A team of one undergraduate, two mathematics graduate students, one
continuing education student and two faculty members from the
Department of Mathematical Sciences at the University of Delaware
scored a perfect 100 in Prof. Nick Trefethen's "100-Dollar, 100-Digit
Challenge." The challenge first appeared in the January/February 2002
issue of SIAM News. The Challenge consisted of ten questions for
which there was no known way to express the solution in terms of
elementary quantities. There were ten questions, and the challenge was
to find the first ten digits for each question. Prof. Trefethen's
original posting stated that he would be impressed with any team that
found 50 correct digits. A copy of the original article is posted on
the SIAM web site.
Prof. Trefethen's web site has a list of the other teams earning
perfect scores as well as the five second place winners who score 99's.
At the conclusion of the contest, twenty teams submitted perfect
scores. The University of Delaware team was recognized as one of
three to receive the $100 reward because the solution was the product
of a unique collaboration between undergraduates, graduates and
At the time of the original posting, Profs. Toby Driscoll and Lou
Rossi were teaching graduate and undergraduate numerical analysis
courses and sought to spark more interest in the topic by answering
the challenge. Soon, other students in the department saw the
problems and were drawn into the group. Thus, continuing education
student Jonathan Leighton, undergraduate Eli Faulkner, and graduate
students Carl DeVore, and Sven Reichard joined the core group.
Interestingly, the only numerical analysts on the team were faculty
advisors Driscoll and Rossi. Eli Faulkner is interested in topology.
Graduate students DeVore and Reichard are candidates in the discrete
mathematics group. Jon Leighton has a variety of interests in applied
mathematics and solid mechanics.
The team quickly found that direct numerical attacks on several of the
problems would require prohibitive amounts of CPU time. Some problems
featured very slowly converging series or very large matrices. Other
problems were dangerously close or beyond the limits of double
precision arithmetic. While the team made heavy use of mathematical
software including Maple and Matlab, it was insight and craftiness
that transformed the inaccessible into the routine in almost every
problem. In the end, all of the team's solutions required at most a
few minutes of CPU time.
© 2002, Department of Mathematical Sciences
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