相关论文: Gaussian continuum basis functions for calculating…
We propose the Gaussian Content as an optional quality parameter for the characterization of laser beams. It is defined as the overlap integral of a given field with an optimally defined Gaussian. The definition is specially suited for…
We perform a detailed analysis of high-order harmonic generation (HHG) in atoms within the strong field approximation (SFA) by considering spatially inhomogeneous monochromatic laser fields. We investigate how the individual pairs of…
Gaussian random number generators attract a widespread interest due to their applications in several fields. Important requirements include easy implementation, tail accuracy, and, finally, a flat spectrum. In this work, we study the…
High-harmonic generation (HHG) is one of the fundamental processes at the heart of attosecond physics. Traditionally viewed as an effective single-particle effect, recent advances have focused on contributions beyond this single-particle…
High-order harmonic generation (HHG) by hydrogenlike atoms/ions in the uniform periodic electric field, formed by the two linearly polarized counterpropagating laser beams of relativistic intensities, is studied. The relativistic quantum…
This work considers estimation and forecasting in a multivariate, possibly high-dimensional count time series model constructed from a transformation of a latent Gaussian dynamic factor series. The estimation of the latent model parameters…
High harmonic generation (HHG) from crystals in strong laser fields has been understood by the band theory of solid, which is based on the periodic boundary condition (PBC) of translational invariant. For systems having PBC of rotational…
This study presents an investigation of second harmonic generation (SHG) resulting from interaction of radially polarized laser beam propagating in homogeneous, unmagnetized plasma. Lorentz force and continuity equations have been used to…
Gaussian processes (GPs) provide a nonparametric representation of functions. However, classical GP inference suffers from high computational cost for big data. In this paper, we propose a new Bayesian approach, EigenGP, that learns both…
Gaussian Probability Path based Generative Models (GPPGMs) generate data by reversing a stochastic process that progressively corrupts samples with Gaussian noise. Despite state-of-the-art results in 3D molecular generation, their…
Gaussian processes (GPs) provide a probabilistic nonparametric representation of functions in regression, classification, and other problems. Unfortunately, exact learning with GPs is intractable for large datasets. A variety of approximate…
In this paper, we present a variational treatment of the linear dependence for a non-orthogonal time-dependent basis set in solving the Schr\"odinger equation. The method is based on: i) the definition of a linearly independent working…
Gaussian Process (GP) models provide a flexible framework for prediction and uncertainty quantification. For most covariance functions, however, exact GP prediction with $n$ points scales as $\mathcal{O}(n^3)$, making it prohibitively…
We study the phase matching of resonant high-harmonic generation (HHG) and high-order frequency mixing (HFM) in plasma. We solve numerically the propagation equations coupled with the time-dependent Schr\"odinger equation for the nonlinear…
We introduce a class of interatomic potential models that can be automatically generated from data consisting of the energies and forces experienced by atoms, derived from quantum mechanical calculations. The resulting model does not have a…
We present theoretical studies of high-order harmonic generation (HHG) in rare gases driven by plasmonic field enhancement. This kind of fields appears when plasmonic nanostructures are illuminated by an intense few-cycle laser and have a…
We study high-order harmonic generation (HHG) resulting from the illumination of plasmonic nanostructures with a short laser pulse. We show that both the inhomogeneities of the local electric field and the confinement of the electron motion…
The generating function method that we had developing has various applications in physics and not only interress undergraduate students but also physicists. We solve simply difficult problems or unsolved commonly used in quantum, nuclear…
The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large datasets. Gaussian Processes are a popular class of models used for this purpose…
Microscopic nonlinear quantum theory of interaction of coherent electromagnetic radiation with gapped bilayer graphene is developed. The Liouville-von Neumann equation for the density matrix is solved numerically at the multiphoton…