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The Mixed Quantum-Classical Initial Value Representation (MQC-IVR) is arecently introduced approximate semiclassical (SC) method for the calculationof real-time quantum correlation functions. MQC-IVR employs a modified Filinovfiltration (MFF) scheme to control the overall phase of the SC integrand,extending the applicability of SC methods to complex systems while retainingtheir ability to accurately describe quantum coherence effects. Here, weaddress questions regarding the effectiveness of the MFF scheme in combinationwith SC dynamics. Previous work showed that this filtering scheme is of limitedutility in the context of semiclassical wavepacket propagation, but we find theMFF is extraordinarily powerful in the context of correlation functions. Byexamining trajectory phase and amplitude contributions to the real-time SCcorrelation function in a model system, we clearly demonstrate that the MFFserves to reduce noise by damping amplitude only in regions of highlyoscillatory phase leading to a reduction in computational effort whileretaining accuracy. Further, we introduce a novel and efficient MQC-IVRformulation that allows for linear scaling in computational cost with the totalsimulation length, a significant improvement over the more-than quadraticscaling exhibited by the original method.

Validating and Implementing Modified Filinov Phase Filtration in Semiclassical Dynamics