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Practical pulse engineering: Gradient ascent without matrix exponentiation |
Gaurav Bhole, Jonathan A. Jones( ) |
Centre for Quantum Computation, Clarendon Laboratory, University of Oxford, Parks Road, OX1 3PU, UK |
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Abstract Since 2005, there has been a huge growth in the use of engineered control pulses to perform desired quantum operations in systems such as nuclear magnetic resonance quantum information processors. These approaches, which build on the original gradient ascent pulse engineering algorithm, remain computationally intensive because of the need to calculate matrix exponentials for each time step in the control pulse. In this study, we discuss how the propagators for each time step can be approximated using the Trotter–Suzuki formula, and a further speedup achieved by avoiding unnecessary operations. The resulting procedure can provide substantial speed gain with negligible costs in the propagator error, providing a more practical approach to pulse engineering.
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Keywords
quantum information
coherent control
pulse sequences in nuclear magnetic resonance
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Corresponding Author(s):
Jonathan A. Jones
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Issue Date: 25 May 2018
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1 |
C. H. Bennett and D. P. DiVincenzo, Quantum information and computation, Nature 404(6775), 247 (2000)
https://doi.org/10.1038/35005001
|
2 |
M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, Cambridge: Cambridge University Press, 2000
|
3 |
C. A. Ryan, C. Negrevergne, M. Laforest, E. Knill, and R. Laflamme, Liquid-state nuclear magnetic resonance as a testbed for developing quantum control methods, Phys. Rev. A 78(1), 012328 (2008)
https://doi.org/10.1103/PhysRevA.78.012328
|
4 |
D. Lu, K. Li, J. Li, H. Katiyar, A. J. Park, G. Feng, T. Xin, H. Li, G. Long, A. Brodutch, J. Baugh, B. Zeng, and R. Laflamme, Enhancing quantum control by bootstrapping a quantum processor of 12 qubits, npj Quantum Information 3, 45 (2017)
|
5 |
R. R. Ernst, G. Bodenhausen, and A. Wokaun, Principles of Nuclear Magnetic Resonance in One and Two Dimensions, Oxford: Oxford University Press, 1987
|
6 |
N. Khaneja, T. Reiss, C. Kehlet, T. Schulte-Herbrüggen, and S. J. Glaser, Optimal control of coupled spin dynamics: Design of NMR pulse sequences by gradient ascent algorithms, J. Magn. Reson. 172(2), 296 (2005)
https://doi.org/10.1016/j.jmr.2004.11.004
|
7 |
P. de Fouquieres, S. G. Schirmer, S. J. Glaser, and I. Kuprov, Second order gradient ascent pulse engineering, J. Magn. Reson. 212(2), 412 (2011)
https://doi.org/10.1016/j.jmr.2011.07.023
|
8 |
D. L. Goodwin and I. Kuprov, Modified Newton–Raphson GRAPE methods for optimal control of spin systems, J. Chem. Phys. 144(20), 204107 (2016)
https://doi.org/10.1063/1.4949534
|
9 |
D. G. Lucarelli, Quantum optimal control via gradient ascent in function space and the time-bandwidth quantum speed limit, arXiv: 1611.00188 (2016)
|
10 |
C. Moler and C. Van Loan, Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later, SIAM Rev. 45(1), 3 (2003)
https://doi.org/10.1137/S00361445024180
|
11 |
N. J. Higham, The scaling and squaring method for the matrix exponential revisited, SIAM J. Matrix Anal. Appl. 26(4), 1179 (2005)
