Add opt-in CuPy fusion for Gaussian xFit fits

[tpn]

Gaussian CuPy fits launch many small operations to evaluate residuals and analytic derivatives. Add opt-in CuPy kernels that combine those operations while keeping the existing normal-equation contractions, LM solver, and final uncertainty diagnostics.

fit_dipoles(images, model="gaussian", backend="cupy", fusion=True)

The CLI selects the same implementation with --backend cupy --fusion, and device pipeline manifests accept xfit.fusion: true. Float32/float64, masks, variances, difference mode, and split mode are supported. Each fit owns its buffers and uses the current CuPy stream. Explicit rounding preserves the arithmetic boundaries that matter for ill-conditioned fits.

The public Gaussian benchmark now reports the first fit separately from every warmed sample. Run it with and without --fusion to compare complete fits, including input transfer and portable results.

Local validation: all 43 selected GPU cases passed without skips, covering fusion, numerical edge cases, independent streams, repeated calls, and the actual CLI. The integrated source also passed 545 CPU tests (94 expected GPU/optional skips) and repository hooks, including Ruff and mypy.

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