Hamiltonian learning for quantum error correction
暂无分享,去创建一个
Sebastian Huber | Evert van Nieuwenburg | Evert P L van Nieuwenburg | Eliska Greplova | Agnes Valenti | S. Huber | E. Greplova | E. V. van Nieuwenburg | Agnes Valenti
[1] Paolo Zanardi,et al. Fidelity analysis of topological quantum phase transitions , 2008, 0803.2243.
[2] Xiaotong Ni,et al. Neural Network Decoders for Large-Distance 2D Toric Codes , 2018, Quantum.
[3] David Poulin,et al. Subsystem surface codes with three-qubit check operators , 2012, Quantum Inf. Comput..
[4] C. Castelnovo,et al. Quantum topological phase transition at the microscopic level , 2007, 0707.2084.
[5] Ronny Thomale,et al. Method to identify parent Hamiltonians for trial states , 2018, Physical Review B.
[6] Matthias Troyer,et al. Neural-network quantum state tomography , 2018 .
[7] Xiao-Liang Qi,et al. Determining a local Hamiltonian from a single eigenstate , 2017, Quantum.
[8] I. Chuang,et al. Quantum Computation and Quantum Information: Bibliography , 2010 .
[9] Hai-Qing Lin,et al. Scaling dimension of fidelity susceptibility in quantum phase transitions , 2008, 0807.3491.
[10] Nathan Wiebe,et al. Robust online Hamiltonian learning , 2012, TQC.
[11] T. Osborne,et al. Interplay of topological order and spin glassiness in the toric code under random magnetic fields , 2010, 1004.4632.
[12] L. Vinet,et al. A ‘missing’ family of classical orthogonal polynomials , 2010, 1011.1669.
[13] Helmut G. Katzgraber,et al. Error tolerance of topological codes with independent bit-flip and measurement errors , 2016, 1603.08729.
[14] Simon J Devitt,et al. Simulating open quantum systems: from many-body interactions to stabilizer pumping , 2011, 1104.2507.
[15] A. Kitaev. Fault tolerant quantum computation by anyons , 1997, quant-ph/9707021.
[16] Ian R. Petersen,et al. A Quantum Hamiltonian Identification Algorithm: Computational Complexity and Error Analysis , 2016, IEEE Transactions on Automatic Control.
[17] Shi-Jian Gu,et al. Fidelity, dynamic structure factor, and susceptibility in critical phenomena. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[18] J. Preskill,et al. Topological quantum memory , 2001, quant-ph/0110143.
[19] Todd A. Brun,et al. Quantum Computing , 2011, Computer Science, The Hardware, Software and Heart of It.
[20] Kenneth Rudinger,et al. Compressed sensing for Hamiltonian reconstruction , 2014, 1410.3029.
[21] Florian Marquardt,et al. Reinforcement Learning with Neural Networks for Quantum Feedback , 2018, Physical Review X.
[22] Stephen Becker,et al. Quantum state tomography via compressed sensing. , 2009, Physical review letters.
[23] Paola Cappellaro,et al. Hamiltonian identifiability assisted by single-probe measurement , 2016, 1609.09446.
[24] John Preskill,et al. Quantum Computing in the NISQ era and beyond , 2018, Quantum.
[25] E Solano,et al. Many-body interactions with tunable-coupling transmon qubits. , 2014, Physical review letters.
[26] Bryan K. Clark,et al. Computational Inverse Method for Constructing Spaces of Quantum Models from Wave Functions , 2018, Physical Review X.
[27] David Olaya,et al. Superconducting nanocircuits for topologically protected qubits , 2009 .
[28] Harry Buhrman,et al. The European Quantum Technologies Roadmap , 2017, 1712.03773.
[29] J. Rarity,et al. Experimental quantum Hamiltonian learning , 2017, Nature Physics.
[30] D. Cory,et al. Hamiltonian learning and certification using quantum resources. , 2013, Physical review letters.
[31] C. K. Andersen,et al. Quantum parameter estimation with a neural network , 2017, 1711.05238.
[32] David Poulin,et al. Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes. , 2018, Physical review letters.
