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Antonio Corcoles
Researcher at IBM
Publications - 58
Citations - 7657
Antonio Corcoles is an academic researcher from IBM. The author has contributed to research in topics: Qubit & Quantum computer. The author has an hindex of 27, co-authored 56 publications receiving 5850 citations.
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Journal ArticleDOI
Supervised learning with quantum-enhanced feature spaces.
Vojtěch Havlíček,Vojtěch Havlíček,Antonio Corcoles,Kristan Temme,Aram W. Harrow,Abhinav Kandala,Jerry M. Chow,Jay M. Gambetta +7 more
TL;DR: In this article, two quantum algorithms for machine learning on a superconducting processor are proposed and experimentally implemented, using a variational quantum circuit to classify the data in a way similar to the method of conventional SVMs.
Journal ArticleDOI
Error mitigation extends the computational reach of a noisy quantum processor
Abhinav Kandala,Kristan Temme,Antonio Corcoles,Antonio Mezzacapo,Jerry M. Chow,Jay M. Gambetta +5 more
TL;DR: This work applies the error mitigation protocol to mitigate errors in canonical single- and two-qubit experiments and extends its application to the variational optimization of Hamiltonians for quantum chemistry and magnetism.
Journal ArticleDOI
Superconducting qubit in a waveguide cavity with a coherence time approaching 0.1 ms
Chad Rigetti,Jay M. Gambetta,Stefano Poletto,Britton Plourde,Jerry M. Chow,Antonio Corcoles,John A. Smolin,Seth Merkel,J. R. Rozen,George A. Keefe,Mary Beth Rothwell,Mark B. Ketchen,Matthias Steffen +12 more
TL;DR: In this paper, the authors reported a superconducting artificial atom with a coherence time of ${T}_{2}^{*}=92$ $\ensuremath{\mu}$s and energy relaxation time of{T}{1}=70$
Journal ArticleDOI
Demonstration of a quantum error detection code using a square lattice of four superconducting qubits
Antonio Corcoles,Easwar Magesan,Srikanth Srinivasan,Andrew W. Cross,Matthias Steffen,Jay M. Gambetta,Jerry M. Chow +6 more
TL;DR: This work presents a quantum error detection protocol on a two-by-two planar lattice of superconducting qubits that detects an arbitrary quantum error on an encoded two-qubit entangled state via quantum non-demolition parity measurements on another pair of error syndrome qubits.
Journal ArticleDOI
Supervised learning with quantum enhanced feature spaces
Vojtech Havlicek,Antonio Corcoles,Kristan Temme,Aram W. Harrow,Jerry M. Chow,Jay M. Gambetta +5 more
TL;DR: Two classification algorithms that use the quantum state space to produce feature maps are demonstrated on a superconducting processor, enabling the solution of problems when the feature space is large and the kernel functions are computationally expensive to estimate.