HOLISMOKES Cañameras, R.; Schuldt, S.; Suyu, S. H. ...
Astronomy and astrophysics (Berlin),
12/2020, Letnik:
644
Journal Article
Recenzirano
Odprti dostop
We present a systematic search for wide-separation (with Einstein radius
θ
E
≳ 1.5″), galaxy-scale strong lenses in the 30 000 deg
2
of the Pan-STARRS 3
π
survey on the Northern sky. With long time ...delays of a few days to weeks, these types of systems are particularly well-suited for catching strongly lensed supernovae with spatially-resolved multiple images and offer new insights on early-phase supernova spectroscopy and cosmography. We produced a set of realistic simulations by painting lensed COSMOS sources on Pan-STARRS image cutouts of lens luminous red galaxies (LRGs) with redshift and velocity dispersion known from the sloan digital sky survey (SDSS). First, we computed the photometry of mock lenses in
g
r
i
bands and applied a simple catalog-level neural network to identify a sample of 1 050 207 galaxies with similar colors and magnitudes as the mocks. Second, we trained a convolutional neural network (CNN) on Pan-STARRS
g
r
i
image cutouts to classify this sample and obtain sets of 105 760 and 12 382 lens candidates with scores of
p
CNN
> 0.5 and > 0.9, respectively. Extensive tests showed that CNN performances rely heavily on the design of lens simulations and the choice of negative examples for training, but little on the network architecture. The CNN correctly classified 14 out of 16 test lenses, which are previously confirmed lens systems above the detection limit of Pan-STARRS. Finally, we visually inspected all galaxies with
p
CNN
> 0.9 to assemble a final set of 330 high-quality newly-discovered lens candidates while recovering 23 published systems. For a subset, SDSS spectroscopy on the lens central regions proves that our method correctly identifies lens LRGs at
z
∼ 0.1–0.7. Five spectra also show robust signatures of high-redshift background sources, and Pan-STARRS imaging confirms one of them as a quadruply-imaged red source at
z
s
= 1.185, which is likely a recently quenched galaxy strongly lensed by a foreground LRG at
z
d
= 0.3155. In the future, high-resolution imaging and spectroscopic follow-up will be required to validate Pan-STARRS lens candidates and derive strong lensing models. We also expect that the efficient and automated two-step classification method presented in this paper will be applicable to the ∼4 mag deeper
g
r
i
stacks from the
Rubin
Observatory Legacy Survey of Space and Time (LSST) with minor adjustments.
Galaxy redshifts are a key characteristic for nearly all extragalactic studies. Since spectroscopic redshifts require additional telescope and human resources, millions of galaxies are known without ...spectroscopic redshifts. Therefore, it is crucial to have methods for estimating the redshift of a galaxy based on its photometric properties, the so-called photo-
z
. We have developed NetZ, a new method using a convolutional neural network (CNN) to predict the photo-
z
based on galaxy images, in contrast to previous methods that often used only the integrated photometry of galaxies without their images. We use data from the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP) in five different filters as the training data. The network over the whole redshift range between 0 and 4 performs well overall and especially in the high-
z
range, where it fares better than other methods on the same data. We obtained a precision |
z
pred
−
z
ref
| of
σ
= 0.12 (68% confidence interval) with a CNN working for all galaxy types averaged over all galaxies in the redshift range of 0 to ∼4. We carried out a comparison with a network trained on point-like sources, highlighting the importance of morphological information for our redshift estimation. By limiting the scope to smaller redshift ranges or to luminous red galaxies, we find a further notable improvement. We have published more than 34 million new photo-
z
values predicted with NetZ. This shows that the new method is very simple and swift in application, and, importantly, it covers a wide redshift range that is limited only by the available training data. It is broadly applicable, particularly with regard to upcoming surveys such as the
Rubin
Observatory Legacy Survey of Space and Time, which will provide images of billions of galaxies with similar image quality as HSC. Our HSC photo-
z
estimates are also beneficial to the
Euclid
survey, given the overlap in the footprints of the HSC and
Euclid
.
