[docs] measuring_kernels: explicit vector<bool> return + to_bools

PR NVIDIA#4409 made MLIR-mode `mz(qview)` return
`std::vector<measure_handle>`, so `__qpu__ auto kernel2()` now
deduces a handle-bearing return. `Marshal.cpp::hasLegalType`
filters such kernels out of `GenKernelExecution`'s worklist, the
`.run` companion is never generated, and `cudaq::run(1000,
kernel2)` fails at runtime with `runnable kernel ... is not
present`.

Spell the return as `std::vector<bool>` and wrap `mz(q)` with
`cudaq::to_bools(...)` so the kernel signature stays in the
host-visible subset. Host-side `result[0]` is now a `bool` and
`static_cast<int>(result[0])` is well-defined; previously it
would have routed through `measure_handle::operator bool()`,
which `std::abort()`s in MLIR mode.

The `[Begin Run0]` / `[End Run0]` Sphinx literalinclude markers
are unchanged.

Signed-off-by: Pradnya Khalate <pkhalate@nvidia.com>
Co-authored-by: Cursor <cursoragent@cursor.com>

Author: khalatepradnya

docs/sphinx/examples/cpp/measuring_kernels.cpp

@@ -27,7 +27,7 @@ __qpu__ void kernel1() {
 // [End Sample2]
 
 // [Begin Run0]
-__qpu__ auto kernel2() {
+__qpu__ std::vector<bool> kernel2() {
   cudaq::qvector q(2);
   h(q[0]);
   auto b0 = mz(q[0]);
@@ -37,7 +37,7 @@ __qpu__ auto kernel2() {
   if (b0) {
     h(q[1]);
   }
-  return mz(q);
+  return cudaq::to_bools(mz(q));
 }
 
 int main() {