Abstracts
        Ian F. Blake, Dept. of Electrical and Computer 
          Engineering, University of Toronto
          Directions in Cryptography 
          The notion of a one-way function and their use in public key cryptography, 
          introduced in the mid-seventies, led the field of security in a variety 
          of directions. An area of particular interest is the effort to determine 
          the difficulty of certain mathematical tasks, such as integer factorization 
          and the modular discrete logarithm function. Additionally, the use of 
          such mathematical functions in the formulation and implementation of 
          protocols which achieve achieve useful communication functions, has 
          been an area of intense recent interest. This talk will address recent 
          progress on certain aspects of these two areas.
        Henri Darmon, Dept. of Mathematics and 
          Statistics, McGill University
          Elliptic curves and Kronecker's solution to Pell's equation 
          A celebrated 1865 paper of Kronecker describes how to solve Pell's equation 
          in terms of values of the Dedekind eta-function. I will describe his 
          approach, assuming no prior number theoretic background, and indicate 
          how it can be modified to construct rational points on elliptic curves 
          in terms of the modular symbols of Birch and Manin; the latter topic 
          is part of a work in progress with Massimo Bertolini.
        Ian Munro, University of Waterloo
          Succinct Data Structures
          Although computer memories, at all levels of the hierarchy, have grown 
          dramatically over the past few years, increased problem size continues 
          to outstrip this growth. Recently developed data compression techniques 
          attack one major aspect of the problem, but here we focus on structural 
          information: combinatorial objects such as trees, other classes of graphs, 
          permutations and the like. The interest is in representations that are 
          not only terse, but also permit the basic operations one would expect 
          on the underlying data type to be performed quickly without decoding 
          large portions of the data. We call such data structures succinct. The 
          archtypical example is the binary tree, whose usual representation requires 
          4n lg n bits, if we are to navigate up and down the tree and report 
          subtree size. The information theoretic minimum, however, is only about 
          2n bits. We present a representation requiring essentially this mimimal 
          space while supporting, in constant time, the natural operations used 
          in traversing a tree. The general approach is then applied to several 
          other structures to obtain optimal (or near optimal) space bounds while. 
        
        Keith J. Worsley, Dept. of Mathematics 
          and Statistics, McGill University
          The geometry of random images in astrophysics and brain mapping 
          The geometry in the title is not the geometry of lines and angles 
          but the geometry of topology, shape and knots. For example, galaxies 
          are not distributed randomly in the universe, but they tend to form 
          clusters, or sometimes strings, or even sheets of high galaxy density. 
          How can this be handled statistically? The Euler characteristic (EC) 
          of the set of high density regions has been used to measure the topology 
          of such shapes; it counts the number of connected components of the 
          set, minus the number of `holes', plus the number of `hollows'. Despite 
          its complex definition, the exact expectation of the EC can be found 
          for some simple models, so that observed EC can be compared with expected 
          EC to check the model. A similar problem arises in functional magnetic 
          resonance imaging (fMRI), where the EC is used to detect local increases 
          in brain activity due to an external stimulus. The famous Nash Embedding 
          Theorem helps us to extend these ideas to manifolds, so that we can 
          detect changes in brain shape via structure masking, surface extraction, 
          and 3D deformation fields. Finally, we look at some curious random fields 
          whose excursion sets are strings, and we show using the Siefert representation 
          that these strings can be knotted.
        back to New FRSC Day main page
        Audio and Slides 
          of Talks
        back to top