Global properties of core-collapse supernovae in numerical simulations

The exact progenitor-remnant connection of core-collapse supernovae (CCSNe), i.e. if a star explodes, and if it leaves behind a neutron star (NS) or a black hole (BH), is not well understood yet. The understanding of CCSNe and their explosion mechanism(s) is a long standing problem that many astrophysicists tried to illuminate. The uncertainty of the explosion mechanism and the explodability also affect the prediction of the nucleosynthesis yields in the ejecta of CCSNe that contribute to the galactic chemical enrichment. In this thesis we study the explodability, explosion properties, and the ejecta of neutrino-driven CCSNe with numerical simulations. This includes the study of the dynamics and trends of CCSNe in dependence of progenitor properties. To investigate the explodability and the progenitor-remnant connection quantitatively one has to study large samples of CCSN progenitors. Even though multi-dimensional simulations provide a promising and necessary tool to study the exact nature of the possible explosion mechanisms, sophisticated three-dimensional models are computationally too expensive to be used in the analysis of large samples of progenitors. With some exceptions for the lightest progenitors of CCSNe, self-consistent numerically affordable one-dimensional simulations that incorporate detailed microphysics, general relativity and sophisticated neutrino-transport fail to explode. The main focus of this thesis lies on the PUSH method, a parametrized framework to efficiently investigate CCSNe for large samples of progenitors in spherically symmetric simulations. By investigations of CCSNe we can determine the explodability and the nucleosynthesis yields in the ejecta of the explosions obtained for the progenitors, as well as dependencies of explosion properties on the progenitor properties. Main strengths of the presented PUSH method in comparison with other artificial methods are obtaining the mass cut directly from the simulations and the PNS as well as the electron flavor neutrino luminosities are computed self-consistent at all simulation times. No changes of the involved electron neutrino and anti-neutrino cross sections are made. To achieve successful explosions in otherwise non-exploding models in spherical symmetry, we rely on the neutrino-driven mechanism. In this mechanism of CCSNe electron neutrinos and antineutrinos are able to heat matter behind the stalled shock front in the gain region sufficiently to induce a shock revival that ultimately leads to an explosion. It has been found, that for efficient heating by neutrinos behind the shock multi-dimensional effects as convection are crucial. In our simulations we tap the energy of the $\mu-$ and $\tau-$neutrino luminosities that otherwise stream out of the system and increase the effective heating by neutrinos in regions where electron flavor neutrinos heat the matter. This enables us to successfully induce physically motivated parametrized neutrino-driven CCSNe in spherically symmetric simulations with a realistic SN equation of state (EOS). After calibrating the PUSH method to SN~1987A for a suitable progenitor model, we proceed to explore large progenitor samples with solar metallicity. This is done by using observational properties of other CCSNe. By extending the calibration of the PUSH method with a dependency on compactness we can investigate CCSN simulations for progenitor models across the ZAMS mass range. We study large samples of progenitors with solar metallicity and discuss trends of the obtained results for explosion energy, nucleosynthesis yields and explodability. The resulting progenitor-remnant connection, the resulting prediction of the neutron star and black hole birth mass distributions that can be compared to observations are presented. In the final part of this thesis we discuss work done with the three-dimensional magnetohydrodynamics code with neutrino transport ELEPHANT and compare our parametrized spherically symmetric CCSN simulations to three-dimensional simulations

PUSHing Core-Collapse Supernovae to Explosions in Spherical Symmetry: Nucleosynthesis Yields

Core-collapse supernovae (CCSNe) are the extremely energetic deaths of massive stars. They play a vital role in the synthesis and dissemination of many heavy elements in the universe. In the past, CCSN nucleosynthesis calculations have relied on artificial explosion methods that do not adequately capture the physics of the innermost layers of the star. The PUSH method, calibrated against SN1987A, utilizes the energy of heavy-flavor neutrinos emitted by the proto-neutron star (PNS) to trigger parametrized explosions. This makes it possible to follow the consistent evolution of the PNS and to ensure a more accurate treatment of the electron fraction of the ejecta. Here, we present the Iron group nucleosynthesis results for core-collapse supernovae, exploded with PUSH, for two different progenitor series. Comparisons of the calculated yields to observational metal-poor star data are also presented. Nucleosynthesis yields will be calculated for all elements and over a wide range of progenitor masses. These yields can be immensely useful for models of galactic chemical evolution.Comment: 3 pages, 3 figures, poster presentation to appear in the proceedings of the 14th International Symposium on Nuclei in the Cosmos (NIC-XIV), Ed. S. Kubono, JPS (Japan Physical Society

Explosion Dynamics of Parametrized Spherically Symmetric Core-Collapse Supernova Simulations

We report on a method, PUSH, for triggering core-collapse supernova (CCSN) explosions of massive stars in spherical symmetry. This method provides a framework to study many important aspects of core collapse supernovae: the effects of the shock passage through the star, explosive supernova nucleosynthesis and the progenitor-remnant connection. Here we give an overview of the method, compare the results to multi-dimensional simulations and investigate the effects of the progenitor and the equation of state on black hole formation.Comment: Proceedings for Nuclei in the Cosmos XIV, Niigata, Japan (2016

Equalizing resolution in smoothed-particle hydrodynamics calculations using self-adaptive sinc kernels

The smoothed-particle hydrodynamics (SPH) technique is a numerical method for solving gas-dynamical problems. It has been applied to simulate the evolution of a wide variety of astrophysical systems. The method has a second-order accuracy, with a resolution that is usually much higher in the compressed regions than in the diluted zones of the fluid. In this work, we propose and check a scheme to balance and equalize the resolution of SPH between high- and low-density regions. This method relies on the versatility of a family of interpolators called Sinc kernels, which allows increasing the interpolation quality by varying only a single parameter (the exponent of the Sinc function). The scheme is checked and validated through a number of numerical tests, from standard one-dimensional Riemann problems in shock tubes, to multidimensional simulations of explosions, hydrodynamic instabilities and the collapse of a sun-like polytrope. The analysis of the hydrodynamical simulations suggests that the scheme devised to equalizing accuracy improves the treatment of the post-shock regions and, in general, of the rarefacted zones of fluids while causing no harm to the growth of hydrodynamic instabilities. The method is robust and easy to implement with a low computational overload. It conserves mass, energy, and momentum and reduces to the standard SPH scheme in regions of the fluid that have smooth density gradients.Comment: 29 pages, 18 figures, accepted by A&

Influence of Reproductive and Environmental Factors on Population Size .. of Wild Hyacinth [Camassia angusta (Engelm.· and A. Gray) Blank. (Liliaceae)], an Illinois Endangered Species

Wild hyacinth (Camassia angusta) is a perennial species native to mesic prairies of the midwestern and south-central United States. In Illinois, the only extant population of this state-endangered species is in a small section of degraded black-soil prairie along a railroad track right-of-way south of Elwin, Macon County. The objectives of this study were to determine the population status, seed production, and effects of scarification and stratification on germination of C. angusta. The population was surveyed from 1990 to 2007. A survey of other plant species present was conducted in 1999. The site consisted of approximately 75% native and 25% exotic species. The number of flowering stems of Camassia angusta fluctuated significantly (28 to 169 plants) during the course of this study. Prescribed spring burns and a construction equipment disturbance may be partially responsible for these fluctuations. A large percentage of undeveloped fruit, resulting in low seed production ( \u3c3,000), as well as low seed germination (8%), may be responsible for this population\u27s inability to increase consistently in number of individuals

Trends in Causes and Distribution, and Effects of Whitebark Pine Decline on Grizzly Bear Mortality in the Greater Yellowstone Ecosystem

Documented grizzly bear (Ursus arctos) mortalities have been increasing in recent years in the Greater Yellowstone Ecosystem (GYE), due, in part, to increases in bear numbers and range expansion. Previous research has documented that variable seed production of whitebark pine (WBP; Pinus albicaulis), an important fall food, is inversely related to grizzly bear fall mortality.  However, WBP has experienced widespread mortality during the last decade because of mountain pine beetle (Dendroctonus ponderosae) infestations. We investigated trends in causes and distribution of human-caused mortalities for independent-aged (? 2 yrs old) grizzly bears in the GYE during 1975–2012, and the effect of WBP cone production on numbers of fall (> 1 August) mortalities (n = 172) during the period of WBP decline (2000-2012) using Poisson regression. During 1975–1982, 91 percent of mortalities occurred within the Grizzly Bear Recovery Zone and primary causes were poaching/malicious killings and losses related to conflicts with livestock. During the two most recent decades most mortalities were associated with ungulate hunting, usually involving self-defense kills, or anthropogenic sites, and an increasing percentage of mortalities occurred outside the recovery zone. Using predictor variables of cone production, sex, location in or out of the Recovery Zone, and year suggests: 1) annual cone production was still predictive of human-caused fall mortalities, 2) no evidence of a difference in annual numbers of fall mortalities between males and females, and 3) an increase in annual mortalities over the study period, with most of this increase outside the Recovery Zone

