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Communication: Exciton–phonon information flow in the energy transfer process of photosynthetic complexes
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1.
1. R. E. Blankenship, Molecular Mechanisms of Photosynthesis, 1st ed. (Wiley, New York, 2002), p. 336.
2.
2. Y.-C. Cheng and G. R. Fleming, Annu. Rev. Phys. Chem. 60, 241 (2009).
http://dx.doi.org/10.1146/annurev.physchem.040808.090259
3.
3. G. S. Engel, T. R. Calhoun, E. L. Read, T.-K. Ahn, T. Mancal, Y.-C. Cheng, R. E. Blankenship, and G. R. Fleming, Nature (London) 446, 782 (2007).
http://dx.doi.org/10.1038/nature05678
4.
4. H. Lee, Y.-C. Cheng, and G. R. Fleming, Science 316, 1462 (2007).
http://dx.doi.org/10.1126/science.1142188
5.
5. G. Panitchayangkoon, D. Hayes, K. A. Fransted, J. R. Caram, E. Harel, J. Wen, R. E. Blankenship, and G. S. Engel, Proc. Natl. Acad. Sci. U.S.A. 107, 12766 (2010).
http://dx.doi.org/10.1073/pnas.1005484107
6.
6. E. Collini, C. Y. Wong, K. E. Wilk, P. M.G. Curmi, P. Brumer, and G. D. Scholes, Nature (London) 463, 644 (2010).
http://dx.doi.org/10.1038/nature08811
7.
7. S. Jang, Y.-C. Cheng, D. R. Reichman, and J. D. Eaves, J. Chem. Phys. 129, 101104 (2008).
http://dx.doi.org/10.1063/1.2977974
8.
8. J. Roden, A. Eisfeld, W. Wolff, and W. Strunz, Phys. Rev. Lett. 103, 058301 (2009).
http://dx.doi.org/10.1103/PhysRevLett.103.058301
9.
9. J. Wu, F. Liu, Y. Shen, J. Cao, and R. J. Silbey, New J. Phys. 12, 105012 (2010).
http://dx.doi.org/10.1088/1367-2630/12/10/105012
10.
10. J. Piilo, S. Maniscalco, K. Härkönen, and K.-A. Suominen, Phys. Rev. Lett. 100, 180402 (2008).
http://dx.doi.org/10.1103/PhysRevLett.100.180402
11.
11. P. Rebentrost, R. Chakraborty, and A. Aspuru-Guzik, J. Chem. Phys. 131, 184102 (2009).
http://dx.doi.org/10.1063/1.3259838
12.
12. M. Thorwart, J. Eckel, J. Reina, P. Nalbach, and S. Weiss, Chem. Phys. Lett. 478, 234 (2009).
http://dx.doi.org/10.1016/j.cplett.2009.07.053
13.
13. J. Prior, A. Chin, S. Huelga, and M. Plenio, Phys. Rev. Lett. 105, 050404 (2010).
http://dx.doi.org/10.1103/PhysRevLett.105.050404
14.
14. A. Ishizaki and G. R. Fleming, J. Chem. Phys. 130, 234110 (2009).
http://dx.doi.org/10.1063/1.3155214
15.
15. A. Ishizaki and G. R. Fleming, J. Chem. Phys. 130, 234111 (2009).
http://dx.doi.org/10.1063/1.3155372
16.
16. A. Ishizaki and G. R. Fleming, Proc. Natl. Acad. Sci. U.S.A. 106, 17255 (2009).
http://dx.doi.org/10.1073/pnas.0908989106
17.
17. H.-P. Breuer, E.-M. Laine, and J. Piilo, Phys. Rev. Lett. 103, 210401 (2009).
http://dx.doi.org/10.1103/PhysRevLett.103.210401
18.
18. E.-M. Laine, J. Piilo, and H.-P. Breuer, Phys. Rev. A 81, 062115 (2010).
http://dx.doi.org/10.1103/PhysRevA.81.062115
19.
19. M. Wolf, J. Eisert, T. Cubitt, and J. Cirac, Phys. Rev. Lett. 101, 150402 (2008).
http://dx.doi.org/10.1103/PhysRevLett.101.150402
20.
20. A. K. Rajagopal, A. R. Usha Devi, and R. W. Rendell, Phys. Rev. A 82, 042107 (2010).
http://dx.doi.org/10.1103/PhysRevA.82.042107
21.
21. A. Rivas, S. Huelga, and M. Plenio, Phys. Rev. Lett. 105, 050403 (2010).
http://dx.doi.org/10.1103/PhysRevLett.105.050403
22.
22.The trace distance is computed by summing over the absolute values of the eigenvalues of the matrix ρ1(t) − ρ2(t).
23.
23. M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, 1st ed. (Cambridge University Press, Cambridge, 2000).
24.
24. J. Adolphs and T. Renger, Biophys. J. 91, 2778 (2006).
http://dx.doi.org/10.1529/biophysj.105.079483
25.
25. Q. Shi, L. Chen, G. Nan, R.-X. Xu, and Y. Yan, J. Chem. Phys. 130, 084105 (2009).
http://dx.doi.org/10.1063/1.3077918
26.
26. K. H. Hughes, C. D. Christ, and I. Burghardt, J. Chem. Phys. 131, 024109 (2009).
http://dx.doi.org/10.1063/1.3159671
27.
27. J. Zhu, S. Kais, P. Rebentrost, and A. Aspuru-Guzik, J. Phys. Chem. B 115, 1531 (2011).
http://dx.doi.org/10.1021/jp109559p
28.
28. P. Rebentrost, M. Mohseni, and A. Aspuru-Guzik, J. Phys. Chem. B 113, 9942 (2009).
http://dx.doi.org/10.1021/jp901724d
29.
29. J. Yuen-Zhou, M. Mohseni, and A. Aspuru-Guzik, e-print arXiv:cond-mat/1006.4866.
http://aip.metastore.ingenta.com/content/aip/journal/jcp/134/10/10.1063/1.3563617
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Figures

