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By combining classical Monte Carlo and Bethe ansatz techniques we devise a numerical method to construct the Truncated Generalized Gibbs Ensemble (TGGE) for the spin-1/2 isotropic Heisenberg ($XXX$) chain. The key idea is to sample the…

Strongly Correlated Electrons · Physics 2015-07-28 Vincenzo Alba

Identifying variational wave functions that efficiently parametrize the physically relevant states in the exponentially large Hilbert space is one of the key tasks towards solving the quantum many-body problem. Powerful tools in this…

Quantum Physics · Physics 2019-04-19 Lorenzo Pastori , Raphael Kaubruegger , Jan Carl Budich

We present a theory of ghost-free massive gravity where the mass of the graviton is generated through the Brout-Englert-Higgs (BEH) mechanism and one of the four scalar fields used is that of mimetic gravity. The mass term is not of the…

High Energy Physics - Theory · Physics 2018-06-26 Ali H. Chamseddine , Viatcheslav Mukhanov

We introduce a novel approach to improve unsupervised hashing. Specifically, we propose a very efficient embedding method: Gaussian Mixture Model embedding (Gemb). The proposed method, using Gaussian Mixture Model, embeds feature vector…

Computer Vision and Pattern Recognition · Computer Science 2017-07-05 Tuan Hoang , Thanh-Toan Do , Dang-Khoa Le Tan , Ngai-Man Cheung

We investigate fundamental properties of meta-generalized-gradient approximations (meta-GGAs) to the exchange-correlation energy functional, which have an implicit density dependence via the Kohn-Sham kinetic-energy density. To this…

Chemical Physics · Physics 2014-12-10 F. G. Eich , Maria Hellgren

Successful modern generalized gradient approximations (GGA) are biased toward atomic energies. Restoration of the first-principles gradient expansion for the exchange energy over a wide range of density gradients eliminates this bias. We…

We explicitly build a generalized local-density approximation (GLDA) correlation functional based on one-dimensional (1D) uniform electron gases (UEGs). The fundamental parameters of the GLDA \textemdash a generalization of the widely-known…

Chemical Physics · Physics 2015-08-12 Pierre-François Loos

Density matrix embedding theory (DMET) is a powerful quantum embedding method for solving strongly correlated quantum systems. Theoretically, the performance of a quantum embedding method should be limited by the computational cost of the…

Computational Physics · Physics 2020-08-19 Xiaojie Wu , Michael Lindsey , Tiangang Zhou , Yu Tong , Lin Lin

Gutzwiller's semiclassical trace formula for the density of states in a chaotic system diverges near bifurcations of periodic orbits, where it must be replaced with uniform approximations. It is well known that, when applying these…

Chaotic Dynamics · Physics 2009-10-31 T. Bartsch , J. Main , G. Wunner

The exact one-loop beta functions for the four-derivative terms (Weyl tensor squared, Ricci scalar squared and the Gauss-Bonnet) are derived for the minimal six-derivative quantum gravity (QG) theory in four spacetime dimensions. The…

High Energy Physics - Theory · Physics 2021-10-29 Leslaw Rachwal , Leonardo Modesto , Aleksandr Pinzul , Ilya L. Shapiro

Density functional theory (DFT) has transformed our ability to investigate and understand electronic ground states. In its original formulation, however, DFT is not suited to addressing (e.g.) degenerate ground states, mixed states with…

Chemical Physics · Physics 2025-10-30 Tim Gould , Leeor Kronik , Stefano Pittalis

We extend the previously proposed one-parameter double-hybrid density-functional theory [K. Sharkas, J. Toulouse, and A. Savin, J. Chem. Phys. 134, 064113 (2011)] to meta-generalized-gradient-approximation (meta-GGA) exchange-correlation…

Chemical Physics · Physics 2014-02-27 Sidi Ould Souvi , Kamal Sharkas , Julien Toulouse

We derive expressions required in generalizing the Gutzwiller approximation to models comprising arbitrarily degenerate localized orbitals.

Condensed Matter · Physics 2009-10-30 Takuya Okabe

We present a density-matrix embedding theory (DMET) study of the one-dimensional Hubbard-Holstein model, which is paradigmatic for the interplay of electron-electron and electron-phonon interactions. Analyzing the single-particle excitation…

We revisit the topic of two-state quantum systems using Geometric Algebra (GA) in three dimensions $\mathcal G_3$. In this description, both the quantum states and Hermitian operators are written as elements of $\mathcal G_3$. By writing…

Mathematical Physics · Physics 2021-03-10 Pedro Amao , Hernán Castillo

We use the Gaussian variational principle to apply cMERA to interacting quantum field theories in arbitrary spacetime dimensions. By establishing a correspondence between the first two terms in the variational expansion and the Gaussian…

High Energy Physics - Theory · Physics 2018-06-07 Jordan S. Cotler , Javier Molina-Vilaplana , Mark T. Mueller

This thesis explores the cosmological implications of modified gravity, focusing on nonmetricity-based $f(Q)$ gravity as an alternative to the $\Lambda$CDM model in explaining cosmic acceleration. Chapter I lays the theoretical groundwork…

General Relativity and Quantum Cosmology · Physics 2025-04-15 Gaurav N. Gadbail

We revisit ghost dark matter, the possibility that ghost condensation may serve as an alternative to dark matter. In particular, we investigate the Friedmann-Robertson-Walker (FRW) background evolution and the large-scale structure (LSS) in…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 Tomonori Furukawa , Shuichiro Yokoyama , Kiyotomo Ichiki , Naoshi Sugiyama , Shinji Mukohyama

We present a finite-temperature extension of density matrix embedding theory (FT-DMET) for realistic crystalline systems. We describe a practical framework for constructing extended bath orbitals, solving the embedding problem, and…

Computational Physics · Physics 2026-01-06 Laurence Giordano , Y. Stanley Tan , Zhi-Hao Cui , Chong Sun

A generalized Gaussian process model (GGPM) is a unifying framework that encompasses many existing Gaussian process (GP) models, such as GP regression, classification, and counting. In the GGPM framework, the observation likelihood of the…

Machine Learning · Statistics 2013-11-28 Lifeng Shang , Antoni B. Chan