:: Library Catalog

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Opis bibliograficzny
Główni autorzy:	Barborini, Matteo, Charry, Jorge, Ditte, Matej, Leventis, Andronikos, Kafanas, Georgios, Tkatchenko, Alexandre
Format:	Preprint
Wydane:	2025
Hasła przedmiotowe:	Chemical Physics
Dostęp online:	https://arxiv.org/abs/2511.03439
Etykiety:	Dodaj etykietę Nie ma etykietki, Dołącz pierwszą etykiete!

Podobne zapisy

Two Protons, Two Positrons, and Four Electrons: Covalent Bond with van der Waals Characteristics
od: Charry, Jorge, i wsp.
Wydane: (2026)

Accurate quantum Monte Carlo forces for machine-learned force fields: Ethanol as a benchmark
od: Slootman, Emiel, i wsp.
Wydane: (2024)

Quantum Field Approaches to Chemical Systems
od: Karimpour, Reza, i wsp.
Wydane: (2026)

A Transferable Model of Molecular Exchange-Repulsion Interaction from Anisotropic Valence Density Overlap
od: Wing, Dahvyd, i wsp.
Wydane: (2025)

Are Molecules Magical? Non-Stabilizerness in Molecular Bonding
od: Sarkis, Matthieu, i wsp.
Wydane: (2025)

Deep quantum Monte Carlo approach for polaritonic chemistry
od: Tang, Yifan, i wsp.
Wydane: (2025)

QMe14S, A Comprehensive and Efficient Spectral Dataset for Small Organic Molecules
od: Yuan, Mingzhi, i wsp.
Wydane: (2025)

NNQS-AFQMC: Neural network quantum states enhanced fermionic quantum Monte Carlo
od: Xiao, Zhi-Yu, i wsp.
Wydane: (2025)

How Atoms Interact Within Molecules
od: Kabylda, Adil, i wsp.
Wydane: (2026)

Reweighting scheme for the calculation of grand-canonical expectation values in quantum Monte Carlo simulations with a fermion sign problem
od: Hamann, Paul, i wsp.
Wydane: (2025)

Partitioning the electronic wave function using deep variational Monte Carlo
od: Mezera, Matěj, i wsp.
Wydane: (2025)

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water-methane dimer
od: Della Pia, Flaviano, i wsp.
Wydane: (2025)

aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
od: Henkes, Tobias, i wsp.
Wydane: (2025)

Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy Calculations
od: Hilfiker, Mathias, i wsp.
Wydane: (2025)

Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules
od: Kabylda, Adil, i wsp.
Wydane: (2022)

Excited states in auxiliary field quantum Monte Carlo
od: Mahajan, Ankit, i wsp.
Wydane: (2025)

QCell: Comprehensive Quantum-Mechanical Dataset Spanning Diverse Biomolecular Fragments
od: Kabylda, Adil, i wsp.
Wydane: (2025)

MBD-ML: Many-body dispersion from machine learning for molecules and materials
od: Moerman, Evgeny, i wsp.
Wydane: (2026)

Method-independent cusps for atomic orbitals in quantum Monte Carlo
od: Quady, Trine Kay, i wsp.
Wydane: (2024)

Auxiliary-field quantum Monte Carlo method with quantum selected configuration interaction
od: Yoshida, Yuichiro, i wsp.
Wydane: (2025)

Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows
od: Huang, Benchen, i wsp.
Wydane: (2024)

Electron-pair densities with time-dependent quantum Monte-Carlo
od: Christov, Ivan P.
Wydane: (2013)

Systematic improvement of trial states in phaseless auxiliary-field quantum Monte Carlo
od: Kjønstad, Eirik F., i wsp.
Wydane: (2025)

Deep learning quantum Monte Carlo for solids
od: Qian, Yubing, i wsp.
Wydane: (2024)

Solvation effects on halides core spectra with Multilevel Real-Time quantum embedding
od: B., Jessica A. Martinez, i wsp.
Wydane: (2024)

Quantum-Accurate Conformational Stabilities and Vibrational Dynamics in Molecules and Proteins with Machine-Learned Force Fields
od: Suárez-Dou, Sergio, i wsp.
Wydane: (2026)

Analyzing Atomic Interactions in Molecules as Learned by Neural Networks
od: Esders, Malte, i wsp.
Wydane: (2024)

Optimizing excited states in quantum Monte Carlo: A reassessment of double excitations
od: Shepard, Stuart, i wsp.
Wydane: (2025)

Phaseless auxiliary-field quantum Monte Carlo method for cavity-QED matter systems
od: Weber, Lukas, i wsp.
Wydane: (2024)

A CPD-enabled low-scaling environment solver in a coupled cluster based static quantum embedding theory
od: Pierce, Karl, i wsp.
Wydane: (2026)

Auxiliary field quantum Monte Carlo at the basis set limit: application to lattice constants
od: Humer, Moritz, i wsp.
Wydane: (2026)

A quantum computing approach to fixed-node Monte Carlo using classical shadows
od: Blunt, Nick S., i wsp.
Wydane: (2024)

Extended system-bath entanglement theorem for multiple bosonic or fermionic environments
od: Su, Yu, i wsp.
Wydane: (2024)

$Δ$-Machine Learning to Elevate DFT-based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol
od: Nandi, Apurba, i wsp.
Wydane: (2024)

Can phaseless auxiliary-field quantum Monte Carlo with broken symmetry trials describe iron-sulfur clusters?
od: Kjønstad, Eirik F., i wsp.
Wydane: (2026)

X marks the spot: accurate energies from intersecting extrapolations of continuum quantum Monte Carlo data
od: Hosseini, Seyed Mohammadreza, i wsp.
Wydane: (2024)

Rapidly convergent quantum Monte Carlo using a Chebyshev projector
od: Zhao, Zijun, i wsp.
Wydane: (2024)

Reducing the time-step errors in diffusion Monte Carlo
od: Anderson, Tyler A., i wsp.
Wydane: (2023)

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo
od: Goswami, Shubhang, i wsp.
Wydane: (2024)

MLQD: A package for machine learning-based quantum dissipative dynamics
od: Ullah, Arif, i wsp.
Wydane: (2023)