Weiwen Jiang

PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud

2024

Benefiting from cloud computing, today's early-stage quantum computers can be remotely accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it poses a high risk of data leakage in quantum machine learning (QML). To …

Computational Performance Bounds Prediction in Quantum Computing with Unstable Noise

2025 · arXiv (Cornell University)

Quantum computing has significantly advanced in recent years, boasting devices with hundreds of quantum bits (qubits), hinting at its potential quantum advantage over classical computing. Yet, noise in quantum devices poses significant barriers to realizing …