Path integrals for causal diamonds and the covariant entropy principle
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Massively parallel computer architectures create new opportunities for the performance of long-time scale molecular dynamics (MD) simulations. Here, we introduce the path-accelerated molecular dynamics method that takes advantage of distributed computing to reduce the wall-clock time of MD simulation via parallelization with respect to stochastic MD time steps. The marginal distribution for the time evolution of a system is expressed in terms of a path integral, enabling the use of path sampling techniques to numerically integrate MD trajectories. By parallelizing the evaluation of the path action with respect to time and by initializing the path configurations from a nonequilibrium distribution, the algorithm enables significant speedups in terms of the length of MD trajectories that can be integrated in a given amount of wall-clock time. The method is demonstrated for Brownian dynamics, although it is generalizable to other stochastic equations of motion including open systems. We apply the method to two simple systems, a harmonic oscillator and a Lennard-Jones liquid, and we show that in comparison to the conventional Euler integration scheme for Brownian dynamics, the new method can reduce the wall-clock time for integrating trajectories of a given length by more than three orders of magnitude in the former system and more than two in the latter. This new method for parallelizing MD in the dimension of time can be trivially combined with algorithms for parallelizing the MD force evaluation to achieve further speedup.
Spectroscopic chemical detection requires knowledge or determination of an optical path for accurate quantification of path-integrated concentration of species. Continuous- wave-laser-based spectroscopic systems operating in an open integrated-path remote sensing configuration are usually not equipped for optical path determination. Here we demonstrate a measurement technique capable of simultaneous spectroscopic chemical quantification and range finding. Here, the range-finding functionality is implemented with chirped laser dispersion spectroscopy. The methodology is potentially useful for remote chemical sensing in a hard-target LIDAR configuration and for automatic calibration of gas cells with unknown or varying lengths.
In this study, the crack-tip opening angle (CTOA) approach was incorporated into a damage growth finite element program, MADGIC (Micromechanics Analysis and Damage Growth in Composites), and was used to predict stable tearing in a middle-crack tension 2024-T3 aluminum alloy specimen. The MADGIC code is a displacement based finite element program implemented with an incremental elastic-plastic algorithm used to model elastic-plastic behavior and a nodal splitting and nodal force relaxation algorithm used to generate crack surfaces. Predictions of the applied stress as a function of crack extension and applied stress as a function of load-line displacement were in good agreement with experiments and with similar predictions made using an existing finite element program, ZIP2D. In addition, path integrals, namely, the J-integral and T*-integral, were also evaluated and compared with the CTOA approach. There appears to be a weak relationship between the CTOA and the T*-integral evaluated on a specific integration path during crack extension beyond maximum applied stress. This study further verifies that the CTOA can be used as an effective elastic-plastic fracture mechanics parameter to predict crack growth.