G
Graeme Smith
Researcher at University of Colorado Boulder
Publications - 254
Citations - 7138
Graeme Smith is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Radar & Bistatic radar. The author has an hindex of 41, co-authored 246 publications receiving 5762 citations. Previous affiliations of Graeme Smith include University of Toronto & Ohio State University.
Papers
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Journal ArticleDOI
Large-Area Mapping at 850 Microns. II. Analysis of the Clump Distribution in the ρ Ophiuchi Molecular Cloud
Doug Johnstone,Christine D. Wilson,Gerald Moriarty-Schieven,Gilles Joncas,Graeme Smith,E. M. Gregersen,Michel Fich +6 more
TL;DR: In this paper, a survey of the central 700 arcmin2 region of the ρ Ophiuchi molecular cloud at 850 μm using the Submillimeter Common-User Bolometer Array (SCUBA) on the James Clerk Maxwell Telescope is presented.
Journal ArticleDOI
Quantum communication with zero-capacity channels.
Graeme Smith,Jon Yard +1 more
TL;DR: It is shown theoretically that two quantum channels, each with a transmission capacity of zero, can have a nonzero capacity when used together, implying that the quantum capacity does not completely specify a channel's ability to transmit quantum information.
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Unitary-projective entanglement dynamics
TL;DR: In this article, a toy model of Bell pair dynamics was constructed and it was shown that measurements can keep a system in a state of low, i.e., area-law, entanglement, in contrast with the volume-law entenglement produced by generic pure unitary time evolution.
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Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances
TL;DR: The results presented show the first through-the-wall (TTW) detections of moving personnel using passive WiFi radar, and it is shown that a new interference suppression technique based on the CLEAN algorithm can improve the SIR by approximately 19 dB.
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Efficient method for computing the maximum-likelihood quantum state from measurements with additive Gaussian noise.
TL;DR: An efficient method for computing the maximum-likelihood mixed quantum state (with density matrix ρ) given a set of measurement outcomes in a complete orthonormal operator basis subject to Gaussian noise is provided.