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ALMA has spatially resolved over 200 annular structures in protoplanetary discs, many of which are suggestive of the presence of planets. Constraining the mass of these putative planets is quite degenerate for it depends on the disc…

Earth and Planetary Astrophysics · Physics 2023-06-14 Yinhao Wu , Clément Baruteau , Sergei Nayakshin

We propose a new family of high order staggered semi-implicit discontinuous Galerkin (DG) methods for the simulation of natural convection problems. Assuming small temperature fluctuations, the Boussinesq approximation is valid and the flow…

Computational Physics · Physics 2019-12-05 Saray Busto , Maurizio Tavelli , Walter Boscheri , Michael Dumbser

Stochastic Gradient Descent (SGD) is a popular optimization method which has been applied to many important machine learning tasks such as Support Vector Machines and Deep Neural Networks. In order to parallelize SGD, minibatch training is…

Machine Learning · Statistics 2014-05-14 Peilin Zhao , Tong Zhang

A novel, particle based, probabilistic approach for the simulation of cloud microphysics is proposed, which is named the Super-Droplet Method (SDM). This method enables accurate simulation of cloud microphysics with less demanding cost in…

Atmospheric and Oceanic Physics · Physics 2022-08-02 Shin-ichiro Shima , Kanya Kusano , Akio Kawano , Tooru Sugiyama , Shintaro Kawahara

We perform smoothed particle hydrodynamics (SPH) simulations of an isolated galaxy with a new treatment for dust formation and destruction. To this aim, we treat dust and metal production self-consistently with star formation and supernova…

Astrophysics of Galaxies · Physics 2017-01-19 Shohei Aoyama , Kuan-Chou Hou , Ikkoh Shimizu , Hiroyuki Hirashita , Keita Todoroki , Jun-Hwan Choi , Kentaro Nagamine

A novel multiscale numerical method is developed to accelerate direct simulation Monte Carlo (DSMC) simulations for polyatomic gases with internal energy. This approach applies the general synthetic iterative scheme to stochastic…

Computational Physics · Physics 2025-01-22 Liyan Luo , Tao Huang , Qi Li , Lei Wu

Context: How planets form in protoplanetary disks and what drives the formation of their seeds is still a major unknown. It is an accepted theory that multiple processes can trap dusty material in radially narrow rings or vortex-like…

Earth and Planetary Astrophysics · Physics 2025-03-19 Dominik Ostertag , Mario Flock

The streaming instability is a leading mechanism for concentrating solids and initiating planetesimal formation in protoplanetary disks. Although numerous studies have explored its linear growth, nonlinear evolution, and implications for…

Small dust grains are essential ingredients of star, disk and planet formation. We present an Eulerian numerical approach to study small dust grains dynamics in the context of star and protoplanetary disk formation. It is designed for…

Instrumentation and Methods for Astrophysics · Physics 2019-06-19 Ugo Lebreuilly , Benoît Commerçon , Guillaume Laibe

Stochastic gradient descent (\textsc{Sgd}) methods are the most powerful optimization tools in training machine learning and deep learning models. Moreover, acceleration (a.k.a. momentum) methods and diagonal scaling (a.k.a. adaptive…

Machine Learning · Statistics 2018-10-02 Qi Deng , Yi Cheng , Guanghui Lan

In this paper we propose a novel arbitrary high order accurate semi-implicit space-time DG method for the solution of the three-dimensional incompressible Navier-Stokes equations on staggered unstructured curved tetrahedral meshes. As…

Numerical Analysis · Mathematics 2016-06-22 Maurizio Tavelli , Michael Dumbser

To facilitate the study of black hole fueling, star formation, and feedback in galaxies, we outline a method for treating the radial forces on interstellar gas due to absorption of photons by dust grains. The method gives the correct…

Astrophysics of Galaxies · Physics 2015-06-04 G. S. Novak , J. P. Ostriker , L. Ciotti

We present redshift-zero synthetic observational data considering dust attenuation and dust emission for the thirty galaxies of the Auriga project, calculated with the SKIRT radiative transfer code. The post-processing procedure includes…

We present the results of three-dimensional numerical simulations that include the effects of hydrodynamical forces and gas drag upon an evolving dusty gas disk. We briefly describe a new parallel, two phase numerical code based upon the…

This paper exposes a novel exploratory formalism, which end goal is the numerical simulation of the dynamics of a cloud of particles weakly or strongly coupled with a turbulent fluid. Giventhe large panel of expertise of the list of…

Analysis of PDEs · Mathematics 2019-10-21 Ludovic Goudenège , Adam Larat , Julie Llobell , Marc Massot , David Mercier , Olivier Thomine , Aymeric Vié

We propose a dimensionality reduction and unsupervised clustering method for the automatic classification and reduced-order modeling of density-stratified turbulence in laboratory experiments. We apply this method to 113 long shadowgraph…

Fluid Dynamics · Physics 2023-05-09 Adrien Lefauve , Miles M. P. Couchman

Simulated annealing (SA) is a kind of relaxation method for finding equilibria of Hamiltonian systems. A set of evolution equations is solved with SA, which is derived from the original Hamiltonian system so that the energy of the system…

Plasma Physics · Physics 2022-10-19 M. Furukawa , P. J. Morrison

The inner regions of protoplanetary disks are host to the sublimation of dust grains, a process traditionally modeled using equilibrium thermodynamics. We demonstrate through ab-initio density functional theory (DFT) and kinetic Monte Carlo…

Earth and Planetary Astrophysics · Physics 2025-09-16 Sheng Xu , Lile Wang , Luis C. Ho , Renyue Cen , Shenzhen Xu

Flutter flight test involves the evaluation of the airframes aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are captured and analyzed to extract the frequencies and damping…

Signal Processing · Electrical Eng. & Systems 2024-08-05 Arpan Das , Pier Marzocca , Giuliano Coppotelli , Oleg Levinski , Paul Taylor

Large-scale non-convex sparsity-constrained problems have recently gained extensive attention. Most existing deterministic optimization methods (e.g., GraSP) are not suitable for large-scale and high-dimensional problems, and thus…

Machine Learning · Computer Science 2019-12-03 Fanhua Shang , Bingkun Wei , Hongying Liu , Yuanyuan Liu , Jiacheng Zhuo