NVIDIA / NVIDIA/cuda-quantum

[Python, Remote-Sim] Cannot use cudaq::complex() for remote simulation

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Description

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Describe the bug

Runtime error when using np arrays with dtype=cudaq.complex() on remote simulator.

Steps to reproduce the bug

test.py


import numpy as np
import cudaq

cudaq.set_target("remote-mqpu", url="localhost:3030")

c = np.array([1. / np.sqrt(2.),  1. / np.sqrt(2.), 0., 0.],
                dtype=cudaq.complex())
state = cudaq.State.from_data(c)

@cudaq.kernel
def kernel(s: cudaq.State):
    q = cudaq.qvector(s)

counts = cudaq.sample(kernel, state)
assert '00' in counts
assert '10' in counts

Run commands (in parallel):

bin/cudaq-qpud --port 3030
python3 test.py  

Result:

RuntimeError: [sim-state] invalid data precision.

Note: changing the dtype to complex works.

Expected behavior

Runs successfully when using cudaq.complex() dtype on both nvidia and remote-mqpu targets.

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

Contributor guide

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the reproducer in test.py and run bin/cudaq-qpud --port 3030 alongside python3 test.py. Compare the handling of dtype=cudaq.complex() on the remote-mqpu and nvidia targets; done means the remote run completes without the invalid data precision error and both expected counts are present.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, python
Domain
backend
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
42/100

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