123 research outputs found
Geometric picture of quantum discord for two-qubit quantum states
Among various definitions of quantum correlations, quantum discord has
attracted considerable attention. To find analytical expression of quantum
discord is an intractable task. Exact results are known only for very special
states, namely, two-qubit X-shaped states. We present in this paper a geometric
viewpoint, from which two-qubit quantum discord can be described clearly. The
known results about X state discord are restated in the directly perceivable
geometric language. As a consequence, the dynamics of classical correlations
and quantum discord for an X state in the presence of decoherence is endowed
with geometric interpretation. More importantly, we extend the geometric method
to the case of more general states, for which numerical as well as analytica
results about quantum discord have not been found yet. Based on the support of
numerical computations, some conjectures are proposed to help us establish
geometric picture. We find that the geometric picture for these states has
intimate relationship with that for X states. Thereby in some cases analytical
expressions of classical correlations and quantum discord can be obtained.Comment: 9 figure
A Two-Stage Robust Optimization for Centralized-Optimal Dispatch of Photovoltaic Inverters in Active Distribution Networks
Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation
Temporal video segmentation and classification have been advanced greatly by
public benchmarks in recent years. However, such research still mainly focuses
on human actions, failing to describe videos in a holistic view. In addition,
previous research tends to pay much attention to visual information yet ignores
the multi-modal nature of videos. To fill this gap, we construct the Tencent
`Ads Video Segmentation'~(TAVS) dataset in the ads domain to escalate
multi-modal video analysis to a new level. TAVS describes videos from three
independent perspectives as `presentation form', `place', and `style', and
contains rich multi-modal information such as video, audio, and text. TAVS is
organized hierarchically in semantic aspects for comprehensive temporal video
segmentation with three levels of categories for multi-label classification,
e.g., `place' - `working place' - `office'. Therefore, TAVS is distinguished
from previous temporal segmentation datasets due to its multi-modal
information, holistic view of categories, and hierarchical granularities. It
includes 12,000 videos, 82 classes, 33,900 segments, 121,100 shots, and 168,500
labels. Accompanied with TAVS, we also present a strong multi-modal video
segmentation baseline coupled with multi-label class prediction. Extensive
experiments are conducted to evaluate our proposed method as well as existing
representative methods to reveal key challenges of our dataset TAVS
Bi-level Programming Based Optimal Strategy to LSEs with Demand Response Bids
With the increasing demand-side participation in electricity market, as a profit-seeking market participant, load-serving entities (LSEs) have been trying to apply demand response (DR) programs to induce the demand elasticity to further their profit. However, due to the different preference of DRs, it is difficult for LSEs to generate the optimal strategic bidding strategy considering DR in the ISO/RTO’s market. Therefore, this paper proposed a bi-level optimization model with the consideration of demand response bidding to maximize the total profit of LSEs: 1) conceptually, different from previous related works, the consumers participate DR through setting their bidding prices to LSEs with respect to their own preference and LSEs should determine the optimal reward value of DR as well as the amount of demanded electricity; and 2) technically, an original method has been implemented to solve the bi-level optimization model. The closed form of shadow price function with respect to the total load demand is derived to reduce the complexity of the proposed bi-level model. Hence, the proposed model is converted to a mixed integer second order cone programming and able to achieve the global optimality. It needs to be note that the closed form of shadow price introduced in this paper can also be applied to other bi-level programming models. Moreover, case studies have been performed to demonstrate the validity of the proposed method: 1) the proposed method to obtain the closed form of real-time price is verified on a 9-bus system; 2) 118-bus test system with three demand response participants is tested to show that by the proposed method, LSE can benefit from the DRs under various circumstance
Vertically-aligned Mn(OH)2 nanosheet films for flexible all-solid-state electrochemical supercapacitors
The arrangement of the electrode materials is a significant contributor for constructing high performance supercapacitor. Here, vertically-aligned Mn(OH)2 nanosheet thin films were synthesized by cathodic electrodeposition technique on flexible Au coated polyethylene terephthalate substrates. Morphologies, microstructures, chemical compositions and valence state of the nanosheet films were characterized systematically. It shows that the nanosheets arranged vertically to the substrate, forming a porous nanowall structures and creating large open framework, which greatly facilitate the adsorption or diffusion of electrolyte ions for faradaic redox reaction. Electrochemical tests of the films show the specific capacitance as high as 240.2 F g−1 at 1.0 A g−1. The films were employed to assemble symmetric all-solid-state supercapacitors with LiCl/PVA gel severed as solid electrolyte. The solid devices exhibit high volumetric capacitance of 39.3 mF cm−3 at the current density 0.3 mA cm−3 with robust cycling stability. The superior performance is attributed to the vertically-aligned configuration
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