Extracting Coupling-Mode Spectral Densities with Two-Dimensional Electronic Spectroscopy
Source abstract
Abstract
Methods for reconstructing the spectral density of a vibrational environment from experimental data can yield key insights into the impact of the environment on molecular function. Although such experimental methods exist, they generally only access vibrational modes that couple diagonally to the electronic system. Here we present a method for extracting the spectral density of modes that couple to the transition between electronic states, using two-dimensional electronic spectroscopy. To demonstrate this, we use a process-tensor method that can simulate two-dimensional electronic spectroscopy measurements in a numerically exact way. To explain how the extraction works, we also derive an approximate analytical solution, which illustrates that the non-Markovianity of the environment plays an essential role in the existence of the simulated signal.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Spectroscopy and Quantum Chemical Studies · Molecular spectroscopy and chirality · Photoreceptor and optogenetics research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
SUPA, School of Physics and Astronomy
University of St Andrews
Sorbonne Université, CNRS, Institut des NanoSciences de Paris, 4 place Jussieu, 75005 Paris, France
Funding
Engineering and Physical Sciences Research Council · Agence Nationale de la Recherche
References (57)
Show source-provided references
1. Mukamel S. · 1999
2. 10.1038/nphys251510.1038/nphys2515 ↗
3. 10.1038/s41467-022-30565-410.1038/s41467-022-30565-4 ↗
4. 10.1073/pnas.230998712010.1073/pnas.2309987120 ↗
5. 10.1038/s41467-019-09039-710.1038/s41467-019-09039-7 ↗
6. 10.1021/jp106713q10.1021/jp106713q ↗
7. 10.1038/s41467-020-19800-y10.1038/s41467-020-19800-y ↗
8. 10.1038/s41557-022-01026-810.1038/s41557-022-01026-8 ↗
9. 10.1038/s41557-021-00841-910.1038/s41557-021-00841-9 ↗
10. 10.1021/acs.jpclett.4c0067710.1021/acs.jpclett.4c00677 ↗
11. 10.1021/acs.jpclett.4c0238610.1021/acs.jpclett.4c02386 ↗
12. Breuer H. P. · 200710.1093/acprof:oso/9780199213900.001.0001 ↗
13. 10.1063/1.490051210.1063/1.4900512 ↗
14. 10.1016/j.jlumin.2007.02.05310.1016/j.jlumin.2007.02.053 ↗
15. 10.1021/jp075170d10.1021/jp075170d ↗
16. 10.1021/jp900836p10.1021/jp900836p ↗
17. 10.1002/aelm.20200025510.1002/aelm.202000255 ↗
18. 10.1021/cr078377b10.1021/cr078377b ↗
19. 10.1021/acs.jpcc.1c0269310.1021/acs.jpcc.1c02693 ↗
20. 10.1038/s43586-023-00267-210.1038/s43586-023-00267-2 ↗
21. 10.1103/PhysRevA.90.02211010.1103/PhysRevA.90.022110 ↗
22. 10.1103/RevModPhys.89.01500110.1103/RevModPhys.89.015001 ↗
23. 10.1063/5.001159910.1063/5.0011599 ↗
24. 10.1103/PhysRevA.101.05210810.1103/PhysRevA.101.052108 ↗
25. 10.1063/5.010792510.1063/5.0107925 ↗
26. 10.1063/5.014188210.1063/5.0141882 ↗
27. 10.1103/PhysRevB.108.11531210.1103/PhysRevB.108.115312 ↗
28. 10.1016/j.aop.2014.06.01310.1016/j.aop.2014.06.013 ↗
29. 10.1103/PhysRevB.107.12510310.1103/PhysRevB.107.125103 ↗
30. 10.1103/PhysRevLett.123.09040210.1103/PhysRevLett.123.090402 ↗
31. 10.1103/PhysRevLett.123.10050210.1103/PhysRevLett.123.100502 ↗
32. 10.1103/PhysRevA.97.01212710.1103/PhysRevA.97.012127 ↗
33. 10.1103/PhysRevLett.123.24060210.1103/PhysRevLett.123.240602 ↗
34. 10.1088/1367-2630/aa874410.1088/1367-2630/aa8744 ↗
35. 10.1038/s41467-018-05617-310.1038/s41467-018-05617-3 ↗
36. 10.1103/PhysRevLett.126.20040110.1103/PhysRevLett.126.200401 ↗
37. 10.1038/s41567-022-01544-910.1038/s41567-022-01544-9 ↗
38. 10.1103/PhysRevLett.132.20040310.1103/PhysRevLett.132.200403 ↗
39. 10.1103/PhysRevX.14.01101010.1103/PhysRevX.14.011010 ↗
40. 10.1063/5.022536710.1063/5.0225367 ↗
41. 10.1021/acs.jpca.2c0778110.1021/acs.jpca.2c07781 ↗
42. 10.1063/5.006295010.1063/5.0062950 ↗
43. 10.1039/b926051j10.1039/b926051j ↗
44. The TEMPO collaboration, OQuPy: A Python package to efficiently simulate non-Markovian open quantum systems with process tensors. 2024.
45. 10.1103/PhysRevResearch.7.01320910.1103/PhysRevResearch.7.013209 ↗
46. 10.22331/q-2022-10-25-84710.22331/q-2022-10-25-847 ↗
47. 10.1103/PhysRevResearch.5.03307810.1103/PhysRevResearch.5.033078 ↗
48. 10.1007/BF0133676810.1007/BF01336768 ↗
49. 10.1038/nchem.237110.1038/nchem.2371 ↗
50. 10.1021/acs.jpclett.4c0037210.1021/acs.jpclett.4c00372 ↗
51. 10.1021/ja306547810.1021/ja3065478 ↗
52. 10.1038/nchem.130310.1038/nchem.1303 ↗
53. 10.1039/C9SC02329A10.1039/C9SC02329A ↗
54. 10.1063/1.164479410.1063/1.1644794 ↗
55. 10.1103/PhysRevLett.123.04040110.1103/PhysRevLett.123.040401 ↗
56. Fux, G. E. Process tensor networks for non-Markovian open quantum systems. PhD thesis, University of St Andrews, St Andrews, 2022; 10.17630/sta/259.10.17630/sta/259 ↗
57. 10.1038/s41598-021-99718-710.1038/s41598-021-99718-7 ↗