On the Computation of High Order Rys Quadrature Weights and Nodes

Since its introduction in 1976, the Rys Quadrature method has proven a very attractive method for evaluating electron repulsion integrals for calculations using Gaussian type orbitals. Since then, there have been considerable refinements of the method, but at it's core, Gaussian weights and nodes are used to exactly evaluate using a numerical approach to the transform integral. One of the powers of the Rys Quadrature method is the relative ease in evaluating integrals involving functions of high angular momentum. In this work we report on the complete resolution of these numerical difficulties, and we have easily computed accurate quadrature weights and nodes up to order 101. All calculations were carried out using 128-bit precision

Efficient calculation of molecular integrals over London atomic orbitals

The use of London atomic orbitals (LAOs) in a non-perturbative manner enables the determination of gauge-origin invariant energies and properties for molecular species in arbitrarily strong magnetic fields. Central to the efficient implementation of such calculations for molecular systems is the evaluation of molecular integrals, particularly the electron repulsion integrals (ERIs). We present an implementation of several different algorithms for the evaluation of ERIs over Gaussian-type LAOs at arbitrary magnetic field strengths. The efficiency of generalized McMurchie-Davidson (MD), Head-Gordon-Pople (HGP) and Rys quadrature schemes is compared. For the Rys quadrature implementation, we avoid the use of high precision arithmetic and interpolation schemes in the computation of the quadrature roots and weights, enabling the application of this algorithm seamlessly to a wide range of magnetic fields. The efficiency of each generalised algorithm is compared by numerical application, classifying the ERIs according to their total angular momenta and evaluating their performance for primitive and contracted basis sets. In common with zero-field integral evaluation, no single algorithm is optimal for all angular momenta thus a simple mixed scheme is put forward, which selects the most efficient approach to calculate the ERIs for each shell quartet. The mixed approach is significantly more efficient than the exclusive use of any individual algorithm

New Multithreaded Hybrid CPU/GPU Approach to Hartree−Fock

In this article, a new multithreaded Hartree–Fock CPU/GPU method is presented which utilizes automatically generated code and modern C++ techniques to achieve a significant improvement in memory usage and computer time. In particular, the newly implemented Rys Quadrature and Fock Matrix algorithms, implemented as a stand-alone C++ library, with C and Fortran bindings, provides up to 40% improvement over the traditional Fortran Rys Quadrature. The C++ GPU HF code provides approximately a factor of 17.5 improvement over the corresponding C++ CPU code

Truncated Hermite polynomials

We consider the family of polynomials $p_{n}\left( x;z\right) ,$ orthogonal with respect to the inner product $$\left\langle f,g\right\rangle = \int_{-z}^{z} f\left( x\right) g\left( x\right) e^{-x^{2}} \,dx.$$ We show some properties about the coefficients in their 3-term recurrence relation, connections between $p_{n}\left( x;z\right)$ and $p_{n}^{\prime}\left( x;z\right) ,$ a second order differential equation satisfied by $p_{n}\left( x;z\right) ,$ and an electrostatic interpretation of their zeros.Comment: 37 page

An efficient computation of parameters in the Rys quadrature formula

We present an efficient procedure for constructing the so-called Gauss-Rys quadrature formulas and the corresponding polynomials orthogonal on (−1, 1) with respect to the even weight function w(t; x) = exp(−xt2), where x a positive parameter. Such GaussRys quadrature formulas were investigated earlier e.g. by M. Dupuis, J. Rys, H.F. King [J. Chem. Phys. 65 (1976), 111 − 116; J. Comput. Chem. 4 (1983), 154 − 157], D.W. Schwenke [Comput. Phys. Comm. 185 (2014), 762 − 763], and B.D. Shizgal [Comput. Theor. Chem. 1074 (2015), 178 − 184], and were used to evaluate electron repulsion integrals in quantum chemistry computer codes. The approach in this paper is based to a transformation of quadratures on (−1, 1) with N nodes to ones on (0, 1) with only [(N + 1)/2] nodes and their construction. The method of modified moments is used for getting recurrence coefficients. Numerical experiments are included.Bulletin de l'Académie serbe des sciences. Classe des sciences mathématiques et naturelles. Sciences mathématiques. - 43, 151 (2018

Neural networks for optical channel equalization in high speed communication systems

