142 papers
This paper introduces an optimal-tuning scheme for multiconfigurational short-range density functional theory (MC-srDFT) that determines the system-specific range-separation parameter via the ionization potential derived from Extended Koopmans' Theorem, significantly improving the accuracy of static and dynamic dipole polarizabilities compared to standard universal parameters.
This study demonstrates that while mean-field methods fail to predict polariton formation with a Fock state cavity initialization, full-quantum simulations reveal that such non-classical initial conditions uniquely induce light-matter entanglement and specific operator oscillations, highlighting the necessity of a quantum electrodynamics treatment for capturing these phenomena.
This paper introduces a novel, size-extensive, and convergent degenerate coupled-cluster (CC) theory capable of handling arbitrary reference states and a related quasidegenerate variant (QCC) for strong correlation, demonstrating superior accuracy and convergence over existing methods like EOM-CC, CI, and MBGF through high-order implementations.
This paper introduces the Open Polymers 2026 (OPoly26) dataset, a publicly released collection of over 6.57 million density functional theory calculations on polymeric systems designed to overcome previous computational limitations and enhance machine learning models for predicting polymer properties.
This paper establishes a geometric control framework for boundary-catalytic branching processes by utilizing a Steklov spectral problem to determine the critical absorption rates required to balance population growth and achieve a steady state, while identifying a threshold beyond which such control becomes impossible.
This paper presents a dynamical method for measuring the saturation vapor pressures and enthalpies of vaporization of low-volatility liquids across an extended temperature range of -10 to 35°C, validated through experiments on four reference substances.
Meta FAIR introduces Open Molecules 2025 (OMol25), a large-scale dataset comprising over 100 million high-accuracy DFT calculations across 83 elements and diverse chemical systems, accompanied by baseline models and evaluations to advance machine learning for molecular simulations.
This study demonstrates that intermolecular Coulombic decay (ICD) enables a novel collective energy transfer mechanism where multiple photoexcited pyridine molecules funnel energy to ionize a non-absorbing argon spectator atom, offering new insights for light harvesting and biomolecular photoprotection.
This study reveals that acetaldehyde exhibits two distinct roaming pathways during photodissociation—one at longer distances analogous to formaldehyde and a unique shorter-range pathway facilitated by repulsive interactions—suggesting that its enhanced roaming propensity stems from multiple mechanisms rather than just fragment mass.
This paper presents and experimentally demonstrates two independent optical methods for absolute primary nanothermometry using rare-earth-doped nanoparticles, which determine temperature solely from the internal population dynamics of Stark sublevels without external references, thereby enabling single-ion, wide-range thermal sensing at the nanoscale.
This paper introduces OrbEvo, an equivariant graph transformer model that efficiently predicts time-dependent electronic wavefunctions and related physical properties under external fields by learning to evolve orbital coefficients through autoregressive rollout, thereby overcoming the computational bottlenecks of conventional real-time time-dependent density functional theory.
This study demonstrates through 3D quantum wave packet calculations that bilayer graphdiyne membranes exhibit enhanced quantum transport and interlayer-separation-dependent resonances compared to monolayers, suggesting their superior potential for isotope separation applications.
This paper extends the Harrow-Hassidim-Lloyd (HHL) algorithm to qutrits by introducing Weyl-Heisenberg gadgets and a practical implementation scheme, demonstrating that the qutrit version achieves comparable precision with fewer qudits and a similar number of two-qudit gates compared to the traditional qubit-based approach.
This paper revisits the pseudomode formalism for open quantum systems to investigate design subtleties, demonstrating how non-diagonalizable couplings generate unique spectral densities, revealing significant freedom in parameter construction, challenging convergence assumptions for evenly distributed modes, and connecting the concept to scattering theory.
This paper presents an open-source universal machine learning interatomic potential covering 97 elements, including minor actinides, by integrating a newly constructed heavy element dataset with existing resources to enable advanced materials design for nuclear applications.
This paper introduces GET-SEI, a general framework combining graph contrastive learning, extended dynamic mode decomposition, and transition path theory to automatically characterize local atomic environments and quantify lithium transport kinetics and pathways across diverse solid-state electrolyte/lithium metal interfaces for targeted SEI engineering.
The paper introduces MAD-1.5, a highly curated and standardized dataset covering 102 elements with consistent r²SCAN DFT calculations, which enables the development of the PET-MAD-1.5 model achieving exceptional accuracy and stability for universal atomistic machine learning.
This paper presents a phase-sensitive tip-enhanced sum frequency generation spectroscopy technique that utilizes temporally asymmetric pulses to suppress non-resonant background interference, thereby achieving nanoscale spatial resolution and enabling the detection of weak vibrational signals and determination of absolute molecular orientations at surfaces.
This study demonstrates that a robust nanofabrication protocol restoring atomic-scale purity to epitaxial graphene on SiC enables the emergence of macroscopic excitonic coherence in HMTP overlayers, revealing a Davydov-split vibronic manifold where a dark excitonic branch dominates radiative relaxation via a polaron-mediated pathway.
This paper proposes a hybrid quantum-classical scheme utilizing quantum dominant orbital selection (QDOS) and subspace dynamical correlation (SDC) to accurately evaluate molecular energies on fault-tolerant quantum computers while avoiding the computational bottleneck of extracting full wavefunction data.