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High-fidelity large-eddy simulations are suitable to obtain insight into the complex flow dynamics in extended wind farms. In order to better understand these flow dynamics, we use dynamic mode decomposition (DMD) to analyze and reconstruct…

Fluid Dynamics · Physics 2022-04-26 Xuan Dai , Da Xu , Mengqi Zhang , Richard J. A. M. Stevens

SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and…

Machine Learning · Computer Science 2025-02-04 Javier Bernal , Jose Torres-Jimenez

Traditionally, single realizations of the turbulent state have been the object of study in shear flow turbulence. When a statistical quantity was needed it was obtained from a spatial, temporal or ensemble average of sample realizations of…

Fluid Dynamics · Physics 2022-10-27 Brian F. Farrell , Petros J. Ioannou

In order to explain grain growth to mm sized particles and their retention in outer regions of protoplanetary disks, as it is observed at sub-mm and mm wavelengths, we investigate if strong inhomogeneities in the gas density profiles can…

Earth and Planetary Astrophysics · Physics 2012-02-14 P. Pinilla , T. Birnstiel , L. Ricci , C. P. Dullemond , A. L. Uribe , L. Testi , A. Natta

A new high order accurate staggered semi-implicit space-time discontinuous Galerkin (DG) method is presented for the simulation of viscous incompressible flows on unstructured triangular grids in two space dimensions. The staggered DG…

Numerical Analysis · Mathematics 2020-10-09 Francesco Lohengrin Romeo , Michael Dumbser , Maurizio Tavelli

Stochastic Gradient Descent (SGD) methods see many uses in optimization problems. Modifications to the algorithm, such as momentum-based SGD methods have been known to produce better results in certain cases. Much of this, however, is due…

Machine Learning · Computer Science 2025-04-22 Eric Lu

We present an acceleration method for sequences of large-scale linear systems, such as the ones arising from the numerical solution of time-dependent partial differential equations coupled with algebraic constraints. We discuss different…

Numerical Analysis · Mathematics 2024-03-29 Margherita Guido , Daniel Kressner , Paolo Ricci

Aims. Monte Carlo Radiative Transfer (MCRT) simulations are a powerful tool for understanding the role of dust in astrophysical systems and its influence on observations. However, due to the strong coupling of the radiation field and medium…

Instrumentation and Methods for Astrophysics · Physics 2023-02-01 Majda Smole , João Rino-Silvestre , Santiago González-Gaitán , Marko Stalevski

Recent (sub)millimeter polarization observations of protoplanetary disks reveal toroidally aligned, effectively prolate dust grains large enough (at least ~100 $\mu$m) to efficiently scatter millimeter light. The alignment mechanism for…

Earth and Planetary Astrophysics · Physics 2025-10-02 Zhe-Yu Daniel Lin , Zhi-Yun Li , Haifeng Yang , Leslie W. Looney , Ian W. Stephens , Manuel Fernández-López , Rachel E. Harrison

Static alias analysis of different type of programming languages has been drawing researcher attention. However most of the results of existing techniques for alias analysis are not precise enough compared to needs of modern compilers.…

Programming Languages · Computer Science 2014-05-20 Mohamed A. El-Zawawy , Mohammad N. Alanazi

We consider straggler-resilient learning. In many previous works, e.g., in the coded computing literature, straggling is modeled as random delays that are independent and identically distributed between workers. However, in many practical…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-30 Albin Severinson , Eirik Rosnes , Salim El Rouayheb , Alexandre Graell i Amat

Stochastic gradient descent (SGD) is a standard optimization method to minimize a training error with respect to network parameters in modern neural network learning. However, it typically suffers from proliferation of saddle points in the…

Machine Learning · Computer Science 2017-11-23 Haiping Huang , Taro Toyoizumi

Planet formation is a multi-scale process in which the coagulation of $\mathrm{\mu m}$-sized dust grains in protoplanetary disks is strongly influenced by the hydrodynamic processes on scales of astronomical units ($\approx 1.5\times 10^8…

Earth and Planetary Astrophysics · Physics 2022-11-09 Thomas Pfeil , Miles Cranmer , Shirley Ho , Philip J. Armitage , Tilman Birnstiel , Hubert Klahr

Particle tagging is an efficient, but approximate, technique for using cosmological N-body simulations to model the phase-space evolution of the stellar populations predicted, for example, by a semi-analytic model of galaxy formation. We…

Astrophysics of Galaxies · Physics 2017-08-21 Andrew P. Cooper , Shaun Cole , Carlos S. Frenk , Theo Le Bret , Andrew Pontzen

We present a 3D semi-analytic model of self-gravitating discs, and include a prescription for dust trapping in the disc spiral arms. Using Monte-Carlo radiative transfer we produce synthetic ALMA observations of these discs. In doing so we…

Earth and Planetary Astrophysics · Physics 2020-09-02 James Cadman , Cassandra Hall , Ken Rice , Tim J. Harries , Pamela D. Klaassen

To mimic protoplanetary discs (PPDs) evolution, 2D simulations with self-gravity must introduce a softening prescription of the gravitational potential. When the disc is only made of gas the smoothing length is proportional to the gas scale…

Earth and Planetary Astrophysics · Physics 2023-07-12 Steven Rendon Restrepo , Pierre Barge

We present a numerical formulation for the solution of non-isothermal, compressible, Navier-Stokes equations with thermal fluctuations to describe mesoscale transport phenomena in multispecies fluid mixtures. The novelty of our numerical…

When calculating satellite trajectories in low-earth orbit, engineers need to adequately estimate aerodynamic forces. But to this day, obtaining the drag acting on the complicated shapes of modern spacecraft suffers from many sources of…

Computational Physics · Physics 2013-12-16 J. Brent Parham , L. A. Barba

Surrogate-assisted search-based testing (SA-SBT) aims to reduce the computational time for testing compute-intensive systems. Surrogates enhance testing techniques by improving test case generation focusing the testing budget on the most…

Software Engineering · Computer Science 2023-05-02 Shiva Nejati , Lev Sorokin , Damir Safin , Federico Formica , Mohammad Mahdi Mahboob , Claudio Menghi

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola