arXiv subjects

Yujie Zhang

Publications and source records attributed to Yujie Zhang.

95 records · Page 6Linked to original sources

arXiv2019

Channel Activation of CHSH Nonlocality

Quantum channels that break CHSH nonlocality on all input states are known as CHSH-breaking channels. In quantum networks, such channels are useless for distributing correlations that can violate the CHSH Inequality. Motivated by previous work on activation of nonlocality in quantum states, here we demonstrate an analogous activation of CHSH-breaking channels. That is, we show that certain pairs of CHSH-breaking channels are no longer CHSH-breaking when used in combination. We find that this type of activation can emerge in both uni-directional and bi-directional communication scenarios.

quant-ph↗

arXiv2019

Dual-Pump Approach to Photon-Pair Generation: Demonstration of Enhanced Characterization and Engineering Capabilities

We experimentally study the generation of photon pairs via spontaneous four-wave mixing with two distinct laser pulses. We find that the dual-pump technique enables new capabilities: 1) a new characterization methodology to measure noise contributions, source brightness and photon collection efficiencies directly from raw photon-count measurements; 2) an enhanced ability to generate heralded single photons in a pure quantum state; and 3) the ability to derive upper and lower bounds on heralded-photon quantum state purity from measurements of photon-number statistics even in the presence of noise. Such features are highly valuable in photon-pair sources for quantum applications.

quant-ph↗

arXiv2019

Bi2Te3/Sb2Te3 Heterojunction and Thermophotovoltaic Cells Absorbing the Radiation from Room-temperature Surroundings

The thermophotovoltaic cells which can convert the infrared radiation from room-temperature surroundings into electricity are of significance due to their potential applications in many fields. In this work, narrow bandgap Bi2Te3/Sb2Te3 thin film thermophotovoltaic cells were fabricated, and the formation mechanism of Bi2Te3/Sb2Te3 p-n heterojunctions was investigated. During the formation of the heterojunctions at room temperature, both electrons and holes diffuse in the same direction from n-type Bi2Te3 thin films to p-type Sb2Te3 thin films rather than conventional bi-directional diffusion. Because the strong intrinsic excitation generates a large number of intrinsic carriers which weaken the built-in electric field of the heterojunctions, their I-V curves become similar to straight lines. It is also demonstrated that Bi2Te3/Sb2Te3 thermophotovoltaic cells can output electrical power under the infrared radiation from a room-temperature heat source. This work proves that it is possible to convert the infrared radiation from dark and room-temperature surroundings into electricity through narrow bandgap thermophotovoltaic cells.

physics.app-ph↗

arXiv2018

Deep learning based inverse method for layout design

Layout design with complex constraints is a challenging problem to solve due to the non-uniqueness of the solution and the difficulties in incorporating the constraints into the conventional optimization-based methods. In this paper, we propose a design method based on the recently developed machine learning technique, Variational Autoencoder (VAE). We utilize the learning capability of the VAE to learn the constraints and the generative capability of the VAE to generate design candidates that automatically satisfy all the constraints. As such, no constraints need to be imposed during the design stage. In addition, we show that the VAE network is also capable of learning the underlying physics of the design problem, leading to an efficient design tool that does not need any physical simulation once the network is constructed. We demonstrated the performance of the method on two cases: inverse design of surface diffusion induced morphology change and mask design for optical microlithography.

eess.SP↗

arXiv2018

Adaptive tomography of qubits: Purity versus statistical fluctuations

The success of quantum information processing applications relies on accurate and efficient characterization of quantum states, especially nearly-pure states. In this work, we investigate a procedure for adaptive qubit state tomography which achieves $O(1/N)$ scaling in accuracy for large $N$. We analyze the performance of the adaptive protocol on the characterization of pure, mixed and nearly-pure states, and clarify the interplay between the purity of the state and the statistical fluctuations of the measurement results. Our results highlight the subtle difference between the characterization of nearly-pure states and those of pure or highly mixed states.

quant-ph↗