Results 111 to 120 of about 1,930,444 (347)

Gaussian Decoherence and Gaussian Echo from Spin Environments [PDF]

open access: yes, 2006
We examine an exactly solvable model of decoherence -- a spin-system interacting with a collection of environment spins. We show that in this simple model (introduced some time ago to illustrate environment--induced superselection) generic assumptions ...
Cucchietti, F. M.   +2 more
core   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani   +2 more
wiley   +1 more source

Biaxial Gaussian Beams, Hermite–Gaussian Beams, and Laguerre–Gaussian Vortex Beams in Isotropy-Broken Materials

open access: yesPhotonics
We have developed the paraxial approximation for electromagnetic fields in arbitrary isotropy-broken media in terms of the ray–wave tilt and the curvature of materials’ Fresnel wave surfaces.
Maxim Durach
doaj   +1 more source

Which is the right option for Indian market: Gaussian, normal inverse Gaussian, or Tsallis?

open access: yesIIMB Management Review, 2019
This paper models Nifty spot prices using frameworks based on Gaussian distribution (geometric Brownian motion) and non-Gaussian distributions, viz. normal inverse Gaussian (NIG), and Tsallis distributions, to investigate which model best captures the ...
Prasenjit Chakrabarti   +1 more
doaj   +1 more source

GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs

open access: yes, 2019
This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian Processes (GP), and ...
AS Stordal   +17 more
core   +1 more source

Non-Gaussianity and intermittency in an ensemble of Gaussian fields [PDF]

open access: yesNew Journal of Physics, 2016
Motivated by the need to capture statistical properties of turbulent systems in simple, analytically tractable models, an ensemble of Gaussian sub-ensembles with varying properties of the correlation function such as variance and length scale is investigated. The ensemble statistics naturally exhibit non-Gaussianity and intermittency.
openaire   +3 more sources

A Different Perspective on the Solid Lubrication Performance of Black Phosphorous: Friend or Foe?

open access: yesAdvanced Engineering Materials, EarlyView.
Researchers investigate black phosphorous (BP) as a standalone solid lubricant coating through ball‐on‐disc linear‐reciprocating sliding experiments in dry conditions. Testing on different metals shows BP doesn't universally reduce friction and wear. However, it achieves 33% friction reduction on rougher iron surfaces and 23% wear reduction on aluminum.
Matteo Vezzelli   +5 more
wiley   +1 more source

Ince-Gaussian laser beams as superposition of Hermite-Gaussian or Laguerre-Gaussian beams

open access: yesКомпьютерная оптика
We obtain explicit analytic expressions for the Ince-Gaussian (IG) beams for several first indices p = 3, 4, 5, 6. Earlier, explicit expressions have been derived for amplitudes of the IG beams with p = 0, 1, 2 and without regard for the ellipticity ...
E.G. Abramochkin   +2 more
doaj   +1 more source

BILANGAN BULAT GAUSSIAN Z[i]

open access: yesJurnal Matematika UNAND, 2020
Tulisan ini membahas tentang bilangan bulat Gaussian Z[i]. Bilangan bulat Gaussian didefinisikan sebagai himpunan dari bilangan a+bi dengan a, b adalah bilangan bulat dan i 2 = −1.
ELIZA SURYA NINGSIH   +2 more
doaj   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

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