Fix type casting error in thc_jax.py#1396
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The test failed in CI because the function compute_objective_batched in src/openfermion/resource_estimates/pbc/thc/factorizations/thc_jax.py did a `float()` cast on the value it was to return. This does not work with JAX. The function is decorated with `@jax.jit`, makking it a JIT-compiled function. During JAX's trace-compilation, the argument variables are abstract `Tracer` objects rather than concrete floats. Calling `float()` on a `Tracer` object causes a `jax.errors.ConcretizationTypeError` because the actual value is not known when building the JAX computation graph.
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This pull request modifies the compute_objective_batched function in thc_jax.py to return the JAX array res directly instead of casting it to a Python float. This change prevents potential issues with JAX's JIT compilation and tracing. There are no review comments, and I have no additional feedback to provide.
fdmalone
approved these changes
Jul 2, 2026
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When running mypy, an error would occur because the function compute_objective_batched in src/openfermion/resource_estimates/pbc/thc/factorizations/thc_jax.py did a
float()cast on the value it was to return. The function is decorated with@jax.jit, making it a JIT-compiled function. During JAX's trace-compilation, the argument variables are abstractTracerobjects rather than concrete floats. Callingfloat()on aTracerobject causes ajax.errors.ConcretizationTypeErrorbecause the actual value is not known when building the JAX computation graph.The change here uses
castfromtyping, which satisfies mypy's static analysis at compile-time and does not interfere with JAX's graph tracer.