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pro vyhledávání: '"Denchev, Vasil S."'
Autor:
Kechedzhi, Kostyantyn, Smelyanskiy, Vadim, McClean, Jarrod R., Denchev, Vasil S., Mohseni, Masoud, Isakov, Sergei, Boixo, Sergio, Altshuler, Boris, Neven, Hartmut
We analyze a new computational role of coherent multi-qubit quantum tunneling that gives rise to bands of non-ergodic extended (NEE) quantum states each formed by a superposition of a large number of computational states (deep local minima of the ene
Externí odkaz:
http://arxiv.org/abs/1807.04792
Autor:
Denchev, Vasil S., Boixo, Sergio, Isakov, Sergei V., Ding, Nan, Babbush, Ryan, Smelyanskiy, Vadim, Martinis, John, Neven, Hartmut
Publikováno v:
Phys. Rev. X 6, 031015 (2016)
Quantum annealing (QA) has been proposed as a quantum enhanced optimization heuristic exploiting tunneling. Here, we demonstrate how finite range tunneling can provide considerable computational advantage. For a crafted problem designed to have tall
Externí odkaz:
http://arxiv.org/abs/1512.02206
We propose a totally corrective boosting algorithm with explicit cardinality regularization. The resulting combinatorial optimization problems are not known to be efficiently solvable with existing classical methods, but emerging quantum optimization
Externí odkaz:
http://arxiv.org/abs/1504.01446
Autor:
Boixo, Sergio, Smelyanskiy, Vadim N., Shabani, Alireza, Isakov, Sergei V., Dykman, Mark, Denchev, Vasil S., Amin, Mohammad, Smirnov, Anatoly, Mohseni, Masoud, Neven, Hartmut
Publikováno v:
Nature Communications 7:10327 (2016)
Quantum tunneling, a phenomenon in which a quantum state traverses energy barriers above the energy of the state itself, has been hypothesized as an advantageous physical resource for optimization. Here we show that multiqubit tunneling plays a compu
Externí odkaz:
http://arxiv.org/abs/1502.05754
Autor:
Boixo, Sergio, Smelyanskiy, Vadim N., Shabani, Alireza, Isakov, Sergei V., Dykman, Mark, Denchev, Vasil S., Amin, Mohammad, Smirnov, Anatoly, Mohseni, Masoud, Neven, Hartmut
Quantum tunneling is a phenomenon in which a quantum state traverses energy barriers above the energy of the state itself. Tunneling has been hypothesized as an advantageous physical resource for optimization. Here we present the first experimental e
Externí odkaz:
http://arxiv.org/abs/1411.4036
We propose a non-convex training objective for robust binary classification of data sets in which label noise is present. The design is guided by the intention of solving the resulting problem by adiabatic quantum optimization. Two requirements are i
Externí odkaz:
http://arxiv.org/abs/1205.1148
In a previous publication we proposed discrete global optimization as a method to train a strong binary classifier constructed as a thresholded sum over weak classifiers. Our motivation was to cast the training of a classifier into a format amenable
Externí odkaz:
http://arxiv.org/abs/0912.0779
This paper describes how to make the problem of binary classification amenable to quantum computing. A formulation is employed in which the binary classifier is constructed as a thresholded linear superposition of a set of weak classifiers. The weigh
Externí odkaz:
http://arxiv.org/abs/0811.0416
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