Abstract
We present the largest and most homogeneous collection of near-infrared (NIR) spectra of Type Ia supernovae (SNe Ia): 339 spectra of 98 individual SNe obtained as part of the Carnegie ...Supernova Project-II. These spectra, obtained with the FIRE spectrograph on the 6.5 m Magellan Baade telescope, have a spectral range of 0.8–2.5
μ
m. Using this sample, we explore the NIR spectral diversity of SNe Ia and construct a template of spectral time series as a function of the light-curve-shape parameter, color stretch
s
BV
. Principal component analysis is applied to characterize the diversity of the spectral features and reduce data dimensionality to a smaller subspace. Gaussian process regression is then used to model the subspace dependence on phase and light-curve shape and the associated uncertainty. Our template is able to predict spectral variations that are correlated with
s
BV
, such as the hallmark NIR features: Mg
ii
at early times and the
H
-band break after peak. Using this template reduces the systematic uncertainties in
K
-corrections by ∼90% compared to those from the Hsiao template. These uncertainties, defined as the mean
K
-correction differences computed with the color-matched template and observed spectra, are on the level of 4 × 10
−4
mag on average. This template can serve as the baseline spectral energy distribution for light-curve fitters and can identify peculiar spectral features that might point to compelling physics. The results presented here will substantially improve future SN Ia cosmological experiments, for both nearby and distant samples.
Abstract We report an analysis of a sample of 186 spectroscopically confirmed Type II supernova (SN) light curves (LCs) obtained from a combination of Zwicky Transient Facility (ZTF) and Asteroid ...Terrestrial-impact Last Alert System observations. We implement a method to infer physical parameters from these LCs using hydrodynamic models that take into account the progenitor mass, the explosion energy, and the presence of circumstellar matter (CSM). The CSM is modeled via the mass-loss rate, wind acceleration at the surface of the progenitor star with a β velocity law, and the CSM radius. We also infer the time of explosion, attenuation ( A V ), and the redshift for each SN. Our results favor low-mass progenitor stars ( M ZAMS < 14 M ⊙ ) with a dense CSM ( M ̇ > 10 −3 M ⊙ yr −1 , CSM radius ∼ 10 15 cm, and β > 2). Additionally, we find that the redshifts inferred from the SN LCs are significantly more accurate than those inferred using the host galaxy photometric redshift, suggesting that this method could be used to infer more accurate host galaxy redshifts from large samples of Type II SNe in the LSST era. Lastly, we compare our results with similar works from the literature.
Supernova (SN) 2017cbv in NGC 5643 is one of a handful of Type Ia supernovae (SNe Ia) reported to have excess blue emission at early times. This paper presents extensive BVRIYJHKs-band light curves ...of SN 2017cbv, covering the phase from −16 to +125 days relative to B-band maximum light. The SN 2017cbv reached a B-band maximum of 11.710 0.006 mag, with a postmaximum magnitude decline of Δm15(B) = 0.990 0.013 mag. The SN suffered no host reddening based on Phillips intrinsic color, the Lira-Phillips relation, and the CMAGIC diagram. By employing the CMAGIC distance modulus = 30.58 0.05 mag and assuming H0 = 72 km s−1 Mpc−1, we found that 0.73 M 56Ni was synthesized during the explosion of SN 2017cbv, which is consistent with estimates using reddening- and distance-free methods via the phases of the secondary maximum of the near-IR- (NIR-) band light curves. We also present 14 NIR spectra from −18 to +49 days relative to the B-band maximum light, providing constraints on the amount of swept-up hydrogen from the companion star in the context of the single degenerate progenitor scenario. No Paβ emission feature was detected from our postmaximum NIR spectra, placing a hydrogen mass upper limit of 0.1 M . The overall optical/NIR photometric and NIR spectral evolution of SN 2017cbv is similar to that of a normal SN Ia, even though its early evolution is marked by a flux excess not seen in most other well-observed normal SNe Ia. We also compare the exquisite light curves of SN 2017cbv with some Mch delayed detonation models and sub-Mch double detonation models.
We introduce Deep-HiTS, a rotation-invariant convolutional neural network (CNN) model for classifying images of transient candidates into artifacts or real sources for the High cadence Transient ...Survey (HiTS). CNNs have the advantage of learning the features automatically from the data while achieving high performance. We compare our CNN model against a feature engineering approach using random forests (RFs). We show that our CNN significantly outperforms the RF model, reducing the error by almost half. Furthermore, for a fixed number of approximately 2000 allowed false transient candidates per night, we are able to reduce the misclassified real transients by approximately one-fifth. To the best of our knowledge, this is the first time CNNs have been used to detect astronomical transient events. Our approach will be very useful when processing images from next generation instruments such as the Large Synoptic Survey Telescope. We have made all our code and data available to the community for the sake of allowing further developments and comparisons at https://github.com/guille-c/Deep-HiTS.