[33] Eyal Bairey,et al. Learning a Local Hamiltonian from Local Measurements. , 2018, Physical review letters.
[34] M. Mariantoni,et al. Surface codes: Towards practical large-scale quantum computation , 2012, 1208.0928.
[35] Helmut G. Katzgraber,et al. Optimal error correction in topological subsystem codes , 2012, 1204.1838.
[36] N. Maskara,et al. Advantages of versatile neural-network decoding for topological codes , 2018, Physical Review A.
[37] P. Zoller,et al. Dissipative quantum error correction and application to quantum sensing with trapped ions , 2017, Nature Communications.
[38] Giacomo Torlai,et al. Neural Decoder for Topological Codes. , 2016, Physical review letters.
[39] D. Gross,et al. Efficient quantum state tomography. , 2010, Nature communications.
[40] T. Monz,et al. An open-system quantum simulator with trapped ions , 2011, Nature.
[41] N. Wiebe,et al. Tomography and generative training with quantum Boltzmann machines , 2016, 1612.05204.
[42] P L Gould,et al. Observation of a resonant four-body interaction in cold cesium Rydberg atoms. , 2011, Physical review letters.
[43] Marco Picco,et al. Strong disorder fixed points in the two-dimensional random-bond Ising model , 2006 .
[44] Martin Suchara,et al. Efficient Algorithms for Maximum Likelihood Decoding in the Surface Code , 2014, 1405.4883.
[45] N. Read,et al. Random-bond Ising model in two dimensions: The Nishimori line and supersymmetry , 2001 .
[46] N. Paunkovic,et al. Ground state overlap and quantum phase transitions. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[47] Adam C. Whiteside,et al. Towards practical classical processing for the surface code: Timing analysis , 2012, 1202.5602.
[48] University of Toronto,et al. Exchange interaction between three and four coupled quantum dots: Theory and applications to quantum computing , 2004 .
[49] Paolo Zanardi,et al. Quantum critical scaling of the geometric tensors. , 2007, Physical review letters.
[50] V. Negnevitsky,et al. Estimation of a general time-dependent Hamiltonian for a single qubit , 2016, Nature Communications.
[51] A Honecker,et al. Universality class of the Nishimori point in the 2D +/- J random-bond Ising model. , 2001, Physical review letters.
[52] Jens Eisert,et al. Reinforcement learning decoders for fault-tolerant quantum computation , 2018, Mach. Learn. Sci. Technol..
[53] Hilbert J Kappen,et al. Learning quantum models from quantum or classical data , 2018, Journal of Physics A: Mathematical and Theoretical.
[54] Reger,et al. Three-dimensional random-bond Ising model: Phase diagram and critical properties. , 1986, Physical review letters.
[55] Todd A. Brun,et al. Quantum Error Correction , 2019, Oxford Research Encyclopedia of Physics.
[56] Joel Johansson,et al. Quantum error correction for the toric code using deep reinforcement learning , 2018, Quantum.
[57] Xiaotong Ni,et al. Scalable Neural Network Decoders for Higher Dimensional Quantum Codes , 2017, 1710.09489.
[58] Harry Buhrman,et al. The quantum technologies roadmap: a European community view , 2018, New Journal of Physics.
[59] D. Gottesman. Theory of fault-tolerant quantum computation , 1997, quant-ph/9702029.
[60] Jun Zhang,et al. Quantum Hamiltonian identification from measurement time traces. , 2014, Physical review letters.
[61] Daniel Gottesman,et al. Stabilizer Codes and Quantum Error Correction , 1997, quant-ph/9705052.
[62] Franco Nori,et al. Coupling strength estimation for spin chains despite restricted access , 2008, 0810.2866.
[63] NathanWiebe,et al. Quantum bootstrapping via compressed quantum Hamiltonian learning , 2015 .
[64] M S Kim,et al. Hamiltonian tomography in an access-limited setting without state initialization. , 2008, Physical review letters.
[65] Stefan Zohren,et al. Circuit design for multi-body interactions in superconducting quantum annealing systems with applications to a scalable architecture , 2016, 1603.09521.
[66] Archil Avaliani,et al. Quantum Computers , 2004, ArXiv.