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1 code implementation • 14 Aug 2020 • Andrea Mari, Thomas R. Bromley, Nathan Killoran

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

no code implementations • 10 Jan 2020 • Seth Lloyd, Maria Schuld, Aroosa Ijaz, Josh Izaac, Nathan Killoran

Quantum classifiers are trainable quantum circuits used as machine learning models.

Quantum Physics

4 code implementations • 17 Dec 2019 • Andrea Mari, Thomas R. Bromley, Josh Izaac, Maria Schuld, Nathan Killoran

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.

1 code implementation • 16 Dec 2019 • Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri, Josh Izaac, Nicolás Quesada, Alain Delgado Gran, Maria Schuld, Jeremy Swinarton, Zeid Zabaneh, Nathan Killoran

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing.

Quantum Physics Computational Physics

1 code implementation • 4 Sep 2019 • James Stokes, Josh Izaac, Nathan Killoran, Giuseppe Carleo

A quantum generalization of Natural Gradient Descent is presented as part of a general-purpose optimization framework for variational quantum circuits.

no code implementations • 1 Feb 2019 • Guillaume Verdon, Juan Miguel Arrazola, Kamil Brádler, Nathan Killoran

We introduce a quantum approximate optimization algorithm (QAOA) for continuous optimization.

Quantum Physics

no code implementations • 27 Nov 2018 • Maria Schuld, Ville Bergholm, Christian Gogolin, Josh Izaac, Nathan Killoran

An important application for near-term quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning.

Quantum Physics

26 code implementations • 12 Nov 2018 • Ville Bergholm, Josh Izaac, Maria Schuld, Christian Gogolin, Shahnawaz Ahmed, Vishnu Ajith, M. Sohaib Alam, Guillermo Alonso-Linaje, B. AkashNarayanan, Ali Asadi, Juan Miguel Arrazola, Utkarsh Azad, Sam Banning, Carsten Blank, Thomas R Bromley, Benjamin A. Cordier, Jack Ceroni, Alain Delgado, Olivia Di Matteo, Amintor Dusko, Tanya Garg, Diego Guala, Anthony Hayes, Ryan Hill, Aroosa Ijaz, Theodor Isacsson, David Ittah, Soran Jahangiri, Prateek Jain, Edward Jiang, Ankit Khandelwal, Korbinian Kottmann, Robert A. Lang, Christina Lee, Thomas Loke, Angus Lowe, Keri McKiernan, Johannes Jakob Meyer, J. A. Montañez-Barrera, Romain Moyard, Zeyue Niu, Lee James O'Riordan, Steven Oud, Ashish Panigrahi, Chae-Yeun Park, Daniel Polatajko, Nicolás Quesada, Chase Roberts, Nahum Sá, Isidor Schoch, Borun Shi, Shuli Shu, Sukin Sim, Arshpreet Singh, Ingrid Strandberg, Jay Soni, Antal Száva, Slimane Thabet, Rodrigo A. Vargas-Hernández, Trevor Vincent, Nicola Vitucci, Maurice Weber, David Wierichs, Roeland Wiersema, Moritz Willmann, Vincent Wong, Shaoming Zhang, Nathan Killoran

PennyLane's core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation.

3 code implementations • 27 Jul 2018 • Juan Miguel Arrazola, Thomas R. Bromley, Josh Izaac, Casey R. Myers, Kamil Brádler, Nathan Killoran

In the simplest case of a single input state, our method discovers circuits for preparing a desired quantum state.

Quantum Physics

8 code implementations • 18 Jun 2018 • Nathan Killoran, Thomas R. Bromley, Juan Miguel Arrazola, Maria Schuld, Nicolás Quesada, Seth Lloyd

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.

no code implementations • 23 Apr 2018 • Pierre-Luc Dallaire-Demers, Nathan Killoran

Quantum machine learning is expected to be one of the first potential general-purpose applications of near-term quantum devices.

8 code implementations • 9 Apr 2018 • Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, Christian Weedbrook

We introduce Strawberry Fields, an open-source quantum programming architecture for light-based quantum computers.

Quantum Physics Computational Physics

no code implementations • 19 Mar 2018 • Maria Schuld, Nathan Killoran

We interpret the process of encoding inputs in a quantum state as a nonlinear feature map that maps data to quantum Hilbert space.

Quantum Physics

2 code implementations • 17 Dec 2017 • Nathan Killoran, Leo J. Lee, Andrew Delong, David Duvenaud, Brendan J. Frey

We propose generative neural network methods to generate DNA sequences and tune them to have desired properties.

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