348 citations · 6.3k across the 139 of their papers we have counts for
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Structure Factors of the Kagome-Lattice Heisenberg antiferromagnets at finite temperatures
Nicholas E. Sherman, Rajiv R. P. Singh
We compute the real-space spin correlations and frquency and wave-vector resolved dynamic structure factors for the nearest-neighbor Kagome-Lattice Heisenberg Antifer…
Exotic pairing symmetry of interacting Dirac fermions on a flux lattice
Huaiming Guo, Ehsan Khatami, Yao Wang +3
The pairing symmetry of interacting Dirac fermions on the -flux lattice is studied with the determinant quantum Monte Carlo and numerical linked cluster expansion methods. The e…
Principal Component Analysis for Fermionic Critical Points
Natanael C. Costa, Wenjian Hu, Z. J. Bai +2
We use determinant Quantum Monte Carlo (DQMC), in combination with the principal component analysis (PCA) approach to unsupervised learning, to extract information about phase tran…
High temperature thermodynamics of the honeycomb-lattice Kitaev-Heisenberg model: A high temperature series expansion study
Rajiv R. P. Singh, Jaan Oitmaa
We develop high temperature series expansions for the thermodynamic properties of the honeycomb-lattice Kitaev-Heisenberg model. Numerical results for uniform susceptibility, heat…
Critical and Griffiths-McCoy singularities in quantum Ising spin-glasses on d-dimensional hypercubic lattices: A series expansion study
R. R. P. Singh, A. P. Young
We study the transverse-field Ising spin glass model at zero temperature on d-dimensional hypercubic lattices and in the Sherrington-Kirkpatrick (SK) model, by series expan…
Discovering Phases, Phase Transitions and Crossovers through Unsupervised Machine Learning: A critical examination
Wenjian Hu, Rajiv R. P. Singh, Richard T. Scalettar
We apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical…