Probing the Initial Conditions for Star Formation with Monte Carlo Radiative Transfer Simulations

2008 ◽  
pp. 259-270
Author(s):  
Dimitris Stamatellos ◽  
Anthony P. Whitworth
Keyword(s):  
Monte Carlo ◽  
Star Formation ◽  
Radiative Transfer ◽  
Initial Conditions

scholarly journals The initial conditions of high-mass star formation: radiative transfer models of IRDCs seen in theHerschelHi-GAL survey

2011 ◽  
Vol 526 ◽  
pp. A159 ◽  
Author(s):  
L. A. Wilcock ◽  
J. M. Kirk ◽  
D. Stamatellos ◽  
D. Ward-Thompson ◽  
A. Whitworth ◽  
...  
Keyword(s):  
Star Formation ◽  
Radiative Transfer ◽  
Initial Conditions ◽  
High Mass ◽  
Mass Star ◽  
Radiative Transfer Models ◽  
Transfer Models

scholarly journals Can jets make the radioactively powered emission from neutron star mergers bluer?

2020 ◽  
Vol 500 (2) ◽  
pp. 1772-1783
Author(s):  
L Nativi ◽  
M Bulla ◽  
S Rosswog ◽  
C Lundman ◽  
G Kowal ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Neutron Star ◽  
Radiative Transfer ◽  
Initial Conditions ◽  
Heavy Elements ◽  
Electromagnetic Transients ◽  
Relativistic Hydrodynamic ◽  
Hydrodynamic Simulations ◽  
Relativistic Jet ◽  
Nuclear Composition

ABSTRACT Neutron star mergers eject neutron-rich matter in which heavy elements are synthesized. The decay of these freshly synthesized elements powers electromagnetic transients (‘macronovae’ or ‘kilonovae’) whose luminosity and colour strongly depend on their nuclear composition. If the ejecta are very neutron-rich (electron fraction Ye < 0.25), they contain fair amounts of lanthanides and actinides that have large opacities and therefore efficiently trap the radiation inside the ejecta so that the emission peaks in the red part of the spectrum. Even small amounts of this high-opacity material can obscure emission from lower lying material and therefore act as a ‘lanthanide curtain’. Here, we investigate how a relativistic jet that punches through the ejecta can potentially push away a significant fraction of the high opacity material before the macronova begins to shine. We use the results of detailed neutrino-driven wind studies as initial conditions and explore with 3D special relativistic hydrodynamic simulations how jets are propagating through these winds. Subsequently, we perform Monte Carlo radiative transfer calculations to explore the resulting macronova emission. We find that the hole punched by the jet makes the macronova brighter and bluer for on-axis observers during the first few days of emission, and that more powerful jets have larger impacts on the macronova.

scholarly journals EDGE: a new approach to suppressing numerical diffusion in adaptive mesh simulations of galaxy formation

2020 ◽  
Vol 501 (2) ◽  
pp. 1755-1765
Author(s):  
Andrew Pontzen ◽  
Martin P Rey ◽  
Corentin Cadiou ◽  
Oscar Agertz ◽  
Romain Teyssier ◽  
...  
Keyword(s):  
Star Formation ◽  
Galaxy Formation ◽  
Adaptive Mesh Refinement ◽  
Large Scale ◽  
Initial Conditions ◽  
Dwarf Galaxy ◽  
High Redshift ◽  
Morphological Structure ◽  
Adaptive Mesh ◽  
Numerical Diffusion

ABSTRACT We introduce a new method to mitigate numerical diffusion in adaptive mesh refinement (AMR) simulations of cosmological galaxy formation, and study its impact on a simulated dwarf galaxy as part of the ‘EDGE’ project. The target galaxy has a maximum circular velocity of $21\, \mathrm{km}\, \mathrm{s}^{-1}$ but evolves in a region that is moving at up to $90\, \mathrm{km}\, \mathrm{s}^{-1}$ relative to the hydrodynamic grid. In the absence of any mitigation, diffusion softens the filaments feeding our galaxy. As a result, gas is unphysically held in the circumgalactic medium around the galaxy for $320\, \mathrm{Myr}$, delaying the onset of star formation until cooling and collapse eventually triggers an initial starburst at z = 9. Using genetic modification, we produce ‘velocity-zeroed’ initial conditions in which the grid-relative streaming is strongly suppressed; by design, the change does not significantly modify the large-scale structure or dark matter accretion history. The resulting simulation recovers a more physical, gradual onset of star formation starting at z = 17. While the final stellar masses are nearly consistent ($4.8 \times 10^6\, \mathrm{M}_{\odot }$ and $4.4\times 10^6\, \mathrm{M}_{\odot }$ for unmodified and velocity-zeroed, respectively), the dynamical and morphological structure of the z = 0 dwarf galaxies are markedly different due to the contrasting histories. Our approach to diffusion suppression is suitable for any AMR zoom cosmological galaxy formation simulations, and is especially recommended for those of small galaxies at high redshift.

scholarly journals Importance of the initial conditions for star formation - III. Statistical properties of embedded protostellar clusters

2012 ◽  
Vol 420 (4) ◽  
pp. 3264-3280 ◽  
Author(s):  
Philipp Girichidis ◽  
Christoph Federrath ◽  
Richard Allison ◽  
Robi Banerjee ◽  
Ralf S. Klessen
Keyword(s):  
Star Formation ◽  
Initial Conditions ◽  
Statistical Properties

scholarly journals Automated Search-Based Robustness Testing for Autonomous Vehicle Software

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Kevin M. Betts ◽  
Mikel D. Petty
Keyword(s):  
Monte Carlo ◽  
Performance Metrics ◽  
Initial Conditions ◽  
Autonomous Vehicle ◽  
Vehicle Control ◽  
Test Case ◽  
Test Cases ◽  
Control Software ◽  
Robustness Testing ◽  
Testing Techniques

Autonomous systems must successfully operate in complex time-varying spatial environments even when dealing with system faults that may occur during a mission. Consequently, evaluating the robustness, or ability to operate correctly under unexpected conditions, of autonomous vehicle control software is an increasingly important issue in software testing. New methods to automatically generate test cases for robustness testing of autonomous vehicle control software in closed-loop simulation are needed. Search-based testing techniques were used to automatically generate test cases, consisting of initial conditions and fault sequences, intended to challenge the control software more than test cases generated using current methods. Two different search-based testing methods, genetic algorithms and surrogate-based optimization, were used to generate test cases for a simulated unmanned aerial vehicle attempting to fly through an entryway. The effectiveness of the search-based methods in generating challenging test cases was compared to both a truth reference (full combinatorial testing) and the method most commonly used today (Monte Carlo testing). The search-based testing techniques demonstrated better performance than Monte Carlo testing for both of the test case generation performance metrics: (1) finding the single most challenging test case and (2) finding the set of fifty test cases with the highest mean degree of challenge.

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