sparse_2007_psc
sparse_2007_psc,
"Stalking the Wild Integral",
I gave a talk , to the
"Science for Lunch Bunch" (free pizza)
at the Pittsburgh Supercomputing Center, on 27 June 2007.
I also presented this talk to the MATH 2070 -
Numerical Methods in Scientific Computing class,
at the University of Pittsburgh,
23 November 2009.
A plain text abstract of the talk is available as
sparse_2007_psc.txt.
The following graphics files were used:
-
cc_1d.png,
PNG image of
the arrangement of Clenshaw Curtis abscissas in 1D.
-
cc_d2_o17x17.png,
PNG image of
a 2D product grid made from two order 17 Clenshaw Curtis rules.
-
cc_d2_o9x5.png,
PNG image of
a 2D product grid made from order 9 and order 5 Clenshaw Curtis rules.
-
cc_d3_level5.png,
PNG image of
a 3D Smolyak sparse grid of level 5, based on Clenshaw Curtis rules.
-
cc_sparse_2d.png,
PNG image of
a 2D Smolyak sparse grid of level 4.
-
explorer.png,
PNG image of
an explorer.
-
fsu_logo.pdf,
a logo.
-
integral_rectangles.m,
a MATLAB program for displaying an approximation to an integral.
-
integral_rectangles.png,
PNG image
suggesting how a 1D integral can be approximated
by rectangles;
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interp.m,
a MATLAB program for displaying stages in interpolatory quadrature.
-
interp1.png,
PNG image
of the stage 1 in interpolatory quadrature;
-
interp2.png,
PNG image
of the stage 2 in interpolatory quadrature;
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interp3.png,
PNG image
of the stage 3 in interpolatory quadrature;
-
interp4.png,
PNG image
of the stage 4 in interpolatory quadrature;
-
latin_center_02_00100.png,
PNG image of
100 points in a 2D Latin Square.
-
level4_o1x17.png,
PNG image of
the 1x17 component of a 2D level 4 sparse grid.
-
level4_o3x9.png,
PNG image of
the 3x9 component of a 2D level 4 sparse grid.
-
level4_o5x5.png,
PNG image of
the 5x5 component of a 2D level 4 sparse grid.
-
level4_o9x3.png,
PNG image of
the 17x1 component of a 2D level 4 sparse grid.
-
level4_o17x1.png,
PNG image of
the 17x1 component of a 2D level 4 sparse grid.
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mc5_p28.png,
PNG image of
the results of 5 distinct Monte Carlo approximations to
integrand 28.
-
mc5_versus_smolyak_p28.png,
PNG image of
a comparison of 5 distinct Monte Carlo approximations
versus the Smolyak approach on integrand 28.
-
mc_versus_smolyak_p28.png,
PNG image of
a comparison of a Monte Carlo approximation
versus the Smolyak approach on integrand 28.
-
monte_carlo_1d.png,
PNG image of
a possible arrangement of the first 100 sample points in
a 1D Monte Carlo procedure.
-
monte_carlo_2d.txt,
the coordinates of 1000 Monte Carlo points in the unit square.
-
monte_carlo_p28.f90,
a FORTRAN90 program, for use with
TEST_NINT,
for applying Monte Carlo to integrand 28.
-
monte_carlo_p28.out,
output from a run of the monte_carlo_p28.f90 program.
-
monte_carlo_p28_one.txt,
integration error data for one Monte Carlo approximation to
integrate problem 28.
-
monte_carlo_p28_five.txt,
integration error data for 5 Monte Carlo approximations to
integrate problem 28.
-
monte_carlo_2d.png,
PNG image of
a possible arrangement of the first 1000 sample points in
a 2D Monte Carlo procedure.
-
monte_carlo_p28.png,
PNG image of
the results of a Monte Carlo approximation to
integrand 28.
-
pool.png,
PNG image of
a swimming pool.
-
pool_depth.png,
PNG image of
the variation in depth of a swimming pool;
-
quasi_monte_carlo_1d.png,
PNG image of
a possible arrangement of the first 100 sample points in
a 1D Quasi Monte Carlo procedure.
-
quasi_monte_carlo_2d.png,
PNG image of
a possible arrangement of the first 1000 sample points in
a 2D Quasi Monte Carlo procedure.
-
quasi_monte_carlo_2d.txt,
the coordinates of 1000 Quasi Monte Carlo points in the unit square.
-
roulette_wheel.png,
PNG image of
a roulette wheel;
-
smolyak_p28.png,
PNG image of
the results of a series of Smolyak approximations to
integrand 28.
-
smolyak_p28.txt,
integration error data for Smolyak approximations to
integrate problem 28.
-
stochastic_mc.pdf,
a PDF image of
the results of 5 Monte Carlo approximations to the stochastic
diffusion problem, in 11D, with varying values of the
correlation length L.
-
stochastic_mc_and_sm.pdf,
a PDF image of
a comparison of the Smolyak procedure and 5 Monte Carlo
approximations to the stochastic
diffusion problem, in 11D, with varying values of the
correlation length L.
Last revised on 10 February 2024.