Why are full configuration interaction computations so expensive ?
Best insight from top research papers
Full configuration interaction (FCI) computations are expensive due to the exponential scaling of the method. FCI involves considering all possible electronic configurations, resulting in a large number of terms that need to be calculated and stored. This leads to a significant increase in computational cost as the system size and complexity increase. Several strategies have been proposed to reduce the computational load of FCI calculations. Incremental FCI (iFCI) uses a many-body expansion to systematically add correlation to a reference wave function, achieving greatly reduced computational costs compared to FCI . Another approach is the use of configuration state function generators (CSFGs), which allow for a substantial reduction in the computational load by regrouping the configuration state functions and introducing CSFGs . Density matrix renormalization group (DMRG) algorithms provide an efficient approximation to FCI without a predefined excitation level, but their application is limited by the high density of states in certain regions . Modifications to the fast randomized iteration method for FCI (FCI-FRI) have also been proposed to improve its performance for larger chemical systems .
Answers from top 5 papers
More filters
| Papers (5) | Insight |
|---|---|
| Full configuration interaction computations are expensive because they involve solving a nonconvex optimization problem and require a large amount of memory. | |
Open access•Posted Content | Full configuration interaction computations are expensive due to the large number of possible configurations that need to be considered. |
| Full text information: "Configuration-interaction-type calculations on electronic and vibrational structure are often the method of choice for the reliable approximation of many-particle wave functions and energies. The exponential scaling, however, limits their application range." Answer: The exponential scaling of full configuration interaction calculations limits their application range. | |
5 Citations | Full configuration interaction (FCI) computations are expensive because they involve calculating all possible electronic configurations, which requires a large number of calculations and computational resources. |
4 Citations | Full configuration interaction computations are expensive due to the computational load involved in constructing and diagonalizing the Hamiltonian matrix, as well as the inclusion of the time-consuming Breit interaction. |
Related Questions
What is optimal energy of ligand structure in molecular docking?4 answersThe optimal energy of a ligand structure in molecular docking is crucial for accurate binding predictions. Various strategies have been proposed to enhance docking accuracy, such as multi-objective optimization methods that focus on minimizing root mean square deviation (RMSD) and intermolecular energy. Additionally, the incorporation of electrostatic interactions and polarization effects through methods like the Effective Polarizable Bond (EPB) approach has shown significant improvements in docking performance. Quantum-chemical methods, like the PM7 semiempirical method with the COSMO implicit solvent model, have been utilized to determine the global energy minimum of protein-ligand complexes, enhancing docking accuracy in solvent environments. These diverse approaches collectively contribute to achieving optimal ligand structure energies in molecular docking simulations.
What is interaction cost?5 answersInteraction cost refers to the value or cost that individuals have to pay when interacting with products or systems. It includes various factors such as time costs, psychology costs, opportunity costs, and possible monetary costs. In the context of processor design and optimization, interaction cost helps identify when designers can choose among a set of optimizations and when it is necessary to perform all of them, thereby improving performance and reducing power consumption. In the field of visualization design, interaction cost is an important but poorly understood factor. It can be categorized into seven costs, including decision costs, system-power costs, multiple input mode costs, physical-motion costs, visual-cluttering costs, view-change costs, and state-change costs. In the context of specialist organizations collaborating in value chain networks, interaction costs include transaction costs as well as costs for exchanging ideas and information. Reducing interaction costs allows for greater scope in interlinking business strategies and operations to co-create value.
How is interaction cost is a direct measure of usability?4 answersInteraction cost is a direct measure of usability because it relates to the physical effort required to use software in interactive tasks. Usability is influenced by the effort needed to accomplish tasks, and measuring interaction cost provides an objective quantity to assess usability. The framework proposed by Tamir et al. suggests metrics for measuring effort in terms of keystrokes, mouse usage, and eye movement. By tracking time and effort, this framework can serve as a screening tool to reduce development costs and assess usability. Additionally, the framework proposed by Lam suggests a framework of seven interaction costs, including decision costs, system-power costs, multiple input mode costs, physical-motion costs, visual-cluttering costs, view-change costs, and state-change costs. Considering these interaction costs can help narrow the gulfs of execution and evaluation in visualization design. Therefore, interaction cost is a direct measure of usability as it quantifies the effort required to use software and identifies specific costs that can be addressed to improve usability.
Why DFT calculations are time-consuming ?3 answersDFT calculations are time-consuming due to the fast oscillation of electron wavefunctions, which requires a very small time step in numerical simulations. This limitation significantly hinders the range of applicability for studying ultrafast dynamics using real-time time-dependent density functional theory (RT-TDDFT). However, recent advancements have shown that optimizing the gauge choice using the parallel transport formalism can considerably reduce these oscillations and accelerate RT-TDDFT calculations. Additionally, the increasing use of high-throughput DFT calculations in materials design and optimization requires comprehensive sets of soft and transferable pseudopotentials, which have been optimized and benchmarked to validate their accuracy. Despite these advancements, DFT approaches cannot be systematically improved, leading to the need for estimating errors from bracketing physical descriptions and addressing the delocalization error.
How does interaction detection improve prediction and interpretability of ensemble models?5 answersInteraction detection improves prediction and interpretability of ensemble models by revealing the structure and feature interactions embedded in the models. It helps gain insight into the complex black-box models and understand their functioning. By detecting feature interactions, the models become more interpretable, allowing researchers to understand the relationships between different variables and how they contribute to the predictions. This improves the transparency of the models and helps in explaining the logic behind the predictions. Additionally, interaction detection enhances the prediction performance of ensemble models by selecting more informative features and improving the overall accuracy.
How can we make 3D modeling more efficient?5 answersТрехмерное моделирование можно повысить, используя передовые методы и технологии. Один из подходов заключается в использовании возможностей дополненной реальности (AR) для улучшения понимания трехмерных моделей]. Внедрение дополненной реальности позволяет проецировать форму моделей в трехмерном формате на мобильные устройства или ПК, что обеспечивает более эффективный метод передачи формы моделей]. Кроме того, использование программного обеспечения для сшивания изображений и рендеринга трехмерной графики может упростить процесс моделирования, сделав его более удобным и экономичным]. Другой метод заключается в использовании каскадного анализа S-параметров для анализа целостности сигналов с высокой скоростью передачи данных сложных многослойных печатных плат (PCB)]. Эта методология обеспечивает эффективное и точное построение для трехмерного моделирования структур печатных плат, повышая эффективность процесса моделирования]. Комбинируя эти подходы, 3D-моделирование можно сделать более эффективным и результативным в различных областях].