Circuit differences.

from qiskit import QuantumCircuit, Aer
import networkx as nx

def maxcut_obj(x, G):
    """
    Given a bitstring as a solution, this function returns
    the number of edges shared between the two partitions
    of the graph.
    
    Args:
        x: str
           solution bitstring
           
        G: networkx graph
        
    Returns:
        obj: float
             Objective
    """
    obj = 0
    for i, j in G.edges():
        if x[i] != x[j]:
            obj -= 1
            
    return obj


def compute_expectation(counts, G):
    
    """
    Computes expectation value based on measurement results
    
    Args:
        counts: dict
                key as bitstring, val as count
           
        G: networkx graph
        
    Returns:
        avg: float
             expectation value
    """
    
    avg = 0
    sum_count = 0
    for bitstring, count in counts.items():
        
        obj = maxcut_obj(bitstring[::-1], G)
        avg += obj * count
        sum_count += count
        
    return avg/sum_count


# We will also bring the different circuit components that
# build the qaoa circuit under a single function
def create_qaoa_circ(G, theta):
    
    """
    Creates a parametrized qaoa circuit
    
    Args:  
        G: networkx graph
        theta: list
               unitary parameters
                     
    Returns:
        qc: qiskit circuit
    """
    
    nqubits = len(G.nodes())
    p = len(theta)//2  # number of alternating unitaries
    qc = QuantumCircuit(nqubits)
    
    beta = theta[:p]
    gamma = theta[p:]
    
    # initial_state
    for i in range(0, nqubits):
        qc.h(i)
    
    for irep in range(0, p):
        
        # problem unitary
        for pair in list(G.edges()):
            qc.rzz(2 * gamma[irep], pair[0], pair[1])

        # mixer unitary
        for i in range(0, nqubits):
            qc.rx(2 * beta[irep], i)
            
    qc.measure_all()
        
    return qc

# Finally we write a function that executes the circuit on the chosen backend
def get_expectation(G, shots=512):
    
    """
    Runs parametrized circuit
    
    Args:
        G: networkx graph
        p: int,
           Number of repetitions of unitaries
    """
    
    backend = Aer.get_backend('qasm_simulator')
    backend.shots = shots
    
    def execute_circ(theta):
        
        qc = create_qaoa_circ(G, theta)
        counts = backend.run(qc, seed_simulator=10, 
                             nshots=512).result().get_counts()
        
        return compute_expectation(counts, G)
    
    return execute_circ

from qiskit import QuantumCircuit, transpile
from qiskit_aer import AerSimulator
import networkx as nx

def maxcut_obj(x, G):
    """
    Given a bitstring as a solution, this function returns
    the number of edges shared between the two partitions
    of the graph.

    Args:
        x: str
           solution bitstring

        G: networkx graph

    Returns:
        obj: float
             Objective
    """
    obj = 0
    for i, j in G.edges():
        if x[i] != x[j]:
            obj -= 1

    return obj


def compute_expectation(counts, G):

    """
    Computes expectation value based on measurement results

    Args:
        counts: dict
                key as bitstring, val as count

        G: networkx graph

    Returns:
        avg: float
             expectation value
    """

    avg = 0
    sum_count = 0
    for bitstring, count in counts.items():

        obj = maxcut_obj(bitstring[::-1], G)
        avg += obj * count
        sum_count += count

    return avg/sum_count


# We will also bring the different circuit components that
# build the qaoa circuit under a single function
def create_qaoa_circ(G, theta):

    """
    Creates a parametrized qaoa circuit

    Args:
        G: networkx graph
        theta: list
               unitary parameters

    Returns:
        qc: qiskit circuit
    """

    nqubits = len(G.nodes())
    p = len(theta)//2  # number of alternating unitaries
    qc = QuantumCircuit(nqubits)

    beta = theta[:p]
    gamma = theta[p:]

    # initial_state
    for i in range(0, nqubits):
        qc.h(i)

    for irep in range(0, p):

        # problem unitary
        for pair in list(G.edges()):
            qc.rzz(2 * gamma[irep], pair[0], pair[1])

        # mixer unitary
        for i in range(0, nqubits):
            qc.rx(beta[irep], i)

    qc.measure_all()

    return qc

# Finally we write a function that executes the circuit on the chosen backend
def get_expectation(G, shots=512):

    """
    Runs parametrized circuit

    Args:
        G: networkx graph
        shots: int,
           Number of measurement shots per circuit execution
    """

    backend = AerSimulator()

    def execute_circ(theta):

        qc = create_qaoa_circ(G, theta)
        # Qiskit 2.x backends no longer transpile implicitly in run()
        tqc = transpile(qc, backend, optimization_level=0)
        counts = backend.run(tqc, shots=shots, seed_simulator=10
                             ).result().get_counts()

