13 research outputs found
Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package
This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design
Cellular neural networks with memristive cell devices
In this paper, we present simulation measurements of a memristor crossbar device. We designed a PCB memristor package and the appropriate measurement board. Technical details of these circuits are presented. Cellular like topology of this crossbar device can provide high density and local connectivity. We gave a formula to evaluate the direction of the change of the states of the memristor array in case of a given voltage input. Our simulation results show that a memristor crossbar can be a trainable weight-matrix of a fully connected neural network if the memristors have ohmic non-linearity