22,087 research outputs found
Switchable valley functionalities of an junction in 2D semiconductors
We show that an junction in 2D semiconductors can flexibly
realize two basic valleytronic functions, i.e. valley filter and valley source,
with gate controlled switchability between the two. Upon carrier flux passing
through the junction, the valley filter and valley source functions are enabled
respectively by intra- and inter-valley scatterings, and the two functions
dominate respectively at small and large band-offset between the and
regions. It can be generally shown that, the valley filter effect has
an angular dependent polarity and vanishes under angular integration, by the
same constraint from time-reversal symmetry that leads to its absence in
one-dimension. These findings are demonstrated for monolayer transition metal
dichalcogenides and graphene using tight-binding calculations. We further show
that junction along chiral directions can concentrate the valley pump in an
angular interval largely separated from the bias direction, allowing efficient
havest of valley polarization in a cross-bar device
Kernel Truncated Regression Representation for Robust Subspace Clustering
Subspace clustering aims to group data points into multiple clusters of which
each corresponds to one subspace. Most existing subspace clustering approaches
assume that input data lie on linear subspaces. In practice, however, this
assumption usually does not hold. To achieve nonlinear subspace clustering, we
propose a novel method, called kernel truncated regression representation. Our
method consists of the following four steps: 1) projecting the input data into
a hidden space, where each data point can be linearly represented by other data
points; 2) calculating the linear representation coefficients of the data
representations in the hidden space; 3) truncating the trivial coefficients to
achieve robustness and block-diagonality; and 4) executing the graph cutting
operation on the coefficient matrix by solving a graph Laplacian problem. Our
method has the advantages of a closed-form solution and the capacity of
clustering data points that lie on nonlinear subspaces. The first advantage
makes our method efficient in handling large-scale datasets, and the second one
enables the proposed method to conquer the nonlinear subspace clustering
challenge. Extensive experiments on six benchmarks demonstrate the
effectiveness and the efficiency of the proposed method in comparison with
current state-of-the-art approaches.Comment: 14 page
High-frequency Light Reflector via Low-frequency Light Control
We show that the momentum of light can be reversed via the atomic coherence
created by another light with one or two orders of magnitude lower frequency.
Both the backward retrieval of single photons from a timed Dicke state and the
reflection of continuous waves by high-order photonic band gaps are analysed.
The required control field strength scales linearly with the nonlinearity
order, which is explained by the dynamics of superradiance lattices.
Experiments are proposed with Rb atoms and Be ions. This holds
promise for light-controllable X-ray reflectors.Comment: 5 pages, 5 figure
ShuttleSet22: Benchmarking Stroke Forecasting with Stroke-Level Badminton Dataset
In recent years, badminton analytics has drawn attention due to the
advancement of artificial intelligence and the efficiency of data collection.
While there is a line of effective applications to improve and investigate
player performance, there are only a few public badminton datasets that can be
used for researchers outside the badminton domain. Existing badminton singles
datasets focus on specific matchups; however, they cannot provide comprehensive
studies on different players and various matchups. In this paper, we provide a
badminton singles dataset, ShuttleSet22, which is collected from high-ranking
matches in 2022. ShuttleSet22 consists of 30,172 strokes in 2,888 rallies in
the training set, 1,400 strokes in 450 rallies in the validation set, and 2,040
strokes in 654 rallies in the testing set with detailed stroke-level metadata
within a rally. To benchmark existing work with ShuttleSet22, we test the
state-of-the-art stroke forecasting approach, ShuttleNet, with the
corresponding stroke forecasting task, i.e., predict the future strokes based
on the given strokes of each rally. We also hold a challenge, Track 2:
Forecasting Future Turn-Based Strokes in Badminton Rallies, at CoachAI
Badminton Challenge 2023 to boost researchers to tackle this problem. The
baseline codes and the dataset will be made available on
https://github.com/wywyWang/CoachAI-Projects/tree/main/CoachAI-Challenge-IJCAI2023.Comment: IT4PSS @ IJCAI-23 and CoachAI Badminton Challenge Track 2 @ IJCAI-23.
Challenge website: https://sites.google.com/view/coachai-challenge-2023
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