Can Computer Algebra be Liberated from its Algebraic Yoke ?

So far, the scope of computer algebra has been needlessly restricted to exact algebraic methods. Its possible extension to approximate analytical methods is discussed. The entangled roles of functional analysis and symbolic programming, especially the functional and transformational paradigms, are put forward. In the future, algebraic algorithms could constitute the core of extended symbolic manipulation systems including primitives for symbolic approximations.Comment: 8 pages, 2-column presentation, 2 figure

A mathematica‐based CAL matrix‐theory tutor for scientists and engineers

Under the TLTP initiative, the Mathematics Departments at Imperial College and Leeds University are jointly developing a CAL method directed at supplementing the level of mathematics of students entering science and engineering courses from diverse A‐level (or equivalent) backgrounds. The aim of the joint project is to maintain — even increase ‐ the number of students enrolling on such first‐year courses without lowering the courses’ existing mathematical standards

Parents and Children Together: Design and Implementation of Two Healthy Marriage Programs

The Parents and Children Together (PACT) evaluation, conducted by Mathematica Policy Research for the Office of Research, Planning, and Evaluation, Administration for Children and Families (ACF), U.S. Department of Health and Human Services, is examining a set of Healthy Marriage (HM) and Responsible Fatherhood (RF) grantees funded by ACF's Office of Family Assistance (OFA) in 2011. Recognizing that grantees' programs continue to grow and develop, the PACT evaluation aims to provide foundational information to guide ongoing and future program design and evaluation efforts, and to build the evidence base for programming

Symbolic Maximum Likelihood Estimation with Mathematica

Mathematica is a symbolic programming language that empowers the user to undertake complicated algebraic tasks. One such task is the derivation of maximum likelihood estimators, demonstrably an important topic in statistics at both the research and expository level. In this paper, a Mathematica package is provided that contains a function entitled SuperLog. This function utilises pattern-matching code that enhances Mathematica's ability to simplify expressions involving the natural logarithm of a product of algebraic terms. This enhancement to Mathematica's functionality can be of particular benefit for maximum likelihood estimation

Generating and using truly random quantum states in Mathematica

The problem of generating random quantum states is of a great interest from the quantum information theory point of view. In this paper we present a package for Mathematica computing system harnessing a specific piece of hardware, namely Quantis quantum random number generator (QRNG), for investigating statistical properties of quantum states. The described package implements a number of functions for generating random states, which use Quantis QRNG as a source of randomness. It also provides procedures which can be used in simulations not related directly to quantum information processing.Comment: 12 pages, 3 figures, see http://www.iitis.pl/~miszczak/trqs.html for related softwar

Excursions into FeynArts and FormCalc

Programming techniques which extend the capabilities of FeynArts and FormCalc are introduced and explained using examples from real applications.Comment: 5 pages, proceedings contribution to Loops and Legs 2006, Eisenach, German