        return compute_expectation(counts, G)

    return execute_circ

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    {
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    {
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      "status": "pass",
      "summary": "target: module weighting of exact probabilities: agree (|\u0394| = 2e-15)",
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    {
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    {
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      "observed": 1024,
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      "observed": -1.677734375,
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      "summary": "reference: module weighting of captured counts: agree (|\u0394| = 0)",
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      "summary": "reference: module weighting of exact probabilities: agree (|\u0394| = 1.33e-15)",
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    {
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    {
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    {
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      ],
      "id": "measurement/cycle5/p2/shots-17",
      "kind": "measurement",
      "metric": null,
      "observed": [
        [
          0,
          0
        ],
        [
          1,
          1
        ],
        [
          2,
          2
        ],
        [
          3,
          3
        ],
        [
          4,
          4
        ]
      ],
      "reason_code": "equal",
      "required": true,
      "scope_ids": [
        "cycle5/p2/shots-17"
      ],
      "status": "pass",
      "summary": "both sides: terminal identity measurement, one classical register of width n",
      "tolerance": null
    },
    {
      "artifact_refs": [],
      "circuit_result_id": null,
      "expected": null,
      "id": "probability/cycle5/p2/shots-17",
      "kind": "probability",
      "metric": 0.02758285724841416,
      "observed": null,
      "reason_code": "numeric_mismatch",
      "required": true,
      "scope_ids": [
        "cycle5/p2/shots-17"
      ],
      "status": "difference",
      "summary": "ideal output distributions: max |\u0394p| = 0.0276",
      "tolerance": 1e-10
    },
    {
      "artifact_refs": [],
      "circuit_result_id": null,
      "expected": -3.0281950739059216,
      "id": "exact-objective/cycle5/p2/shots-17",
      "kind": "exact-objective",
      "metric": 0.16590613867563908,
      "observed": -3.1941012125815607,
      "reason_code": "numeric_mismatch",
      "required": true,
      "scope_ids": [
        "cycle5/p2/shots-17"
      ],
      "status": "difference",
      "summary": "independent exact objective, reference vs target: differ (|\u0394| = 0.166)",
      "tolerance": 1e-10
    },
    {
      "artifact_refs": [],
      "circuit_result_id": null,
      "expected": 1024,
      "id": "shots-preservation/cycle5/p2/shots-17",
      "kind": "shots-preservation",
      "metric": null,
      "observed": 17,
      "reason_code": "shots_preservation_mismatch",
      "required": true,
      "scope_ids": [
        "cycle5/p2/shots-17"
      ],
      "status": "difference",
      "summary": "completed shots: reference 1024, target 17",
      "tolerance": null
    }
  ],
  "circuit_results": [
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-a/shots-17"
      ],
      "id": "circuit-result-8700bcf5cababb823f46d4ffd9d8362ebabb8f7acf92f57260fd55edc7804d56",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "05ffb5237902e17adf6b79feeb3504de74436ac95b53393ae8f4fa807f508d19",
      "status": "difference",
      "target_qasm_sha256": "51900b6a4e63b5f6c76aaba34b0ef50f1e3515c98042f819638ca49c02a1f7b8"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p1-b/shots-17"
      ],
      "id": "circuit-result-a58e12b903d29c7fbc4f249484197613629e6f7a036dc32953e2091060ca766c",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "4fef82407e0a074cc6bf8a42e007c5c0d9aa398397349beabaeb63647fcbf1df",
      "status": "difference",
      "target_qasm_sha256": "044f322be9b9da4628ba71183a4692d6c50821b962fd7754a4d0ae1d9bf94d1f"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "textbook_cycle4/p2/shots-512",
        "textbook_cycle4/p2/shots-17"
      ],
      "id": "circuit-result-331b768b6f7e1fbd9141d6e27c579b3276a8cd4bad68fc1cd7b1d749f50f10d4",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "61736110b245f364d34ca22086175643ff9cf36007fa5ad6103244426d9e4992",
      "status": "difference",
