Breaking the color-reddening degeneracy in type Ia supernovae

A new method to study the intrinsic color and luminosity of type Ia supernovae (SNe Ia) is presented. A metric space built using principal component analysis (PCA) on spectral series SNe Ia between -12.5 and +17.5 days from B maximum is used as a set of predictors. This metric space is built to be insensitive to reddening. Hence, it does not predict the part of color excess due to dust-extinction. At the same time, the rich variability of SN Ia spectra is a good predictor of a large fraction of the intrinsic color variability. Such metric space is a good predictor of the epoch when the maximum in the B-V color curve is reached. Multivariate Partial Least Square (PLS) regression predicts the intrinsic B band light-curve and the intrinsic B-V color curve up to a month after maximum. This allows to study the relation between the light curves of SNe Ia and their spectra. The total-to-selective extinction ratio RV in the host-galaxy of SNe Ia is found, on average, to be consistent with typical Milky-Way values. This analysis shows the importance of collecting spectra to study SNe Ia, even with large sample publicly available. Future automated surveys as LSST will provide a large number of light curves. The analysis shows that observing accompaning spectra for a significative number of SNe will be important even in the case of "normal" SNe Ia.Comment: 11 pages, 11 figure

Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNeIa through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using Deep Learning, we were capable of performing such identification in a 4 dimensional feature space (+1 for time evolution), while the standard Principal Component Analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first order effect in the determination of SNIa subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNeIa subtypes (and outliers). All tools used in this work were made publicly available in the Python package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox (https://github.com/COINtoolbox/DRACULA).Comment: 16 pages, 12 figures, accepted for publication in MNRA

Anger and depressive ruminations as predictors of dysregulated behaviours in borderline personality disorder.

BACKGROUND: Anger and depressive ruminations have recently received empirical attention as processes related to borderline personality disorder (BPD). The Emotional Cascade Model (Selby, Anestis, & Joiner, 2008) suggests that negative affect (such as anger and sadness) may trigger rumination, which in turn may increase the duration and extent of negative affect, leading to dysregulated behaviours aimed at reducing such intense and unpleasant emotions. AIM: The aim of this study is to explore the relationships between emotional dysregulation, anger and depressive ruminations, and their role in predicting dysregulated behaviours (such as aggression and self-harm) in a clinical sample of patients with BPD. METHODS: Ninety-one patients with a diagnosis of BPD were recruited from three outpatient community mental health centres and asked to complete a comprehensive assessment for personality disorder symptoms, emotion dysregulation, anger and depressive ruminations, aggression, and self-harm. RESULTS: Anger and depressive ruminations were found to be significantly associated to, respectively, self-harm and aggression, beyond the variance accounted by emotional dysregulation. CONCLUSIONS: Rumination may act as a mediator between emotional dysregulation and dysregulated behaviours in BPD. Future research should examine whether clinical techniques aimed at reducing rumination may be helpful in reducing dysregulated behaviours in patients with BPD. "This is the pre-peer reviewed version of the following article: Martino, F., Caselli, G., Di Tommaso, J., Sassaroli, S., Spada, M.M ., Valenti, B., Berardi, D., Sasdelli, A and Menchetti, M (2017) Anger and depressive ruminations as predictors of dysregulated behaviours in borderline personality disorder. Clinical Psychology and Psychotherapy., which has been published in final form at 10.1002/cpp.2152 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

The UV/optical spectra of the Type Ia supernova SN 2010jn: a bright supernova with outer layers rich in iron-group elements

Radiative transfer studies of Type Ia supernovae (SNe Ia) hold the promise of constraining both the time-dependent density profile of the SN ejecta and its stratification by element abundance which, in turn, may discriminate between different explosion mechanisms and progenitor classes. Here we present a detailed analysis of Hubble Space Telescope ultraviolet (UV) and ground-based optical spectra and light curves of the SN Ia SN 2010jn (PTF10ygu). SN 2010jn was discovered by the Palomar Transient Factory (PTF) 15 days before maximum light, allowing us to secure a time-series of four UV spectra at epochs from -11 to +5 days relative to B-band maximum. The photospheric UV spectra are excellent diagnostics of the iron-group abundances in the outer layers of the ejecta, particularly those at very early times. Using the method of 'Abundance Tomography' we have derived iron-group abundances in SN 2010jn with a precision better than in any previously studied SN Ia. Optimum fits to the data can be obtained if burned material is present even at high velocities, including significant mass fractions of iron-group elements. This is consistent with the slow decline rate (or high 'stretch') of the light curve of SN 2010jn, and consistent with the results of delayed-detonation models. Early-phase UV spectra and detailed time-dependent series of further SNe Ia offer a promising probe of the nature of the SN Ia mechanism.Comment: 17 pages, 9 figures (v3: several small updates to content including models; v2: metadata fixed), MNRAS, in pres

