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1. h-CMD: An efficient hybrid fast centroid and quasi-centroid molecular dynamics method for the simulation of vibrational spectra

   https://doi.org/10.1063/5.0248115  

   Limbu, Dil_K; London, Nathan; Faruque, Md_Omar; Momeni, Mohammad_R (January 2025, The Journal of Chemical Physics)

   Developing efficient path integral (PI) methods for atomistic simulations of vibrational spectra in heterogeneous condensed phases and interfaces has long been a challenging task. Here, we present the h-CMD method, short for hybrid centroid molecular dynamics, which combines the recently introduced fast quasi-CMD (f-QCMD) method with fast CMD (f-CMD). In this scheme, molecules that are believed to suffer more seriously from the curvature problem of CMD, e.g., water, are treated with f-QCMD, while the rest, e.g., solid surfaces, are treated with f-CMD. To test the accuracy of the newly introduced scheme, the infrared spectra of the interfacial D2O confined in the archetypal ZIF-90 framework are simulated using h-CMD compared to a variety of other PI methods, including thermostatted ring-polymer molecular dynamics (T-RPMD) and partially adiabatic CMD as well as f-CMD and experiment as reference. Comparisons are also made with classical MD, where nuclear quantum effects are neglected entirely. Our detailed comparisons at different temperatures of 250–600 K show that h-CMD produces O–D stretches that are in close agreement with the experiment, correcting the known curvature problem and redshifting of the stretch peaks of CMD. h-CMD also corrects the known issues associated with too artificially dampened and broadened spectra of T-RPMD, which leads to missing the characteristic doublet feature of the interfacial confined water, rendering it unsuitable for these systems. The new h-CMD method broadens the applicability of f-QCMD to heterogeneous condensed phases and interfaces, where defining curvilinear coordinates for the entire system is not feasible. 

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2. Ring-polymer, centroid, and mean-field approximations to multi-time Matsubara dynamics

   https://doi.org/10.1063/5.0021843  

   Jung, Kenneth A.; Videla, Pablo E.; Batista, Victor S. (September 2020, The Journal of Chemical Physics)
3. Efficient Centroid-Linkage Clustering

   Bateni, MH; Dhulipala, L; Fletcher, W; Gowda, K; Hershkowitz, DE; Jayaram, R; Lacki, J (December 2024, NeurIPS 2024)

   We give an algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a $$c$$-approximate clustering in roughly $$n^{1+O(1/c^2)}$$ time. We obtain our result by combining a new Centroid-Linkage HAC algorithm with a novel fully dynamic data structure for nearest neighbor search which works under adaptive updates. We also evaluate our algorithm empirically. By leveraging a state-of-the-art nearest-neighbor search library, we obtain a fast and accurate Centroid-Linkage HAC algorithm. Compared to an existing state-of-the-art exact baseline, our implementation maintains the clustering quality while delivering up to a $$36\times$$ speedup due to performing fewer distance comparisons. 

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4. Efficient centroid-linkage clustering

   Bateni, Mohammad; Dhulipala, Laxman; Fletcher, Willem; Gowda, Kishen; Hershkowitz, D Ellis; Jayaram, Rajesh; Łącki, Jakub (June 2025, Proceedings of the 38th International Conference on Neural Information Processing Systems)
5. Symmetric Molecular Dynamics

   https://doi.org/10.1021/acs.jctc.2c00401  

   Cox, Sam; White, Andrew D. (June 2022, Journal of Chemical Theory and Computation)