Zobrazeno 1 - 10
of 106
pro vyhledávání: '"Jeggle P"'
Autor:
Jeggle, Kai, Czerkawski, Mikolaj, Serva, Federico, Saux, Bertrand Le, Neubauer, David, Lohmann, Ulrike
IceCloudNet is a novel method based on machine learning able to predict high-quality vertically resolved cloud ice water contents (IWC) and ice crystal number concentrations (N$_\textrm{ice}$). The predictions come at the spatio-temporal coverage and
Externí odkaz:
http://arxiv.org/abs/2410.04135
Autor:
Jeggle, Kai, Czerkawski, Mikolaj, Serva, Federico, Saux, Bertrand Le, Neubauer, David, Lohmann, Ulrike
Publikováno v:
NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning
Clouds containing ice particles play a crucial role in the climate system. Yet they remain a source of great uncertainty in climate models and future climate projections. In this work, we create a new observational constraint of regime-dependent ice
Externí odkaz:
http://arxiv.org/abs/2310.03499
The pair-distribution function, which provides information about correlations in a system of interacting particles, is one of the key objects of theoretical soft matter physics. In particular, it allows for microscopic insights into the phase behavio
Externí odkaz:
http://arxiv.org/abs/2307.14558
The worldwide COVID-19 pandemic has led to a significant growth of interest in the development of mathematical models that allow to describe effects such as social distancing measures, the development of vaccines, and mutations. Several of these mode
Externí odkaz:
http://arxiv.org/abs/2307.00437
Cirrus clouds are key modulators of Earth's climate. Their dependencies on meteorological and aerosol conditions are among the largest uncertainties in global climate models. This work uses three years of satellite and reanalysis data to study the li
Externí odkaz:
http://arxiv.org/abs/2305.02090
Autor:
Jeggle, Julian, Wittkowski, Raphael
Recently, there has been much progress in the formulation and implementation of methods for generic many-particle simulations. These models, however, typically either do not utilize shared memory hardware or do not guarantee data-race freedom for arb
Externí odkaz:
http://arxiv.org/abs/2302.14170
Publikováno v:
New Journal of Physics 23, 063023 (2021)
Most field theories for active matter neglect effects of memory and inertia. However, recent experiments have found inertial delay to be important for the motion of self-propelled particles. A major challenge in the theoretical description of these e
Externí odkaz:
http://arxiv.org/abs/2102.02169
Publikováno v:
Journal of Chemical Physics 156, 194904 (2022)
We consider chirality in active systems by exemplarily studying the phase behavior of planar systems of interacting Brownian circle swimmers with a spherical shape. Continuing previous work presented in [G.-J. Liao, S. H. L. Klapp, Soft Matter, 2018,
Externí odkaz:
http://arxiv.org/abs/2010.05262
Publikováno v:
Journal of Chemical Physics 152, 194903 (2020)
We investigate the full pair-distribution function of a homogeneous suspension of spherical active Brownian particles interacting by a Weeks-Chandler-Andersen potential in two spatial dimensions. The full pair-distribution function depends on three c
Externí odkaz:
http://arxiv.org/abs/1912.02965
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