Zobrazeno 1 - 10
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pro vyhledávání: '"McDevitt P"'
We explain how the disparate kinematics of quantum mechanics (finite-dimensional Hilbert space of QM) and special relativity (Minkowski spacetime from the Lorentz transformations of SR) can both be based on one principle (relativity principle). This
Externí odkaz:
http://arxiv.org/abs/2404.13064
A surrogate model of the runaway electron avalanche growth rate in a magnetic fusion plasma is developed. This is accomplished by employing a physics-informed neural network (PINN) to learn the parametric solution of the adjoint to the relativistic F
Externí odkaz:
http://arxiv.org/abs/2403.04948
A reduced kinetic method (RKM) with a first-principle collision operator is introduced in a 1D2V planar geometry and implemented in a computationally inexpensive code to investigate non-local ion heat transport in multi-species plasmas. The RKM succe
Externí odkaz:
http://arxiv.org/abs/2403.03595
Publikováno v:
Phys. Plasmas 31 (2024) 062701
A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the
Externí odkaz:
http://arxiv.org/abs/2402.08495
The exponential growth (avalanching) of runaway electrons (REs) during a tokamak disruption continues to be a large uncertainty in RE modeling. The present work investigates the impact of tokamak geometry on the efficiency of the avalanche mechanism
Externí odkaz:
http://arxiv.org/abs/2401.11291
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Accurate detection and tracking of animals across diverse environments are crucial for studying brain and behavior. Recently, computer vision techniques have become essential for high-throughput behavioral studies; however, localizing animal
Externí odkaz:
https://doaj.org/article/965206f2b94f43f9aa93d8d762c26463
Autor:
McDevitt, Christopher
Publikováno v:
Phys. Plasmas 30 (2023) 092501
A challenging aspect of the description of a tokamak disruption is evaluating the hot tail runaway electron (RE) seed that emerges during the thermal quench. This problem is made challenging due to the requirement of describing a strongly non-thermal
Externí odkaz:
http://arxiv.org/abs/2306.13224
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract Physics-informed neural networks (PINNs) are an emerging technology that can be used both in place of and in conjunction with conventional simulation methods. In this paper, we used PINNs to perform a forward simulation without leveraging kn
Externí odkaz:
https://doaj.org/article/41b4fd499b7e44d5b4d28a3213369001
To study population dynamics, ecologists and wildlife biologists use relative abundance data, which are often subject to temporal preferential sampling. Temporal preferential sampling occurs when sampling effort varies across time. To account for pre
Externí odkaz:
http://arxiv.org/abs/2212.05180
High resolution simulations of incompressible flows have become routine across a range of engineering applications. Despite their routine use, due to the high dimensional parameter space present for most practical applications, a comprehensive explor
Externí odkaz:
http://arxiv.org/abs/2211.06375