Image of FIG. 1.

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FIG. 1.

(a) Trace distance of the states and as a function of time for a two-site system (dimer) in the hierarchy equation of motion model. The trace distance evolves from maximally distinguishable (=1) for the initial states to indistinguishable (=0) for the thermal equilibrium state. At intermediate times, the trace distance increases, which is due to a reversal of the information flow. Various bath correlation times are shown, 150 fs (blue), 100 fs (red), and 50 fs (yellow). For long correlation times, that is, a bath with more memory, the regions of increasing trace distance are more pronounced. (b) The distance in Eq. (4) illustrates the information content in the non-Markovian degrees of freedom of this model for the same system, initial states, and bath correlation times as in (a). The anticorrelated oscillations of the two figures show the information flow between the system and the NM degrees of freedom.

Image of FIG. 2.

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FIG. 2.

Non-Markovianity as a function of the parameters of a dimer system (a)–(d), and the Fenna–Matthews–Olson complex (e) and (f), in the hierarchy equation of motion approach. For the dimer: (a) coupling J 12, (b) site energy difference , (c) bath dissipation rate (which is related to the bath correlation time by ,), and (d) reorganization energy (log-scale). The solid lines are calculations of Eq. (2) with the initial states being and , while the dots are calculations of NM-itymax, i.e., with optimized initial states. Dashed line segments indicate that a parameter was scanned beyond the validity of the truncation condition. For the FMO complex: (e) bath dissipation rate and (f) reorganization energy. In all figures, except in (c) and (e), we use the different bath correlation times: 50 fs (blue), 100 fs (purple), and 150 fs (red).

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/content/aip/journal/jcp/134/10/10.1063/1.3563617
2011-03-10
2014-04-20

Abstract

Non-Markovian and nonequilibrium phonon effects are believed to be key ingredients in the energy transfer in photosynthetic complexes, especially in complexes which exhibit a regime of intermediate exciton–phonon coupling. In this work, we utilize a recently developed measure for non-Markovianity to elucidate the exciton–phonon dynamics in terms of the information flow between electronic and vibrational degrees of freedom. We study the measure in the hierarchical equation of motion approach which captures strong coupling effects and nonequilibrium molecular reorganization. We propose an additional trace distance measure for the information flow that could be extended to other master equations. We find that for a model dimer system and for the Fenna–Matthews–Olson complex the non-Markovianity is significant under physiological conditions.

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Scitation: Communication: Exciton–phonon information flow in the energy transfer process of photosynthetic complexes
http://aip.metastore.ingenta.com/content/aip/journal/jcp/134/10/10.1063/1.3563617
10.1063/1.3563617
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