  The Vector-QM24 (VQM24) dataset attempts to more comprehensively cover all
possible neutral closed shell small organic and inorganic molecules and their
conformers at state of the art level of theory. We have used density functional
theory ($\omega$B97X-D3/cc-pVDZ) to optimize 577k conformational isomers
corresponding to 258k constitutional isomers.Isomers included contain up to
five heavy atoms (non-hydrogen) consisting of $p$-block elements C, N, O, F,
Si, P, S, Cl, Br. Single point diffusion quantum Monte Carlo
(DMC@PBE0(ccECP/cc-pVQZ)) energies are reported for the sub-set of the lowest
conformers of 10,793 molecules with up to 4 heavy atoms.This dataset has been
systematically generated by considering all combinatorially possible
stoichiometries, and graphs (according to Lewis rules as implemented in the
{\tt SURGE} package), along with all stable conformers identified by GFN2-xTB.
Apart from graphs, geometries, rotational constants, and vibrational normal
modes, VQM24 includes internal, atomization, electron-electron repulsion,
exchange correlation, dispersion, vibrational frequency, Gibbs free, enthalpy,
ZPV, molecular orbital energies; as well as entropy, and heat capacities.
Electronic properties include multipole moments (dipole, quadrupole, octupole,
hexadecapole), electrostatic potentials at nuclei (alchemical potential),
Mulliken charges, and molecular wavefunctions. VQM24 represents a highly
accurate and unbiased dataset of molecules, ideal for testing and training
transferable, scalable, and generative ML models of real quantum systems.
