<p>We build a computer program to reconstruct convex bodies using even <i>L</i><sub><i>p</i></sub> surface area measures for <i>p</i> ≥ 1. Firstly, we transform the minimization problem <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10473_2025_110_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="27" /> </InlineMediaObject> <EquationSource Format="TEX">\(\cal{P}_1\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <msub> <mrow> <mi mathvariant="script">P</mi> </mrow> <mn>1</mn> </msub> </math></EquationSource> </InlineEquation>, which is equivalent to solving the even <i>L</i><sub><i>p</i></sub> Minkowski problem, into a convex optimization problem <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10473_2025_110_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\(\cal{P}_4\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <msub> <mrow> <mi mathvariant="script">P</mi> </mrow> <mn>4</mn> </msub> </math></EquationSource> </InlineEquation> with a finite number of constraints. This transformation makes it suitable for computational resolution. Then, we prove that the approximate solutions obtained by solving the problem <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10473_2025_110_Article_IEq3.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\(\cal{P}_4\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <msub> <mrow> <mi mathvariant="script">P</mi> </mrow> <mn>4</mn> </msub> </math></EquationSource> </InlineEquation> converge to the theoretical solution when <i>N</i> and <i>k</i> are sufficiently large. Finally, based on the convex optimization problem <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10473_2025_110_Article_IEq4.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">\(\cal{P}_4\)</EquationSource> <EquationSource Format="MATHML"><math display="block"> <msub> <mrow> <mi mathvariant="script">P</mi> </mrow> <mn>4</mn> </msub> </math></EquationSource> </InlineEquation>, we provide an algorithm for reconstructing convex bodies from even <i>L</i><sub><i>p</i></sub> surface area measures, and present several examples implemented using MATLAB.</p>

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Reconstruction problems of convex bodies from even Lp surface area measures

  • Juewei Hu,
  • Gangsong Leng

摘要

We build a computer program to reconstruct convex bodies using even Lp surface area measures for p ≥ 1. Firstly, we transform the minimization problem \(\cal{P}_1\) P 1 , which is equivalent to solving the even Lp Minkowski problem, into a convex optimization problem \(\cal{P}_4\) P 4 with a finite number of constraints. This transformation makes it suitable for computational resolution. Then, we prove that the approximate solutions obtained by solving the problem \(\cal{P}_4\) P 4 converge to the theoretical solution when N and k are sufficiently large. Finally, based on the convex optimization problem \(\cal{P}_4\) P 4 , we provide an algorithm for reconstructing convex bodies from even Lp surface area measures, and present several examples implemented using MATLAB.