1,174 research outputs found
Scalar scattering amplitude in the Gaussian wave-packet formalism
Kenzo Ishikawa, Kenji Nishiwaki, Kin-ya Oda, Scalar scattering amplitude in the Gaussian wave-packet formalism, Progress of Theoretical and Experimental Physics, Volume 2020, Issue 10, October 2020, 103B04, https://doi.org/10.1093/ptep/ptaa127
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New effect in wave-packet scatterings of quantum fields: Saddle points, Lefschetz thimbles, and Stokes phenomenon
We find a new contribution in wave-packet scatterings, which has been
overlooked in the standard formulation of S-matrix. As a concrete example, we
consider a two-to-two scattering of light scalars by another
intermediate heavy scalar , in the Gaussian wave-packet formalism:
. This contribution can be interpreted as an
"in-time-boundary effect" of for the corresponding
decay, proposed by Ishikawa et al., with a newly found modification that would
cure the previously observed ultraviolet divergence. We show that such an
effect can be understood as a Stokes phenomenon in an integral over complex
energy plane: The number of relevant saddle points and Lefschetz thimbles
(steepest descent paths) discretely changes depending on the configurations of
initial and final states in the scattering.Comment: 5 pages with 3 pages of Supplemental Material, 3 figure
Deep sound-field denoiser: optically-measured sound-field denoising using deep neural network
This paper proposes a deep sound-field denoiser, a deep neural network (DNN)
based denoising of optically measured sound-field images. Sound-field imaging
using optical methods has gained considerable attention due to its ability to
achieve high-spatial-resolution imaging of acoustic phenomena that conventional
acoustic sensors cannot accomplish. However, the optically measured sound-field
images are often heavily contaminated by noise because of the low sensitivity
of optical interferometric measurements to airborne sound. Here, we propose a
DNN-based sound-field denoising method. Time-varying sound-field image
sequences are decomposed into harmonic complex-amplitude images by using a
time-directional Fourier transform. The complex images are converted into
two-channel images consisting of real and imaginary parts and denoised by a
nonlinear-activation-free network. The network is trained on a sound-field
dataset obtained from numerical acoustic simulations with randomized
parameters. We compared the method with conventional ones, such as image
filters and a spatiotemporal filter, on numerical and experimental data. The
experimental data were measured by parallel phase-shifting interferometry and
holographic speckle interferometry. The proposed deep sound-field denoiser
significantly outperformed the conventional methods on both the numerical and
experimental data.Comment: 13 pages, 8 figures, 2 table
An Algorithm for the Assignment Problem with Stochastic Side Constraints
In this paper, we consider the assignment problem with stochastic side constraints, and propose a practical algorithm for solving it. Such a problem may arise, for example, when the assignment requires some scarce resources and the total amounts of those resources are subject to a random variation. Therefore, the problem seems quite general and significant in practice. This algorithm takes a special structure of the problem into account, and may be regarded as a heuristic modification of the method for two-stage linear programming under uncertainty. Although we cannot guarantee that the solution obtained by the proposed algorithm will coincide with the true optimal solution of the problem, our limited computational experience on small test problems indicates that good approximate solutions can be obtained in a fairly small computation time
Brain Imaging of Nicotinic Receptors in Alzheimer's Disease
Neuronal nicotinic acetylcholine receptors (nAChRs) are a family of ligand-gated ion channels which are widely distributed in the human brain. Several lines of evidence suggest that two major subtypes (Ī±4Ī²2 and Ī±7) of nAChRs play an important role in the pathophysiology of Alzheimer's disease (AD). Postmortem studies demonstrated alterations in the density of these subtypes of nAChRs in the brain of patients with AD. Currently, nAChRs are one of the most attractive therapeutic targets for AD. Therefore, several researchers have made an effort to develop novel radioligands that can be used to study quantitatively the distribution of these two subtypes in the human brain with positron emission tomography (PET) and single-photon emission computed tomography (SPECT). In this paper, we discuss the current topics on in vivo imaging of two subtypes of nAChRs in the brain of patients with AD
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