Bump the all-julia-packages group across 1 directory with 2 updates

[dependabot]

Updates the requirements on Catalyst and DiffEqBase to permit the latest version.
Updates Catalyst to 16.2.0

Release notes

Sourced from Catalyst's releases.

v16.2.0

Catalyst v16.2.0

Diff since v16.1.2

Merged pull requests:

• Bump codecov/codecov-action from 5 to 6 (#1453) (@​dependabot[bot])
• Bump compat for OrdinaryDiffEq v7 / SciMLBase v3 ecosystem (#1466) (@​ChrisRackauckas-Claude)
• refactor: ignore certain system metadata during serialization (#1475) (@​AayushSabharwal)
• Bump the all-julia-packages group across 2 directories with 4 updates (#1476) (@​dependabot[bot])
• Make docs compatible with Turing 0.45 (handles #1476) (#1477) (@​ChrisRackauckas-Claude)
• Centralize CI on SciML reusable workflows + Runic + typo fixes (#1478) (@​ChrisRackauckas-Claude)
• Bump the all-julia-packages group across 3 directories with 18 updates (#1479) (@​dependabot[bot])

Changelog

Sourced from Catalyst's changelog.

Breaking updates and feature summaries across releases

Unreleased (on master)

Catalyst 16.1

• Added use_jump_ratelaws keyword argument to ode_model, sde_model, hybrid_model, ODEProblem, SDEProblem, and HybridProblem. When set to true, both drift and diffusion terms use the jump/stochastic rate law (binomial propensities) instead of the ODE rate law (power-based). This gives the mathematically correct CLE derived from the CME when species populations are integers. Defaults to false for backward compatibility.

Catalyst 16.0

Catalyst 16 is a major release that transitions from ModelingToolkit (MT) v9 to ModelingToolkitBase (the base for ModelingToolkit v11); introduces unified hybrid model support for mixed ODE/SDE/Jump systems; supports user-provided coupled ODEs, SDEs, jump processes, and jump-diffusions; and modernizes the conversion and problem-creation API.

Please also see the ModelingToolkit NEWS.md for all the changes that have occurred in ModelingToolkit as part of v10 and v11, and which are now relevant for Catalyst users.

BREAKING: ModelingToolkitBase replaces ModelingToolkit

• Catalyst now depends on and re-exports ModelingToolkitBase instead of ModelingToolkit. This ensures Catalyst remains fully MIT-licensed after the library split that occurred in ModelingToolkit v11. ModelingToolkitBase provides the core symbolic system infrastructure (types, accessors, problem construction) that Catalyst needs. With this update, Catalyst moves from ModelingToolkit v9 to ModelingToolkitBase 1.12+ (part of ModelingToolkit v11).

  Most commonly used functions (unknowns, parameters, equations, @mtkcompile, etc.) are available through ModelingToolkitBase. However, if you relied on structural_simplify, now part of mtkcompile, for reducing models with algebraic equations, you may need to explicitly load ModelingToolkit to obtain equivalent levels of model reduction and optimization:

  using Catalyst
  using ModelingToolkit  # only if you need MTK-specific features not in MTKBase

  The version of mtkcompile in ModelingToolkitBase is less feature filled than in ModelingToolkit, but please be aware that the latter version now loads AGPL-licensed libraries that may impose additional restrictions on your code.

BREAKING: Conversion functions renamed

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Commits

• 3c24a17 Update Project.toml
• 08e33b1 Merge pull request #1479 from SciML/dependabot/julia/all-julia-packages-08a47...
• 2466e1f Merge branch 'master' into dependabot/julia/all-julia-packages-08a474db6d
• dc25874 Merge pull request #1453 from SciML/dependabot/github_actions/codecov/codecov...
• 52df5c4 Bump the all-julia-packages group across 3 directories with 18 updates
• a61242f Merge pull request #1477 from ChrisRackauckas-Claude/dependabot-turing-0.45-d...
• 7040da1 Merge branch 'master' into dependabot-turing-0.45-doc-compat
• 5111190 Merge pull request #1478 from ChrisRackauckas-Claude/centralize-ci
• 2c03cb7 Drop Runic reformatting and check from this PR
• 64c8b0e Centralize CI on SciML reusable workflows; apply Runic + fix typos
• Additional commits viewable in compare view

Updates DiffEqBase to 7.5.5

Changelog

Sourced from DiffEqBase's changelog.

