A5073926074- Quantum and electron transport phenomena
- Quantum Computing Algorithms and Architecture
- Sentiment Analysis and Opinion Mining
- Advanced Fiber Laser Technologies
- Nonlinear Photonic Systems
- Machine Learning in Materials Science
- Laser-Matter Interactions and Applications
- Remote-Sensing Image Classification
- Quantum Information and Cryptography
- Infrastructure Maintenance and Monitoring
- Advanced Text Analysis Techniques
- Biochemical Analysis and Sensing Techniques
- Expert finding and Q&A systems
- Force Microscopy Techniques and Applications
- Adversarial Robustness in Machine Learning
- Advanced Chemical Sensor Technologies
- Quantum many-body systems
- Advanced Electron Microscopy Techniques and Applications
- Advanced Memory and Neural Computing
- Image Processing Techniques and Applications
- Concrete Corrosion and Durability
- Misinformation and Its Impacts
- Spam and Phishing Detection
- Mental Health via Writing
- Topological and Geometric Data Analysis
Tsinghua University
2022-2025
Beijing University of Posts and Telecommunications
2016-2023
Shanghai Key Laboratory of Trustworthy Computing
2016-2021
Singapore Institute of Manufacturing Technology
2014
Topologically ordered phases of matter elude Landau's symmetry-breaking theory, featuring a variety intriguing properties such as long-range entanglement and intrinsic robustness against local perturbations. Their extension to periodically driven systems gives rise exotic new phenomena that are forbidden in thermal equilibrium. Here, we report the observation signatures phenomenon-a prethermal topologically time crystal-with programmable superconducting qubits arranged on square lattice. By...
Symmetry-protected topological phases cannot be described by any local order parameter and are beyond the conventional symmetry-breaking paradigm for understanding quantum matter. They characterized boundary states robust against perturbations that respect protecting symmetry. In a clean system without disorder, these edge modes typically only occur ground of systems with bulk energy gap would not survive at finite temperatures due to mobile thermal excitations. Here, we report observation...
<title>Abstract</title> Symmetry-protected topological phases cannot be described by any local order parameter and are beyond the conventional symmetry-breaking paradigm for understanding quantum matter. They characterized boundary modes that remain stable under symmetry respecting perturbations. In clean, gapped systems without disorder, stability of these edge is restricted to ground state manifold; at finite temperatures, interactions with mobile thermal excitations lead their decay....
Abstract We study the robustness of machine learning approaches to adversarial perturbations, with a focus on supervised scenarios. find that typical phase classifiers based deep neural networks are extremely vulnerable perturbations: adding tiny amount carefully crafted noises into original legitimate examples will cause make incorrect predictions at notably high confidence level. Through lens activation maps, we some important underlying physical principles and symmetries remain be...
Classification and identification of different phases the transitions between them is a central task in condensed matter physics. Machine learning, which has achieved dramatic success wide range applications, holds promise to bring unprecedented perspectives for this challenging task. However, despite exciting progress made along direction, reliability machine-learning approaches experimental settings demands further investigation. Here, with nitrogen-vacancy center platform, we report...
Health support has been sought by the public from online social media after outbreak of novel coronavirus disease 2019 (COVID-19). In addition to physical symptoms caused virus, there are adverse impacts on psychological responses. Therefore, precisely capturing emotions becomes crucial providing adequate support. By constructing a domain-specific COVID-19 health emergency discrete emotion lexicon, we utilized one million theme texts Chinese platform Weibo analyze social-emotional...
Sentiment analysis is a hot topic in couple of years. Emotion, an affective state expressed by human cognitive process, widely embedded user-generated content (UGC). Traditional research mainly focused on polarity and paid less attention to the nature emotion that elicited from underlying structure with multiple discrete dimensions. Informed OCC model hierarchical structure, we firstly detect extract emotions online reviews JD.com, one most famous electronic product marketplaces China....
Deep Convolution neural network (DCNN) has been widely used in the healthy maintenance of civil infrastructure. Using DCNN to improve crack detection performance attracted many researchers' attention. In this paper, a light-weight spatial attention module is proposed strengthen representation capability ResNet and performance. It utilizes mechanism interested objects global receptive field convolution layers. Global average information over all channels are construct an scalar. The scalar...
We propose a general and systematic strategy to compile arbitrary quantum channels without using ancillary qubits, based on proximal policy optimization -- powerful deep reinforcement learning algorithm. rigorously prove that, in sharp contrast the case of compiling unitary gates, it is impossible an channel precision with any given finite elementary set, regardless length decomposition sequence. However, for fixed accuracy $\epsilon$ one can construct universal set constant number...
The development of the education system has put forward a high demand for academic Q&A. In this paper, we use technologies such as Flask, WeChat public platform, knowledge graph, and Q&A pair matching to build graph containing 9 categories with 20 entities more than 200 about 1000 entity attributes in size, using important notification documents issued by colleges schools data sources, realize an end-to-end intelligent system. advantages features real-time talkability, low latency, fault...
We propose a general and systematic strategy to compile arbitrary quantum channels without using ancillary qubits, based on proximal policy optimization -- powerful deep reinforcement learning algorithm. rigorously prove that, in sharp contrast the case of compiling unitary gates, it is impossible an channel precision with any given finite elementary set, regardless length decomposition sequence. However, for fixed accuracy $ε$ one can construct universal set constant number $ε$-dependent...