Condensed Matter Theory Group Meetings: Summer 18/19
This term’s meetings will take place at 11am on Thursdays. Please volunteer a talk or make known any masters students who are willing to give talks.
Sometimes we run Dice Seminars, which occur over the course of 5 weeks or so, and consist of us collaboratively learning about a given topic, by reading a paper or paper section, and rolling a dice to determine who will talk about what they’ve read. The previous topic was “Topological Insulators”, and ran for an extended period. The topic before that was “Weyl Semimetals”.
There are ~weekly condensed matter seminars at 3pm on Fridays, which will be interesting for anyone attending our group meetings. These are advertised internally.
If you would like to be added to the mailing list for these meetings, please subscribe or contact Ryan or Marcin (addresses at page footer).
(To Be Rolled)
|Dice seminar – machine learning weeks 9-11||C36|
|Adhesion of graphene to hexagonal boron nitride and gold||C36|
|Defect Formation Energies in Graphene||C36|
|Entanglement transition from variable-strength weak measurements||C36|
|Ryan Hunt &|
|Tim Jansen||An atom in Jellium||C36|
|Dr. Nakano||QMC and the “TurboRVB” code|
Talks for next term: Alessandro Romito, Gabriel Bean, Marcin Szyniszewski
Dr. Nakano – QMC and the “TurboRVB” code
First-principles quantum Monte Carlo (QMC) techniques, such as variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC), are among the state-of-the-art numerical methods used to obtain highly accurate many-body wave functions. These methods are especially useful when tackling challenging cases such as low-dimensional materials because QMC is no longer dependent on any semi-empirical exchange-correlation functions. We have been intensively improving a QMC code “TurboRVB,” which has been mainly developed by Prof. Sandro Sorella (SISSA). I am going to talk about two recent improvements in the QMC algorithm.
The first topic is about all-electron calculations. Although it is convenient to replace core electrons in QMC calculations as in DFT, such replacement sometimes induces nontrivial biases. All-electron calculations in QMC are not as widely used as in DFT because the computational cost scales with Z^5.5−6.5, where Z is the atomic number. We have recently developed new algorithms to drastically decrease computational costs of all-electron DFT (valid only for QMC), and all-electron lattice regularized diffusion monte Carlo (LRDMC)[4,5]. I will present basic ideas of the new algorithms and show several applications such as a binding energy calculation of the sodium dimer.
The second topic is about a workflow system for QMC optimizations. We are currently developing a python wrapper for TurboRVB, which is called Genius-TurboRVB (g-turbo), in order to “automatize” the complicated optimization procedure of a many-body wave function. The wrapper also makes it much easier to prepare input files, to analyze output files, and to perform advanced calculations. I will present fundamental features and several applications of the wrapper, for example, a phonon dispersion calculation of a solid.
 S. Sorella, et al. Phys. Rev. Lett. 121, 066402 (2018).
 S. Sorella, https://people.sissa.it/~sorella/web/, accessed 4 August (2019).
 K. Nakano, et al. J. Chem. Theory Comput. 15, 4044-4055 (2019).
 M. Casula, et al. Phys. Rev. Lett. 95, 100201 (2005).
 K. Nakano, et al. to be submitted to Phys. Rev. Lett.
 K. Nakano, et al. in preparation.