Out of scope kernel

[zohimchandani]

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Describe the bug

import cudaq 

def ghz(n): 
            
    kernel = cudaq.make_kernel()

    qubits = kernel.qalloc(n)

    kernel.h(qubits[0])
        
    for i in range(n): 
        if i+1==n: 
            break 
        else: 
            kernel.cx(qubits[i], qubits[i+1])
            
    kernel.mz(qubits)
    
    return kernel 

cudaq.set_target("nvidia")
cudaq.sample(ghz(4)).dump()

The code above executes fine however changing the target yields an error:

cudaq.set_target("nvidia-mqpu")
cudaq.sample_async(ghz(4), qpu_id = 0).get().dump()

Segmentation fault (core dumped)

The fix is the following:

def ghz(kernel, n): 
    qubits = kernel.qalloc(n)
    kernel.h(qubits[0])
    for i in range(n): 
        if i+1==n: 
            break 
        else: 
            kernel.cx(qubits[i], qubits[i+1])
    kernel.mz(qubits)
    return kernel 


kernel = cudaq.make_kernel()
cudaq.sample_async(ghz(kernel, 10), qpu_id = 0).get().dump()

The kernel must be created outside of the function and passed in as an argument. This may be due to kernel going out of scope.

Not sure if there is something we need to fix here but curious to note it down in case we can think of a workaround.

Steps to reproduce the bug

NA

Expected behavior

NA

Is this a regression? If it is, put the last known working version (or commit) here.

Not a regression

Environment

• CUDA Quantum version:
• Python version:
• C++ compiler:
• Operating system:

Suggestions

No response