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Compute in a simulation norm, distance and scalar product of points that are drawn from the hypercube <math>H_d</math> (coordinate-wise) uniformly, i.e., <math>x=(x_1,\dots,x_d)</math> is drawn such that <math>x_i\sim\mathcal{U}([-1,1])</math> for <math>i=1,\dots,d</math>. Make plots and tables similar to [[#FIG-1|Figure]] and [[#TAB-1 [[#TAB-3 ||Table]]\,--\,]]. Compare the experimental data with our theoretical results above. | Compute in a simulation norm, distance and scalar product of points that are drawn from the hypercube <math>H_d</math> (coordinate-wise) uniformly, i.e., <math>x=(x_1,\dots,x_d)</math> is drawn such that <math>x_i\sim\mathcal{U}([-1,1])</math> for <math>i=1,\dots,d</math>. Make plots and tables similar to [[#FIG-1|Figure]] and [[#TAB-1 [[#TAB-3 ||Table]]\,--\,]]. Compare the experimental data with our theoretical results above. |
Latest revision as of 02:43, 1 June 2024
Compute in a simulation norm, distance and scalar product of points that are drawn from the hypercube [math]H_d[/math] (coordinate-wise) uniformly, i.e., [math]x=(x_1,\dots,x_d)[/math] is drawn such that [math]x_i\sim\mathcal{U}([-1,1])[/math] for [math]i=1,\dots,d[/math]. Make plots and tables similar to Figure and [[#TAB-1 |Table\,--\,]]. Compare the experimental data with our theoretical results above.