activity
20232026
most citedProbabilistic forecast of nonlinear dynamical systems with uncertainty quantification

17 citations · 26 across the 9 of their papers we have counts for

collaborators

12 papers

cond-mat.mtrl-sci2026

Exciton-driven coherent dressing in transient absorption

Jinyuan Wu, Chang Shu, Yang-hao Chan +1

While coherent excitons have recently been observed to dress electronic states in time- and angle-resolved photoemission spectroscopy (tr-ARPES), exciton-driven dressing in optical…

cond-mat.mtrl-sci2026

Altermagnetism produces pair emission and absorption from dark excitons and magnons in LaOMnSe

Birender Singh, Xian Xu, Sabrina R. Hatt +21

Altermagnets' (AMs) non-relativistic spin splitting enables novel states, spintronic and magneto-optical devices, though their optical signatures remain elusive. Here, we report ex…

physics.comp-ph2026

Gauge-Equivariant Representation Learning of Bloch States

Chengyan Zhang, Xian Xu, Bowen Hou +1

Representation learning, or featurization, of mean-field Bloch states provides an important route for incorporating electronic information into machine-learning models of first-pri…

cond-mat.mtrl-sci2025

What is the signature of a trion in photoemission?

Jinyuan Wu, Zachary H. Withers, Thomas K. Allison +1

Recent advances in time- and angle-resolved photoemission spectroscopy (tr-ARPES) allow for the probing of multiparticle excited-states in reciprocal space. While neutral two-parti…

cond-mat.mtrl-sci2025★ 1 cited

MBFormer: A General Transformer-based Learning Paradigm for Many-body Interactions in Real Materials

Bowen Hou, Xian Xu, Jinyuan Wu +1

Recently, radical progress in machine learning (ML) has revolutionized computational materials science, enabling unprecedentedly rapid materials discovery and property prediction,…

cond-mat.mtrl-sci2025★ 1 cited

Direct Observation of Massless Excitons and Linear Exciton Dispersion

Luna Y. Liu, Steffi Y. Woo, Jinyuan Wu +3

Excitons -- elementary excitations formed by bound electron-hole pairs -- govern the optical properties and excited-state dynamics of materials. In two-dimensions (2D), excitons ar…

cond-mat.mtrl-sci2025

Moiré-Tunable Localization of Simultaneous Type I and Type II Band Alignment in a MoSe2/WS2 Heterobilayer

Jiaxuan Guo, Zachary H. Withers, Ziling Li +9

Moiré heterobilayers exhibiting spatially varying band alignment and electron and hole localization that can be precisely controlled through the twist angle have emerged as excitin…

physics.comp-ph2025

Data-driven Low-rank Approximation for Electron-hole Kernel and Acceleration of Time-dependent GW Calculations

Bowen Hou, Jinyuan Wu, Victor Chang Lee +3

Many-body electron-hole interactions are essential for understanding non-linear optical processes and ultrafast spectroscopy of materials. Recent first principles approaches based…

cond-mat.mtrl-sci2024★ 6 cited

Optical absorption spectroscopy probes water wire and its ordering in a hydrogen-bond network

Fujie Tang, Diana Y. Qiu, Xifan Wu

Water wires, quasi-one-dimensional chains composed of hydrogen-bonded (H-bonded) water molecules, play a fundamental role in numerous chemical, physical, and physiological processe…

cond-mat.mtrl-sci2024★ 1 cited

Unsupervised Learning of Individual Kohn-Sham States: Interpretable Representations and Consequences for Downstream Predictions of Many-Body Effects

Bowen Hou, Jinyuan Wu, Diana Y. Qiu

Representation learning for the electronic structure problem is a major challenge of machine learning in computational condensed matter and materials physics. Within quantum mechan…

cond-mat.mtrl-sci2024

Driving non-trivial quantum phases in conventional semiconductors with intense excitonic fields

Vivek Pareek, David R. Bacon, Xing Zhu +12

Inducing novel quantum phases and topologies in materials using intense light fields is a key objective of modern condensed matter physics, but nonetheless faces significant experi…

stat.ME2023★ 17 cited

Probabilistic forecast of nonlinear dynamical systems with uncertainty quantification

Mengyang Gu, Yizi Lin, Victor Chang Lee +1

Data-driven modeling is useful for reconstructing nonlinear dynamical systems when the underlying process is unknown or too expensive to compute. Having reliable uncertainty assess…