6 papers
The trainability of photonic quantum circuits
Alexander Makarovskiy, Adam Taylor, Zhenghao Li +5
Variational quantum algorithms are a leading approach to near-term quantum computing, but their scalability can be limited by barren plateaus and the sampling cost of resolving sma…
Machine learning of quantum data using optimal similarity measurements
Zhenghao Li, Hao Zhan, Shana H. Winston +11
Quantum machine learning seeks a computational advantage in data processing by evaluating functions of quantum states, such as their similarity, that can be classically intractable…
Continuous-time noise mitigation in analogue quantum simulation
Gabriele Bressanini, Yue Ma, Hyukjoon Kwon +1
Analogue quantum simulators offer a promising route to explore quantum many-body dynamics beyond classical reach in the near term. However, their vulnerability to noise limits the…
Optimal Quantum Information Transmission Under a Continuous-Variable Erasure Channel
Adam Taylor, Michael Hanks, Hyukjoon Kwon +1
Quantum capacity gives the fundamental limit of information transmission through a channel. However, evaluating the quantum capacities of a continuous-variable bosonic quantum chan…
Photonic Hybrid Quantum Computing
Jaehak Lee, Srikrishna Omkar, Yong Siah Teo +4
Photons are a ubiquitous carrier of quantum information: they are fast, suffer minimal decoherence, and do not require huge cryogenic facilities. Nevertheless, their intrinsically…
Experimental demonstration of generalized quantum fluctuation theorems in the presence of coherence
Hui Li, Jie Xie, Hyukjoon Kwon +3
Fluctuation theorems have elevated the second law of thermodynamics to a statistical realm by establishing a connection between time-forward and time-reversal probabilities, provid…