QPU usage time dependency on circuit depth and overhead processes
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The issue is the QPU usage time on IBM machines. Let me describe the problem. I have a small circuit to manipulate 3 qubits (it is an optimization problem and I don't think the details are relevant, but can be provided if needed). This circuit is ran for 8 initial configurations (000, 001,...,111) and the results are measured. This process takes around 5-6 s of QPU time for 2000 shots on an IBM open-instance machine (ibm_fez in this case), which I think is a lot. So, first question: is this real
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QPU usage time dependency on circuit depth and overhead processes
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The issue is the QPU usage time on IBM machines. Let me describe the problem.
I have a small circuit to manipulate 3 qubits (it is an optimization problem and I don't think the details are relevant, but can be provided if needed). This circuit is ran for 8 initial configurations (000, 001,...,111) and the results are measured. This process takes around 5-6 s of QPU time for 2000 shots on an IBM open-instance machine (ibm_fez in this case), which I think is a lot. So, first question: is this really a lot or my expectation is wrong?
Then I noticed that the transpiled circuit has around 120 layers and the reason is that the gates in the original circuit are not native for IBM. Therefore, the original circuit was mapped to use the native gates, resulting in a transpiled circuit of around 13 layers. However, the QPU execution time hasn't changed at all. Second question: was it correct to expect a change in execution time by reducing the number of layers by a factor 10x?
Third and final question: Are there any any over-heading processes in IBM machines that are so large that in fact kill any optimization in the circuits for small problems or my code is so wrong and inefficient that any real machine will struggle to run it?
Hope the problem statement and questions are clear, but please ask question if not.
qiskitquantum-circuitoptimizationhardware
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edited 10 hours ago
asked Mar 13 at 16:35
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