scholarly journals SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

2021 ◽  
Vol 923 (2) ◽  
pp. 265
Author(s):  
W. D. Kenworthy ◽  
D. O. Jones ◽  
M. Dai ◽  
R. Kessler ◽  
D. Scolnic ◽  
...  
Keyword(s):  
Spectral Energy Distribution ◽  
Cosmological Parameters ◽  
Training Sample ◽  
Training Data ◽  
Optical Data ◽  
Spectral Energy ◽  
Model Framework ◽  
Type Ia ◽  
Estimation Of Uncertainties ◽  
Improved Model

Abstract A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low-z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low-z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/, and the model is integrated into the sncosmo and SNANA software packages.

scholarly journals Significant luminosity differences of two twin Type Ia supernovae

2019 ◽  
Vol 491 (4) ◽  
pp. 5991-5999 ◽  
Author(s):  
Ryan J Foley ◽  
Samantha L Hoffmann ◽  
Lucas M Macri ◽  
Adam G Riess ◽  
Peter J Brown ◽  
...  
Keyword(s):  
Light Curve ◽  
Spectral Energy Distribution ◽  
Cosmological Parameters ◽  
Spectral Energy ◽  
Type Ia Supernovae ◽  
Curve Shape ◽  
Type Ia ◽  
Optical Light Curve ◽  
Ia Supernovae ◽  
Peak Luminosity

ABSTRACT The Type Ia supernovae (SNe Ia) 2011by, hosted in NGC 3972, and 2011fe, hosted in M101, are optical ‘twins,’ having almost identical optical light-curve shapes, colours, and near-maximum-brightness spectra. However, SN 2011fe had significantly more ultraviolet (UV; 1600 &lt; λ &lt; 2500 Å) flux than SN 2011by before and at peak luminosity. Several theoretical models predict that SNe Ia with higher progenitor metallicity should (1) have additional UV opacity and thus lower UV flux; (2) have an essentially unchanged optical spectral-energy distribution; (3) have a similar optical light-curve shape; and (4) because of the excess neutrons, produce more stable Fe-group elements at the expense of radioactive 56Ni and thus have a lower peak luminosity. Following these predictions, Foley and Kirshner suggested that the difference in UV flux between SNe 2011by and 2011fe was the result of their progenitors having significantly different metallicities. They also measured a large, but insignificant, difference between the peak absolute magnitudes of the SNe (ΔMV, peak = 0.60 ± 0.36 mag), with SN 2011fe being more luminous. We present a new Cepheid-based distance to NGC 3972, substantially improving the precision of the distance measurement for SN 2011by. With these new data, we determine that the SNe have significantly different peak luminosities (ΔMV, peak = 0.335 ± 0.069 mag). Consequently, SN 2011fe produced 38 per cent more 56Ni than SN 2011by, consistent with predictions for progenitor metallicity differences for these SNe, although alternative models may also explain this difference. We discuss how progenitor metallicity differences can contribute to the intrinsic scatter for light-curve-shape-corrected SN luminosities, the use of ‘twin’ SNe for measuring distances, and implications for using SNe Ia for constraining cosmological parameters.

scholarly journals Photometric redshifts for X-ray-selected active galactic nuclei in the eROSITA era

2019 ◽  
Vol 489 (1) ◽  
pp. 663-680 ◽  
Author(s):  
M Brescia ◽  
M Salvato ◽  
S Cavuoti ◽  
T T Ananna ◽  
G Riccio ◽  
...  
Keyword(s):  
Active Galactic Nuclei ◽  
Large Fraction ◽  
Spectral Energy Distribution ◽  
Galactic Nuclei ◽  
Training Sample ◽  
Spectral Energy ◽  
Ancillary Data ◽  
Photometric Redshifts ◽  
X Ray

ABSTRACT With the launch of eROSITA (extended Roentgen Survey with an Imaging Telescope Array), successfully occurred on 2019 July 13, we are facing the challenge of computing reliable photometric redshifts for 3 million of active galactic nuclei (AGNs) over the entire sky, having available only patchy and inhomogeneous ancillary data. While we have a good understanding of the photo-z quality obtainable for AGN using spectral energy distribution (SED)-fitting technique, we tested the capability of machine learning (ML), usually reliable in computing photo-z for QSO in wide and shallow areas with rich spectroscopic samples. Using MLPQNA as example of ML, we computed photo-z for the X-ray-selected sources in Stripe 82X, using the publicly available photometric and spectroscopic catalogues. Stripe 82X is at least as deep as eROSITA will be and wide enough to include also rare and bright AGNs. In addition, the availability of ancillary data mimics what can be available in the whole sky. We found that when optical, and near- and mid-infrared data are available, ML and SED fitting perform comparably well in terms of overall accuracy, realistic redshift probability density functions, and fraction of outliers, although they are not the same for the two methods. The results could further improve if the photometry available is accurate and including morphological information. Assuming that we can gather sufficient spectroscopy to build a representative training sample, with the current photometry coverage we can obtain reliable photo-z for a large fraction of sources in the Southern hemisphere well before the spectroscopic follow-up, thus timely enabling the eROSITA science return. The photo-z catalogue is released here.

