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Nathan Killoran
Researcher at University of Ulm
Publications - 64
Citations - 5558
Nathan Killoran is an academic researcher from University of Ulm. The author has contributed to research in topics: Quantum computer & Quantum. The author has an hindex of 26, co-authored 53 publications receiving 3241 citations. Previous affiliations of Nathan Killoran include University of Waterloo & University of Toronto.
Papers
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Journal ArticleDOI
Quantum Machine Learning in Feature Hilbert Spaces
Maria Schuld,Nathan Killoran +1 more
TL;DR: This Letter interprets the process of encoding inputs in a quantum state as a nonlinear feature map that maps data to quantum Hilbert space and shows how it opens up a new avenue for the design of quantum machine learning algorithms.
Journal ArticleDOI
Evaluating analytic gradients on quantum hardware
TL;DR: This paper shows how gradients of expectation values of quantum measurements can be estimated using the same, or almost the same the architecture that executes the original circuit, and proposes recipes for the computation of gradients for continuous-variable circuits.
Posted Content
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm,Josh Izaac,Maria Schuld,Christian Gogolin,M. Sohaib Alam,Shahnawaz Ahmed,Juan Miguel Arrazola,Carsten Blank,Alain Delgado,Soran Jahangiri,Keri A. McKiernan,Johannes Jakob Meyer,Zeyue Niu,Antal Száva,Nathan Killoran +14 more
TL;DR: 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, and it extends the automatic differentiation algorithms common in optimization and machine learning to include quantum and hybrid computations.
Journal ArticleDOI
Quantum generative adversarial networks
TL;DR: This work extends adversarial training to the quantum domain and shows how to construct generative adversarial networks using quantum circuits, as well as showing how to compute gradients -- a key element in generatives adversarial network training -- using another quantum circuit.
Journal ArticleDOI
Quantum circuits with many photons on a programmable nanophotonic chip.
Juan Miguel Arrazola,Ville Bergholm,Kamil Bradler,Thomas R. Bromley,Matthew J. Collins,Ish Dhand,A. Fumagalli,Thomas Gerrits,A. Goussev,Lukas G. Helt,J. Hundal,Theodor Isacsson,Robert B. Israel,Josh Izaac,Soran Jahangiri,Rafal Janik,Nathan Killoran,Shreya P. Kumar,Jonathan Lavoie,Adriana E. Lita,Dylan H. Mahler,M. Menotti,Blair Morrison,Sae Woo Nam,Leonhard Neuhaus,Haoyu Qi,Nicolás Quesada,A. Repingon,Krishna Kumar Sabapathy,Maria Schuld,Daiqin Su,Jeremy Swinarton,Antal Száva,K. Tan,P. Tan,V. D. Vaidya,Z. Vernon,Zeid Zabaneh,Yanbao Zhang +38 more
TL;DR: In this article, a full-stack hardware-software system for executing many-photon quantum circuit operations using integrated nanophotonics is presented, comprising a programmable nanophotonic chip operating at room temperature, interfaced with a fully automated control system.