@article{FackeldeyRoehmNiknejadetal., author = {Fackeldey, Konstantin and R{\"o}hm, Jonas and Niknejad, Amir and Chewle, Surahit and Weber, Marcus}, title = {Analyzing Raman Spectral Data without Separabiliy Assumption}, series = {Journal of Mathematical Chemistry}, volume = {3}, journal = {Journal of Mathematical Chemistry}, number = {59}, publisher = {Springer}, doi = {10.1007/s10910-020-01201-7}, pages = {575 -- 596}, abstract = {Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the Time-Resolved-Raman-Sprectroscopy the vibration spectra of a chemical sample are recorded sequentially over a time interval, such that conclusions for intermediate products (transients) can be drawn within a chemical process. The observed data-matrix M from a Raman spectroscopy can be regarded as a matrix product of two unknown matrices W and H, where the first is representing the contribution of the spectra and the latter represents the chemical spectra. One approach for obtaining W and H is the non-negative matrix factorization. We propose a novel approach, which does not need the commonly used separability assumption. The performance of this approach is shown on a real world chemical example.}, language = {en} } @article{FackeldeyNiknejadWeber, author = {Fackeldey, Konstantin and Niknejad, Amir and Weber, Marcus}, title = {Finding Metastabilities in Reversible Markov Chains based on Incomplete Sampling: Case of Molecular Simulation}, series = {Special Matrices}, journal = {Special Matrices}, number = {5/1}, doi = {10.1515/spma-2017-0006}, pages = {73 -- 81}, language = {en} } @article{SikorskiNiknejadWeberetal., author = {Sikorski, Alexander and Niknejad, Amir and Weber, Marcus and Donati, Luca}, title = {Tensor-SqRA: Modeling the transition rates of interacting molecular systems in terms of potential energies}, series = {Journal of Chemical Physics}, volume = {160}, journal = {Journal of Chemical Physics}, doi = {10.1063/5.0187792}, pages = {104112}, abstract = {Estimating the rate of rare conformational changes in molecular systems is one of the goals of molecular dynamics simulations. In the past few decades, a lot of progress has been done in data-based approaches toward this problem. In contrast, model-based methods, such as the Square Root Approximation (SqRA), directly derive these quantities from the potential energy functions. In this article, we demonstrate how the SqRA formalism naturally blends with the tensor structure obtained by coupling multiple systems, resulting in the tensor-based Square Root Approximation (tSqRA). It enables efficient treatment of high-dimensional systems using the SqRA and provides an algebraic expression of the impact of coupling energies between molecular subsystems. Based on the tSqRA, we also develop the projected rate estimation, a hybrid data-model-based algorithm that efficiently estimates the slowest rates for coupled systems. In addition, we investigate the possibility of integrating low-rank approximations within this framework to maximize the potential of the tSqRA.}, language = {en} }