La demande future de bande passante pour les données dépassera les capacités des systèmes de communication optique actuels, qui approchent de leurs limites en raison des limitations de la bande passante électrique des composants de l’émetteur. L’interférence intersymbole (ISI) due à cette limitation de bande est le principal facteur de dégradation pour atteindre des débits de données élevés. Dans ce mémoire, nous étudions plusieurs techniques de réseaux neuronaux (NN) pour combattre les limites physiques des composants de l’émetteur pilotés à des débits de données élevés et exploitant les formats de modulation avancés avec une détection cohérente. Notre objectif principal avec les NN comme égaliseurs de canaux ISI est de surmonter les limites des récepteurs optimaux conventionnels, en fournissant une complexité évolutive moindre et une solution quasi optimale. Nous proposons une nouvelle architecture bidirectionnelle profonde de mémoire à long terme (BiLSTM), qui est efficace pour atténuer les graves problèmes d’ISI causés par les composants à bande limitée. Pour la première fois, nous démontrons par simulation que notre BiLSTM profonde proposée atteint le même taux d’erreur sur les bits(TEB) qu’un estimateur de séquence à maximum de vraisemblance (MLSE) optimal pour la modulation MDPQ. Les NN étant des modèles pilotés par les données, leurs performances dépendent fortement de la qualité des données d’entrée. Nous démontrons comment les performances du BiLSTM profond réalisable se dégradent avec l’augmentation de l’ordre de modulation. Nous examinons également l’impact de la sévérité de l’ISI et de la longueur de la mémoire du canal sur les performances de la BiLSTM profonde. Nous étudions les performances de divers canaux synthétiques à bande limitée ainsi qu’un canal optique mesuré à 100 Gbaud en utilisant un modulateur photonique au silicium (SiP) de 35 GHz. La gravité ISI de ces canaux est quantifiée grâce à une nouvelle vue graphique des performances basée sur les écarts de performance de base entre les solutions optimales linéaires et non linéaires classiques. Aux ordres QAM supérieurs à la QPSK, nous quantifions l’écart de performance BiLSTM profond par rapport à la MLSE optimale à mesure que la sévérité ISI augmente. Alors qu’elle s’approche des performances optimales de la MLSE à 8QAM et 16QAM avec une pénalité, elle est capable de dépasser largement la solution optimale linéaire à 32QAM. Plus important encore, l’avantage de l’utilisation de modèles d’auto-apprentissage comme les NN est leur capacité à apprendre le canal pendant la formation, alors que la MLSE optimale nécessite des informations précises sur l’état du canal.The future demand for the data bandwidth will surpass the capabilities of current optical communication systems, which are approaching their limits due to the electrical bandwidth limitations of the transmitter components. Inter-symbol interference (ISI) due to this band limitation is the major degradation factor to achieve high data rates. In this thesis, we investigate several neural network (NN) techniques to combat the physical limits of the transmitter components driven at high data rates and exploiting the advanced modulation formats with coherent detection. Our main focus with NNs as ISI channel equalizers is to overcome the limitations of conventional optimal receivers, by providing lower scalable complexity and near optimal solution. We propose a novel deep bidirectional long short-term memory (BiLSTM) architecture, that is effective in mitigating severe ISI caused by bandlimited components. For the first time, we demonstrate via simulation that our proposed deep BiLSTM achieves the same bit error rate (BER) performance as an optimal maximum likelihood sequence estimator (MLSE) for QPSK modulation. The NNs being data-driven models, their performance acutely depends on input data quality. We demonstrate how the achievable deep BiLSTM performance degrades with the increase in modulation order. We also examine the impact of ISI severity and channel memory length on deep BiLSTM performance. We investigate the performances of various synthetic band-limited channels along with a measured optical channel at 100 Gbaud using a 35 GHz silicon photonic(SiP) modulator. The ISI severity of these channels is quantified with a new graphical view of performance based on the baseline performance gaps between conventional linear and nonlinear optimal solutions. At QAM orders above QPSK, we quantify deep BiLSTM performance deviation from the optimal MLSE as ISI severity increases. While deep BiLSTM approaches the optimal MLSE performance at 8QAM and 16QAM with a penalty, it is able to greatly surpass the linear optimal solution at 32QAM. More importantly, the advantage of using self learning models like NNs is their ability to learn the channel during the training, while the optimal MLSE requires accurate channel state information

Efficient calculation of molecular integrals over London atomic orbitals

The use of London atomic orbitals (LAOs) in a non-perturbative manner enables the determination of gauge-origin invariant energies and properties for molecular species in arbitrarily strong magnetic fields. Central to the efficient implementation of such calculations for molecular systems is the evaluation of molecular integrals, particularly the electron repulsion integrals (ERIs). We present an implementation of several different algorithms for the evaluation of ERIs over Gaussian-type LAOs at arbitrary magnetic field strengths. The efficiency of generalized McMurchie-Davidson (MD), Head-Gordon-Pople (HGP) and Rys quadrature schemes is compared. For the Rys quadrature implementation, we avoid the use of high precision arithmetic and interpolation schemes in the computation of the quadrature roots and weights, enabling the application of this algorithm seamlessly to a wide range of magnetic fields. The efficiency of each generalised algorithm is compared by numerical application, classifying the ERIs according to their total angular momenta and evaluating their performance for primitive and contracted basis sets. In common with zero-field integral evaluation, no single algorithm is optimal for all angular momenta thus a simple mixed scheme is put forward, which selects the most efficient approach to calculate the ERIs for each shell quartet. The mixed approach is significantly more efficient than the exclusive use of any individual algorithm

Numerical Representation of the Incomplete Gamma Function of Complex Argument

Various approaches to the numerical representation of the Incomplete Gamma Function F_m(z) for complex arguments z and small integer indexes m are compared with respect to numerical fitness (accuracy and speed). We consider power series, Laurent series, Gautschi's approximation to the Faddeeva function, classical numerical methods of treating the standard integral representation, and others not yet covered by the literature. The most suitable scheme is the construction of Taylor expansions around nodes of a regular, fixed grid in the z-plane, which stores a static matrix of higher derivatives. This is the obvious extension to a procedure often in use for real-valued z.Comment: REVTeX4, 48 pages, 16 PostScript figures. Corrected typos in Eqs. (46), (47) and on bottom p. 43. Added Ref [32