Determinant representations for scalar products of the XXZ Gaudin model with general boundary terms

We obtain the determinant representations of the scalar products for the XXZ Gaudin model with generic non-diagonal boundary terms.Comment: Latex file, 17 page

Interlayer Interactions in Anisotropic Atomically-thin Rhenium Diselenide

Recently, two-dimensional (2D) materials with strong in-plane anisotropic properties such as black phosphorus have demonstrated great potential for developing new devices that can take advantage of its reduced lattice symmetry with potential applications in electronics, optoelectronics and thermoelectrics. However, the selection of 2D material with strong in-plane anisotropy has so far been very limited and only sporadic studies have been devoted to transition metal dichalcogenides (TMDC) materials with reduced lattice symmetry, which is yet to convey the full picture of their optical and phonon properties, and the anisotropy in their interlayer interactions. Here, we study the anisotropic interlayer interactions in an important TMDC 2D material with reduced in-plane symmetry - atomically thin rhenium diselenide (ReSe2) - by investigating its ultralow frequency interlayer phonon vibration modes, the layer dependent optical bandgap, and the anisotropic photoluminescence (PL) spectra for the first time. The ultralow frequency interlayer Raman spectra combined with the first study of polarization-resolved high frequency Raman spectra in mono- and bi-layer ReSe2 allows deterministic identification of its layer number and crystal orientation. PL measurements show anisotropic optical emission intensity with bandgap increasing from 1.26 eV in the bulk to 1.32 eV in monolayer, consistent with the theoretical results based on first-principle calculations. The study of the layer-number dependence of the Raman modes and the PL spectra reveals the relatively weak van der Waals interaction and 2D quantum confinement in atomically-thin ReSe2.Comment: 17 pages, 5 figures, supplementary informatio

Spatial Interference: From Coherent To Incoherent

It is well known that direct observation of interference and diffraction pattern in the intensity distribution requires a spatially coherent source. Optical waves emitted from portions beyond the coherence area possess statistically independent phases, and will degrade the interference pattern. In this paper we show an optical interference experiment, which seems contrary to our common knowledge, that the formation of the interference pattern is related to a spatially incoherent light source. Our experimental scheme is very similar to Gabor's original proposal of holography[1], just with an incoherent source replacing the coherent one. In the statistical ensemble of the incoherent source, each sample field produces a sample interference pattern between object wave and reference wave. These patterns completely differ from each other due to the fluctuation of the source field distribution. Surprisingly, the sum of a great number of sample patterns exhibits explicitly an interference pattern, which contains all the information of the object and is equivalent to a hologram in the coherent light case. In this sense our approach would be valuable in holography and other interference techniques for the case where coherent source is unavailable, such as x-ray and electron sources.Comment: 8 pages, 5 figure

A Robust Hessian-based Trust Region Algorithm for Spherical Conformal Parameterizations

Surface parameterizations are widely applied in computer graphics, medical imaging and transformation optics. In this paper, we rigorously derive the gradient vector and Hessian matrix of the discrete conformal energy for spherical conformal parameterizations of simply connected closed surfaces of genus-$0$. In addition, we give the sparsity structure of the Hessian matrix, which leads to a robust Hessian-based trust region algorithm for the computation of spherical conformal maps. Numerical experiments demonstrate the local quadratic convergence of the proposed algorithm with low conformal distortions. We subsequently propose an application of our method to surface registrations that still maintains local quadratic convergence

A Pricing Strategy Reflecting the Cost of Power Volatility to Facilitate Decentralized Demand Response

Previous pricing strategies including time-of-use price and dynamic price reflect system marginal cost and calculate consumers’ bills according to the quantity of their electricity usage. Little effort is made to understand the impact of power volatility on total production costs. This paper thus proposes a novel pricing strategy reflecting the cost arising from power volatility. Firstly, the impact of volatility on the production cost is investigated to quantify volatility cost. Secondly, a novel pricing model is proposed to allocate the volatility cost to consumers and renewable energy generations (REGs). It can reveal the coupling relationship between an individual load/REG curve and the system load curve. Thirdly, under the proposed pricing strategy, customers/REGs help to flatten the system load curve and reduce the production cost in a decentralized manner, which is certificated theoretically based on the Haar wavelet transforms. Validation on residential level loads shows that the volatility and peak-to-valley difference of aggregated load curve is reduced by 34.07% and 19.81%, respectively. The problem of synchronous response among customers faced by hourly price strategies is addressed by the proposed strategy. A test on megawatt-level loads shows a 61.95% reduction in system load volatility and a 2.21% reduction in production cost. It also reduces the peak-to-valley difference by 6.52%

Open-Vocabulary Argument Role Prediction for Event Extraction

The argument role in event extraction refers to the relation between an event and an argument participating in it. Despite the great progress in event extraction, existing studies still depend on roles pre-defined by domain experts. These studies expose obvious weakness when extending to emerging event types or new domains without available roles. Therefore, more attention and effort needs to be devoted to automatically customizing argument roles. In this paper, we define this essential but under-explored task: open-vocabulary argument role prediction. The goal of this task is to infer a set of argument roles for a given event type. We propose a novel unsupervised framework, RolePred for this task. Specifically, we formulate the role prediction problem as an in-filling task and construct prompts for a pre-trained language model to generate candidate roles. By extracting and analyzing the candidate arguments, the event-specific roles are further merged and selected. To standardize the research of this task, we collect a new event extraction dataset from WikiPpedia including 142 customized argument roles with rich semantics. On this dataset, RolePred outperforms the existing methods by a large margin. Source code and dataset are available on our GitHub repository: https://github.com/yzjiao/RolePredComment: EMNLP 2022 Finding