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Understanding the spectrum of noise acting on a qubit can yield valuable information about its environment, and crucially underpins the optimization of dynamical decoupling protocols that can mitigate such noise.
1902
Earlier work this paper cites.
1903
Earlier work this paper cites.
1904
Earlier work this paper cites.
1908
Earlier work this paper cites.
E. Hahn, Spin Echoes, Phys. Rev. 80
1950
Earlier work this paper cites.
H. Y. Carr and E. M. Purcell, Effects of diffusion on free precession in nuclear magnetic resonance experiments, Phys. Rev. 94
1954
Earlier work this paper cites.
S. Meiboom and D. Gill, Modified spin-echo method for measuring nuclear relaxation times, Rev. Sci. 29
1958
Earlier work this paper cites.
J. R. Klauder and P. W. Anderson, Spectral Diffusion Decay in Spin Resonance Experiments, Phys. Rev. 125
1962
Earlier work this paper cites.
K. Fukushima, Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position, Biological Cybernetics 36
1980
Earlier work this paper cites.
B. A. Pearlmutter, Learning state space trajectories in recurrent neural networks, IJCNN Int Jt Conf Neural Network , 365 (1989)
1989
Earlier work this paper cites.
K. Hornik, Some new results on neural network approximation, Neural Networks 6
1993
Earlier work this paper cites.
D. Kraft, Algorithm 733: TOMP–Fortran Modules for Optimal Control Calculations, ACM Trans. Math. Softw. 20
1994
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Comput. 9
1997
Earlier work this paper cites.
L. Viola and S. Lloyd, Dynamical suppression of decoherence in two-state quantum systems, Phys. Rev. A 58
1998
Earlier work this paper cites.
2001
Earlier work this paper cites.
2003
Earlier work this paper cites.
2003
Earlier work this paper cites.
K. Khodjasteh and D. A. Lidar, Fault-tolerant quantum dynamical decoupling, Phys. Rev. Lett. 95
2005
Earlier work this paper cites.
G. S. Uhrig, Keeping a Quantum Bit Alive by Optimized π \pi -Pulse Sequences, Phys. Rev. Lett. 98
2006
Cited alongside, same era.
G. B. Huang, L. Chen, and C.-k. Siew, Universal Approximation Using Incremental Constructive Feedforward Networks With Random Hidden Nodes, IEEE Trans. Neural. Netw. Learn. Syst. 17
2006
Cited alongside, same era.
2008
Cited alongside, same era.
2009
Cited alongside, same era.
G. A. Álvarez and D. Suter, Measuring the spectrum of colored noise by dynamical decoupling, Phys. Rev. Lett. 107
2011
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin, Attention is all you need, in Advances in Neural Information Processing Systems 30 , edited by I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Curran Associates, Inc., 2017) pp. 5998–6008
2017
Later among the works it cites.
2018
Later among the works it cites.
S. G. Worswick, J. A. Spencer, G. Jeschke, and I. Kuprov, Deep neural network processing of DEER data, Sci. Adv. 4
2018
Later among the works it cites.
S. Hernández-Gómez, F. Poggiali, P. Cappellaro, and N. Fabbri, Noise spectroscopy of a quantum-classical environment with a diamond qubit, Phys. Rev. B 98
2018
Later among the works it cites.
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Cited alongside, same era.
2011
Cited alongside, same era.
J. Bylander, S. Gustavsson, F. Yan, F. Yoshihara, K. Harrabi, G. Fitch, D. G. Cory, Y. Nakamura, J. S. Tsai, and W. D. Oliver, Noise spectroscopy through dynamical decoupling with a superconducting flux qubit, Nat. Phys. 7
2011
Cited alongside, same era.
2012
Cited alongside, same era.
J. Medford, Ł. Cywiński, C. Barthel, C. M. Marcus, M. P. Hanson, and A. C. Gossard, Scaling of dynamical decoupling for spin qubits, Phys. Rev. Lett. 108
2012
Cited alongside, same era.
2015
Cited alongside, same era.
C. Olah, Understanding LSTM Networks (2015)
2015
Cited alongside, same era.
F. Chollet and Others, Keras (2015)
2015
Cited alongside, same era.
J. Yoneda, K. Takeda, T. Otsuka, T. Nakajima, M. R. Delbecq, G. Allison, T. Honda, T. Kodera, S. Oda, Y. Hoshi, N. Usami, K. M. Itoh, and S. Tarucha, A quantum-dot spin qubit with coherence limited by charge noise and fidelity higher than 99.9%, Nat. Nanotechnol. 13
2018
Later among the works it cites.
J. Chen, G. Q. Zeng, W. Zhou, W. Du, and K. D. Lu, Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization, Energy Convers. Manag. 165
2018
Later among the works it cites.
2018
Later among the works it cites.
L. Z. He, M. C. Zhang, C. W. Wu, Y. Xie, W. Wu, and P. X. Chen, Effects of imperfect pulses on dynamical decoupling using quantum trajectory method, Chinese Physics B 27
2018
Later among the works it cites.
N. Borodinov, S. Neumayer, S. V. Kalinin, O. S. Ovchinnikova, R. K. Vasudevan, and S. Jesse, Deep neural networks for understanding noisy data applied to physical property extraction in scanning probe microscopy, npj Comput. Mater. 5
2019
Later among the works it cites.
C. Zhang and X. Wang, Spin-qubit noise spectroscopy from randomized benchmarking by supervised learning, Phys. Rev. A 99
2019
Later among the works it cites.
A. T. Taguchi, E. D. Evans, S. A. Dikanov, and R. G. Griffin, Convolutional Neural Network Analysis of Two-Dimensional Hyperfine Sublevel Correlation Electron Paramagnetic Resonance Spectra, J. Phys. Chem. L. 10
2019
Later among the works it cites.
R.-B. Wu, H. Ding, D. Dong, and X. Wang, Learning robust and high-precision quantum controls, Phys. Rev. A 99
2019
Later among the works it cites.
C. T. C. Arsene, R. Hankins, and H. Yin, Deep learning models for denoising ecg signals, in 2019 27th European Signal Processing Conference (EUSIPCO) (2019) pp. 1–5
2019
Later among the works it cites.
2019
Later among the works it cites.
Y. Romach, A. Lazariev, I. Avrahami, F. Kleißler, S. Arroyo-Camejo, and N. Bar-Gill, Measuring Environmental Quantum Noise Exhibiting a Nonmonotonic Spectral Shape, Physical Review Applied 11
2019
Later among the works it cites.
L. Biewald, Experiment Tracking with Weights and Biases , Tech. Rep. (2020)
2020
Closest in time.
P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. Jarrod Millman, N. Mayorov, A. R. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, b. Polat, Y. Feng, E. W. Moore, J. Vand erPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, and S. . . Contributors, SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, Nat. Methods 17
2020
Closest in time.