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arXiv · 2606.14891

CVXPY 1.9: Recent Advances in Optimization Modeling Software

William Zhang·Parth Nobel·Aryaman Jeendgar·Riley Murray·Philipp Schiele·Steven Diamond
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Abstract

CVXPY is a Python-embedded domain-specific language for convex optimization that lets users express problems in mathematical notation while the system verifies convexity and reduces valid programs to solver-ready form. This paper reports on the major advances from versions 1.1 through 1.9. These include a unified conic quadratic program (CQP) standard form for canonicalization; a stacked-slices backend that accelerates parameterized programs; first-class support for N-dimensional expressions; explicit sparsity for variables; support for multiple variable attributes; cones/atoms relevant to quantum information theory; and the introduction of disciplined nonlinear programming (DNLP). We outline the design, algorithms, and modeling consequences of these features.

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William Zhang, Parth Nobel, Aryaman Jeendgar, Riley Murray, Philipp Schiele, Steven Diamond. 2026-06-12. CVXPY 1.9: Recent Advances in Optimization Modeling Software. https://arxiv.org/abs/2606.14891

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