Navid Ghadermarzy

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We investigate whether quantum annealers with select chip layouts can outperform classical computers in reinforcement learning tasks. We associate a transverse field Ising spin Hamiltonian with a layout of qubits similar to that of a deep Boltzmann machine (DBM) and use simulated quantum annealing (SQA) to numerically simulate quantum sampling from this(More)
In this paper we address the recovery conditions of weighted`p minimization for signal reconstruction from compressed sensing measurements when partial support information is available. We show that weighted`p minimization with H < p < I is stable and robust under weaker sufficient conditions compared to weighted`1 minimization. Moreover, the sufficient(More)
Anna Levit,1 Daniel Crawford,1 Navid Ghadermarzy,1, 2 Jaspreet S. Oberoi,1, 3 Ehsan Zahedinejad,1 and Pooya Ronagh1, 2, ̊ 1QBit, 458-550 Burrard Street, Vancouver (BC), Canada V6C 2B5 Department of Mathematics, The University of British Columbia, 121-1984 Mathematics Road, Vancouver (BC), Canada V6T 1Z2 School of Engineering Science, Simon Fraser(More)
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