Reconcile NumPy pin with QiskitOpt for shared benchmark environments

[bernalde]

Part of the benchmark runtime follow-up tracked in JuliaQUBO/QUBOBenchmarks.jl#19.

Problem

DWave v0.7.2 resolves on its own, but its hard pip numpy pin cannot share a Python environment with QiskitOpt v0.7.0.

Current registered DWave CondaPkg.toml:

[deps]
python = ">=3.11,<=3.13"

[pip.deps]
numpy = "==2.4.6"
dwave-ocean-sdk = "==9.3.0"
dwave_networkx = "==0.8.18"

QiskitOpt v0.7.0 currently declares:

[deps]
python = ">=3.11,<3.12"

[pip.deps]
numpy = "~=2.2.0"
qiskit = "~=2.3.0"
qiskit-aer = "~=0.17.0"
qiskit-ibm-runtime = "~=0.46.0"
qiskit-optimization = "~=0.7.0"
scipy = "~=1.15.0"

The Python bounds are compatible, but the numpy bounds are not.

Evidence

CondaPkg.resolve() succeeds for DWave alone and for QiskitOpt alone.

For DWave + QiskitOpt, CondaPkg writes:

[pypi-dependencies]
numpy = "==2.4.6,~=2.2.0"

and pixi fails with:

failed to solve the pypi requirements
you require numpy ∅

Requested work

• Check whether DWave.jl really needs the hard numpy ==2.4.6 pin.
• If not, relax the bound to a range that can coexist with QiskitOpt or remove the direct numpy pin if dwave-ocean-sdk already constrains it adequately.
• If the hard pin is required, document why and link that decision back to JuliaQUBO/QUBOBenchmarks.jl#19 so the benchmark harness can isolate DWave from QiskitOpt.

Acceptance criteria

• CondaPkg.resolve() succeeds for DWave + QiskitOpt, or this package explicitly documents why DWave cannot share a Python environment with QiskitOpt.
• The chosen policy has a minimal smoke check.

[bernalde]

CIMOptimizer's Python upper-bound blocker is cleared in registered v0.2.2.

• Fixed by Support Python 3.11 CondaPkg runtime CIMOptimizer.jl#21.
• Registered in New version: CIMOptimizer v0.2.2 JuliaRegistries/General#159489.
• Verified with the default Julia registry path using Pkg.add(Pkg.PackageSpec(name="CIMOptimizer", version=v"0.2.2")); using CIMOptimizer, which printed CIMOptimizer version=0.2.2.

That leaves this issue focused on DWave/QiskitOpt: DWave v0.7.2's numpy ==2.4.6 pin still conflicts with QiskitOpt v0.7.0's numpy ~=2.2.0 in shared benchmark environments. The next useful check here is whether DWave actually needs the exact NumPy pin, or whether it can relax/remove it and add a minimal DWave + QiskitOpt CondaPkg resolve smoke.

[bernalde]

@JuliaRegistrator register

[JuliaRegistrator]

Registration pull request updated: JuliaRegistries/General/159495

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## Breaking changes

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Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.7.3 -m "<description of version>" 93b634cec9834697434cb1a747b8fdfc993c492f
git push origin v0.7.3

[bernalde]

@JuliaRegistrator register

Release notes:

DWave v0.7.3

• Relax DWave's direct NumPy dependency to ~=2.2.0 so it can share a CondaPkg environment with QiskitOpt v0.7.0.
• Keep dwave-ocean-sdk ==9.3.0 and dwave_networkx ==0.8.18 pinned.

This release resolves the DWave/QiskitOpt NumPy conflict tracked for shared JuliaQUBO benchmark environments.

[JuliaRegistrator]

Registration pull request updated: JuliaRegistries/General/159495

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.7.3 -m "<description of version>" 93b634cec9834697434cb1a747b8fdfc993c492f
git push origin v0.7.3