arXiv subjects

Benran Zhang

Publications and source records attributed to Benran Zhang.

6 recordsLinked to original sources

arXiv2026

Ab initio time-dependent GW approach for nonequilibrium exciton-phonon coupled dynamics across momentum space

The dynamics of optical excitations in materials generally involves intertwined electron-hole (e-h) and electron-phonon (e-ph) interactions out of equilibrium. However, a full theoretical description of such nonequilibrium dynamics requires a systematic treatment of the coherent excitonic excitations and exciton-phonon interactions across the entire crystal momentum space in real time, which remains a major challenge and out of reach for first-principles approaches. Here, we present a new ab initio time-dependent adiabatic GW methodology that incorporates full finite-momentum e-h and e-ph couplings, enabling real-time simulations of the coherently coupled exciton-phonon dynamics. The excitonic excitations are naturally described by the equation of motion of the interacting single-particle density matrix, whereas their couplings to phonons are formulated within a linear-response framework, hence the simulations can be efficiently carried out within a primitive unit cell. We demonstrate the capabilities of this new approach by investigating the direct-to-indirect exciton transitions in monolayer WSe2 in a pump-probe setup of time-resolved and angle-resolved photoemission spectroscopy. Our results reveal that the phonon-mediated ultrafast intervalley dynamics of excitons of this system is within ~0.5 ps, manifested as in-gap photoemission intensity transfer from the K-valley to the Q-valley. This work establishes a comprehensive and practical nonequilibrium Green's function framework for accurately simulating nonequilibrium and coherent excitations involving coupled excitons and phonons from first principles.

cond-mat.mtrl-sci↗

arXiv2026

Agents' Last Exam

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional domains. We argue that this gap is largely an evaluation problem: widely used benchmarks lack sustained performance measurement on real and economically valuable workflows. This paper introduces Agents' Last Exam (ALE), a benchmark designed to evaluate AI agents on long horizon, economically valuable, real world tasks with verifiable outcomes. Developed in collaboration with 250+ industry experts, ALE covers non-physical industries defined with reference to O*NET / SOC 2018 (the U.S. federal occupational taxonomy). It is organized around a task taxonomy with 55 sub fields grouped into 13 industry clusters covering 1K+ tasks. Current results show that the hardest tier remains far from saturated: across mainstream harness and backbone configurations, the average full pass rate is below 1%. ALE is designed as a living benchmark: its task pool grows continuously as new workflows and industries are onboarded. More broadly, ALE is intended not merely as another leaderboard, but as an instrument for closing the gap between benchmark success and GDP relevant impact.

cs.AI↗

arXiv2025

Many-Body Correlation Effects in Fr\"ohlich Electron-Phonon Coupling

In compound semiconductors and insulators, the polar electron-phonon coupling diverges at long range, known as the Fr\"ohlich interaction. Modern first-principles electron-phonon calculations treat the Fr\"ohlich interaction in a semiclassical electrostatic formalism based on density-functional perturbation theory. Here, using many-body $GW$ perturbation theory, we reveal important electron correlation effects in the Fr\"ohlich-type electron-phonon coupling, which are missed by the prevailing approaches and rooted in the fundamentally distinct behavior between quasiparticle self-energy and semi-local exchange-correlation functionals in the long-range limit. Going beyond the electrostatic treatment, we derive and implement the $GW$ self-energy contribution to the long-range polar electron-phonon coupling, and demonstrate its critical role and nontrivial behaviors in properties such as electron linewidth and polaron formation in several prototype semiconductors. Remarkably, calculations on photoemission kink in electron-doped TiO$_2$ achieve excellent agreement with experiment. Our work establishes the many-body generalization of the Fr\"ohlich interaction that is essential for accurate electron-phonon calculations at the full $GW$ level combined with Wannier interpolation techniques.

cond-mat.mtrl-sci↗

arXiv2025

Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms

Advanced ab initio materials simulations face growing challenges as increasing systems and phenomena complexity requires higher accuracy, driving up computational demands. Quantum many-body GW methods are state-of-the-art for treating electronic excited states and couplings but often hindered due to the costly numerical complexity. Here, we present innovative implementations of advanced GW methods within the BerkeleyGW package, enabling large-scale simulations on Frontier and Aurora exascale platforms. Our approach demonstrates exceptional versatility for complex heterogeneous systems with up to 17,574 atoms, along with achieving true performance portability across GPU architectures. We demonstrate excellent strong and weak scaling to thousands of nodes, reaching double-precision core-kernel performance of 1.069 ExaFLOP/s on Frontier (9,408 nodes) and 707.52 PetaFLOP/s on Aurora (9,600 nodes), corresponding to 59.45% and 48.79% of peak, respectively. Our work demonstrates a breakthrough in utilizing exascale computing for quantum materials simulations, delivering unprecedented predictive capabilities for rational designs of future quantum technologies.

cond-mat.mtrl-sci↗

arXiv2025

Moir\'e excitons in generalized Wigner crystals

Moir\'e superlattices of transition-metal dichalcogenide bilayers host strong Coulomb interactions residing in narrow electron bands, leading to correlated insulating states at fractional carrier doping densities, known as generalized Wigner crystals. In excited states, the formation of moir\'e excitons is expected to be fundamentally shaped by the Wigner-crystal ground states, manifesting an intricate interplay between electronic and excitonic correlations. However, the microscopic description of these Wigner crystalline excitons (WCEs) remains elusive, largely subject to speculations, and is further needed for the understanding of exotic excitonic phases (e.g., exciton insulators and exciton density waves) and their unique properties (e.g., anomalous exciton diffusion). Here, using first-principles many-body GW-Bethe-Salpeter-equation calculations, we directly reveal the internal structures of WCEs in angle-aligned MoSe2/MoS2 moir\'e heterostructure at hole fillings of 1/3 and 2/3. Our results unveil the propagation of correlation effects from the ground state to excited states, shaping the real-space characteristics of WCEs. The strong two-particle excitonic correlations dominate over the kinetic energy of free electron-hole pairs, in analog to the strong single-particle correlations of flat bands. We propose that such unusual excited-state correlation effects of WCEs can be experimentally probed by photocurrent tunneling microscopy. Our work provides a microscopic understanding of strongly correlated WCEs, suggesting them as a highly tunable mixed boson-fermion platform to study many-body interactions and phenomena.

cond-mat.mtrl-sci↗

arXiv2024

Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic

Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search (LNS), is the current state-of-the-art approach where a fast initial solution is iteratively optimized by destroying and repairing selected paths of the solution. Current MAPF-LNS variants commonly use an adaptive selection mechanism to choose among multiple destroy heuristics. However, to determine promising destroy heuristics, MAPF-LNS requires a considerable amount of exploration time. As common destroy heuristics are non-adaptive, any performance bottleneck caused by these heuristics cannot be overcome via adaptive heuristic selection alone, thus limiting the overall effectiveness of MAPF-LNS in terms of solution cost. In this paper, we propose Adaptive Delay-based Destroy-and-Repair Enhanced with Success-based Self-Learning (ADDRESS) as a single-destroy-heuristic variant of MAPF-LNS. ADDRESS applies restricted Thompson Sampling to the top-K set of the most delayed agents to select a seed agent for adaptive LNS neighborhood generation. We evaluate ADDRESS in multiple maps from the MAPF benchmark set and demonstrate cost improvements by at least 50% in large-scale scenarios with up to a thousand agents, compared with the original MAPF-LNS and other state-of-the-art methods.

cs.AI↗