9,560 research outputs found
Developing a Mathematical Model for Bobbin Lace
Bobbin lace is a fibre art form in which intricate and delicate patterns are
created by braiding together many threads. An overview of how bobbin lace is
made is presented and illustrated with a simple, traditional bookmark design.
Research on the topology of textiles and braid theory form a base for the
current work and is briefly summarized. We define a new mathematical model that
supports the enumeration and generation of bobbin lace patterns using an
intelligent combinatorial search. Results of this new approach are presented
and, by comparison to existing bobbin lace patterns, it is demonstrated that
this model reveals new patterns that have never been seen before. Finally, we
apply our new patterns to an original bookmark design and propose future areas
for exploration.Comment: 20 pages, 18 figures, intended audience includes Artists as well as
Computer Scientists and Mathematician
Generating toric noncommutative crepant resolutions
We present an algorithm that finds all toric noncommutative crepant
resolutions of a given toric 3-dimensional Gorenstein singularity. The
algorithm embeds the quivers of these algebras inside a real 3-dimensional
torus such that the relations are homotopy relations. One can project these
embedded quivers down to a 2-dimensional torus to obtain the corresponding
dimer models. We discuss some examples and use the algorithm to show that all
toric noncommutative crepant resolutions of a finite quotient of the conifold
singularity can be obtained by mutating one basic dimer model. We also discuss
how this algorithm might be extended to higher dimensional singularities
Predictability of evolutionary trajectories in fitness landscapes
Experimental studies on enzyme evolution show that only a small fraction of
all possible mutation trajectories are accessible to evolution. However, these
experiments deal with individual enzymes and explore a tiny part of the fitness
landscape. We report an exhaustive analysis of fitness landscapes constructed
with an off-lattice model of protein folding where fitness is equated with
robustness to misfolding. This model mimics the essential features of the
interactions between amino acids, is consistent with the key paradigms of
protein folding and reproduces the universal distribution of evolutionary rates
among orthologous proteins. We introduce mean path divergence as a quantitative
measure of the degree to which the starting and ending points determine the
path of evolution in fitness landscapes. Global measures of landscape roughness
are good predictors of path divergence in all studied landscapes: the mean path
divergence is greater in smooth landscapes than in rough ones. The
model-derived and experimental landscapes are significantly smoother than
random landscapes and resemble additive landscapes perturbed with moderate
amounts of noise; thus, these landscapes are substantially robust to mutation.
The model landscapes show a deficit of suboptimal peaks even compared with
noisy additive landscapes with similar overall roughness. We suggest that
smoothness and the substantial deficit of peaks in the fitness landscapes of
protein evolution are fundamental consequences of the physics of protein
folding.Comment: 14 pages, 7 figure
Constructs and evaluation strategies for intelligent speculative parallelism - armageddon revisited
This report addresses speculative parallelism (the assignment of spare processing resources to tasks which are not known to be strictly required for the successful completion of a computation) at the user and application level. At this level, the execution of a program is seen
as a (dynamic) tree —a graph, in general. A solution for a problem is a traversal of this graph from the initial state to a node known to be the answer. Speculative parallelism then represents the assignment of resources to múltiple branches of this graph even if they are not positively known to be on the path to a solution. In highly non-deterministic programs the branching factor can be very high and a naive assignment will very soon use up all the
resources. This report presents work assignment strategies other than the usual depth-first and breadth-first. Instead, best-first strategies are used. Since their definition is application-dependent, the application language contains primitives that allow the user (or application programmer) to a) indÃcate when intelligent OR-parallelism should be used; b) provide the functions that define "best," and c) indÃcate when to use them.
An abstract architecture enables those primitives to perform the search in a "speculative" way, using several processors, synchronizing them, killing the siblings of the path leading to the answer, etc. The user is freed from worrying about these interactions. Several search strategies are proposed and their implementation issues are addressed. "Armageddon," a global pruning method, is introduced, together with both a software and a hardware implementation for it. The concepts exposed are applicable to áreas of Artificial Intelligence such as extensive expert systems, planning, game playing, and in general to large search problems. The proposed strategies, although
showing promise, have not been evaluated by simulation or experimentation
Rapid Mixing for Lattice Colorings with Fewer Colors
We provide an optimally mixing Markov chain for 6-colorings of the square
lattice on rectangular regions with free, fixed, or toroidal boundary
conditions. This implies that the uniform distribution on the set of such
colorings has strong spatial mixing, so that the 6-state Potts antiferromagnet
has a finite correlation length and a unique Gibbs measure at zero temperature.
Four and five are now the only remaining values of q for which it is not known
whether there exists a rapidly mixing Markov chain for q-colorings of the
square lattice.Comment: Appeared in Proc. LATIN 2004, to appear in JSTA
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