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Hace 1 día · La ley de Stefan-Boltzmann tiene numerosas aplicaciones en distintos campos de la ciencia y la ingeniería. A continuación, se detallan algunas de las aplicaciones más destacadas: 1. Astrofísica. En astrofísica, la ley de Stefan-Boltzmann es crucial para determinar la luminosidad de estrellas y otros cuerpos celestes.
Hace 5 días · This paper proposes an improved cumulant collision model for the pseudo-potential lattice Boltzmann method (LBM) to increase the stability of multiphase flow simulations involving low viscosities. This model is based on the work of Kharmiani et al. in (J Stat Phys 175: 47, 2019), which can be extended regardless of the collision model. The original cumulant collision model (Geier et al. in ...
Hace 5 días · The lattice Boltzmann method (LBM) is a computational fluid dynamics (CFD) simulation method that is derived from the theory of molecular motion. It divides the fluid domain into regular grids and simulates the flow and collision of particles on these grids to model the behavior of the fluid [ 1 ].
Hace 1 día · The printed nc-FETs demonstrate an extremely low subthreshold slope of ∼2.3 mV/decade at room temperature, which remains below the Boltzmann’s limit for over 5 orders of magnitude of drain currents. Furthermore, the unipolar depletion-load-type inverters fabricated using n-type nc-FETs have demonstrated an extraordinary signal gain of 2691.
Hace 2 días · Restricted Boltzmann machines are powerful tools in the field of generative, probabilistic learning, capable of capturing complex dependencies in data. By understanding their architecture and operational principles, one can employ them for diverse purposes such as dimensionality reduction, feature learning and even representing and analyzing various physical systems.
Hace 5 días · Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Magdalenka, Poland
Hace 1 día · This method leverages a temperature-scaled Boltzmann influence function to linearize the model, producing well-calibrated predictions and measuring complexity in labeled and unlabeled settings. The IF-COMP method regularizes the model’s response to additional data points by applying a proximal objective that penalizes movement in function and weight space.
