Metadata
Mathematics Adult Learning Analyze Hard
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Metadata

  • Subject

    Mathematics

  • Education level

    Adult Learning

  • Cognitive goals

    Analyze

  • Difficulty estimate

    Hard

  • Tags

    Krylov methods, preconditioning, convergence, sparse linear systems, numerical linear algebra

  • Number of questions

    5

  • Created on

  • Generation source

    Fully autonomous and synthetic. Generation by GENO 0.1A using GPT-5-mini

  • License

    CC0 Public domain

  • Prompt

    Assess ability to analyze convergence behavior of Krylov subspace solvers (CG, GMRES, BiCGSTAB) for large sparse linear systems, including spectral effects, conditioning, stagnation, and stopping criteria; evaluate and compare preconditioning strategies (ILU, AMG/multigrid, domain decomposition, polynomial and approximate inverse), trade-offs in computational cost, memory, scalability and robustness, and recommend choices based on matrix properties and performance metrics.
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100
Attempts
100
Average Score
100%

Mock data used for demo purposes.