Pål Dahle

The Dalton quantum chemistry program system

Dalton is a powerful general‐purpose program system for the study of molecular electronic structure at the Hartree–Fock, Kohn–Sham, multiconfigurational self‐consistent‐field, Møller–Plesset, configuration‐interaction, and coupled‐cluster levels of theory. Apart from the total energy, a wide variety of molecular properties may be calculated using these electronic‐structure models. Molecular gradients and Hessians are available for geometry optimizations, molecular dynamics, and vibrational studies, whereas magnetic resonance and optical activity can be studied in a gauge‐origin‐invariant manner. Frequency‐dependent molecular properties can be calculated using linear, quadratic, and cubic response theory. A large number of singlet and triplet perturbation operators are available for the study of one‐, two‐, and three‐photon processes. Environmental effects may be included using various dielectric‐medium and quantum‐mechanics/molecular‐mechanics models. Large molecules may be studied using linear‐scaling and massively parallel algorithms. Dalton is distributed at no cost from http://www.daltonprogram.org for a number of UNIX platforms.

Efficient parallel implementation of response theory: Calculations of the second hyperpolarizability of polyacenes

We describe an efficient parallel implementation of response theory for calculations of molecular properties, and demonstrate its performance by calculations on a series of polyacene molecules, fro ...

The Cotton–Mouton effect of liquid water. Part II: The semi-continuum model

We present gauge-origin independent calculations of the Cotton‐Mouton effect of liquid water. The liquid is represented by a semi-continuum model such that the central molecule is surrounded by its first solvation shell, which explicitly accounts for the strong interaction between the water molecule of interest and its closest neighbors. The long-range interactions with the solvent are modeled by a dielectric continuum surrounding the water molecule and the first solvation shell. We employ large basis sets, using London atomic orbitals in order to obtain gauge-origin independent results close to the Hartree‐Fock limit. It is demonstrated that the direct interaction between neighboring molecules leads to a large effect on the calculated Cotton‐Mouton constant, which undergoes a sign change from the gas to liquid phase, as observed previously for the linear electro-optical effect @K. V. Mikkelsen et al., J. Chem. Phys 102, 9362 ~1995!#. Our best estimate for the molar Cotton‐Mouton constant, 238.1i10 220 G 22 cm 3 mol 21 ~corrected for local field effects!, is in reasonable agreement with the experimental value of 2118(15)i10 220 G 22 cm 3 mol 21 . We expect that the remaining discrepancy is mainly due to an inadequate treatment of electron correlation.

Generalized integral-screening for efficient calculations of nonlinear optical properties of large molecules

We describe the implementation of integral screening in the integral-direct SCF calculation of cubic response functions. The screening is applied to all computational steps that involve the construction of Fock matrices or one-index transformed Fock matrices. We apply this implementation to study the length dependence of the polarizability and second hyperpolarizability of diphenylpolyenes. It is demonstrated that calculations of the second hyperpolarizability of molecules containing more than 140 atoms are now accessible by ab initio methods on a time scale that makes it of interest in real applications.

The Hartree–Fock magnetizability of C60

Abstract Using London atomic orbitals and a recent parallel implementation of our second-order ab initio property code, we have determined the Hartree–Fock limit for the magnetizability of C60 to be −359±5 ppm cgs, in excellent agreement with earlier basis-set limit extrapolations. Using diamagnetic exaltation as a criterion for aromaticity, our calculations show that C60 is an aromatic molecule with a relative diamagnetic exaltation greater than that of benzene.

Estimation of facies probabilities on the Snorre Field using geostatistical AVA inversion

We have done a geostatistical inversion of seismic data to facies probabilities. As a first step, we invert the seismic data for elastic parameters using the Bayesian AVA inversion method of Buland et al. (2003). Next, we use an analysis of the uncertainty in the posterior distribution to filter the elastic parameters given in well logs. By comparing these filtered well logs with facies logs, we establish a relationship between facies and seismic data. This relationship is combined with the elastic parameters from the inversion to estimate facies probabilities for the entire volume.

Fast and Accurate Approximation to Kriging Using Common Data Neighborhoods

Unknown values of a random field can be predicted from observed data using kriging. As data sets grow in size, the computation times become large. To facilitate kriging with large data sets, an approximation where the kriging is performed in sub-segments with common data neighborhoods has been developed. It is shown how the accuracy of the approximation can be controlled by increasing the common data neighborhood. For four different variograms, it is shown how large the data neighborhoods must be to get an accuracy below a chosen threshold, and how much faster these calculations are compared to the kriging where all data are used. Provided that variogram ranges are small compared to the domain of interest, kriging with common data neighborhoods provides excellent speed-ups (2–40) while maintaining high numerical accuracy. Results are presented both for data neighborhoods where the neighborhoods are the same for all sub-segments, and data neighborhoods where the neighborhoods are adapted to fit the data densities around the sub-segments. Kriging in sub-segments with common data neighborhoods is well suited for parallelization and the speed-up is almost linear in the number of threads. A comparison is made to the widely used moving neighborhood approach. It is demonstrated that the accuracy of the moving neighborhood approach can be poor and that computational speed can be slow compared to kriging with common data neighborhoods.

Integration of Seismic Data and Uncertainties in the Facies Model – Application to the Snorre Field

In this paper, we prove the benefit of a consistent and quantitative use of 3D seismic data to constrain the facies model built on a complex reservoir, Snorre, located in the Norwegian Sea. The workflow starts with the application of Bayesian seismic inversion to 3D angle stacks, allowing the estimation of elastic parameter probability distributions over the reservoir. Uncertainty decrease with respect to the prior model is quantified for each elastic parameter. The estimated uncertainties are then used input to design a filter which is applied to well logs to propagate seismic uncertainties in the next step: Seismic facies modeling. We use therefore a non-parametric probabilistic classification algorithm, supervised by the filtered well logs and blocked facies. The resulting sand and shale probabilities are then controlled at blind wells, with an overall match with facies proportions from wells around 70%. Finally, the probabilities are used as a quantitative 3D constraint to stochastic object-based channel modeling techniques. By drawing different realizations from this model, we prove that the use of seismic data allows better focusing the spatial distribution of the channels.

Explicit Electron Correlation by a Combined Use of Gaussian-Type Orbitals and Gaussian-Type Geminals

In MP2‐GGn theory, the second‐order Mo/ller–Plesset (MP2) energy is recovered by a combined Gaussian‐orbital—Gaussian‐geminal (GG) expansion of the first‐order wave function. While the restriction of geminals to doubly occupied orbital pairs (MP2‐GG0) provides a modest improvement on standard MP2 theory, their inclusion also in all singly‐excited (MP2‐GG1) and doubly‐excited (MP2‐GG2) pairs recovers essentially all of the correlation energy in small (double‐ and triple‐zeta) basis sets. For several small systems, our MP2‐GGn energies represent the best MP2 energies reported in the literature.

Geostatistical AVO Inversion On Smørbukk Sør

Seismic inversion has traditionally been treated as a deterministic problem. However, there are several uncertain aspects. There is noise in the seismic amplitude data, and the frequency resolution is limited, so neither high nor low frequencies can be resolved from the seismic data alone. Using a geostatistical approach to the problem of seismic inversion, the uncertainty may be treated in a consistent and robust way. We have used the Bayesian linearized AVO inversion method of Buland A. et al. (2003) to take the uncertainty in seismic data into account.