33 citations · 157 across the 13 of their papers we have counts for
13 papers
Approaching Thouless Energy and Griffiths Regime in Random Spin Systems By Singular Value Decomposition
Wen-Jia Rao
We employ singular value decomposition (SVD) to study the eigenvalue spectra of random spin systems. By SVD, eigenvalue spectrum is decomposed into orthonormal modes with wei…
Power-Law Random Banded Matrix Ensemble as the Effective Model for Many-Body Localization Transition
Wen-Jia Rao
We employ the power-law random band matrix (PRBM) ensemble with single tuning parameter as the effective model for many-body localization (MBL) transition in random spin system…
Random Matrix Model for Eigenvalue Statistics in Random Spin Systems
Wen-Jia Rao
We propose a working strategy to describe the eigenvalue statistics of random spin systems along the whole phase diagram with thermal to many-body localization (MBL) transition. Ou…
Critical Level Statistics at the Many-Body Localization Transition Region
Wen-Jia Rao
We study the critical level statistics at the many-body localization (MBL) transition region in random spin systems. By employing the inter-sample randomness as indicator, we manag…
Scaling of the Reduced Energy Spectrum of Random Matrix Ensemble
Wen-Jia Rao, M. N. Chen
We study the reduced energy spectrum , which is constructed by picking one level from every levels of the original spectrum , in a Gaussian ensemble…
Higher-order level spacings in random matrix theory based on Wigner's conjecture
Wen-Jia Rao
The distribution of higher order level spacings, i.e. the distribution of with is derived analytically using a Wigner-like surmise for Gau…
Learning What a Machine Learns in a Many-Body Localization Transition
Rubah Kausar, Wen-Jia Rao, Xin Wan
We employ a convolutional neural network to explore the distinct phases in random spin systems with the aim to understand the specific features that the neural network chooses to i…
Identifying Product Order with Restricted Boltzmann Machines
Wen-Jia Rao, Zhenyu Li, Qiong Zhu +2
Unsupervised machine learning via a restricted Boltzmann machine is an useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the…
SU(3) quantum critical model emerging from a spin-1 topological phase
Wen-Jia Rao, Guo-Yi Zhu, Guang-Ming Zhang
Different from the spin-1 Haldane gapped phase, we propose a novel SO(3) spin-1 matrix product state (MPS), whose parent Hamiltonian includes three-site spin interactions. From the…
Quantum antiferromagnetic Heisenberg half-odd integer spin model as the entanglement Hamiltonian of the integer spin Affleck-Kennedy-Lieb-Tasaki states
Wen-Jia Rao, Guang-Ming Zhang, Kun Yang
Applying a symmetric bulk bipartition to one-dimensional Affleck-Kennedy-Lieb-Tasaki valence bond solid (VBS) states for the integer spin-S Haldane gapped phase, we can create an a…
Emergent infinite-randomness fixed points from the extensive random bipartitions of the spin-1 Affleck-Kennedy-Lieb-Tasaki topological state
Min Lu, Wen-Jia Rao, Rajesh Narayanan +2
Quantum entanglement under an extensive bipartition can reveal the critical boundary theory of a topological phase in the parameter space. In this study we demonstrate that the inf…
Critical entanglement spectrum of one-dimensional symmetry protected topological phases
Wen-Jia Rao, Xin Wan, Guang-Ming Zhang
Under an appropriate symmetric extensive bipartition in a one-dimensional symmetry protected topological (SPT) phase, a bulk critical entanglement spectrum can be obtained, resembl…
Disentangling topological degeneracy in the entanglement spectrum of one-dimensional symmetry protected topological phases
Wen-Jia Rao, Guang-Ming Zhang, Kun Yang
One-dimensional valence bond solid (VBS) states represent the simplest symmetry protected topological phases. We show that their ground state entanglement spectrum contains both to…