Special Session at ICMS 2026: Computational Aspects of Weighted Projective Spaces
Aim and Scope
Weighted projective spaces and their graded analogues provide the natural framework for a wide range of problems in algebraic geometry, arithmetic geometry, computational number theory, and artificial intelligence. They appear in the classification of singularities, moduli of curves, toric and orbifold geometry, and the theory of graded rings and invariants.
Their computational study is central to tasks such as computing invariants of singular varieties, resolving quotient singularities, point-counting over finite fields, determining zeta functions, and analyzing moduli of hypersurfaces. Recent developments extend these ideas to graded neural networks, graded transformers, and graded codes, where graded vector spaces model hierarchical, weighted, or symmetry-structured data.
This session brings together researchers developing algorithms, symbolic methods, numerical tools, and open-source software for weighted and graded projective geometry, with applications spanning algebraic geometry, arithmetic geometry, coding theory, and AI.
Keywords: Weighted projective spaces, graded geometry, symbolic computation, finite fields, point-counting, zeta functions, Python, SymPy, SageMath, AI, graded neural networks.