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Andreas Savin

Publications and source records attributed to Andreas Savin.

At least 19 recordsLinked to original sources

Correcting basis-set errors due to the absence of the electron-electron cusp using an adiabatic correction

This article proposes an analytical method to address the slow convergence of electronic structure calculations caused by the inability of finite one-particle basis sets to describe the electron-electron cusp. An equivalence is established between a calculation using a finite basis set with the physical Coulomb interaction and a calculation using a complete basis set with a model interaction (specifically, the error-function screened Coulomb potential characterized by a range-separation parameter $\mu$). By leveraging the adiabatic connection formalism, a simple, parameter-free correction formula is derived. It depends only on the on-top pair density and a locally defined range-separation parameter ($\mu$) derived from the basis set itself. This `adiabatic connection based basis-set error correction' (ABC) is derived from the asymptotic expansion of the wave function at large $\mu$ for small inter-electronic distances. Therefore it is applicable to both ground and excited states without the restriction imposed by the Hohenberg-Kohn theorem. Numerical tests illustrate that the method achieves chemical accuracy using smaller basis sets than typically required.

physics.chem-ph

Long-range configuration interaction with an ab initio short-range correction and an asymptotic lower bound

Short-range corrections to long-range selected configuration interaction calculations are derived from perturbation theory considerations and applied to harmonium (with two to six electrons for some low-lying states). No fitting to reference data is used, and the method is applicable to ground and excited states. The formulas derived are rigorous when the physical interaction is approached. In this regime, the second-order expression provides a lower bound to the long-range full configuration interaction energy. A long-range/short-range separation of the interaction between electrons at a distance of the order of one atomic unit provides total energies within chemical accuracy, and, for the systems studied, provide better results than short-range density functional approximations.

physics.chem-ph

A modified expression for the Hamiltonian expectation value exploiting the short-range behavior of the wave function

The expectation value of the Hamiltonian using a model wave function is widely used to estimate the eigenvalues of electronic Hamiltonians. We explore here a modified formula for models based on long-range interaction. It scales differently the singlet and triplet component of the repulsion between electrons not present in the model (its short-range part). The scaling factors depend uniquely on the parameter used in defining the model interaction, and are constructed using only exact properties. We show results for the ground states and low-lying excited states of Harmonium with two to six electrons. We obtain important improvements for the estimation of the exact energy, not only over the model energy, but also over the expectation value of the Hamiltonian.

physics.chem-ph

Exploring the role of mean-field potentials and short-range wave function behavior in the adiabatic connection

In this article, we explore the construction of Hamiltonians with long-range interactions and their corrections using the short-range behavior of the wave function. A key aspect of our investigation is the examination of the one-particle potential, kept constant in our previous work, and the effects of its optimization on the adiabatic connection. Our methodology involves the use of a parameter-dependent potential dependent on a single parameter to facilitate practical computations. We analyze the energy errors and densities in a two-electron system (harmonium) under various conditions, employing different confinement potentials and interaction parameters. The study reveals that while the mean-field potential improves the expectation value of the physical Hamiltonian, it does not necessarily improve the energy of the system within the bounds of chemical accuracy. We also delve into the impact of density variations in adiabatic connections, challenging the common assumption that a mean field improves results. Our findings indicate that as long as energy errors remain within chemical accuracy, the mean field does not significantly outperform a bare potential. This observation is attributed to the effectiveness of corrections based on the short-range behavior of the wave function, a universal characteristic that diminishes the distinction between using a mean field or not.

physics.chem-ph

Second-order adiabatic connection: The theory and application to two electrons in a parabolic confinement

The adiabatic connection formalism, usually based on the first-order perturbation theory, has been generalized to an arbitrary order. The generalization stems from the observation that the formalism can be derived from a properly arranged Taylor expansion. The second-order theory is developed in detail and applied to the description of two electrons in a parabolic confinement (harmonium). A significant improvement relative to the first-order theory has been obtained.

physics.chem-ph

Erfonium: A Hooke Atom with Soft Interaction Potential

Properties of erfonium, a Hooke atom with the Coulomb interaction potential $1/r$ replaced by a non-singular $\text{erf}(\mu r)/r$ potential are investigated. The structure of the Hooke atom potential and properties of its energy spectrum, relative to the ones of the spherical harmonic oscillator and of harmonium, are analyzed. It is shown, that at a certain value of $\mu$ the system changes its behavior from a harmonium-like regime to a harmonic-oscillator-like regime.