Chronic Intestinal Failure in Children: An International Multicenter Cross-Sectional Survey

Background: The European Society for Clinical Nutrition and Metabolism database for chronic intestinal failure (CIF) was analyzed to investigate factors associated with nutritional status and the intravenous supplementation (IVS) dependency in children. Methods: Data collected: demographics, CIF mechanism, home parenteral nutrition program, z-scores of weight-for-age (WFA), length or height-for-age (LFA/HFA), and body mass index-for-age (BMI-FA). IVS dependency was calculated as the ratio of daily total IVS energy over estimated resting energy expenditure (%IVSE/REE). Results: Five hundred and fifty-eight patients were included, 57.2% of whom were male. CIF mechanisms at age 1–4 and 14–18 years, respectively: SBS 63.3%, 37.9%; dysmotility or mucosal disease: 36.7%, 62.1%. One-third had WFA and/or LFA/HFA z-scores < −2. One-third had %IVSE/REE > 125%. Multivariate analysis showed that mechanism of CIF was associated with WFA and/or LFA/HFA z-scores (negatively with mucosal disease) and %IVSE/REE (higher for dysmotility and lower in SBS with colon in continuity), while z-scores were negatively associated with %IVSE/REE. Conclusions: The main mechanism of CIF at young age was short bowel syndrome (SBS), whereas most patients facing adulthood had intestinal dysmotility or mucosal disease. One-third were underweight or stunted and had high IVS dependency. Considering that IVS dependency was associated with both CIF mechanisms and nutritional status, IVS dependency is suggested as a potential marker for CIF severity in children

A metric space for Type Ia supernova spectra

We develop a new framework for use in exploring Type Ia supernovae (SNe Ia) spectra. Combining principal component analysis (PCA) and partial least square (PLS) analysis we are able to establish correlations between the principal components (PCs) and spectroscopic/photometric SNe Ia features. The technique was applied to ∼120 SN and ∼800 spectra from the Nearby Supernova Factory. The ability of PCA to group together SNe Ia with similar spectral features, already explored in previous studies, is greatly enhanced by two important modifications: (1) the initial data matrix is built using derivatives of spectra over the wavelength, which increases the weight of weak lines and discards extinction, and (2) we extract time evolution information through the use of entire spectral sequences concatenated in each line of the input data matrix. These allow us to define a stable PC parameter space which can be used to characterize synthetic SN Ia spectra by means of real SN features. Using PLS, we demonstrate that the information from important previously known spectral indicators (namely the pseudo-equivalent width of Si II 5972 Å/Si II 6355 Å and the line velocity of S II 5640 Å/Si II 6355 Å) at a given epoch is contained within the PC space and can be determined through a linear combination of the most important PCs. We also show that the PC space encompasses photometric features like B/V magnitudes, B − V colours and SALT2 parameters c and x1. The observed colours and magnitudes, which are heavily affected by extinction, cannot be reconstructed using this technique alone. All the above-mentioned applications allowed us to construct a metric space for comparing synthetic SN Ia spectra with observations

Abundance stratification in Type Ia supernovae - IV. The luminous, peculiar SN 1991T

The abundance distribution of the elements in the ejecta of the peculiar, luminous Type Ia supernova (SN Ia) 1991T is obtained modelling spectra from before maximum light until a year after the explosion, with the method of ‘Abundance Tomography’. SN 1991T is different from other slowly declining SNe Ia (e.g. SN 1999ee) in having a weaker Si II 6355 line and strong features of iron group elements before maximum. The distance to the SN is investigated along with the abundances and the density profile. The ionization transition that happens around maximum sets a strict upper limit on the luminosity. Both W7 and the WDD3 delayed detonation models are tested. WDD3 is found to provide marginally better fits. In this model the core of the ejecta is dominated by stable Fe with a mass of about 0.15 M⊙, as in most SNe Ia. The layer above is mainly 56Ni up to v ∼ 10 000 km s−1 (≈0.78 M⊙). A significant amount of 56Ni (∼3 per cent) is located in the outer layers. A narrow layer between 10 000 km s−1 and ∼12 000 km s−1 is dominated by intermediate-mass elements (IME), ∼0.18 M⊙. This is small for a SN Ia. The high luminosity and the consequently high ionization, and the high 56Ni abundance at high velocities, explain the peculiar early-time spectra of SN 1991T. The outer part is mainly of oxygen, ∼0.3 M⊙. Carbon lines are never detected, yielding an upper limit of 0.01 M⊙ for C. The abundances obtained with the W7 density model are qualitatively similar to those of the WDD3 model. Different elements are stratified with moderate mixing, resembling a delayed detonation

Astronomical Distance Determination in the Space Age: Secondary Distance Indicators

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations. © 2018, The Author(s)