scholarly journals COMBO-17+4: An Optical-NIR Survey for Galaxies out to z=2

2006 ◽  
Vol 2 (S235) ◽  
pp. 419-419
Author(s):  
M-H. Nicol ◽  
K. Meisenheimer ◽  
C. Tapken ◽  
C. Wolf
Keyword(s):  
Galaxy Evolution ◽  
Near Infrared ◽  
Spectral Energy Distribution ◽  
Broad Band ◽  
Optical Data ◽  
Spectral Energy ◽  
Data Set ◽  
Infrared Observation ◽  
Redshift Range ◽  
Red Sequence

AbstractClassifying Object by Medium-Band Observations in 17 filters (COMBO-17) has already produced a very accurate picture of galaxy evolution since z~1 based on 25000 galaxies in 17 medium optical bands. We now extend the range of reliable multi-color redshifts with COMBO-17+4, a deep optical-NIR survey which will combine the existing optical data set of COMBO-17 with near infrared observation in three medium bands: Y(λ/Δλ = 1040/80nm), J1(1190/130nm) and J2(1320/130nm) and one broad band H(1650/300nm). The NIR bands extend the photometric redshift range to z~2.1. COMBO 17+4 will provide the first large sample of galaxies (>5000) at 1<z<2 with a redshifts accuracy of Δz<0.03(1+z). Three fields are observed: Abell 901, Abell 226 and the COMBO 11h-field, for a total coverage of 0.77□2 of the sky. Each COMBO 17+4 field measures 31 × 30 sqarcmin. The NIR bands are observed with the Omega2000 camera at Calar Alto Observatory in Spain.The scientific goals for this study are multiple. COMBO-17+4 will enable us to establish the luminosity function for the red sequence and blue galaxies in the redshift range 1<z<2. Also it will be possible to determine the formation history at z=2 by analyzing the width of the red sequence galaxies. Moreover this survey will provide several thousand of individual galaxy masses (with an accuracy <30%) obtained with Spectral Energy Distribution (SED) template fitting. Once the masses are obtained the mass function will provide a useful tool to test the hierarchical model of evolution of galaxies by checking whether the massive red sequence galaxies (logM>10.5) are already in place at z>1.5 (9Gyr).We present first results from the full 21 bands photometry in half of the Abell 901 field. It allows us to study not only z>1 galaxies but also the stellar content of several hundred cluster galaxies.

scholarly journals Artificial neural network spectral light curve template for type Ia supernovae and its cosmological constraints

2021 ◽  
pp. 2150149
Author(s):  
Qiao-Bin Cheng ◽  
Chao-Jun Feng ◽  
Xiang-Hua Zhai ◽  
Xin-Zhou Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Light Curve ◽  
Spectral Energy Distribution ◽  
Spectral Energy ◽  
Type Ia Supernovae ◽  
Light Curve Analysis ◽  
Type Ia ◽  
Artificial Neural ◽  
Ia Supernovae

The spectral energy distribution (SED) sequence for type Ia supernovae (SN Ia) is modeled by an artificial neural network. The SN Ia luminosity is characterized as a function of phase, wavelength, a color parameter and a decline rate parameter. After training and testing the neural network, the SED sequence could give both the spectrum with wavelength range from 3000 Åto 8000 Åand the light curve with phase from 20 days before to 50 days after the maximum luminosity for the supernovae with different colors and decline rates. Therefore, we call this the Artificial Neural Network Spectral Light Curve Template (ANNSLCT) model. We retrain the Joint Light-curve Analysis (JLA) supernova sample by using the ANNSLCT model and obtain the parameters for each supernova to make a constraint on the cosmological [Formula: see text]CDM model. We find that the best fitting values of these parameters are very close to those from the JLA sample trained with the Spectral Adaptive Lightcurve Template 2 (SALT2) model. It is expectable that the ANNSLCT model has potential to analyze more SN Ia multi-color light curves measured in future observation projects.

