Rami Barends

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A quantum computer can solve hard problems, such as prime factoring, database searching and quantum simulation, at the cost of needing to protect fragile quantum states from error. Quantum error correction provides this protection by distributing a logical state among many physical quantum bits (qubits) by means of quantum entanglement. Superconductivity is(More)
Quantum computing becomes viable when a quantum state can be protected from environment-induced error. If quantum bits (qubits) are sufficiently reliable, errors are sparse and quantum error correction (QEC) is capable of identifying and correcting them. Adding more qubits improves the preservation of states by guaranteeing that increasingly larger clusters(More)
P. J. J. O’Malley, R. Babbush, I. D. Kivlichan, J. Romero, J. R. McClean, R. Barends, J. Kelly, P. Roushan, A. Tranter, N. Ding, B. Campbell, Y. Chen, Z. Chen, B. Chiaro, A. Dunsworth, A. G. Fowler, E. Jeffrey, E. Lucero, A. Megrant, J. Y. Mutus, M. Neeley, C. Neill, C. Quintana, D. Sank, A. Vainsencher, J. Wenner, T. C. White, P. V. Coveney, P. J. Love, H.(More)
R. Barends,1, ∗ J. Kelly,1, ∗ A. Megrant,1 A. Veitia,2 D. Sank,1 E. Jeffrey,1 T. C. White,1 J. Mutus,1 A. G. Fowler,1, 3 B. Campbell,1 Y. Chen,1 Z. Chen,1 B. Chiaro,1 A. Dunsworth,1 C. Neill,1 P. O’Malley,1 P. Roushan,1 A. Vainsencher,1 J. Wenner,1 A. N. Korotkov,2 A. N. Cleland,1 and John M. Martinis1 Department of Physics, University of California, Santa(More)
Andrey V. Rodionov,1 Andrzej Veitia,1 R. Barends,2 J. Kelly,2 Daniel Sank,2 J. Wenner,2 John M. Martinis,2 Robert L. Kosut,3 and Alexander N. Korotkov1 1Department of Electrical Engineering, University of California, Riverside, California 92521, USA 2Department of Physics, University of California, Santa Barbara, California 93106, USA 3SC Solutions, 1261(More)
A quantum processor (QuP) can be used to exploit quantum mechanics to find the prime factors of composite numbers[1]. Compiled versions of Shor’s algorithm have been demonstrated on ensemble quantum systems[2] and photonic systems[3–5], however this has yet to be shown using solid state quantum bits (qubits). Two advantages of superconducting qubit(More)
one million A. Megrant, C. Neill, R. Barends, B. Chiaro, Yu Chen, L. Feigl, J. Kelly, Erik Lucero, Matteo Mariantoni, P. J. J. O’Malley, D. Sank, A. Vainsencher, J. Wenner, T. C. White, Y. Yin, J. Zhao, C. J. Palmstrøm, John M. Martinis, and A. N. Cleland Department of Physics, University of California, Santa Barbara, California 93106-9530, USA Department(More)
Quantum mechanics can help to solve complex problems in physics and chemistry, provided they can be programmed in a physical device. In adiabatic quantum computing, a system is slowly evolved from the ground state of a simple initial Hamiltonian to a final Hamiltonian that encodes a computational problem. The appeal of this approach lies in the combination(More)
We present a method for optimizing quantum control in experimental systems, using a subset of randomized benchmarking measurements to rapidly infer error. This is demonstrated to improve single- and two-qubit gates, minimize gate bleedthrough, where a gate mechanism can cause errors on subsequent gates, and identify control crosstalk in superconducting(More)
J. Wenner, Yi Yin, Yu Chen, R. Barends, B. Chiaro, E. Jeffrey, J. Kelly, A. Megrant, J. Mutus, C. Neill, P. J. J. O’Malley, P. Roushan, D. Sank, A. Vainsencher, T. C. White, Alexander N. Korotkov, A. N. Cleland, and John M. Martinis Department of Physics, University of California, Santa Barbara, California 93106, USA Department of Physics, Zhejiang(More)