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

偏光高速度干渉計を用いた音場可視化計測に関する研究

早大学位記番号:新8114早稲田大

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 $\phi$ by another intermediate heavy scalar $\Phi$, in the Gaussian wave-packet formalism: $\phi\phi\to\Phi\to\phi\phi$. This contribution can be interpreted as an "in-time-boundary effect" of $\Phi$ for the corresponding $\Phi\to\phi\phi$ 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 (α4β2 and α7) 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