OrdinaryDiffEq.jl v7 / DifferentialEquations.jl v8 Breaking Changes

This release bumps to SciMLBase v3, RecursiveArrayTools v4, and includes breaking changes across DiffEqBase, OrdinaryDiffEqCore, and all solver sublibraries. It also coincides with the DifferentialEquations.jl v8 umbrella release, which is itself a breaking change to the user-facing meta-package.

DifferentialEquations.jl v8: scope reduction

DifferentialEquations.jl v8 no longer re-exports the full SciML solver suite. Previously, using DifferentialEquations pulled in OrdinaryDiffEq, StochasticDiffEq, DelayDiffEq, BoundaryValueDiffEq, Sundials, JumpProcesses, SteadyStateDiffEq, LinearSolve, NonlinearSolve, Optimization, etc. — a large default surface that drove up using time and made it unclear which package any given solver actually came from.

In v8, using DifferentialEquations only loads OrdinaryDiffEq. All other solver families have been removed from the umbrella. If your code relied on DifferentialEquations for SDEs, DDEs, BVPs, jumps, steady states, or any non-ODE solver, you will need to add the topic-specific package to your project explicitly.

Migration

Find the topic you need a solver for and add the corresponding sublib(s) directly. The DiffEqDocs tutorials and solver pages now specify, per algorithm, which package it ships from. Common cases:

Topic	Old (DiffEq v7 umbrella)	New (DiffEq v8)
ODEs	using DifferentialEquations	using OrdinaryDiffEq (or using OrdinaryDiffEqTsit5, OrdinaryDiffEqRosenbrock, … for individual solver families)
Stochastic ODEs	using DifferentialEquations	using StochasticDiffEq
Delay ODEs	using DifferentialEquations	using DelayDiffEq
Boundary value problems	using DifferentialEquations	using BoundaryValueDiffEq (or one of BoundaryValueDiffEqMIRK, BoundaryValueDiffEqFIRK, BoundaryValueDiffEqShooting, …)
Jump processes	using DifferentialEquations	using JumpProcesses
Steady state	using DifferentialEquations	using SteadyStateDiffEq
DAEs (mass matrix or implicit)	using DifferentialEquations	using OrdinaryDiffEq (mass matrix), using Sundials (IDA), or topic sublib
Sundials wrappers (CVODE, IDA, ARKODE)	using DifferentialEquations	using Sundials
Linear / nonlinear / optimization	using DifferentialEquations	using LinearSolve / using NonlinearSolve / using Optimization

For ODE work specifically, prefer importing only the sublib you need (e.g. using OrdinaryDiffEqTsit5: Tsit5) rather than the umbrella using OrdinaryDiffEq — the v7 ecosystem split lets you trim using time substantially. The DiffEqDocs tutorials and solver index annotate every algorithm with its host sublib.

Why

Removing the meta-package's broad re-exports lets each topic's package version cycle independently, eliminates the long using DifferentialEquations precompile chain for users who only need ODEs, and makes the dependency graph for any given script honest about what's actually being loaded.

This change is independent of the OrdinaryDiffEq v7 changes below — OrdinaryDiffEq v7 ships with DifferentialEquations v8, but you can also use OrdinaryDiffEq v7 directly without the umbrella package at all.

OrdinaryDiffEq.jl v7 Breaking Changes

This release bumps to SciMLBase v3, RecursiveArrayTools v4, and includes breaking changes across DiffEqBase, OrdinaryDiffEqCore, and all solver sublibraries.

Themes of the v7 release

Most of the breaking changes fall into a small set of recurring themes. Keep these in mind while reading the migration table — they explain why an individual change exists and often suggest the right migration direction:

• Time to first solve (TTFS) reduction. Direct deps on Static.jl, StaticArrayInterface.jl, Polyester.jl, and StaticArrays.jl were dropped; using OrdinaryDiffEq now loads only the default solver set; ODEFunction switched to AutoSpecialize. All of this means less code loaded and more precompilation caching on first solve.

• Type stability everywhere. All Bool solver/solve keyword arguments (autodiff, verbose, alias, lazy, …) were replaced by typed objects. Passing a Bool no longer changes dispatch in ways the compiler cannot specialize on, and the reverse is no longer allowed to silently fall back through slow generic paths. For example:

  # v6 — a Bool
  Rosenbrock23(autodiff = true)
  solve(prob, alg; verbose = false, alias = true)

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Commits

• See full diff in compare view

[dependabot]

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot recreate.

[dependabot]

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot recreate.

[dependabot]

Looks like these dependencies are updatable in another way, so this is no longer needed.