Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: Wavelets as basis functions to represent the coarse-graining potential in multiscale coarse graining approach
Autor/-in: Maiolo, Massimo
Vancheri, A.
Krause, R.
Danani, A.
DOI: 10.1016/j.jcp.2015.07.039
Erschienen in: Journal of Computational Physics
Band(Heft): 300
Seite(n): 592
Seiten bis: 604
Erscheinungsdatum: 2015
Verlag / Hrsg. Institution: Elsevier
ISSN: 0021-9991
Sprache: Englisch
Fachgebiet (DDC): 510: Mathematik
530: Physik
Zusammenfassung: In this paper, we apply Multiresolution Analysis (MRA) to develop sparse but accurate representations for the Multiscale Coarse-Graining (MSCG) approximation to the many-body potential of mean force. We rigorously framed the MSCG method into MRA so that all the instruments of this theory become available together with a multitude of new basis functions, namely the wavelets. The coarse-grained (CG) force field is hierarchically decomposed at different resolution levels enabling to choose the most appropriate wavelet family for each physical interaction without requiring an a priori knowledge of the details localization. The representation of the CG potential in this new efficient orthonormal basis leads to a compression of the signal information in few large expansion coefficients. The multiresolution property of the wavelet transform allows to isolate and remove the noise from the CG force-field reconstruction by thresholding the basis function coefficients from each frequency band independently. We discuss the implementation of our wavelet-based MSCG approach and demonstrate its accuracy using two different condensed-phase systems, i.e. liquid water and methanol. Simulations of liquid argon have also been performed using a one-to-one mapping between atomistic and CG sites. The latter model allows to verify the accuracy of the method and to test different choices of wavelet families. Furthermore, the results of the computer simulations show that the efficiency and sparsity of the representation of the CG force field can be traced back to the mathematical properties of the chosen family of wavelets. This result is in agreement with what is known from the theory of multiresolution analysis of signals.
URI: https://digitalcollection.zhaw.ch/handle/11475/12898
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: Life Sciences und Facility Management
Organisationseinheit: Institut für Computational Life Sciences (ICLS)
Enthalten in den Sammlungen:Publikationen Life Sciences und Facility Management

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Maiolo, M., Vancheri, A., Krause, R., & Danani, A. (2015). Wavelets as basis functions to represent the coarse-graining potential in multiscale coarse graining approach. Journal of Computational Physics, 300, 592–604. https://doi.org/10.1016/j.jcp.2015.07.039
Maiolo, M. et al. (2015) ‘Wavelets as basis functions to represent the coarse-graining potential in multiscale coarse graining approach’, Journal of Computational Physics, 300, pp. 592–604. Available at: https://doi.org/10.1016/j.jcp.2015.07.039.
M. Maiolo, A. Vancheri, R. Krause, and A. Danani, “Wavelets as basis functions to represent the coarse-graining potential in multiscale coarse graining approach,” Journal of Computational Physics, vol. 300, pp. 592–604, 2015, doi: 10.1016/j.jcp.2015.07.039.
MAIOLO, Massimo, A. VANCHERI, R. KRAUSE und A. DANANI, 2015. Wavelets as basis functions to represent the coarse-graining potential in multiscale coarse graining approach. Journal of Computational Physics. 2015. Bd. 300, S. 592–604. DOI 10.1016/j.jcp.2015.07.039
Maiolo, Massimo, A. Vancheri, R. Krause, and A. Danani. 2015. “Wavelets as Basis Functions to Represent the Coarse-Graining Potential in Multiscale Coarse Graining Approach.” Journal of Computational Physics 300: 592–604. https://doi.org/10.1016/j.jcp.2015.07.039.
Maiolo, Massimo, et al. “Wavelets as Basis Functions to Represent the Coarse-Graining Potential in Multiscale Coarse Graining Approach.” Journal of Computational Physics, vol. 300, 2015, pp. 592–604, https://doi.org/10.1016/j.jcp.2015.07.039.


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