Publications

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1701 Publications visible to you, out of a total of 1701

Abstract (Expand)

We present Singularity-EOS, a new performance-portable library for equations of state and related capabilities. Singularity-EOS provides a large set of analytic equations of state, such as the Gruneisen equation of state, and tabulated equation of state data under a unified interface. It also provides support capabilities around these equations of state, such as Python wrappers, solvers for finding pressure-temperature equilibrium between multiple equations of state, and a unique modifier framework, allowing the user to transform a base equation of state, for example by shifting or scaling the specific internal energy. All capabilities are performance portable, meaning they compile and run on both CPU and GPU for a wide variety of architectures.

Authors: Jonah M. Miller, Daniel A. Holladay, Jeffrey H. Peterson, Christopher M. Mauney, Richard Berger, Anna Pietarila Graham, Karen C. Tsai, Brandon Barker, Alexander Holas, Ann E. Mattsson, Mariam Gogilashvili, Joshua C. Dolence, Chad D. Meyer, Sriram Swaminarayan, Christoph Junghans

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract

Not specified

Authors: Marco Vetter, Friedrich K. Röpke, Fabian R. N. Schneider, Rüdiger Pakmor, Sebastian T. Ohlmann, Mike Y. M. Lau, Robert Andrassy

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract

Not specified

Authors: Rüdiger Pakmor, Ingrid Pelisoli, Stephen Justham, Abinaya S. Rajamuthukumar, Friedrich K. Röpke, Fabian R. N. Schneider, Selma E. de Mink, Sebastian T. Ohlmann, Philipp Podsiadlowski, Javier Morán-Fraile, Marco Vetter, Robert Andrassy

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract (Expand)

ABSTRACT Protostellar binaries harbour complex environment morphologies. Observations represent a snapshot in time, and projection and optical depth effects impair our ability to interpret them. Carefulto interpret them. Careful comparison with high-resolution models that include the larger star-forming region can help isolate the driving physical processes and give context in the time domain to the observations. We carry out four zoom-in simulations with au scale resolution that result in three binaries and a single star. For the first time ever, we follow the detailed evolution of a protobinary in a full molecular cloud context until a circumbinary disc forms. We investigate the gas dynamics around the young stars and extract disc sizes. Using radiative transfer, we obtain the evolutionary tracer Tbol of the binary systems. We find that the centrifugal radius in prestellar cores is a poor estimator of the resulting disc size due to angular momentum transport at all scales. For binaries, the disc sizes are regulated periodically by the binary orbit, having larger radii close to the apastron. The bolometric temperature differs systematically between edge-on and face-on views and shows a high-frequency time dependence correlated with the binary orbit and a low-frequency time dependence with larger episodic accretion events. These oscillations can cause the appearance of the system to change rapidly from class 0 to class I and, for short periods, even bring it to class II. The highly complex structure in early stages, as well as the binary orbit itself, affects the classical interpretation of protostellar classes, and the direct translation to evolutionary stages has to be done with caution and include other evolutionary indicators such as the extent of envelope material.

Authors: Vito Tuhtan, Rami Al-Belmpeisi, Mikkel Bregning Christensen, Rajika Kuruwita, Troels Haugbølle

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract (Expand)

ABSTRACT Star formation is a multiscale problem, and only global simulations that account for the connection from the molecular cloud-scale gas flow to the accreting protostar can reflect the observedr can reflect the observed complexity of protostellar systems. Star-forming regions are characterized by supersonic turbulence, and as a result, it is not possible to simultaneously design models that account for the larger environment and in detail reproduce observed stellar systems. Instead, the stellar inventories can be matched statistically, and the best matches found that approximate specific observations. Observationally, a combination of single-dish telescopes and interferometers are now able to resolve the nearest protostellar objects on all scales from the protostellar core to the inner $10\, \mathrm{au}$. We present a new non-parametric methodology which uses high-resolution simulations and post-processing methods to match simulations and observations using deep learning. Our goal is to perform a down-selection from large data sets of synthetic images to a ranked list of best-matching candidates with respect to the observation. This is particularly useful for binary and multiple stellar systems that form in turbulent environments. The objective is to accelerate the rate at which we can do such comparisons, remove biases from hand-picking matches, and contribute to identifying the underlying physical processes that drive the creation and evolution of observed protostellar systems.

Authors: Rami Al-Belmpeisi, Vito Tuhtan, Mikkel Bregning Christensen, Rajika Kuruwita, Troels Haugbølle

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract

Not specified

Authors: Marco Vetter, Friedrich K. Röpke, Fabian R. N. Schneider, Rüdiger Pakmor, Sebastian T. Ohlmann, Mike Y. M. Lau, Robert Andrassy

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract

Not specified

Authors: Rüdiger Pakmor, Ingrid Pelisoli, Stephen Justham, Abinaya S. Rajamuthukumar, Friedrich K. Röpke, Fabian R. N. Schneider, Selma E. de Mink, Sebastian T. Ohlmann, Philipp Podsiadlowski, Javier Morán-Fraile, Marco Vetter, Robert Andrassy

Date Published: 1st Nov 2024

Publication Type: Journal

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