Dataset Information

Self-Adapting Short-Range Correlation Functional for Complete Active Space-Based Approximations.

ABSTRACT: We propose a short-range correlation energy correction tailored for active space wave function models. The correction relies on a short-range multideterminant correlation functional computed with a local range-separation parameter that self-adapts to the underlying wave function. This approach is analogous to that of Giner et al. [J. Chem. Phys. 2018, 149, 194301] which addresses the basis set incompleteness error, with the vital distinction that in our protocol the range-separation parameter remains finite in the complete basis set limit, ensuring nonzero short-range correlation. The proposed correlation functional compensates for the missing short-range correlation via two mechanisms: (i) an automatically adapting short-range parameter, which gauges the missing correlation in the electron vicinity, and (ii) the functional's explicit dependence on the on-top pair density, which reduces short-range correlation in regions where electron correlation is mainly static. We integrate our method into the multireference adiabatic connection theory for CASSCF wave functions. The performance of the introduced CAS-AC0-(c,md) model is verified by calculating potential energy curves for alkaline-earth metal dimers (Be₂, Mg₂, Ca₂) and for the chromium dimer, in all cases obtaining promising results.

SUBMITTER: Hapka M

PROVIDER: S-EPMC11345816 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Self-Adapting Short-Range Correlation Functional for Complete Active Space-Based Approximations.

Hapka Michał M Pastorczak Ewa E Pernal Katarzyna K

The journal of physical chemistry. A 20240808 33

We propose a short-range correlation energy correction tailored for active space wave function models. The correction relies on a short-range multideterminant correlation functional computed with a local range-separation parameter that self-adapts to the underlying wave function. This approach is analogous to that of Giner et al. [<i>J. Chem. Phys.</i> <b>2018</b>, 149, 194301] which addresses the basis set incompleteness error, with the vital distinction that in our protocol the range-separatio ...[more]

PMID: 39115208

Similar Datasets

Project description:Numerous varieties of life forms have filled the earth throughout evolution. Evolution consists of two processes: self-replication and interaction with the physical environment and other living things around it. Initiated by von Neumann et al. studies on self-replication in cellular automata have attracted much attention, which aim to explore the logical mechanism underlying the replication of living things. In nature, competition is a common and spontaneous resource to drive self-replications, whereas most cellular-automaton-based models merely focus on some self-protection mechanisms that may deprive the rights of other artificial life (loops) to live. Especially, Huang et al. designed a self-adaptive, self-replicating model using a greedy selection mechanism, which can increase the ability of loops to survive through an occasionally abandoning part of their own structural information, for the sake of adapting to the restricted environment. Though this passive adaptation can improve diversity, it is always limited by the loop's original structure and is unable to evolve or mutate new genes in a way that is consistent with the adaptive evolution of natural life. Furthermore, it is essential to implement more complex self-adaptive evolutionary mechanisms not at the cost of increasing the complexity of cellular automata. To this end, this article proposes new self-adaptive mechanisms, which can change the information of structural genes and actively adapt to the environment when the arm of a self-replicating loop encounters obstacles, thereby increasing the chance of replication. Meanwhile, our mechanisms can also actively add a proper orientation to the current construction arm for the sake of breaking through the deadlock situation. Our new mechanisms enable active self-adaptations in comparison with the passive mechanism in the work of Huang et al. which is achieved by including a few rules without increasing the number of cell states as compared to the latter. Experiments demonstrate that this active self-adaptability can bring more diversity than the previous mechanism, whereby it may facilitate the emergence of various levels in self-replicating structures.

Project description:An algorithm to perform stochastic generalized active space calculations, Stochastic-GAS, is presented, that uses the Slater determinant based FCIQMC algorithm as configuration interaction eigensolver. Stochastic-GAS allows the construction and stochastic optimization of preselected truncated configuration interaction wave functions, either to reduce the computational costs of large active space wave function optimizations, or to probe the role of specific electron correlation pathways. As for the conventional GAS procedure, the preselection of the truncated wave function is based on the selection of multiple active subspaces while imposing restrictions on the interspace excitations. Both local and cumulative minimum and maximum occupation number constraints are supported by Stochastic-GAS. The occupation number constraints are efficiently encoded in precomputed probability distributions, using the precomputed heat bath algorithm, which removes nearly all runtime overhead of GAS. This strategy effectively allows the FCIQMC dynamics to a priori exclude electronic configurations that are not allowed by GAS restrictions. Stochastic-GAS reduced density matrices are stochastically sampled, allowing orbital relaxations via Stochastic-GASSCF, and direct evaluation of properties that can be extracted from density matrices, such as the spin expectation value. Three test case applications have been chosen to demonstrate the flexibility of Stochastic-GAS: (a) the Stochastic-GASSCF [5·(6, 6)] optimization of a stack of five benzene molecules, that shows the applicability of Stochastic-GAS toward fragment-based chemical systems; (b) an uncontracted stochastic MRCISD calculation that correlates 96 electrons and 159 molecular orbitals, and uses a large (32, 34) active space reference wave function for an Fe(II)-porphyrin model system, showing how GAS can be applied to systematically recover dynamic electron correlation, and how in the specific case of the Fe(II)-porphyrin dynamic correlation further differentially stabilizes the 3Eg over the 5A1g spin state; (c) the study of an Fe4S4 cluster's spin-ladder energetics via highly truncated stochastic-GAS [4·(5, 5)] wave functions, where we show how GAS can be applied to understand the competing spin-exchange and charge-transfer correlating mechanisms in stabilizing different spin-states.

Dataset Information

Self-Adapting Short-Range Correlation Functional for Complete Active Space-Based Approximations.

Publications

Self-Adapting Short-Range Correlation Functional for Complete Active Space-Based Approximations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets