Libo Zhang

High-fidelity, high-scalability two-qubit gate scheme for superconducting qubits

2020 · arXiv (Cornell University)

High-quality two-qubit gate operations are crucial for scalable quantum information processing. Often, the gate fidelity is compromised when the system becomes more integrated. Therefore, a low-error-rate, easy-to-scale two-qubit gate scheme is highly desirable. Here, we …

Suppressing Coherent Two-Qubit Errors via Dynamical Decoupling

2021 · Physical Review Applied

Scalable quantum information processing requires the ability to tune multiqubit interactions. This makes the precise manipulation of quantum states particularly difficult for multiqubit interactions because tunability unavoidably introduces sensitivity to fluctuations in the tuning parameters, …

Lexicographic Ranking Supermartingales with Lazy Lower Bounds

2023 · arXiv (Cornell University)

Lexicographic Ranking SuperMartingale (LexRSM) is a probabilistic extension of Lexicographic Ranking Function (LexRF), which is a widely accepted technique for verifying program termination. In this paper, we are the first to propose sound probabilistic extensions …

Neural network based time-resolved state tomography of superconducting qubits

2023 · arXiv (Cornell University)

Superconducting qubits have emerged as a premier platform for large-scale quantum computation, yet the fidelity of state readout is often hindered by random noise and crosstalk, especially in multi-qubit systems. While neural networks trained on …

Multi-Reward as Condition for Instruction-based Image Editing

2024 · arXiv (Cornell University)

High-quality training triplets (instruction, original image, edited image) are essential for instruction-based image editing. Predominant training datasets (e.g., InsPix2Pix) are created using text-to-image generative models (e.g., Stable Diffusion, DALL-E) which are not trained for image …

A Recommendation Model Based on Deep Neural Network

2018 · IEEE Access

In recent years, recommendation systems have been widely used in various commercial platforms to provide recommendations for users. Collaborative filtering algorithms are one of the main algorithms used in recommendation systems. Such algorithms are simple …