surveys.

scholarly journals Central velocity dispersion catalogue of LAMOST-DR7 galaxies

2020 ◽  
Vol 498 (4) ◽  
pp. 5704-5719
Author(s):  
Nicola R Napolitano ◽  
Giuseppe D’Ago ◽  
Crescenzo Tortora ◽  
Gang Zhao ◽  
A-Li Luo ◽  
...  
Keyword(s):  
Galaxy Evolution ◽  
Velocity Dispersion ◽  
Signal To Noise Ratio ◽  
Matter Content ◽  
High Signal ◽  
Data Sets ◽  
Statistical Errors ◽  
The Galaxy ◽  
First Results ◽  
Galaxy Sample

ABSTRACT The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is a major facility to carry out spectroscopic surveys for cosmology and galaxy evolution studies. The seventh data release of the LAMOST ExtraGAlactic Survey (LEGAS) is currently available and including redshifts of 193 361 galaxies. These sources are spread over $\sim 11\, 500$ deg2 of the sky, largely overlapping with other imaging (SDSS and HSC) and spectroscopic (BOSS) surveys. The estimated depth of the galaxy sample, r ∼ 17.8, the high signal-to-noise ratio, and the spectral resolution R = 1800, make the LAMOST spectra suitable for galaxy velocity dispersion (VD) measurements, which are invaluable to study the structure and formation of galaxies and to determine their central dark matter content. We present the first estimates of central VD of $\sim 86\, 000$ galaxies in LAMOST footprint. We have used a wrap-up procedure to perform the spectral fitting using ppxf, and derive VD measurements. Statistical errors are also assessed by comparing LAMOST VD estimates with the ones of SDSS and BOSS over a common sample of $\sim 51\, 000$ galaxies. The two data sets show a good agreement, within the statistical errors, in particular when VD values are corrected to 1 effective radius aperture. We also present a preliminary mass–σ relation and find consistency with previous analyses based on local galaxy samples. These first results suggest that LAMOST spectra are suitable for galaxy VD measurements to complement the available catalogues of galaxy internal kinematics in the Northern hemisphere. We plan to expand this analysis to next LAMOST data releases.

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