We have contributed a book chapter reviewing different methods to model linear and nonlinear spectroscopies in molecular systems
Ultrafast spectroscopies are amongst the most favoured experimental tools to monitor excited state reactivity. Their fast sequence of laser pulses are able to grasp subtle changes in the registered signals which serve to "observe" molecular (nuclear) motion in real time.[1]
This chapter reviews some of our work over the last few years in developing and applying theoretical spectroscopic schemes to model the signals registered in ultrafast optical experiments, focussing on pump-probe and 2D electronic spectroscopies.[2] This follows previous work done when working with Marco Garavelli at Bologna (Italy) and Lyon (France), in collaboration with Shaul Mukamel at California-Irvine (US).[3]
We cover recent work done in bridging the gap between the registered signals experimentally, i.e. polarisabilities, by introducing theoretical approximations made to produce expressions that represent those very same observables, thus providing simulated signals on an even footing with experiment. The text is meant to ease in those getting started in the field, and goes through basic concepts of nonlinear spectroscopy in the Liouville space by focussing on how the different equations map to the magnitudes one may obtain in standard electronic structure theory software.[2] Different levels of complexity are shown, and are discussed within the context of the underlying working equations and the different magnitudes required. The Nuclear Ensemble Approach (NEA) by Crespo-Otero and Barbatti is also introduced for comparison,[4] and the recent machine learning extension of Cerdán and Roca-Sanjuán[5] is applied to the simulation of photoelectron spectra for the first time.
We show how, depending on the type of signal sought, rather crude approximations (such as those based on "static" profiles assuming excited state minima structures as the sole responsible for fingerprints[6]) may suffice for grasping the main spectral features of a given system. Complex patterns like those arising due to vibrational/vibronic effects,as well as those due to temperature dependence, do require more sophisticated and costly approaches which however are shown to agree remarkably well with the experiment.[7]
We hope this will help those interested in simulating spectra by connecting it to those magnitudes widely computed in theoretical chemistry and coming from electronic structure theory. The chapter contributes to the book "Theoretical and Computational Photochemistry: Fundamentals, Methods, Applications and Synergy with Experimental Approaches" edited by Marco Marazzi and Cristina García-Iriepa (Universidad de Alcalá de Henares, Spain) for Elsevier.
References
[1] M. Miauri, M. Garavelli and G. Cerullo, "Ultrafast Spectroscopy: State of the Art and Open Challenges", J. Am. Chem. Soc. 2020, 142, 3-15.
[2] J. Cuéllar-Zuquin, A. Giussani and J. Segarra-Martí, "Nonlinear spectroscopies", in Theoretical and Computational Chemistry, M. Marazzi and C. García-Iriepa eds., Elsevier, pages 417-445 (2023).
[3] J. Segarra-Martí, A. Nenov, S. Mukamel, M. Garavelli and I. Rivalta, "Towards accurate simulations of two- dimensional electronic spectra", Top. Curr. Chem. 2018, 376, 24. [4] R. Crespo-Otero and M. Barbatti, "Spectrum simulation and decomposition with nuclear ensemble: formal derivation and application to benzene, furan and 2-phenylfuran", Theor. Chem. Acc. 2012, 131, 1237.
[5] L. Cerdán and D. Roca-Sanjuán, "Reconstruction of Nuclear Ensemble Approach Electronic Spectra Using Probabilistic Machine Learning", J. Chem. Theory Comput. 2022, 18, 3052-3064.
[6] A. J. Pepino, J. Segarra-Martí, A. Nenov, R. Improta and M. Garavelli, "Resolving Ultrafast Photoinduced Deactivations in Water-Solvated Pyrimidine Nucleosides", J. Phys. Chem. Lett. 2017, 8, 1777-1783.
[7] A. Nenov, R. Borrego-Varillas, A. Oriana, L. Ganzer, F. Segatta, I. Conti, J. Segarra-Martí, J. Omachi, M. Dapor, S. Taioli, C. Manzoni, S. Mukamel, G. Cerullo and M. Garavelli, J. Phys. Chem. Lett. 2018, 9, 1534-1541.