Abstract
In astronomical surveys, such as the Zwicky Transient Facility, supernovae (SNe) are relatively uncommon objects compared to other classes of variable events. Along with this scarcity, the ...processing of multiband light curves is a challenging task due to the highly irregular cadence, long time gaps, missing values, few observations, etc. These issues are particularly detrimental to the analysis of transient events: SN-like light curves. We offer three main contributions: (1) Based on temporal modulation and attention mechanisms, we propose a deep attention model (TimeModAttn) to classify multiband light curves of different SN types, avoiding photometric or hand-crafted feature computations, missing-value assumptions, and explicit imputation/interpolation methods. (2) We propose a model for the synthetic generation of SN multiband light curves based on the Supernova Parametric Model, allowing us to increase the number of samples and the diversity of cadence. Thus, the TimeModAttn model is first pretrained using synthetic light curves. Then, a fine-tuning process is performed. The TimeModAttn model outperformed other deep learning models, based on recurrent neural networks, in two scenarios: late-classification and early-classification. Also, the TimeModAttn model outperformed a Balanced Random Forest (BRF) classifier (trained with real data), increasing the balanced-
F
1
score from ≈.525 to ≈.596. When training the BRF with synthetic data, this model achieved a similar performance to the TimeModAttn model proposed while still maintaining extra advantages. (3) We conducted interpretability experiments. High attention scores were obtained for observations earlier than and close to the SN brightness peaks. This also correlated with an early highly variability of the learned temporal modulation.
We present well-sampled UBVRIJHK photometry of SN 2002fk starting 12 days before maximum light through 122 days after peak brightness, along with a series of 15 optical spectra from -4 to +95 days ...since maximum. Our observations show the presence of C II lines in the early-time spectra of SN 2002fk, expanding at 11,000 km super(s-1) and persisting until 8 days past maximum light with a velocity of ~9000 km s super(-1). SN 2002fk is characterized by a small velocity gradient of upsilon sub(Si II) = 26 km s super(-1) day super(-1), possibly caused by an off-center explosion with the ignition region oriented toward the observer. The connection between the viewing angle of an off-center explosion and the presence of C II in the early-time spectrum suggests that the observation of C II could be also due to a viewing angle effect. Adopting the Cepheid distance to NGC 1309 we provide the first H sub(0) value based on nearinfrared (near-IR) measurements of a Type Ia supernova (SN) between 63.0 + or - 0.8 (+ or - 3.4 systematic) and 66.7 + or - 1.0 (+ or - 3.5 systematic) km s super(-1) Mpc super(-1), depending on the absolutemagnitude/decline rate relationship adopted. It appears that the near-IR yields somewhat lower (6%-9%) H sub(0) values than the optical. It is essential to further examine this issue by (1) expanding the sample of high-quality near-IR light curves of SNe in the Hubble flow, and (2) increasing the number of nearby SNe with near-IR SN light curves and precise Cepheid distances, which affords the promise to deliver a more precise determination of H sub(0).
We introduce two simplified nuclear networks that can be used in hydrostatic carbon burning reactions occurring in white dwarf interiors. They model the relevant nuclear reactions in carbon-oxygen ...white dwarfs approaching ignition in Type Ia supernova progenitors, including the effects of the main e ---captures and Delta *b-decays that drive the convective Urca process. They are based on studies of a detailed nuclear network compiled by the authors and are defined by approximate sets of differential equations whose derivations are included in the text. The first network, N1, provides a good first-order estimation of the distribution of ashes and it also provides a simple picture of the main reactions occurring during this phase of evolution. The second network, N2, is a more refined version of N1 and can reproduce the evolution of the main physical properties of the full network to the 5% level. We compare the evolution of the mole fraction of the relevant nuclei, the neutron excess, the photon energy generation, and the neutrino losses between both simplified networks and the detailed reaction network in a fixed temperature and density parcel of gas.
Intermediate-mass black holes (IMBHs) have masses between 102 and 106 M and are key to our understanding of the formation of massive black holes. The known population of IMBHs remains small, with a ...few hundred candidates and only a handful of them confirmed as bona fide IMBHs. Until now, the most widely used selection method is based on spectral analysis. Here we present a methodology to select IMBH candidates via optical variability analysis of the nuclear region of local galaxies ( ). Active IMBHs accreting at low rates show small amplitude variability with timescales of hours, as is seen in one of the known IMBHs, NGC 4395. We found a sample of ∼500 galaxies demonstrating fast and small amplitude variation in their week-based light curves. We estimate an average occupancy fraction of 4% and a surface density of ∼3 deg−2, which represent an increase by a factor of ∼40 compared to previous searches. A large fraction (78%) of the candidates are in spiral galaxies. We preliminarily confirm the active galactic nucleus nature of 22 sources via Baldwin, Phillips, and Terlevich diagrams using Sloan Digital Sky Survey legacy spectra. Further confirmation of these candidates will require multiwavelength observations, especially in X-ray and radio bands.
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