4 papers
Quantum sequel of neural network training
Hao Zhang, Alex Kamenev
Training of neural networks (NNs) has emerged as a major consumer of both computational and energy resources. Quantum computers were coined as a root to facilitate training, but no…
Implementation of multiparticle quantum speed limits on observables
Rui-Heng Miao, Zhao-Di Liu, Chen-Xi Ning +4
The energy-time uncertainty relation limits the maximum speed of quantum system evolution and is crucial for determining whether quantum tasks can be accelerated. However, multipar…
Computational complexity of three-dimensional Ising spin glass: Lessons from D-Wave annealer
Hao Zhang, Alex Kamenev
Finding an exact ground state of a three-dimensional (3D) Ising spin glass is proven to be an NP-hard problem (i.e., at least as hard as any problem in the nondeterministic polynom…
Cyclic Quantum Annealing: Searching for Deep Low-Energy States in 5000-Qubit Spin Glass
Hao Zhang, Kelly Boothby, Alex Kamenev
Quantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states…