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<record>
  <title>Memory-efficient Algorithm for the Reverse issue of  Variable Density</title>
  <journal>Electronic Devices</journal>
  <author>Elena N. Akimova, Vladimir E. Misilov, and Maxim S. Arguchinsky</author>
  <volume>13</volume>
  <issue>2</issue>
  <year>2024</year>
  <doi>https://doi.org/10.6025/ed/2024/13/2/49-56</doi>
  <url>https://www.dline.info/ed/fulltext/v13n2/edv13n2_2.pdf</url>
  <abstract>A memory-efficient algorithm is developed and implemented to address the reverse issue of determining the variable density within a curvilinear layer from gravitational information. This algorithm is structured around the stabilized bi-conjugated gradient approach. By approximating the SLAE matrix with a Toeplitz-block-Toeplitz structure, the modification dramatically lowers the need for memory. The parallel versions of the algorithm were created for the Uran supercomputer, utilizing a combination of MPI+OpenMP technology. The practicality of this algorithm was demonstrated through its successful application to a model problem featuring synthetic data.

</abstract>
</record>