We study the total and baryonic mass distributions of the deflector SDSS J0100+1818 through a full strong lensing analysis. The system is composed of an ultra-massive early-type galaxy at
z
= 0.581, ...with a total stellar mass of (1.5 ± 0.3)×10
12
M
⊙
and a stellar velocity dispersion of (450 ± 40) km s
−1
, surrounded by ten multiple images of three background sources, two of which are spectroscopically confirmed at
z
= 1.880. We took advantage of high-resolution HST photometry and VLT/X-shooter spectroscopy to measure the positions of the multiple images and performed a strong lensing study with the software
GLEE
. We tested different total mass profiles for the lens and modeled the background sources first as point-like and then as extended objects. We successfully predict the positions of the observed multiple images and reconstruct over approximately 7200 HST pixels the complex surface brightness distributions of the sources. We measured the cumulative total mass profile of the lens and find a total mass value of (9.1 ± 0.1)×10
12
M
⊙
, within the Einstein radius of approximately 42 kpc, and stellar-over-total mass fractions ranging from (49 ± 12)%, at the half-light radius (
R
e
= 9.3 kpc) of the lens galaxy, to (10 ± 2)%, in the outer regions (
R
= 70 kpc). These results suggest that the baryonic mass component of SDSS J0100+1818 is very concentrated in its core and that the lens early-type galaxy (or group) is immersed in a massive dark matter halo, which allows it to act as a powerful gravitational lens, creating multiple images with exceptional angular separations. This is consistent with what has been found in other ultra-high-mass candidates at intermediate redshift. We also measured the physical sizes of the distant sources, resolving them down to a few hundred parsecs. Finally, we quantify and discuss a relevant source of systematic uncertainties on the reconstructed sizes of background galaxies, associated with the adopted lens total mass model.
We present a search for galaxy-scale strong gravitational lenses in the initial 2500 square degrees of the Canada-France Imaging Survey (CFIS). We designed a convolutional neural network (CNN) ...committee that we applied to a selection of 2 344 002 exquisite-seeing
r
-band images of color-selected luminous red galaxies. Our classification uses a realistic training set where the lensing galaxies and the lensed sources are both taken from real data, namely the CFIS
r
-band images themselves and the
Hubble
Space Telescope (HST). A total of 9460 candidates obtain a score above 0.5 with the CNN committee. After a visual inspection of the candidates, we find a total of 133 lens candidates, of which 104 are completely new. The set of false positives mainly contains ring, spiral, and merger galaxies, and to a lesser extent galaxies with nearby companions. We classify 32 of the lens candidates as secure lenses and 101 as maybe lenses. For the 32 highest quality lenses, we also fit a singular isothermal ellipsoid mass profile with external shear along with an elliptical Sersic profile for the lens and source light. This automated modeling step provides distributions of properties for both sources and lenses that have Einstein radii in the range 0.5″ <
θ
E
< 2.5″. Finally, we introduce a new lens and/or source single-band deblending algorithm based on auto-encoder representation of our candidates. This is the first time an end-to-end lens-finding and modeling pipeline is assembled together, in view of future lens searches in a single band, as will be possible with
Euclid
.
HOLISMOKES Schuldt, S.; Suyu, S. H.; Meinhardt, T. ...
