Towards provably efficient quantum algorithms for large-scale machine-learning models

no code implementations • 6 Mar 2023 • Junyu Liu, Minzhao Liu, Jin-Peng Liu, Ziyu Ye, Yunfei Wang, Yuri Alexeev, Jens Eisert, Liang Jiang

Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process.

Estimating the randomness of quantum circuit ensembles up to 50 qubits

no code implementations • 19 May 2022 • Minzhao Liu, Junyu Liu, Yuri Alexeev, Liang Jiang

Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information.

Quantum Machine Learning Tensor Networks