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- University of TorontoCA13 papers
- University of WaterlooCA11 papers
- Massachusetts Institute of TechnologyUS7 papers
- Vector InstituteCA7 papers
- Freie Universität BerlinDE6 papers
- Institute of Photonic SciencesES6 papers
- Perimeter InstituteCA6 papers
- University of CologneDE6 papers
- Barcelona Institute of Science and TechnologyES5 papers
- Universität UlmDE5 papers
- University of PaviaIT5 papers
- University of YorkGB5 papers
16 papers · 2 filters
Applications of Near-Term Photonic Quantum Computers: Software and Algorithms
Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri +7
Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based pr…
Transfer learning in hybrid classical-quantum neural networks
Andrea Mari, Thomas R. Bromley, Josh Izaac +2
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 quantu…
Degenerate Squeezing in Waveguides: A Unified Theoretical Approach
L. G. Helt, N. Quesada
We consider pulsed-pump spontaneous parametric downconversion (SPDC) as well as pulsed single- and dual-pump spontaneous four-wave mixing processes in waveguides within a unified H…
Constructions of k-uniform and absolutely maximally entangled states beyond maximum distance codes
Zahra Raissi, Adam Teixido, Christian Gogolin +1
Pure multipartite quantum states of n parties and local dimension q are called k-uniform if all reductions to k parties are maximally mixed. These states are relevant for our under…
Stochastic gradient descent for hybrid quantum-classical optimization
Ryan Sweke, Frederik Wilde, Johannes Meyer +4
Within the context of hybrid quantum-classical optimization, gradient descent based optimizers typically require the evaluation of expectation values with respect to the outcome of…
Quantum Natural Gradient
James Stokes, Josh Izaac, Nathan Killoran +1
A quantum generalization of Natural Gradient Descent is presented as part of a general-purpose optimization framework for variational quantum circuits. The optimization dynamics is…