Zobrazeno 1 - 10
of 4 222
pro vyhledávání: '"Pask A"'
Given a row-finite higher-rank $k$-graph $\Lambda$, we define a commutative monoid $T_\Lambda$ which is a higher-rank analogue of the talented monoid of a directed graph. The talented monoid $T_\Lambda$ is canonically a $\mathbb{Z}^k$-monoid with res
Externí odkaz:
http://arxiv.org/abs/2411.07582
We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel method and Bayesian linear regression to compute th
Externí odkaz:
http://arxiv.org/abs/2407.15290
Autor:
Pask, David
We introduce a new family of higher-rank graphs, whose construction was inspired by the graphical techniques of Lambek \cite{Lambek} and Johnstone \cite{Johnstone} used for monoid and category emedding results. We show that they are planar $k$-trees
Externí odkaz:
http://arxiv.org/abs/2407.14048
We present a spectral scheme for atomic structure calculations in pseudopotential Kohn-Sham density functional theory. In particular, after applying an exponential transformation of the radial coordinates, we employ global polynomial interpolation on
Externí odkaz:
http://arxiv.org/abs/2406.00534
Implantable hydrogels should ideally possess mechanical properties matched to the surrounding tissues to enable adequate mechanical function while regeneration occurs. This can be challenging, especially when degradable systems with high water conten
Externí odkaz:
http://arxiv.org/abs/2403.08392
We show that the C*-algebra of a row-finite source-free k-graph is Rieffel-Morita equivalent to a crossed product of an AF algebra by the fundamental group of the k-graph. When the k-graph embeds in its fundamental groupoid, this AF algebra is a Fell
Externí odkaz:
http://arxiv.org/abs/2403.01337
We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme based on the kernel method and Bayesian linear regression, with the train
Externí odkaz:
http://arxiv.org/abs/2402.13450
We present a $\Delta$-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned force field (MLFF) scheme based on the kernel method to capture t
Externí odkaz:
http://arxiv.org/abs/2310.06598
We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with temperature-independ
Externí odkaz:
http://arxiv.org/abs/2308.08132
Autor:
Čertík, Ondřej, Pask, John E., Fernando, Isuru, Goswami, Rohit, Sukumar, N., Collins, Lee A., Manzini, Gianmarco, Vackář, Jiří
We introduce \texttt{featom}, an open source code that implements a high-order finite element solver for the radial Schr\"odinger, Dirac, and Kohn-Sham equations. The formulation accommodates various mesh types, such as uniform or exponential, and th
Externí odkaz:
http://arxiv.org/abs/2307.05856