Hydropyrolysis: implications for radiocarbon pre-treatment and characterization of Black Carbon

Charcoal is the result of natural and anthropogenic burning events, when biomass is exposed to elevated temperatures under conditions of restricted oxygen. This process produces a range of materials, collectively known as pyrogenic carbon, the most inert fraction of which is known as Black Carbon (BC). BC degrades extremely slowly, and is resistant to diagenetic alteration involving the addition of exogenous carbon making it a useful target substance for radiocarbon dating particularly of more ancient samples, where contamination issues are critical. We present results of tests using a new method for the quantification and isolation of BC, known as hydropyrolysis (hypy). Results show controlled reductive removal of non-BC organic components in charcoal samples, including lignocellulosic and humic material. The process is reproducible and rapid, making hypy a promising new approach not only for isolation of purified BC for 14C measurement but also in quantification of different labile and resistant sample C fractions

A weakly stable algorithm for general Toeplitz systems

We show that a fast algorithm for the QR factorization of a Toeplitz or Hankel matrix A is weakly stable in the sense that R^T.R is close to A^T.A. Thus, when the algorithm is used to solve the semi-normal equations R^T.Rx = A^Tb, we obtain a weakly stable method for the solution of a nonsingular Toeplitz or Hankel linear system Ax = b. The algorithm also applies to the solution of the full-rank Toeplitz or Hankel least squares problem.Comment: 17 pages. An old Technical Report with postscript added. For further details, see http://wwwmaths.anu.edu.au/~brent/pub/pub143.htm

Oracle-based optimization applied to climate model calibration

In this paper, we show how oracle-based optimization can be effectively used for the calibration of an intermediate complexity climate model. In a fully developed example, we estimate the 12 principal parameters of the C-GOLDSTEIN climate model by using an oracle- based optimization tool, Proximal-ACCPM. The oracle is a procedure that finds, for each query point, a value for the goodness-of-fit function and an evaluation of its gradient. The difficulty in the model calibration problem stems from the need to undertake costly calculations for each simulation and also from the fact that the error function used to assess the goodness-of-fit is not convex. The method converges to a Fbest fit_ estimate over 10 times faster than a comparable test using the ensemble Kalman filter. The approach is simple to implement and potentially useful in calibrating computationally demanding models based on temporal integration (simulation), for which functional derivative information is not readily available

Introduction to Communication Avoiding Algorithms for Direct Methods of Factorization in Linear Algebra

International audienceModern, massively parallel computers play a fundamental role in a large and rapidly growing number of academic and industrial applications. However, extremely complex hardware architectures, which these computers feature, effectively prevent most of the existing algorithms to scale up to a large number of processors. Part of the reason behind this is the exponentially increasing divide between the time required to communicate a floating-point number between two processors and the time needed to perform a single floating point operation by one of the processors. Previous investigations have typically aimed at overlapping as much as possible communication with computation. While this is important, the improvement achieved by such an approach is not sufficient. The communication problem needs to be addressed also directly at the mathematical formulation and the algorithmic design level. This requires a shift in the way the numerical algorithms are devised, which now need to reduce, or even minimize when possible, the number of communication instances. Communication avoiding algorithms provide such a perspective on designing algorithms that minimize communication in numerical linear algebra. In this document we describe some of the novel numerical schemes employed by those communication avoiding algorithms, with a particular focus on direct methods of factorization

Euclidean Distance Matrices and Applications

Over the past decade, Euclidean distance matrices, or EDMs, have been receiving increased attention for two main reasons. The first reason is that the many applications of EDMs, such as molecular conformation in bioinformatics, dimensionality reduction in machine learning and statistics, and especiall