skip to main content

Attention:

The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Thursday, October 10 until 2:00 AM ET on Friday, October 11 due to maintenance. We apologize for the inconvenience.


Title: NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts
NSF-PAR ID:
10307365
Author(s) / Creator(s):
 ;  ;  ;  ;  
Publisher / Repository:
American Institute of Physics
Date Published:
Journal Name:
The Journal of Chemical Physics
Volume:
155
Issue:
18
ISSN:
0021-9606
Page Range / eLocation ID:
Article No. 184303
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract The synergy between topology and non-Hermiticity in photonics holds immense potential for next-generation optical devices that are robust against defects. However, most demonstrations of non-Hermitian and topological photonics have been limited to super-wavelength scales due to increased radiative losses at the deep-subwavelength scale. By carefully designing radiative losses at the nanoscale, we demonstrate a non-Hermitian plasmonic–dielectric metasurface in the visible with non-trivial topology. The metasurface is based on a fourth order passive parity-time symmetric system. The designed device exhibits an exceptional concentric ring in its momentum space and is described by a Hamiltonian with a non-Hermitian Z 3 ${\mathbb{Z}}_{3}$ topological invariant of V = −1. Fabricated devices are characterized using Fourier-space imaging for single-shot k -space measurements. Our results demonstrate a way to combine topology and non-Hermitian nanophotonics for designing robust devices with novel functionalities. 
    more » « less
  2. null (Ed.)
  3. Abstract

    Acoustic metasurfaces are at the frontier of acoustic functional material research owing to their advanced capabilities of wave manipulation at an acoustically vanishing size. Despite significant progress in the last decade, conventional acoustic metasurfaces are still fundamentally limited by their underlying physics and design principles. First, conventional metasurfaces assume that unit cells are decoupled and therefore treat them individually during the design process. Owing to diffraction, however, the non-locality of the wave field could strongly affect the efficiency and even alter the behavior of acoustic metasurfaces. Additionally, conventional acoustic metasurfaces operate by modulating the phase and are typically treated as lossless systems. Due to the narrow regions in acoustic metasurfaces’ subwavelength unit cells, however, losses are naturally present and could compromise the performance of acoustic metasurfaces. While the conventional wisdom is to minimize these effects, a counter-intuitive way of thinking has emerged, which is to harness the non-locality as well as loss for enhanced acoustic metasurface functionality. This has led to a new generation of acoustic metasurface design paradigm that is empowered by non-locality and non-Hermicity, providing new routes for controlling sound using the acoustic version of 2D materials. This review details the progress of non-local and non-Hermitian acoustic metasurfaces, providing an overview of the recent acoustic metasurface designs and discussing the critical role of non-locality and loss in acoustic metasurfaces. We further outline the synergy between non-locality and non-Hermiticity, and delineate the potential of using non-local and non-Hermitian acoustic metasurfaces as a new platform for investigating exceptional points, the hallmark of non-Hermitian physics. Finally, the current challenges and future outlook for this burgeoning field are discussed.

     
    more » « less
  4. We present new algorithms for optimizing non-smooth, non-convex stochastic objectives based on a novel analysis technique. This improves the current best-known complexity for finding a (δ,ϵ)-stationary point from O(ϵ^(-4),δ^(-1)) stochastic gradient queries to O(ϵ^(-3),δ^(-1)), which we also show to be optimal. Our primary technique is a reduction from non-smooth non-convex optimization to online learning, after which our results follow from standard regret bounds in online learning. For deterministic and second-order smooth objectives, applying more advanced optimistic online learning techniques enables a new complexity of O(ϵ^(-1.5),δ^(-0.5)). Our techniques also recover all optimal or best-known results for finding ϵ stationary points of smooth or second-order smooth objectives in both stochastic and deterministic settings. 
    more » « less