Time- and Space-Efficient Evaluation of Some Hypergeometric Constants

The currently best known algorithms for the numerical evaluation of hypergeometric constants such as $\zeta(3)$ to $d$ decimal digits have time complexity $O(M(d) \log^2 d)$ and space complexity of $O(d \log d)$ or $O(d)$. Following work from Cheng, Gergel, Kim and Zima, we present a new algorithm with the same asymptotic complexity, but more efficient in practice. Our implementation of this algorithm improves slightly over existing programs for the computation of $\pi$, and we announce a new record of 2 billion digits for $\zeta(3)$

Analytical expressions and numerical evaluation of the luminosity distance in a flat cosmology

Accurate and efficient methods to evaluate cosmological distances are an important tool in modern precision cosmology. In a flat $\Lambda$CDM cosmology, the luminosity distance can be expressed in terms of elliptic integrals. We derive an alternative and simple expression for the luminosity distance in a flat $\Lambda$CDM based on hypergeometric functions. Using a timing experiment we compare the computation time for the numerical evaluation of the various exact formulae, as well as for two approximate fitting formulae available in the literature. We find that our novel expression is the most efficient exact expression in the redshift range $z\gtrsim1$. Ideally, it can be combined with the expression based on Carlson's elliptic integrals in the range $z\lesssim1$ for high precision cosmology distance calculations over the entire redshift range. On the other hand, for practical work where relative errors of about 0.1% are acceptable, the analytical approximation proposed by Adachi & Kasai (2012) is a suitable alternative.Comment: 4 pages, 1 figure, accepted for publication in MNRA

Evaluating parametric holonomic sequences using rectangular splitting

We adapt the rectangular splitting technique of Paterson and Stockmeyer to the problem of evaluating terms in holonomic sequences that depend on a parameter. This approach allows computing the $n$-th term in a recurrent sequence of suitable type using $O(n^{1/2})$ "expensive" operations at the cost of an increased number of "cheap" operations. Rectangular splitting has little overhead and can perform better than either naive evaluation or asymptotically faster algorithms for ranges of $n$ encountered in applications. As an example, fast numerical evaluation of the gamma function is investigated. Our work generalizes two previous algorithms of Smith.Comment: 8 pages, 2 figure

Covariant Compton Scattering Kernel in General Relativistic Radiative Transfer

A covariant scattering kernel is a core component in any self-consistent general relativistic radiative transfer formulation in scattering media. An explicit closed-form expression for a covariant Compton scattering kernel with a good dynamical energy range has unfortunately not been available thus far. Such an expression is essential to obtain numerical solutions to the general relativistic radiative transfer equations in complicated astrophysical settings where strong scattering effects are coupled with highly relativistic flows and steep gravitational gradients. Moreover, this must be performed in an efficient manner. With a self-consistent covariant approach, we have derived a closed-form expression for the Compton scattering kernel for arbitrary energy range. The scattering kernel and its angular moments are expressed in terms of hypergeometric functions, and their derivations are shown explicitly in this paper. We also evaluate the kernel and its moments numerically, assessing various techniques for their calculation. Finally, we demonstrate that our closed-form expression produces the same results as previous calculations, which employ fully numerical computation methods and are applicable only in more restrictive settings.Comment: 29 pages, 10 figures, 2 tables; Accepted for publication in MNRA

Recursive Estimation of Orientation Based on the Bingham Distribution

Directional estimation is a common problem in many tracking applications. Traditional filters such as the Kalman filter perform poorly because they fail to take the periodic nature of the problem into account. We present a recursive filter for directional data based on the Bingham distribution in two dimensions. The proposed filter can be applied to circular filtering problems with 180 degree symmetry, i.e., rotations by 180 degrees cannot be distinguished. It is easily implemented using standard numerical techniques and suitable for real-time applications. The presented approach is extensible to quaternions, which allow tracking arbitrary three-dimensional orientations. We evaluate our filter in a challenging scenario and compare it to a traditional Kalman filtering approach