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning

Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detection and characterization of LVH can significantly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating etiologies of LVH. To overcome this challenge, we present EchoNet-LVH - a deep learning workflow that automatically quantifies ventricular hypertrophy with precision equal to human experts and predicts etiology of LVH. Trained on 28,201 echocardiogram videos, our model accurately measures intraventricular wall thickness (mean absolute error [MAE] 1.4mm, 95% CI 1.2-1.5mm), left ventricular diameter (MAE 2.4mm, 95% CI 2.2-2.6mm), and posterior wall thickness (MAE 1.2mm, 95% CI 1.1-1.3mm) and classifies cardiac amyloidosis (area under the curve of 0.83) and hypertrophic cardiomyopathy (AUC 0.98) from other etiologies of LVH. In external datasets from independent domestic and international healthcare systems, EchoNet-LVH accurately quantified ventricular parameters (R2 of 0.96 and 0.90 respectively) and detected cardiac amyloidosis (AUC 0.79) and hypertrophic cardiomyopathy (AUC 0.89) on the domestic external validation site. Leveraging measurements across multiple heart beats, our model can more accurately identify subtle changes in LV geometry and its causal etiologies. Compared to human experts, EchoNet-LVH is fully automated, allowing for reproducible, precise measurements, and lays the foundation for precision diagnosis of cardiac hypertrophy. As a resource to promote further innovation, we also make publicly available a large dataset of 23,212 annotated echocardiogram videos

Glucose transporter-1 deficiency syndrome: the expanding clinical and genetic spectrum of a treatable disorder

Glucose transporter-1 deficiency syndrome is caused by mutations in the SLC2A1 gene in the majority of patients and results in impaired glucose transport into the brain. From 2004-2008, 132 requests for mutational analysis of the SLC2A1 gene were studied by automated Sanger sequencing and multiplex ligation-dependent probe amplification. Mutations in the SLC2A1 gene were detected in 54 patients (41%) and subsequently in three clinically affected family members. In these 57 patients we identified 49 different mutations, including six multiple exon deletions, six known mutations and 37 novel mutations (13 missense, five nonsense, 13 frame shift, four splice site and two translation initiation mutations). Clinical data were retrospectively collected from referring physicians by means of a questionnaire. Three different phenotypes were recognized: (i) the classical phenotype (84%), subdivided into early-onset (<2 years) (65%) and late-onset (18%); (ii) a non-classical phenotype, with mental retardation and movement disorder, without epilepsy (15%); and (iii) one adult case of glucose transporter-1 deficiency syndrome with minimal symptoms. Recognizing glucose transporter-1 deficiency syndrome is important, since a ketogenic diet was effective in most of the patients with epilepsy (86%) and also reduced movement disorders in 48% of the patients with a classical phenotype and 71% of the patients with a non-classical phenotype. The average delay in diagnosing classical glucose transporter-1 deficiency syndrome was 6.6 years (range 1 month-16 years). Cerebrospinal fluid glucose was below 2.5 mmol/l (range 0.9-2.4 mmol/l) in all patients and cerebrospinal fluid : blood glucose ratio was below 0.50 in all but one patient (range 0.19-0.52). Cerebrospinal fluid lactate was low to normal in all patients. Our relatively large series of 57 patients with glucose transporter-1 deficiency syndrome allowed us to identify correlations between genotype, phenotype and biochemical data. Type of mutation was related to the severity of mental retardation and the presence of complex movement disorders. Cerebrospinal fluid : blood glucose ratio was related to type of mutation and phenotype. In conclusion, a substantial number of the patients with glucose transporter-1 deficiency syndrome do not have epilepsy. Our study demonstrates that a lumbar puncture provides the diagnostic clue to glucose transporter-1 deficiency syndrome and can thereby dramatically reduce diagnostic delay to allow early start of the ketogenic die

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase&nbsp;1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation&nbsp;disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age&nbsp; 6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score&nbsp; 652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc&nbsp;= 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N&nbsp;= 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in&nbsp;Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in&nbsp;Asia&nbsp;and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701