Astronomy and astrophysics (Berlin),
02/2021, Letnik:
646
Journal Article
Recenzirano
Odprti dostop
Modeling the mass distributions of strong gravitational lenses is often necessary in order to use them as astrophysical and cosmological probes. With the large number of lens systems (≳10
5
) ...expected from upcoming surveys, it is timely to explore efficient modeling approaches beyond traditional Markov chain Monte Carlo techniques that are time consuming. We train a convolutional neural network (CNN) on images of galaxy-scale lens systems to predict the five parameters of the singular isothermal ellipsoid (SIE) mass model (lens center
x
and
y
, complex ellipticity
e
x
and
e
y
, and Einstein radius
θ
E
). To train the network we simulate images based on real observations from the Hyper Suprime-Cam Survey for the lens galaxies and from the
Hubble
Ultra Deep Field as lensed galaxies. We tested different network architectures and the effect of different data sets, such as using only double or quad systems defined based on the source center and using different input distributions of
θ
E
. We find that the CNN performs well, and with the network trained on both doubles and quads with a uniform distribution of
θ
E
> 0.5″ we obtain the following median values with 1
σ
scatter: Δ
x
= (0.00
−0.30
+0.30
)″, Δ
y
= (0.00
−0.29
+0.30
)″, Δ
θ
E
= (0.07
−0.12
+0.29
)″, Δ
e
x
= −0.01
−0.09
+0.08
, and Δ
e
y
= 0.00
−0.09
+0.08
. The bias in
θ
E
is driven by systems with small
θ
E
. Therefore, when we further predict the multiple lensed image positions and time-delays based on the network output, we apply the network to the sample limited to
θ
E
> 0.8″. In this case the offset between the predicted and input lensed image positions is (0.00
−0.29
+0.29
)″ and (0.00
−0.31
+0.32
)″ for the
x
and
y
coordinates, respectively. For the fractional difference between the predicted and true time-delay, we obtain 0.04
−0.05
+0.27
. Our CNN model is able to predict the SIE parameter values in fractions of a second on a single CPU, and with the output we can predict the image positions and time-delays in an automated way, such that we are able to process efficiently the huge amount of expected galaxy-scale lens detections in the near future.
HOLISMOKES Suyu, S. H.; Huber, S.; Cañameras, R. ...
Astronomy and astrophysics (Berlin),
12/2020, Letnik:
644
Journal Article, Web Resource
Recenzirano
Odprti dostop
We present the HOLISMOKES programme on strong gravitational lensing of supernovae (SNe) as a probe of SN physics and cosmology. We investigate the effects of microlensing on early-phase SN Ia spectra ...using four different SN explosion models. We find that distortions of SN Ia spectra due to microlensing are typically negligible within ten rest-frame days after a SN explosion (< 1% distortion within the 1
σ
spread and ≲10% distortion within the 2
σ
spread). This shows the great prospects of using lensed SNe Ia to obtain intrinsic early-phase SN spectra for deciphering SN Ia progenitors. As a demonstration of the usefulness of lensed SNe Ia for cosmology, we simulate a sample of mock lensed SN Ia systems that are expected to have accurate and precise time-delay measurements in the era of the
Rubin
Observatory Legacy Survey of Space and Time (LSST). Adopting realistic yet conservative uncertainties on their time-delay distances and lens angular diameter distances, of 6.6% and 5%, respectively, we find that a sample of 20 lensed SNe Ia would allow us to constrain the Hubble constant (
H
0
) with 1.3% uncertainty in the flat ΛCDM cosmology. We find a similar constraint on
H
0
in an open ΛCDM cosmology, while the constraint degrades to 3% in a flat
w
CDM cosmology. We anticipate lensed SNe to be an independent and powerful probe of SN physics and cosmology in the upcoming LSST era.
HOLISMOKES Cañameras, R.; Schuldt, S.; Shu, Y. ...
Astronomy and astrophysics (Berlin),
09/2021, Letnik:
653
Journal Article
Recenzirano
Odprti dostop
We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens ...simulations, deep neural network classification, and visual inspection, is aimed at efficiently selecting systems with wide image separations (Einstein radii
θ
E
∼ 1.0–3.0″), intermediate redshift lenses (
z
∼ 0.4–0.7), and bright arcs for galaxy evolution and cosmology. We classified
gri
images of all 62.5 million galaxies in HSC Wide with
i
-band Kron radius ≥0.8″ to avoid strict preselections and to prepare for the upcoming era of deep, wide-scale imaging surveys with Euclid and Rubin Observatory. We obtained 206 newly-discovered candidates classified as definite or probable lenses with either spatially-resolved multiple images or extended, distorted arcs. In addition, we found 88 high-quality candidates that were assigned lower confidence in previous HSC searches, and we recovered 173 known systems in the literature. These results demonstrate that, aided by limited human input, deep learning pipelines with false positive rates as low as ≃0.01% can be very powerful tools for identifying the rare strong lenses from large catalogs, and can also largely extend the samples found by traditional algorithms. We provide a ranked list of candidates for future spectroscopic confirmation.
