Adaptive‐numerical‐bias metadynamics. Issue 31 (26th September 2017)

• Record Type: Journal Article
• Authors: Khanjari, Neda; Eslami, Hossein; Müller‐Plathe, Florian
• Is Part Of: Journal of computational chemistry. Volume 38:Issue 31(2017)
• Page Start: 2721
• Page End: 2729
• Publication Date: 2017-09-26
• Subjects: adaptive biasing potentials -- free energy calculations -- metadynamics -- potential of mean force -- sampling rare events; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.25066
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract : A metadynamics scheme is presented in which the free energy surface is filled with progressively adding adaptive biasing potentials, obtained from the accumulated probability distribution of the collective variables. Instead of adding Gaussians with assigned height and width in conventional metadynamics method, here we add a more realistic adaptive biasing potential to the Hamiltonian of the system. The shape of the adaptive biasing potential is adjusted on the fly by sampling over the visited states. As the top of the barrier is approached, the biasing potentials become wider. This decreases the problem of trapping the system in the niches, introduced by the addition of Gaussians of fixed height in metadynamics. Our results for the free energy profiles of three test systems show that this method is more accurate and converges more quickly than the conventional metadynamics, and is quite comparable (in accuracy and convergence rate) with the well‐tempered metadynamics method. © 2017 Wiley Periodicals, Inc. Abstract : Four pseudorandom number generators were compared with a physical, quantum‐based random number generator using the NIST suite of statistical tests. We then measured the effect of the five random number generators on various calculated properties in different Markov‐chain Monte Carlo simulations. The results show that poor quality pseudorandom number generators produce results that deviate significantly from those obtained with the quantum‐based random number generator. In contrast, the Mersenne‐Twister pseudorandom generator and a 64‐bit Linear Congruential Generator with a scrambler produce results that are statistically indistinguishable from those obtained with the quantum‐based random number generator.