Add kernel math function support

[LubuSeb]

Closes #2942.

Summary

• add C++ AST lowering for asin, acos, and atan, including float overloads
• add Python AST bridge lowering for real-valued NumPy tan, asin, acos, atan, and log
• add focused C++ FileCheck and Python kernel tests for the newly covered math functions

Reproduction / scope

The bounty issue asks for continuous mathematical function support in CUDA-Q kernels. Existing C++ lowering already handled several functions through visitMathLibFunc; this change extends that same path for inverse trig functions. Python lowering already mapped selected NumPy calls through the AST bridge; this change adds the missing real-valued operations there while leaving untested complex inverse trig/log/tan support out of scope.

Minimality

This is limited to the existing lowering tables/switches and targeted tests. It does not refactor the frontend, broaden discrete-control support, or add backend-specific behavior.

Validation

• python -m py_compile python/cudaq/kernel/ast_bridge.py python/tests/kernel/test_kernel_float.py
• git diff --cached --check
• Local standalone <cmath> syntax smoke check for the float overload names used by the new C++ test

Not run locally: CUDA-Q native lit/runtime tests, because the local environment does not have the CUDA-Q compiler/test toolchain installed.

AI assistance disclosure

I used AI assistance to inspect the codebase and draft parts of this change; I reviewed the final patch and validation results before submission.

[copy-pr-bot]

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

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[sacpis]

/ok to test 157f60f

Command Bot: Processing...

[github-actions]

CI Summary (push) — ❌ failed

Run #27433361011 · ✅ 5 · ⏩ 7 · ❌ 1 · ⛔ 0

❌ Failed or cancelled

Job	Result	Link
build_and_test	❌ failure	view

Top-level jobs (13)

Job	Result
binaries	⏩ skipped
build_and_test	❌ failure
config_devdeps	✅ success
config_source_build	⏩ skipped
config_wheeldeps	✅ success
devdeps	✅ success
docker_image	⏩ skipped
gen_code_coverage	⏩ skipped
metadata	✅ success
python_metapackages	⏩ skipped
python_wheels	⏩ skipped
source_build	⏩ skipped
wheeldeps	✅ success

⏩ Skipped jobs (7) — intentionally skipped on PR builds; run on merge_group / workflow_dispatch

Job
binaries
config_source_build
docker_image
gen_code_coverage
python_metapackages
python_wheels
source_build

All sub-jobs (42) — every matrix leg, with links

Job	Status	Link
Build and test (amd64, gcc12, openmpi) / Dev environment (Debug)	✅ success	view
Build and test (amd64, gcc12, openmpi) / Dev environment (Python)	✅ success	view
Build and test (amd64, llvm, openmpi) / Dev environment (Debug)	✅ success	view
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Build and test (arm64, llvm, openmpi) / Dev environment (Python)	❌ failure	view
CI Summary	❔ in_progress	view
Configure build (devdeps)	✅ success	view
Configure build (source_build)	⏩ skipped	view
Configure build (wheeldeps)	✅ success	view
Create CUDA Quantum installer	⏩ skipped	view
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Load dependencies (amd64, gcc12) / Caching	✅ success	view
Load dependencies (amd64, gcc12) / Finalize	✅ success	view
Load dependencies (amd64, gcc12) / Metadata	✅ success	view
Load dependencies (amd64, llvm) / Caching	✅ success	view
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Load dependencies (arm64, gcc12) / Caching	✅ success	view
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Load wheel dependencies (amd64, 12.6) / Caching	✅ success	view
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Load wheel dependencies (amd64, 13.0) / Caching	✅ success	view
Load wheel dependencies (amd64, 13.0) / Finalize	✅ success	view
Load wheel dependencies (amd64, 13.0) / Metadata	✅ success	view
Load wheel dependencies (arm64, 12.6) / Caching	✅ success	view
Load wheel dependencies (arm64, 12.6) / Finalize	✅ success	view
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Load wheel dependencies (arm64, 13.0) / Caching	✅ success	view
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Load wheel dependencies (arm64, 13.0) / Metadata	✅ success	view
Prepare cache clean-up	❔ in_progress	view
Retrieve PR info	✅ success	view

⚠️ Required checks (5/6) — 1 missing — declared in .github/required-checks.yml for push

Required check	Status	Link
Build and test (amd64, llvm, openmpi) / Dev environment (Debug)	✅ success	view
Build and test (amd64, llvm, openmpi) / Dev environment (Python)	✅ success	view
Build and test (arm64, llvm, openmpi) / Dev environment (Debug)	✅ success	view
Build and test (arm64, llvm, openmpi) / Dev environment (Python)	❌ failure	view
Build and test (amd64, gcc12, openmpi) / Dev environment (Debug)	✅ success	view
Build and test (amd64, gcc12, openmpi) / Dev environment (Python)	✅ success	view

[LubuSeb]

Pushed 5f79e6a to address the Python CI failure from the previous tested head: the tests now use NumPy's current inverse-trig spellings (arcsin, arccos, arctan) while the bridge still accepts the existing asin/acos/atan aliases.

Local validation on the latest head:

python -m py_compile python/cudaq/kernel/ast_bridge.py python/tests/kernel/test_kernel_float.py

The latest head currently only has DCO, so it should be ready for another /ok to test when you have a chance.

[sacpis]

/ok to test 5cc9d4a

Command Bot: Processing...

[schweitzpgi]

LGTM

[schweitzpgi]

/ok to test a4daeb0

Command Bot: Processing...

[LubuSeb]

Pushed f8cc1de3c to address the remaining ARM Python CI failure on the latest tested head.

Root cause from the failed job: test_cudaq_uccsd1 now allows either 5 or 6 sampled states, but still asserted all six specific states were present. The failed ARM run hit the valid 5-state case and missed 00000011, so the membership assertion was stricter than the preceding len(counts) == 6 or len(counts) == 5 guard.

The follow-up keeps the test scoped to the known UCCSD output support: observed states must still be a 5-or-6-sized subset of the six expected bitstrings. No math lowering code changed in this commit.

Local validation available in this Windows checkout:

python -m py_compile python/tests/kernel/test_kernel_uccsd.py python/cudaq/kernel/ast_bridge.py python/tests/kernel/test_kernel_float.py
git diff --check

I could not run the CUDA-Q runtime pytest locally because this checkout does not have a built cudaq.kernel runtime installed.

The latest head only has DCO again, so it should need another /ok to test for NVIDIA runners.