| 1. |
|
|
| 2. |
- Audibert, A., et al.
(författare)
-
Black hole feeding and star formation in NGC 1808
- 2021
-
Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 656
-
Tidskriftsartikel (refereegranskat)abstract
- We report on Atacama Large Millimeter Array (ALMA) observations of CO(3-2) emission in the Seyfert2/starburst galaxy NGC1808, at a spatial resolution of 4 pc. Our aim is to investigate the morphology and dynamics of the gas inside the central 0.5 kpc and to probe the nuclear feeding and feedback phenomena. We discovered a nuclear spiral of radius 100 = 45 pc. Within it, we found a decoupled circumnuclear disk or molecular torus of a radius of 0:1300 = 6 pc. The HCN(4-3) and HCO+(4-3) and CS(7-6) dense gas line tracers were simultaneously mapped and detected in the nuclear spiral and they present the same misalignment in the molecular torus. At the nucleus, the HCN/HCO+ and HCN/CS ratios indicate the presence of an active galactic nucleus (AGN). The molecular gas shows regular rotation, within a radius of 400 pc, except for the misaligned disk inside the nuclear spiral arms. The computations of the torques exerted on the gas by the barred stellar potential reveal that the gas within a radius of 100 pc is feeding the nucleus on a timescale of five rotations or on an average timescale of 60 Myr. Some non-circular motions are observed towards the center, corresponding to the nuclear spiral arms. We cannot rule out that small extra kinematic perturbations could be interpreted as a weak outflow attributed to AGN feedback. The molecular outflow detected at 250 pc in the NE direction is likely due to supernovae feedback and it is connected to the kpc-scale superwind.
|
|
| 3. |
- Léget, P-F, et al.
(författare)
-
SUGAR : An improved empirical model of Type Ia supernovae based on spectral features
- 2020
-
Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 636
-
Tidskriftsartikel (refereegranskat)abstract
- 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.
|
|
| 4. |
- Hlozek, R., et al.
(författare)
-
Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)
- 2023
-
Ingår i: Astrophysical Journal Supplement Series. - 0067-0049 .- 1538-4365. ; 267:2
-
Tidskriftsartikel (refereegranskat)abstract
- Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.
|
|
| 5. |
- Rigault, M., et al.
(författare)
-
Strong dependence of Type Ia supernova standardization on the local specific star formation rate
- 2020
-
Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 644
-
Tidskriftsartikel (refereegranskat)abstract
- As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SN Ia) for cosmology, we have statistically classified a large sample of nearby SNe Ia into those that are located in predominantly younger or older environments. This classification is based on the specific star formation rate measured within a projected distance of 1 kpc from each SN location (LsSFR). This is an important refinement compared to using the local star formation rate directly, as it provides a normalization for relative numbers of available SN progenitors and is more robust against extinction by dust. We find that the SNe Ia in predominantly younger environments are ΔY = 0.163 ± 0.029 mag (5.7σ) fainter than those in predominantly older environments after conventional light-curve standardization. This is the strongest standardized SN Ia brightness systematic connected to the host-galaxy environment measured to date. The well-established step in standardized brightnesses between SNe Ia in hosts with lower or higher total stellar masses is smaller, at ΔM = 0.119 ± 0.032 mag (4.5σ), for the same set of SNe Ia. When fit simultaneously, the environment-age offset remains very significant, with ΔY = 0.129 ± 0.032 mag (4.0σ), while the global stellar mass step is reduced to ΔM = 0.064 ± 0.029 mag (2.2σ). Thus, approximately 70% of the variance from the stellar mass step is due to an underlying dependence on environment-based progenitor age. Also, we verify that using the local star formation rate alone is not as powerful as LsSFR at sorting SNe Ia into brighter and fainter subsets. Standardization that only uses the SNe Ia in younger environments reduces the total dispersion from 0.142 ± 0.008 mag to 0.120 ± 0.010 mag. We show that as environment-ages evolve with redshift, a strong bias, especially on the measurement of the derivative of the dark energy equation of state, can develop. Fortunately, data that measure and correct for this effect using our local specific star formation rate indicator, are likely to be available for many next-generation SN Ia cosmology experiments.
|
|
| 6. |
|
|
