Engineering topics

Chan, Garnet

Publications and source records attributed to Chan, Garnet.

5 records

DOE OSTI2026

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗

DOE OSTI2024

Tensor network influence functionals in the continuous-time limit: Connections to quantum embedding, bath discretization, and higher-order time propagation

Not provided.

Materials Science↗

DOE OSTI2020

Theoretical prediction of magnetic exchange coupling constants from broken-symmetry coupled cluster calculations

Exchange coupling constants ( J ) are fundamental to the understanding of spin spectra of magnetic systems. In this study, we investigate the broken-symmetry (BS) approaches of Noodleman and Yamaguchi in conjunction with coupled cluster (CC) methods to obtain exchange couplings. J values calculated from CC in this fashion converge smoothly toward the full configuration interaction result with increasing level of CC excitation. We compare this BS-CC scheme to the complementary equation-of-motion CC approach on a selection of bridged molecular cases and give results from a few other methodologies for context.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Final Technical Report for Predictive Computing for Condensed Matter

This grant supported research into the development of computational methods to predict the properties of materials to high precision. The overarching purpose of such tools is to aid materials discovery by computation, without the need for costly materials synthesis or experimental measurements. A wide variety of computational tools were developed during this grant. Using these tools, we demonstrated that we could achieve the stated goal of computational modeling with predictive accuracy in several prototypical materials: a molecular crystal of benzene, a solid composed entirely of hydrogen, and a model solid intended to mimic the high temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Final technical report: SciDAC partnership "Predictive Computing for Condensed Matter"

Fundamental progress in energy technology depends critically on our ability to design, fabricate, characterize, and optimize advanced materials that can convert, transport, and store energies as well as display useful functions at minimum energy consumptions. To achieve this, we must first understand mechanisms underlying the functions and then be able to design materials with predicted properties. Unlike conventional structural materials, optoelectronic or magnetic materials for energy technology operate by quantum mechanical principles, which are hard to extract from experiments alone. Some representative unsolved problems of condensed-phase electronic structures in general include (1) the detailed mechanism of high-temperature superconductors such as cuprates and iron-arsenide materials; (2) the structures of solids in the presence of polymorphism; (3) excited states in solids and systematically accurate calculations of quasiparticle energy bands; (4) the structure of strongly correlated wave functions of solids. In this project, we aim at establishing general and predictive mathematical theories for solids and computational methods that implement them. We will then apply these methods to outstanding solid-state problems recognized by experimentalists including the above, with a view to solving them computationally. Hence, the project has the following three research objectives, all of which have been met: Predictive Electronic Structure Theories for Solids, Scalable Algorithms and Software, and Applications to Outstanding Condensed Matter Problems.

74 ATOMIC AND MOLECULAR PHYSICS↗