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Alexei Gilchrist

Researcher at Macquarie University

Publications -  91
Citations -  6664

Alexei Gilchrist is an academic researcher from Macquarie University. The author has contributed to research in topics: Quantum computer & Quantum information. The author has an hindex of 28, co-authored 87 publications receiving 5895 citations. Previous affiliations of Alexei Gilchrist include University of Queensland & University of Waikato.

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Simplifying quantum logic using higher-dimensional Hilbert spaces

TL;DR: In this article, the authors present a general technique that harnesses multi-level information carriers to reduce the number of gates required to build quantum logic gate sets, enabling the construction of key quantum circuits with existing technology.

Demonstration of an all-optical quantum controlled-NOT gate

TL;DR: An unambiguous experimental demonstration and comprehensive characterization of quantum CNOT operation in an optical system that produces all four entangled Bell states as a function of only the input qubits' logical values, for a single operating condition of the gate.
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Quantum computation with optical coherent states

TL;DR: In this paper, it was shown that quantum computation circuits using coherent states as the logical qubits can be constructed from simple linear networks, conditional photon measurements, and small coherent superposition resource states.
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Distance measures to compare real and ideal quantum processes

TL;DR: In this paper, the authors identify a gold standard for quantum information processing, a single measure of distance that can be used to compare and contrast different experiments, and enumerate a set of criteria that such a distance measure must satisfy to be both experimentally and theoretically meaningful.
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Quantum process tomography of a controlled-NOT gate.

TL;DR: This work demonstrates complete characterization of a two-qubit entangling process--a linear optics controlled-NOT gate operating with coincident detection--by quantum process tomography by using a maximum-likelihood estimation to convert the experimental data into a physical process matrix.