https://doi.org/10.1137/04061101X
|
12 |
A. H. Al-Mohy and N. J. Higham, A new scaling and squaring algorithm for the matrix exponential, SIAM J. Matrix Anal. Appl. 31(3), 970 (2010)
https://doi.org/10.1137/09074721X
|
13 |
I. I. Maximov, Z. Tošner, and N. C. Nielsen, Optimal control design of NMR and dynamic nuclear polarization experiments using monotonically convergent algorithms, J. Chem. Phys. 128, 184505 (2008)
https://doi.org/10.1063/1.2903458
|
14 |
S. C. Hou, L. C. Wang, and X. X. Yi, Realization of quantum gates by Lyapunov control, Phys. Lett. A 378(9), 699 (2014)
https://doi.org/10.1016/j.physleta.2014.01.008
|
15 |
T. Caneva, T. Calarco, and S. Montangero, Chopped random-basis quantum optimization, Phys. Rev. A 84(2), 022326 (2011)
https://doi.org/10.1103/PhysRevA.84.022326
|
16 |
G. Bhole, V. S. Anjusha, and T. S. Mahesh, Steering quantum dynamics via bang-bang control: Implementing optimal fixed-point quantum search algorithm, Phys. Rev. A 93(4), 042339 (2016)
https://doi.org/10.1103/PhysRevA.93.042339
|
17 |
G. Bhole and T. S. Mahesh, Rapid exponentiation using discrete operators: Applications in optimizing quantum controls and simulating quantum dynamics, arXiv: 1707.02162 (2017)
|
18 |
M. Suzuki, Quantum statistical Monte Carlo methods and applications to spin systems, J. Stat. Phys. 43(5–6), 883 (1986)
https://doi.org/10.1007/BF02628318
|
19 |
K. Waldherr, T. Huckle, T. Auckenthaler, U. Sander, and T. Schulte-Herbrüggen, High Performance Computing in Science and Engineering, Springer, 2010, Ch. Fast 3D Block Parallelisation for the Matrix Multiplication Prefix Problem, pp 39–50
|
20 |
D. G. Cory, M. D. Price, W. Maas, E. Knill, R. Laflamme, W. H.Zurek, T. F. Havel, and S. S. Somaroo, Experimental quantum error correction, Phys. Rev. Lett. 81(10), 2152 (1998)
https://doi.org/10.1103/PhysRevLett.81.2152
|
21 |
S. Boutin, C. K. Andersen, J. Venkatraman, A. J. Ferris, and A. Blais, Resonator reset in circuit QED by optimal control for large open quantum systems, Phys. Rev. A 96(4), 042315 (2017)
https://doi.org/10.1103/PhysRevA.96.042315
|
22 |
T. Xin, S. Huang, S. Lu, K. Li, Z. Luo, Z. Yin, J. Li, D. Lu, G. Long, and B. Zeng, NMRCloudQ: A quantum cloud experience on a nuclear magnetic resonance quantum computer, Sci. Bull. 63(1), 17 (2018)
https://doi.org/10.1016/j.scib.2017.12.022
|
23 |
Y. Zhang, C. A. Ryan, R. Laflamme, and J. Baugh, Coherent control of two nuclear spins using the anisotropic hyperfine interaction, Phys. Rev. Lett. 107(17), 170503 (2011)
https://doi.org/10.1103/PhysRevLett.107.170503
|
24 |
F. Dolde, V. Bergholm, Y. Wang, I. Jakobi, B. Naydenov, S. Pezzagna, J. Meijer, F. Jelezko, P. Neumann, T. Schulte-Herbrüggen, J. Biamonte, and J. Wrachtrup, High-fidelity spin entanglement using optimal control, Nat. Commun. 5, 3371 (2014)
https://doi.org/10.1038/ncomms4371
|
25 |
V. Nebendahl, H. Häffner, and C. F. Roos, Optimal control of entangling operations for trapped-ion quantum computing, Phys. Rev. A 79(1), 012312 (2009)
https://doi.org/10.1103/PhysRevA.79.012312
|
26 |
R. Fisher, F. Helmer, S. J. Glaser, F. Marquardt, and T. Schulte-Herbrüggen, Optimal control of circuit quantum electrodynamics in one and two dimensions, Phys. Rev. B 81(8), 085328 (2010)
https://doi.org/10.1103/PhysRevB.81.085328
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