physics.chem-ph

Correcting models with long-range electron interaction using generalized cusp conditions

Sources of energy errors resulting from the replacement of the physical Coulomb interaction by its long-range $\mathrm{erfc}(\mu r)/r$ approximation are explored. It is demonstrated that the results can be dramatically improved and the range of $\mu$ giving energies within chemical accuracy limits significantly extended, if the generalized cusp conditions are used to represent the wave function at small $r$. The numerical results for two-electron harmonium are presented and discussed.

physics.chem-ph

What is the number of electrons in a spatial domain?

We like to attribute a number of electrons to spatial domains (atoms, bonds, ...). However, as a rule, the number of electrons in a spatial domain is not a sharp number. We thus study probabilities for having any number of electrons (between 0 and the total number of electrons in the system) in a given spatial domain. We show that by choosing a domain that maximizes a chosen probability (or is close to it), one obtains higher probabilities for chemically relevant regions. The probability to have a given electronic arrangement, - for example, by attributing a number of electrons to an atomic shell - can be low. It remains so even in the "best" case, i.e, if the spatial domain is chosen to maximize the chosen probability. In other words, the number of electrons in a spatial region significantly fluctuates. The freedom of choosing the number of electrons we are interested in shows that a "chemical" question is not always well-posed. We show it using as an example the KrF2 molecule.

physics.chem-ph

Two-particle coalescence conditions revisited

The notion of the n-th order local energy, generated by the n-th power of the Hamiltonian, has been introduced. The n-th order two-particle coalescence conditions have been derived from the requirements that the n-th order local energy at the coalescence point is non-singular and equal to the n-th power of the Hamiltonian eigenvalue. The first condition leads to energy-independent constraints. The second one is state-specific. The analysis has been done using a radial, one-dimensional, model Hamiltonian. The model is valid in the asymptotic region of r ~ 0. The coalescence conditions set the relations between the expansion coefficients of the radial wave function into a power series with respect to r.

physics.chem-ph

The effect of uncertainty on building blocks in molecules

Probabilities to find a chosen number of electrons in flexible domains of space are calculated for highly correlated wave functions. Quantum mechanics can produce higher probabilities for chemically relevant arrangements of electrons in these regions. However, the probability to have a given arrangement, e.g., that corresponding to chemical formulas (bonds or atoms), is low although being often maximal. Like in valence bond theory, it is useful to consider alternative distributions of the electrons. Exchanges of electrons should be considered not only between atoms, but also between other types of regions, like those attributed to lone pairs. It is useful to have definitions flexible enough to allow the user to find the reference representations he considers most relevant. We tentatively suggest a tool (the effective number of parties) to help one make the choice.

physics.chem-ph

FLEIM: A stable, accurate and robust extrapolation method at infinity for computing the ground state of electronic Hamiltonians

The Kohn-Sham method uses a single model system, and corrects it by a density functional the exact user friendly expression of which is not known and is replaced by an approximated, usable, model. We propose to use instead more than one model system, and use a greedy extrapolation method to correct the results of the model systems. Evidently, there is a higher price to pay for it. However, there are also gains: within the same paradigm, e.g., excited states and physical properties can be obtained.

physics.chem-ph

Using the Gini coefficient to characterize the shape of computational chemistry error distributions

The distribution of errors is a central object in the assesment and benchmarking of computational chemistry methods. The popular and often blind use of the mean unsigned error as a benchmarking statistic leads to ignore distributions features that impact the reliability of the tested methods. We explore how the Gini coefficient offers a global representation of the errors distribution, but, except for extreme values, does not enable an unambiguous diagnostic. We propose to relieve the ambiguity by applying the Gini coefficient to mode-centered error distributions. This version can usefully complement benchmarking statistics and alert on error sets with potentially problematic shapes.

