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Abstract
We present a new quasi-direct quantum molecular dynamics computational method which offer a compromise between quantum dynamics using a pre-computed potential energy surface (PES) and fully direct quantum dynamics. This method is termed the time-dependent adaptive density-guided approach (TD-ADGA) and is a method for constructing a PES on the fly during a dynamics simulation. This is achieved by acquisition of new single point (SP) calculations and refitting of the PES depending on the need of the dynamics. The TD-ADGA is a further development of the adaptive density-guided approach (ADGA) for PES construction where the placement of SPs is guided by the density of the nuclear wave function. In TD-ADGA, the ADGA framework has been integrated into the time-propagation of the time-dependent nuclear wave function and we use the reduced one-mode density of this wave function to guide when and where new SPs are placed. The PES is thus extended or updated if the wave function moves into new areas or if a certain area becomes more important. We here derive equations for the reduced one-mode density for the time-dependent Hartree (TDH) method and for multi configuration time-dependent Hartree (MCTDH) methods, but the TD-ADGA can be used with any time-dependent wave function method as long as a density is available. The TD-ADGA method has been investigated on molecular systems containing single- and double-minimum potentials and on single- and multi-mode systems. We explore different approaches to handle the fact that the TD-ADGA involves a PES that changes during the computation and show how results can be obtained that are in very good agreement with results obtained by using an accurate reference PES. Dynamics with TD-ADGA is essentially a black box procedure, where only the initialization of the system and how to compute SPs must be provided. The TD-ADGA thus makes it easier to carry out quantum molecular dynamics and the quasi-direct framework opens up the possibility to compute quantum dynamics accurately for larger molecular systems.
Supplementary materials
Title
Additional computational details and results
Description
Table S1: Nuclear wave function basis set details.
Table S2: Fitting coefficient for each of the bromine PES fits.
Figure S1: Fitted PES and required single points for the A state PES obtained by the TI-ADGA and TD-ADGA methods.
Figure S2: Difference plots for the autocorrelation function and its Fourier transform for the bromine dimer.
Figure S3: Expectation value of the displacement coordinate for the bromine dimer.
Figure S4: Animation of selected TD-ADGA iterations in the ammonia simulation.
Figure S5: Expectation value of the displacement coordinate in the ammonia inversion mode using the TD-ADGA with the full restart scheme.
Figure S6: Absolute value of the autocorrelation function for for water in the TD-ADGA rerun.
Figure S7: Flux over the transition state for salicylaldimine in the TD-ADGA rerun calculation.
Figure S8: Absolute value of the autocorrelation function and its Fourier transform for salicylaldimine in the TD-ADGA rerun calculation.
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Title
salicylaldimine_6d.mmol
Description
Transition state structure and corresponding normal coordinates in Midas molecule format
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