Multiwavelength study of different flaring and low-activity states of blazar 4C+21.35

2020 ◽  
Vol 500 (1) ◽  
pp. 1127-1138
Author(s):  
Debbijoy Bhattacharya ◽  
Krishna Mohana A ◽  
Subir Bhattacharyya ◽  
Nilay Bhatt ◽  
C S Stalin
Keyword(s):  
Spectral Energy Distribution ◽  
Broad Band ◽  
Optical Data ◽  
Spectral Energy ◽  
Emission Region ◽  
Electromagnetic Spectrum ◽  
Large Area ◽  
Γ Ray ◽  
The One ◽  
Low Activity

ABSTRACT Blazars, a class of active galactic nuclei, emit over the entire accessible electromagnetic spectrum and modelling of their broad-band spectral energy distribution (SED) is the key to constrain the underlying emission mechanisms. Here we report the results on the one-zone leptonic emission modelling carried out on the blazar 4C+21.35 using multiwavelength data spanning over the period 2008–2018. Broad-band SED modelling using γ-ray data from Fermi-Large Area Telescope, X-ray data from Swift-XRT and AstroSat, and UV–optical data from Swift-UVOT, AstroSat, and Catalina Real-Time Transient Survey was carried out at seven different epochs, including three γ-ray flaring episodes and four quiescent periods (three long-term averaged ones and one during AstroSat observing period). Our SED modelling suggests that two compact emission regions originating at a different time outside the broad-line region and moving away from the core with variation primarily in the jet electron spectra can explain the emission from the high-, moderate-, and low-activity periods. The emissions from high- and first low-activity states are likely to have originated in the first region. The moderate- and second low-activity states are likely due to the second emission region with fresh particle acceleration/injection at a later time.

scholarly journals Spectroscopy of the first resolved strongly lensed Type Ia supernova iPTF16geu

2020 ◽  
Author(s):  
J Johansson ◽  
A Goobar ◽  
S H Price ◽  
A Sagués Carracedo ◽  
L Della Bruna ◽  
...  
Keyword(s):  
Time Delay ◽  
Hubble Space Telescope ◽  
Signal To Noise Ratio ◽  
Spectral Energy Distribution ◽  
Compact Objects ◽  
Light Curves ◽  
Host Galaxy ◽  
Spectral Energy ◽  
Type Ia Supernova ◽  
Type Ia

Abstract We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground based telescopes and the Hubble Space Telescope (HST). From a single epoch of slitless spectroscopy with HST, we resolve spectra of individual lensed supernova images for the first time. This allows us to perform an independent measurement of the time-delay between the two brightest images, Δt = 1.4 ± 5.0 days, which is consistent with the time-delay measured from the light-curves. We also present measurements of narrow emission and absorption lines characterizing the interstellar medium in the SN Ia host galaxy at z = 0.4087, as well as in the foreground lensing galaxy at z = 0.2163. We detect strong Na id absorption in the host galaxy, indicating that iPTF16geu belongs to a subclass of SNe Ia displaying ”anomalously” large Na id column densities compared to dust extinction derived from light curves. For the lens galaxy, we refine the measurement of the velocity dispersion, σ = 129 ± 4 km s−1, which significantly constrains the lens model. We use ground-based spectroscopy, boosted by a factor ∼70 from lensing magnification, to study the properties of a high-z SN Ia with unprecedented signal-to-noise ratio. The spectral properties of the supernova, such as pseudo-Equivalent widths of several absorption features and velocities of the Si ii-line, indicate that iPTF16geu is a normal SN Ia. We do not detect any significant deviations of the SN spectral energy distribution from microlensing of the SN photosphere by stars and compact objects in the lensing galaxy.

scholarly journals SUGAR: An improved empirical model of Type Ia supernovae based on spectral features

2020 ◽  
Vol 636 ◽  
pp. A46 ◽  
Author(s):  
P.-F. Léget ◽  
E. Gangler ◽  
F. Mondon ◽  
G. Aldering ◽  
P. Antilogus ◽  
...  
Keyword(s):  
Spectral Energy Distribution ◽  
Principal Component ◽  
Spectral Energy ◽  
Type Ia Supernovae ◽  
Wide Field ◽  
Spectral Features ◽  
Intrinsic Properties ◽  
Distance Measurements ◽  
Type Ia ◽  
Ia Supernovae

Context. Type Ia supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. Aims. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SUGAR), which improves the spectral description of SNe Ia, and consequently could improve the distance measurements. Methods. This model was constructed from SNe Ia spectral properties and spectrophotometric data from the Nearby Supernova Factory collaboration. In a first step, a principal component analysis-like method was used on spectral features measured at maximum light, which allowed us to extract the intrinsic properties of SNe Ia. Next, the intrinsic properties were used to extract the average extinction curve. Third, an interpolation using Gaussian processes facilitated using data taken at different epochs during the lifetime of an SN Ia and then projecting the data on a fixed time grid. Finally, the three steps were combined to build the SED model as a function of time and wavelength. This is the SUGAR model. Results. The main advancement in SUGAR is the addition of two additional parameters to characterize SNe Ia variability. The first is tied to the properties of SNe Ia ejecta velocity and the second correlates with their calcium lines. The addition of these parameters, as well as the high quality of the Nearby Supernova Factory data, makes SUGAR an accurate and efficient model for describing the spectra of normal SNe Ia as they brighten and fade. Conclusions. The performance of this model makes it an excellent SED model for experiments like the Zwicky Transient Facility, the Large Synoptic Survey Telescope, or the Wide Field Infrared Survey Telescope.

