Mini-Workshop: A toolkit for Order-N first-principles study of the electronic metal-insulator transition.  

The purpose of the workshop is to:

1. Exchange new research ideas

2. Finish work on current joint publications

3. Provide some training on LSMS, TM-DCA codes usage

4. Develop the materials for the next big proposal

5. To assess what went wrong with the previous proposals.

6. complete a rough draft of an NSF XSEDE ECSS  proposal

Date: 05/25/2019-05/31/2019

Location: CCT-LSU

The big picture:  The successful fruition of a 50-year search for the proper single-particle order parameter together with the development of an order-N first-principles code for the study of strongly disordered electronic systems capable of efficient parallelization on the latest and upcoming generation of exascale machines, has led to new opportunities for fundamental discovery involving the disorder-driven metal-insulator transition.  The purpose of this workshop is to bring these researchers together to form a funded active collaboration exploring the physics of strongly disordered energy materials. Public talks give our students some time to talk about their research..

Who:

Mark Jarrell (Louisiana State University),

Yi Zhang (Louisiana State University),

Ka Ming Tam (Louisiana State University),

Nicholas Walker (Louisiana State University),

Samuel Kellar (Louisiana State University),

Yang Wang (Pittsburgh Supercomputer Center),

Markus Eisenbach (Oak Ridge National Lab),

Hanna Terletska (Middle Tennessee State University),

Liviu Chioncel (University of Augsburg, Germany).

Registration/Cost: The Scientific and Public Lectures are open to all*

Schedule: M-F, 9am-5pm (Dinners, lunches and Pool Party are by Invitation Only)

Sponsors: Louisiana State; DOE grant: DE-SC0017861

Mini-Workshop Timetable (events held in MWFA common area or in room 2008B unless otherwise noted).

Yang Wang

Title: Green function approach to ab initio electronic structure calculations.

Abstract: Green function for Kohn-Sham equation is a powerful tool for the calculation of electron density and electronic density of states. In this presentation, I will discuss the formulation of Green function in the framework of full-potential multiple scattering theory and show its applications in ab initio electronic structure calculations for ordered and disordered systems.

Markus Eisenbach

Title: DOE funding opportunities for first principles multiple scattering and disordered systems

Abstract: In this presentation I will give an overview over the past funding opportunities from DOE/BES to which we either submitted internal whitepapers at ORNL or a preproposal to DOE. I will review the feedback that we have received on these proposals with a focus on making future proposals more competitive. Finally, the recent call for Computational Accelerated Application Readiness (CAAR) for the upcoming Frontier system at ORNL might provide an opportunity for some development support for TMDCA-LSMS.

Open Talks

Hanna Terletska [5/28/19 @ 9:30 AM; room 1008B]

Title: Typical Medium DCA method for disordered systems

Abstract: Disorder is inevitably present in many materials and can dramatically affect their properties. One of the most prominent effects of disorder is electron localization. Having a proper numerical tool to treat  disorder effects is necessary for better understanding and control of the properties of real materials.  In this talk, I will discuss the TMDCA method, which we have developed to study electron localization in disordered systems. I will present details on the method construction and will focus on its applications on a model Hamiltonians level.

Yi Zhang [5/28/19 @ 10:30 AM; room 1008B]

Title: Localization in Energy Materials

Abstract: Anderson localization is not only interesting from a scientific point of view, but also has been proposed to play a critical role in materials that can be used for the harvesting and efficient use of energy. Combining two recently developed methods, the effective disorder Hamiltonian method and the typical medium dynamical cluster approximation, has opened the door to investigate localization in such energy materials with first principles simulations. In this talk, I will present our recent studies of localization in the diluted magnetic semiconductor Ga(Mn,N) and the intermediated-band photovoltaic Ti-doped Si.

Liviu Chioncel [5/30/19 @ 9:30 AM; room 1008B]

(please send short bio to jennifer@cct.lsu.edu or kjones@lsu.edu)

Title: Electronic Structure with Muffin-tins.

Abstract: The Exact Muffin-tin Orbitals (EMTO) theory was developed by O.K. Andersen and collaborators starting from the 90s [1]. This method was implemented by L. Vitos [2] of KTH Stockholm and was the first to allow Dynamical Mean-Field Theory (DMFT) formulation within the multiple scattering approach [3]. With a DMFT solver formulated on the Matsubara energies, this method suffers due to the analytic continuation inserted into the iteration steps [4]. We reformulated the LDA+DMFT scheme for the EMTO basis set without the need of analytic continuation [5]. This was recently extended to include on-site disorder within the Coherent Potential Approximation, in addition to DMFT [6]. Even more recently we have succeeded to implement an ab-initio typical medium theory [7].

[1] O. K. Andersen, T. Saha-Dasgupta PRB 62, R16219 (2000)

[2] L. Vitos et. al. Comput. Matter. Sci. 18, 24 (2000)

[3] L. Chioncel et. al.PRB 67 235106 (2003)

[4] A. Oestlin, L. Chioncel, L. Vitos. PRB 86 235107 (2012)

[5] A. Oestlin, L. Vitos, L. Chioncel PRB 96 125156 (2017)

[6] A. Oestlin, L. Vitos, L. Chioncel PRB 98 235135 (2018)

[7] Augsburg, Louisiana, Stockholm collaboration

Ka Ming Tam [5/29/19 @ 9:30 AM; room 1008B]

Title: Neural network quantum impurity solver.

(please send short bio to jennifer@cct.lsu.edu or kjones@lsu.edu)

Abstract: Machine learning methods have been applied to various problems in physics over the past few years. Most of the studies are focused on interpreting the data generated by conventional numerical methods or existing databases. An interesting question is whether it is possible to use the machine learning approach, in particular the neural network, for solving many body problems. In this talk, we present a solver for interacting quantum problem of small clusters based on the neural network. We demonstrate the neural network based solver provides quantitatively accurate spectral function. This opens the opportunity of utilizing the neural network approach as an impurity solver for the dynamical mean field theory. The high throughput of the neural network approach makes it particularly useful for the study of disorder systems.

Public Lectures

Nicholas Walker  [5/27/19 @ 3:30 PM; room 1008B]

Title: A Primer on Machine Learning

Abstract: The field of machine learning provides interesting new avenues into the investigation of physical systems. In this work, various methods from data science and machine learning are described alongside the motivations for their use. These methods include feature space scaling, feature space reduction, cluster analysis, and neural networks. Application of these methods to the 2-dimensional Ising model will be presented along with a discussion of how the results may have impact on future investigations of more complex physical systems.

Note: Samuel and Nick will take pictures during the workshop. We need that for reporting!

Samuel Kellar [5/30/19 @ 9:30 AM; room 1008B]

(please send talk title, abstract, short bio and picture to jennifer@cct.lsu.edu or kjones@lsu.edu)

Need talk title, abstract

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