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| Hundred-Dollar, Hundred-Digit Challenge | |
|---|---|
| Name | Hundred-Dollar, Hundred-Digit Challenge |
| Founder | Scott Aaronson |
| Established | 1999 |
| Location | Online |
| Prize | $100 |
| Discipline | Computational mathematics |
Hundred-Dollar, Hundred-Digit Challenge The Hundred-Dollar, Hundred-Digit Challenge was a public computation contest that invited participants to compute a specified one-hundred-digit decimal expansion to high precision. Initiated by Scott Aaronson and hosted on online forums associated with Mathematica and computational mathematics communities, the contest attracted contributors from across academic institutions such as MIT, Princeton University, University of Cambridge, and research groups at IBM and Microsoft Research. Participants included professional mathematicians, numerical analysts, and hobbyists connected to projects like GIMPS, Project Euler, and communities around software such as Maple and MATLAB.
The contest originated in the late 1990s amid renewed interest in high-precision computation driven by milestones like computations by David Bailey and collaborations involving Richard Brent, Yasumasa Kanada, and teams at University of Tokyo. Influences included historical high-precision efforts associated with John Machin-type formulas, work by Srinivasa Ramanujan, and algorithmic advances from researchers at Bell Labs and Los Alamos National Laboratory. The organizer drew on conversations with contributors active in online communities hosted by usenet groups and the Wolfram Research ecosystem, aiming to create a light-hearted but technically rigorous target for arbitrary-precision arithmetic libraries maintained by teams at GNU Project, Netlib, and commercial vendors like Intel.
The rules specified computation of a particular transcendental value to one hundred correct decimal places, with submission protocols modeled on verification procedures used by projects such as GIMPS and peer-reviewed reports by teams at NIST and MPI research groups. Entrants were required to provide reproducible code, provenance similar to standards from ACM and SIAM, and independent verification by alternate software such as Maple, Mathematica, or libraries from Boost. The modest monetary prize echoed smaller awards in the tradition of prizes like the Million-dollar Millennium Prize Problems in spirit, while encouraging openness and replication practiced at institutions like Stanford University, Harvard University, and Caltech.
Competitors employed algorithms and numerical techniques developed by authorities such as G. H. Hardy, Alan Turing, and algorithm designers at Bell Labs and IBM Research. Methods included binary splitting, fast Fourier transform (FFT) convolution routines popularized by work at MIT and Princeton University, and multiprecision libraries originating from projects like MPFR, GMP, and implementations by contributors affiliated with CNRS and ETH Zurich. Verification strategies used interval arithmetic inspired by work at Los Alamos National Laboratory and analytic identities from classical sources such as Euler and Gauss, while optimization leveraged hardware-specific instructions from Intel and parallel frameworks reminiscent of research at Argonne National Laboratory.
Notable submissions came from individuals and groups connected to academic centers including University of Oxford, University of California, Berkeley, Imperial College London, and corporate research labs like Microsoft Research and IBM Research. Submissions used toolchains based on Mathematica, Maple, PARI/GP, and bespoke code leveraging MPFR and GMP; contributors cited verification techniques similar to those used by Yasumasa Kanada and David Bailey. Some entries included peer commentary from experts at Princeton University and Stanford University, while community validation occurred on platforms frequented by members of Project Euler and Stack Overflow-linked forums.
Though modest in its financial reward, the contest influenced teaching and outreach at universities including MIT, Harvard University, and University of Cambridge by demonstrating reproducible computational practice promoted by societies like SIAM and conferences such as SIGGRAPH and NeurIPS for numerical reproducibility. It highlighted the practical use of libraries from GNU Project and standards advocated by ACM and inspired hobbyist collaborations similar to GIMPS and distributed efforts coordinated through repositories like GitHub. Subsequent high-precision projects at NIST, MPI, and national laboratories referenced this culture of community verification and open submission.
Critics from academic circles at Princeton University, Columbia University, and elsewhere argued that the contest emphasized computational showmanship over theoretical insight, echoing debates seen in contexts involving awards like the Clay Mathematics Institute prizes. Questions were raised about reproducibility when proprietary software such as Mathematica or platform-specific optimizations from Intel were used, paralleling controversies in reproducible research discussed at institutions like Stanford University and organizations like the ACM. Debates also invoked historical tensions between experimental computation advocates exemplified by Srinivasa Ramanujan-style intuition and formalist perspectives from scholars associated with Cambridge University and Princeton University.
Category:Mathematics competitions