build(deps): bump cvxpy from 1.7.5 to 1.8.1 in /requirements

[dependabot]

Bumps cvxpy from 1.7.5 to 1.8.1.

Release notes

Sourced from cvxpy's releases.

v1.8.1

PR	Title	Type
#3093	Fix IndexError with transformed parameters in parametric reshape	Bug fix
#3094	Add KNITRO solver installation instructions to documentation	Docs
#3099	Remove Google Analytics from documentation	Docs
#3113	Use balanced tree for PowConeND to PowCone3D decomposition	Bug fix
#3114	Add CVXPY Workshop 2026 website	Docs
#3115	Add HiGHS and Moreau to related projects	Docs
#3116	Fix cvxpy-base dependencies	Bug fix

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This new release totaled 7 PRs from 3 contributors.

• @​eminyouskn | #3094
• @​PTNobel | #3099, #3113, #3114, #3115, #3116
• @​SteveDiamond | #3093

v1.8.0

CVXPY 1.8

This release is consistent with our semantic versioning guarantee. It comes packed with many new features, bug fixes, and performance improvements.

This version of CVXPY supports Python 3.11 through 3.14. We will support CVXPY 1.8 with bugfixes while developing the 1.9 release. CVXPY 1.7 and older are no longer supported.

Adoption of SPEC 0

In this release we decided to adopt the minimum supported dependencies SPEC (Scientific Python Ecosystem Coordination). Notably, this means that we have dropped support for Python 3.10 and NumPy < 2.0.

New canonicalization backend

This release introduces a new backend which can handle a very large number of parameters. To use the backend, please specify the argument canon_backend="COO" when solving a DPP problem.

New default MILP solver

CVXPY adds the open source solver HiGHS as its default mixed-integer linear programming (MILP) solver. HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems developed by a team from the University of Edinburgh.

Power cone canonicalization

Four atoms, power, geo_mean, pnorm, and inv_prod now take a parameter approx that determines whether CVXPY canonicalizes the atom using many SOCs or one power cone. Feel free to set approx=False and report on whether it improves performance or accuracy!

Logical boolean operations

CVXPY now supports logical boolean operations on boolean expressions via the cp.logic module. The new atoms are cp.logic.AND, cp.logic.OR, cp.logic.NOT, and cp.logic.XOR.

New features

• DPP with complex expressions
• Support for ND matmul
• Support for ND cumsum

... (truncated)

Commits

• 3b96447 Release CVXPY 1.8.1
• b89c4fe Fix cvxpy-base dependencies (#3116)
• 92d8e6e Add HiGHS and Moreau to related projects (#3115)
• 04dfb07 Add CVXPY Workshop 2026 website (#3114)
• de3294d Use balanced tree for PowConeND to PowCone3D decomposition (#3113)
• c35864d Remove Google Analytics from documentation (#3099)
• a41e82c Add KNITRO solver installation instructions to documentation (#3094)
• b1f21ef Fix IndexError with transformed parameters in parametric reshape (#3093)
• e0d5674 Tweaks requirements
• a185560 Begin development of CVXPY 1.8.1
• Additional commits viewable in compare view

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