physics.chem-ph

On connecting density functional approximations to theory

Usually, density functional models are considered approximations to density functional theory, However, there is no systematic connection between the two, and this can make us doubt about a linkage. This attitude can be further enforced by the vagueness of the argumentation for using spin densities. Questioning the foundations of density functional models leads to a search for alternative explanations. Seeing them as using models for pair densities is one of them. Another is considering density functional approximations as a way to extrapolate results obtained in a model system to those of a corresponding physical one.

physics.chem-ph

Models and corrections: range separation for electronic interaction -- lessons from density functional theory

Model Hamiltonians with long-range interaction yield energies that are corrected taking into account the universal behavior of the electron-electron interaction at short range. Although the intention of the paper is to explore the foundations of using density functionals combined with range separation, the approximations presented can be used without them, as illustrated by a calculation on Harmonium. In the regime when the model system approaches the Coulomb system, they allow the calculation of ground states, excited states, and properties, without making use of the Hohenberg-Kohn theorem. Asymptotically, the technique is improvable, allows for error estimates that can validate the results. Some considerations for correcting the errors of finite basis sets in this spirit are also presented. Being related to the present understanding of density functional approximations, the results are comparable to those obtained with the latter, as long as these are accurate.

physics.chem-ph

Impact of non-normal error distributions on the benchmarking and ranking of Quantum Machine Learning models

Quantum machine learning models have been gaining significant traction within atomistic simulation communities. Conventionally, relative model performances are being assessed and compared using learning curves (prediction error vs. training set size). This article illustrates the limitations of using the Mean Absolute Error (MAE) for benchmarking, which is particularly relevant in the case of non-normal error distributions. We analyze more specifically the prediction error distribution of the kernel ridge regression with SLATM representation and L 2 distance metric (KRR-SLATM-L2) for effective atomization energies of QM7b molecules calculated at the level of theory CCSD(T)/cc-pVDZ. Error distributions of HF and MP2 at the same basis set referenced to CCSD(T) values were also assessed and compared to the KRR model. We show that the true performance of the KRR-SLATM-L2 method over the QM7b dataset is poorly assessed by the Mean Absolute Error, and can be notably improved after adaptation of the learning set.

physics.data-an

Acknowledging user requirements for accuracy in computational chemistry benchmarks

Computational chemistry has become an important complement to experimental measurements. In order to choose among the multitude of the existing approximations, it is common to use benchmark data sets, and to issue recommendations based on numbers such as mean absolute errors. We argue, using as an example band gaps calculated with density functional approximations, that a more careful study of the benchmark data is needed, stressing that the user's requirements play a role in the choice of an appropriate method. We also appeal to those who measure data capable of being used as a reference, to publish error estimates. We show how the latter can affect the judgment of approximations used in computational chemistry.

physics.chem-ph

Probabilistic performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. II. Applications

In the first part of this study (Paper I), we introduced the systematic improvement probability (SIP) as a tool to assess the level of improvement on absolute errors to be expected when switching between two computational chemistry methods. We developed also two indicators based on robust statistics to address the uncertainty of ranking in computational chemistry benchmarks: Pinv , the inversion probability between two values of a statistic, and Pr , the ranking probability matrix. In this second part, these indicators are applied to nine data sets extracted from the recent benchmarking literature. We illustrate also how the correlation between the error sets might contain useful information on the benchmark dataset quality, notably when experimental data are used as reference.

physics.chem-ph

Probabilistic performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. I. Theory

The comparison of benchmark error sets is an essential tool for the evaluation of theories in computational chemistry. The standard ranking of methods by their Mean Unsigned Error is unsatisfactory for several reasons linked to the non-normality of the error distributions and the presence of underlying trends. Complementary statistics have recently been proposed to palliate such deficiencies, such as quantiles of the absolute errors distribution or the mean prediction uncertainty. We introduce here a new score, the systematic improvement probability (SIP), based on the direct system-wise comparison of absolute errors. Independently of the chosen scoring rule, the uncertainty of the statistics due to the incompleteness of the benchmark data sets is also generally overlooked. However, this uncertainty is essential to appreciate the robustness of rankings. In the present article, we develop two indicators based on robust statistics to address this problem: P_{inv}, the inversion probability between two values of a statistic, and \mathbf{P}_{r}, the ranking probability matrix. We demonstrate also the essential contribution of the correlations between error sets in these scores comparisons.

stat.ME