scholarly journals Dust in the Wolf–Rayet nebula M 1-67

2020 ◽  
Vol 497 (4) ◽  
pp. 4128-4142
Author(s):  
P Jiménez-Hernández ◽  
S J Arthur ◽  
J A Toalá
Keyword(s):  
Mass Loss ◽  
Galactic Plane ◽  
Spectral Synthesis ◽  
Mass Loss Rate ◽  
Spectral Energy Distribution ◽  
Optical Data ◽  
Spectral Energy ◽  
Wide Field ◽  
Power Law Distribution ◽  
Massive Star Evolution

ABSTRACT The Wolf–Rayet nebula M 1-67 around WR 124 is located above the Galactic plane in a region mostly empty of interstellar medium, which makes it the perfect target to study the mass-loss episodes associated with the late stages of massive star evolution. Archive photometric observations from Wide-field Infrared Survey Explorer(WISE), Spitzer (MIPS), and Herschel (PACS and SPIRE) are used to construct the spectral energy distribution (SED) of the nebula in the wavelength range of 12–500 μm. The infrared (photometric and spectroscopic) data and nebular optical data from the literature are modelled simultaneously using the spectral synthesis code cloudy, where the free parameters are the gas density distribution and the dust grain-sized distribution. The infrared SED can be reproduced by dust grains with two size distributions: an MRN power-law distribution with grain sizes between 0.005 and 0.05 μm and a population of large grains with representative size of 0.9 μm. The latter points towards an eruptive origin for the formation of M 1-67. The model predicts a nebular ionized gas mass of $M_\mathrm{ion} = 9.2^{+1.6}_{-1.5}~\mathrm{M}_\odot$ and the estimated mass-loss rate during the dust formation period is $\dot{M} \approx 6 \times 10^{-4}~ \mathrm{M}_\odot$ yr−1. We discuss the implications of our results in the context of single and binary stellar evolution and propose that M 1-67 represents the best candidate for a post-common envelope scenario in massive stars.

scholarly journals Detailed spectral and morphological analysis of the shell type supernova remnant RCW 86

2018 ◽  
Vol 612 ◽  
pp. A4 ◽  
Author(s):  
◽  
A. Abramowski ◽  
F. Aharonian ◽  
F. Ait Benkhali ◽  
A. G. Akhperjanian ◽  
...  
Keyword(s):  
Kinetic Energy ◽  
Energy Distribution ◽  
Spectral Index ◽  
Supernova Remnant ◽  
Spectral Energy Distribution ◽  
High Energy ◽  
Spectral Energy ◽  
X Ray ◽  
Type Ia Supernova ◽  
Type Ia

Aim. We aim for an understanding of the morphological and spectral properties of the supernova remnant RCW 86 and for insights into the production mechanism leading to the RCW 86 very high-energy γ-ray emission.Methods. We analyzed High Energy Spectroscopic System (H.E.S.S.) data that had increased sensitivity compared to the observations presented in the RCW 86 H.E.S.S. discovery publication. Studies of the morphological correlation between the 0.5–1 keV X-ray band, the 2–5 keV X-ray band, radio, and γ-ray emissions have been performed as well as broadband modeling of the spectral energy distribution with two different emission models.Results. We present the first conclusive evidence that the TeV γ-ray emission region is shell-like based on our morphological studies. The comparison with 2–5 keV X-ray data reveals a correlation with the 0.4–50 TeV γ-ray emission. The spectrum of RCW 86 is best described by a power law with an exponential cutoff at Ecut = (3.5 ± 1.2stat) TeV and a spectral index of Γ ≈ 1.6 ± 0.2. A static leptonic one-zone model adequately describes the measured spectral energy distribution of RCW 86, with the resultant total kinetic energy of the electrons above 1 GeV being equivalent to ~0.1% of the initial kinetic energy of a Type Ia supernova explosion (1051 erg). When using a hadronic model, a magnetic field of B ≈ 100 μG is needed to represent the measured data. Although this is comparable to formerly published estimates, a standard E−2 spectrum for the proton distribution cannot describe the γ-ray data. Instead, a spectral index of Γp ≈ 1.7 would be required, which implies that ∼7 × 1049/ncm−3 has been transferred into high-energy protons with the effective density ncm−3 = n/1 cm−3. This is about 10% of the kinetic energy of a typical Type Ia supernova under the assumption of a density of 1 cm−3.

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