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Quantum Adversarial Machine Learning
Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of machine learning approaches in adversarial settings and developing techniques accordingly to make learning robust to adversarial manipulations.
Quantum Communication between Multiplexed Atomic Quantum Memories
The use of multiplexed atomic quantum memories (MAQM) can significantly enhance the efficiency to establish entanglement in a quantum network.
Quantum Physics
An efficient quantum algorithm for generative machine learning
A central task in the field of quantum computing is to find applications where quantum computer could provide exponential speedup over any classical computer.
Hopf insulators and their topologically protected surface states
Three-dimensional (3D) topological insulators in general need to be protected by certain kinds of symmetries other than the presumed U(1) charge conservation.
