R&D Computer Systems Engineer-Information Security Applications (Early/ Mid Career) | Sandia National Laboratories
R&D Computer Scientist-Web/ Database Applications (Early/ Mid Career) | Sandia National Laboratories
Geekwire: In Hillary Clinton's nomination acceptance speech at the Democratic National Convention, she stated that when it comes to climate change she accepts the scientific consensus. That puts her in direct contrast to Donald Trump, the Republican candidate, who has in the past called global warming a hoax and a money-making industry. Science is rarely mentioned in political campaigns—Trump didn't use the word at all in his own acceptance speech—so Clinton's "I believe in science" line resulted in a lot of plaudits from scientific commentators on social media. Clinton also shared her belief that shifting to clean energy will help bolster the US economy and drive technology and innovation.
Analytic second derivative of the energy for density-functional tight-binding combined with the fragment molecular orbital method
The analytic second derivative of the energy is developed for the fragment molecular orbital (FMO) method combined with density-functional tight-binding (DFTB), enabling simulations of infrared and Raman spectra of large molecular systems. The accuracy of the method is established in comparison to full DFTB without fragmentation for a set of representative systems. The performance of the FMO-DFTB Hessian is discussed for molecular systems containing up to 10 041 atoms. The method is applied to the study of the binding of α-cyclodextrin to polyethylene glycol, and the calculated IR spectrum of an epoxy amine oligomer reproduces experiment reasonably well.
Development of exponentially scaling methods has seen great progress in tackling larger systems than previously thought possible. One such technique, full configuration interaction quantum Monte Carlo, is a useful algorithm that allows exact diagonalization through stochastically sampling determinants. The method derives its utility from the information in the matrix elements of the Hamiltonian, along with a stochastic projected wave function, to find the important parts of Hilbert space. However, the stochastic representation of the wave function is not required to search Hilbert space efficiently, and here we describe a highly efficient deterministic method that can achieve chemical accuracy for a wide range of systems, including the difficult Cr2 molecule. We demonstrate for systems like Cr2 that such calculations can be performed in just a few cpu hours which makes it one of the most efficient and accurate methods that can attain chemical accuracy for strongly correlated systems. In addition our method also allows efficient calculation of excited state energies, which we illustrate with benchmark results for the excited states of C2.