Quantum Embedding Methods: Methods
FOCUS · A58 · ID: 2155736
Presentations
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Dynamical Downfolding and Construction of Effective Hamiltonians for Correlated Systems
ORAL
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Presenters
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Annabelle L Canestraight
- University of California, Santa Barbara
Authors
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Annabelle L Canestraight
- University of California, Santa Barbara
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Vojtech Vlcek
- University of California, Santa Barbara
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Determinantal quantum Monte Carlo solver for cluster perturbation theory
ORAL
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Publication: E. W. Huang, S. Ding, J. Liu, Y. Wang, Phys. Rev. Research 4, L042015 (2022)
Presenters
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Edwin W Huang
- University of Notre Dame
Authors
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Edwin W Huang
- University of Notre Dame
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Shuhan Ding
- Massachusetts Institute of Technology
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Jiarui Liu
- Clemson University
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Yao Wang
- Emory University
- Department of Chemistry, Emory University, Atlanta, GA, 30322, USA
- Clemson University
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Low-energy effective model for H<sub>4</sub> square molecule derived from ab initio calculations
ORAL
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Presenters
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Sonali Joshi
- University of Illinois at Urbana-Champaign
Authors
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Sonali Joshi
- University of Illinois at Urbana-Champaign
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Lucas K Wagner
- University of Illinois at Urbana-Champaign
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Equilibrium Quantum Impurity Problems via Matrix Product State Encoding of the Retarded Action
ORAL
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Publication: https://arxiv.org/abs/2306.17216
Presenters
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Benedikt Kloss
- Flatiron Institute, Simons Foundation
Authors
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Benedikt Kloss
- Flatiron Institute, Simons Foundation
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Julian Thoenniss
- University of Geneva
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Michael Sonner
- Univ of Geneva
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Alessio Lerose
- Univ of Geneva
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Matthew Fishman
- Simons Foundation
- Flatiron Institute, Simons Foundation
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Miles Stoudenmire
- Flatiron Institute
- Flatiron Institute, Simons Foundation
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Olivier P Parcollet
- Flatiron Institute, Simons Foundation
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Antoine Georges
- College de France
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Dmitry A Abanin
- University of Geneva
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A route to systematically improveable effective Hamiltonians in condensed matter
ORAL · Invited
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Presenters
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Lucas K Wagner
- University of Illinois at Urbana-Champaign
Authors
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Lucas K Wagner
- University of Illinois at Urbana-Champaign
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Derivation of the Ghost Gutzwiller Approximation from Quantum Embedding principles: the Ghost Density Matrix Embedding Theory
ORAL
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Publication: Nicola Lanatà, "Derivation of the Ghost Gutzwiller Approximation from Quantum Embedding principles: the Ghost Density Matrix Embedding Theory", arXiv:2305.11895 (2023).
Presenters
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Nicola Lanata
- Rochester Institute of Technology
Authors
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Nicola Lanata
- Rochester Institute of Technology
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Capturing Long-Range Electron Correlation in Ab Initio Green's Function Embedding
ORAL
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Presenters
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Jiachen Li
- Yale University
Authors
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Jiachen Li
- Yale University
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Tianyu Zhu
- Yale University
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Ab-initio downfolding to interacting model Hamiltonians: comprehensive analysis and benchmarking
ORAL
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Presenters
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Malte Roesner
- Institute for Molecules and Materials, Radboud University, 6525 AJ Nijmegen, the Netherlands
- Radboud University
Authors
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Yueqing Chang
- Rutgers, The State University of New Jersey
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Erik van Loon
- Lund Univ/Lund Inst of Tech
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Kyle Eskridge
- Simons Foundation
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Miguel A Morales
- Simons Foundation
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Cyrus E Dreyer
- Stony Brook University (SUNY)
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Andrew Millis
- Columbia University
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Shiwei Zhang
- Simons Foundation
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Tim Wehling
- University of Hamburg
- University Hamburg
- Institute of Theoretical Physics, University of Hamburg, 22607 Hamburg, Germany
- Universität Hamburg
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Lucas K Wagner
- University of Illinois at Urbana-Champaign
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Malte Roesner
- Institute for Molecules and Materials, Radboud University, 6525 AJ Nijmegen, the Netherlands
- Radboud University
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Inchworm quasi Monte Carlo for quantum impurities
ORAL
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Publication: Planned submission to Phys. Rev. Lett. during the fall 2023.
Presenters
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Hugo U Strand
- Örebro University
- School of Science and Technology, Örebro University
Authors
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Hugo U Strand
- Örebro University
- School of Science and Technology, Örebro University
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Joseph Kleinheinz
- University of California
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Igor S Krivenko
- Universität Hamburg
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Low-scaling algorithms for many-body electronic structure and downfolding for quantum embedding
ORAL
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Publication: 1. Chia-Nan Yeh, and Miguel Morales, Low-Scaling Algorithm for the Random Phase Approximation Using Tensor Hypercontraction with k-point Sampling, J. Chem. Theory Comput. 2023, 19, 18, 6197–6207
2. Chia-Nan Yeh, and Miguel Morales, Low-Scaling algorithm for GW approximation and constrained random phase approximation using symmetry-adapted tensor hypercontraction with k-point sampling, in preparationPresenters
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Chia-Nan Yeh
- Center for Computational Quantum Physics, Flatiron Institute
Authors
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Chia-Nan Yeh
- Center for Computational Quantum Physics, Flatiron Institute
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Miguel A Morales
- Simons Foundation
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