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Found 6 papers, 6 papers with code
Estimating the gradient and higher-order derivatives on quantum hardware
For a large class of variational quantum circuits, we show how arbitrary-order derivatives can be analytically evaluated in terms of simple parameter-shift rules, i. e., by running the same circuit with different shifts of the parameters.
Quantum Physics
Transfer learning in hybrid classical-quantum neural networks
We extend the concept of transfer learning, widely applied in modern machine learning algorithms, to the emerging context of hybrid neural networks composed of classical and quantum elements.
Applications of Near-Term Photonic Quantum Computers: Software and Algorithms
Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing.
Quantum Physics Computational Physics
Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer
We determine the time and memory resources as well as the amount of computational nodes required to produce samples for different numbers of modes and detector clicks.
Quantum Physics
Machine learning method for state preparation and gate synthesis on photonic quantum computers
In the simplest case of a single input state, our method discovers circuits for preparing a desired quantum state.
Quantum Physics
Continuous-variable quantum neural networks
The quantum neural network is a variational quantum circuit built in the continuous-variable (CV) architecture, which encodes quantum information in continuous degrees of freedom such as the amplitudes of the electromagnetic field.
