Search arXivSearch

arXiv · 2405.08085

A relativistic third-order algebraic diagrammatic construction theory for electron detachment, attachment and excitation problems

Abstract

We present the theory and implementation of a highly efficient relativistic third-order algebraic diagrammatic construction [ADC(3)] method based on a four-component (4c) Dirac-Coulomb (DC) Hamiltonian for the calculation of ionization potentials (IP), electron affinities (EA), and excitation energies (EE). Benchmarking calculations for IP, EA, and EE were performed on both atomic and molecular systems to assess the accuracy of the newly developed four-component relativistic ADC(3) method. The results show good agreement with the available experimental data. The Hermitian nature of the 4c-ADC(3) Hamiltonian, combined with the perturbative truncation of the wave function, offers significant computational advantages over the standard equation-of-motion coupled-cluster approach, particularly for property calculations. The method's suitability for property calculations is further demonstrated by computing oscillator strengths and excited-state dipole moments for heavy elements.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sudipta Chakraborty, Tamoghna Mukhopadhyay, Malaya K. Nayak, Achintya Kumar Dutta. 2024-10-30. A relativistic third-order algebraic diagrammatic construction theory for electron detachment, attachment and excitation problems. https://arxiv.org/abs/2405.08085

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

SPIBER: Reconstructing Free Energy Landscapes from Short, Unconverged Trajectories with Generative Flow Networks

Molecular systems have many degrees of freedom, but their metastable behavior can often be described by a few collective variables. Identifying these variables and estimating free energies along them from limited simulation data remains a challenging, important problem. Separate short trajectories may sample different metastable states without capturing transitions or establishing their relative equilibrium populations. For unbiased trajectories generated with the same Hamiltonian at a single temperature, alternate methods based on histogram reweighting cannot correct this imbalance. Here we present SPIBER, which combines the State Predictive Information Bottleneck (SPIB) with Generative Flow Networks (GFlowNets). SPIB uses deep learning to approximate slow degrees of freedom through a past-future information bottleneck, retaining information needed to predict future metastable states. We show that this compression limits conditional entropy variations in populated regions, allowing conditional mean potential energies, which are much easier to calculate, to be used to approximate free energy differences. Given sufficient local sampling to estimate these energies, they define the target distribution for GFlowNets, energy-based generative samplers that sample according to estimated thermodynamic stability rather than observed populations. For a particle in a radial double-well potential, for alanine dipeptide, and for the nine-residue peptide AIB9, SPIBER recovers free energy differences between sampled metastable states to within one thermal energy unit of reference values. The method combines collective-variable learning and free energy estimation in up to four latent dimensions, without requiring converged state populations or additional molecular dynamics simulations.

physics.chem-ph

Intrinsic Matching Frustration in Fluctuating Finite Systems

We formulate intrinsic matching frustration (IMF), a fluctuation-induced, kinetics-independent reduction in the mean capacity permitted by a prescribed matching rule. For complementary one-to-one matching, the instantaneous capacity is set by the minority population, so fluctuations produce a nonzero mean deficit even when the two populations are balanced on average. At finite size, this deficit depends on the full distribution of the population difference and is determined by its variance alone only in the Gaussian limit. Compartmentalization hides matching capacity by preventing cancellation between local imbalances of opposite sign. Fusion releases this hidden capacity monotonically under coarse graining, producing a measurable recovery of product yield following local reaction to completion.

physics.chem-ph

Phonon chirality as an additive control of CISS: a symmetry-protected law

Chirality-induced spin selectivity (CISS) is usually associated with molecular handedness. The possible contribution of chiral phonons is less established. We study a helical tight-binding model in which local phonon angular momentum modulates spin-dependent nearest-neighbor hopping. Fewest-switches surface hopping calculations give the transmitted spin polarization $\mathrm{SP}=aC+b\mathrm{PH}$. Here $C$ is the molecular chirality and $\mathrm{PH}$ is the phonon chirality. A mirror symmetry reverses $C$, $\mathrm{PH}$, and $\mathrm{SP}$ simultaneously. This symmetry excludes both a chirality-independent offset and a $C\cdot\mathrm{PH}$ term. The phonon contribution can therefore enhance, cancel, or reverse the molecular CISS signal.

physics.chem-ph