We present our search for strong lens, galaxy-scale systems in the first data release of the Dark Energy Survey (DES), based on a color-selected parent sample of 18 745 029 luminous red galaxies ...(LRGs). We used a convolutional neural network (CNN) to grade this LRG sample with values between 0 (non-lens) and 1 (lens). Our training set of mock lenses is data-driven, that is, it uses lensed sources taken from HST-COSMOS images and lensing galaxies from DES images of our LRG sample. A total of 76 582 cutouts were obtained with a score above 0.9, which were then visually inspected and classified into two catalogs. The first one contains 405 lens candidates, of which 90 present clear lensing features and counterparts, while the other 315 require more evidence, such as higher resolution imaging or spectra, to be conclusive. A total of 186 candidates are newly identified by our search, of which 16 are among the 90 most promising (best) candidates. The second catalog includes 539 ring galaxy candidates. This catalog will be a useful false positive sample for training future CNNs. For the 90 best lens candidates we carry out color-based deblending of the lens and source light without fitting any analytical profile to the data. This method is shown to be very efficient in the deblending, even for very compact objects and for objects with a complex morphology. Finally, from the 90 best lens candidates, we selected 52 systems with one single deflector to test an automated modeling pipeline that has the capacity to successfully model 79% of the sample within an acceptable computing runtime.
We present an extensive CO emission-line survey of the Planck's dusty Gravitationally Enhanced subMillimetre Sources, a small set of 11 strongly lensed dusty star-forming galaxies at z = 2-4 ...discovered with Planck and Herschel satellites, using EMIR on the IRAM 30-m telescope. We detected a total of 45 CO rotational lines from Jup = 3 to Jup = 11, and up to eight transitions per source, allowing a detailed analysis of the gas excitation and interstellar medium conditions within these extremely bright (μLFIR = 0.5 - 3.0 × 1014L⊙), vigorous starbursts. The peak of the CO spectral-line energy distributions (SLEDs) fall between Jup = 4 and Jup = 7 for nine out of 11 sources, in the same range as other lensed and unlensed submillimeter galaxies (SMGs) and the inner regions of local starbursts. We applied radiative transfer models using the large velocity gradient approach to infer the spatially-averaged molecular gas densities, nH2 ≃ 102.6 - 104.1 cm-3, and kinetic temperatures, Tk ≃ 30-1000 K. In five sources, we find evidence of two distinct gas phases with different properties and model their CO SLED with two excitation components. The warm (70-320 K) and dense gas reservoirs in these galaxies are highly excited, while the cooler (15-60 K) and more extended low-excitation components cover a range of gas densities. In two sources, the latter is associated with diffuse Milky Way-like gas phases of density nH2 ≃ 102.4 - 102.8 cm-3, which provides evidence that a significant fraction of the total gas masses of dusty starburst galaxies can be embedded in cool, low-density reservoirs. The delensed masses of the warm star-forming molecular gas range from 0.6to12 × 1010 M⊙. Finally, we show that the CO line luminosity ratios are consistent with those predicted by models of photon-dominated regions (PDRs) and disfavor scenarios of gas clouds irradiated by intense X-ray fields from active galactic nuclei. By combining CO, C I and C II line diagnostics, we obtain average PDR gas densities significantly higher than in normal star-forming galaxies at low-redshift, as well as far-ultraviolet radiation fields 102-104 times more intense than in the Milky Way. These spatially-averaged conditions are consistent with those in high-redshift SMGs and in a range of low-redshift environments, from the central regions of ultra-luminous infrared galaxies and bluer starbursts to Galactic giant molecular clouds. Based on IRAM data obtained with programs 082-12, D09-12, 065-13, 094-13, 223-13, 108-14, and 217-14.
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