The simulation begins by initializing the entire system's wavefunction, |Ψ(r, 0) , by populating the LUMO of the PT molecule, |Φ PT LUMO , and al- In contrast, the LUMO+2 and LUMO+4 orbitals are localized on the PCBM molecule. As the simulation proceeds, the LUMO+3 continues to be the active state until ∼ 50 fs. At this stage, the active state hops from the LUMO+3 to the LUMO+4, but quickly returns to the LUMO+3. At the avoided crossings of the LUMO+3 and LUMO+4 (∼ 50 or 190 fs), we find that both of these orbitals have a mixed character, as shown at the center of Fig. . Hops between the LUMO+3 and LUMO+4 are also observed until 300 fs. Thereafter, the active state switches to the low-lying LUMOs (which have a strong PCBM character) and retains its acceptor character until the end of the simulation (as shown at the right of Fig. ). The hops between the LUMOs correspond to the nonadiabatic transitions. In Figs. and, we present the adiabatic MO and charge populations calculated for the same nuclear trajectory in Fig. , but averaged over 10,000 FSSH trajectories. Due to the nonadiabatic transitions between the various states, the MO populations change with time. However, due to the stochastic nature of the method, these changes are not smooth if we consider only a single CPA-FSSH nuclear trajectory. For example, as shown in Fig. , at 0 fs, the MO population is entirely on LUMO+3. However, as shown in Fig. , until ∼ 300 fs, an active state can continuously hop between the LUMO+3 (localized on PT) and LUMO+4 orbitals (localized on PCBM) due to the presence of several avoided crossings between these MOs for this nuclear trajectory. Due to these continuous hops, the MO population oscillates, and the same oscillation is also reflected in the charge population (Fig. ). Note that, although the same nuclear trajectory is used in obtaining both Figs. 12 and 14a, a one-to-one comparison cannot be made between them. This situation arises because the results in Fig. are averaged over 10,000 FSSH trajectories, whereas the results in Fig. are presented for a single FSSH trajectory. Since the MO energy fluctuations are same for all the 10,000 FSSH trajectories, understanding the nature of a single FSSH trajectory could be useful in understanding the averaged behavior of ten thousand FSSH trajectories. Finally, it is important to note that one cannot accurately assign the charge transfer time-scales using the oscillating charge populations; to obtain any meaningful results, one needs to run at least a few tens of nuclear trajectories. .