      "target_qasm_sha256": "c209abc21e712519308067385434006b75edae1845fe14496e7817ce54fa1044"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-a/shots-17"
      ],
      "id": "circuit-result-3c6a4df9ad50ebfa3d028c73a0ce4aa97bd80e3443798c78580ad996c4ba1113",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "8639d034fc5a3efc6c081ccf95347277db42bba5bc1940620c1ca097074680f9",
      "status": "difference",
      "target_qasm_sha256": "149a393284c8540e62e85a9c5c0cdc0daa5231b72685b0ee32666cf7c79469c2"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p1-b/shots-17"
      ],
      "id": "circuit-result-d64c5d8c2f56f0a22406bfb45772c02b063d6f8f5c807ea75eef012b54995dbb",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "fc787d670aac63e65bcd84c5e843becec9e158f81d8ace6858a36e416ebd06f6",
      "status": "difference",
      "target_qasm_sha256": "c9bc20b8a3f0359f8616f3db5243cd65e4728d3e8465a58d4a573a5a9e0d0e62"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "asymmetric4/p2/shots-512",
        "asymmetric4/p2/shots-17"
      ],
      "id": "circuit-result-865aad3f650499f681f1f7a7954887a6b6ac2e52f4fe1d62e0542c28f08c17ad",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "fb7a2dbffad5255626be301e5799cec8ebe58904a9784aad2c64286099b93fe8",
      "status": "difference",
      "target_qasm_sha256": "cef8dd9eda7b72333775d1b0556260a1bc13242b0c07690d0b2ee8847474581b"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "cycle5/p1-a/shots-512",
        "cycle5/p1-a/shots-17"
      ],
      "id": "circuit-result-4e2427aae66badc43f9da130d448ba293554b1ff22345a6796694589844c1030",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "276f3cc18c91d888ef3686903b7189c8a18439eaa168d484c3e5412d0d0e0028",
      "status": "difference",
      "target_qasm_sha256": "3c68239578de5cf6a1cfe5dda0fb65a2c4af86dcd9b5de90668a5d6eb637fe94"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "cycle5/p1-b/shots-512",
        "cycle5/p1-b/shots-17"
      ],
      "id": "circuit-result-9c01a550993142303f71617bf8973957cb18fd10e03268378c1ca0ac2f127d77",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "8bde8e9b7e2495820f71b77c10fb2eca58505a134b2926ec6889c1a00f5050f1",
      "status": "difference",
      "target_qasm_sha256": "53b610ee88fa8fda2fc193a1761b179df87e1ffa27b67edf85a76baf46d65966"
    },
    {
      "checker_config_sha256": "0d27336eaff61752cc2bd2435fb14d61789562404427f1f3f3c9245e7d30cec8",
      "criterion": "not_equivalent",
      "execution_ids": [
        "cycle5/p2/shots-512",
        "cycle5/p2/shots-17"
      ],
      "id": "circuit-result-788900cc52cbfea75a764015d452429210e77239dac86f3332811dc97703ac09",
      "reason_code": "circuit_not_equivalent",
      "reference_qasm_sha256": "ebb60263036fafde6135b239628eef14d7e7a250189d10e17ff658a2eb5dd49f",
      "status": "difference",
      "target_qasm_sha256": "d102fc8780b1b2d6c2e3edaedb524f718a5a288f2ff0582d5db3ef3e6ad36d65"
    }
  ],
  "coverage": {
    "angle_settings": 3,
    "completed_pairs": 18,
    "expected_executions": [
      "textbook_cycle4/p1-a/shots-512",
      "textbook_cycle4/p1-a/shots-17",
      "textbook_cycle4/p1-b/shots-512",
      "textbook_cycle4/p1-b/shots-17",
      "textbook_cycle4/p2/shots-512",
      "textbook_cycle4/p2/shots-17",
      "asymmetric4/p1-a/shots-512",
      "asymmetric4/p1-a/shots-17",
      "asymmetric4/p1-b/shots-512",
      "asymmetric4/p1-b/shots-17",
      "asymmetric4/p2/shots-512",
      "asymmetric4/p2/shots-17",
      "cycle5/p1-a/shots-512",
      "cycle5/p1-a/shots-17",
      "cycle5/p1-b/shots-512",
      "cycle5/p1-b/shots-17",
      "cycle5/p2/shots-512",
      "cycle5/p2/shots-17"
    ],
    "graphs": 3,
    "missing": {
      "reference": [],
      "target": []
    },
    "not_checked": [
      "optimizer convergence",
      "hardware execution",
      "noise models",
      "dynamic circuits",
      "inputs outside the declared graphs and angles",
      "whole-program equivalence"
    ],
    "observed": {
      "reference": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ],
      "target": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ]
    },
    "shot_requests": [
      512,
      17
    ]
  },
  "evidence_summary": "difference",
  "findings": [
    {
      "check_ids": [
        "circuit/textbook_cycle4/p1-a/shots-512",
        "circuit/textbook_cycle4/p1-a/shots-17",
        "circuit/textbook_cycle4/p1-b/shots-512",
        "circuit/textbook_cycle4/p1-b/shots-17",
        "circuit/textbook_cycle4/p2/shots-512",
        "circuit/textbook_cycle4/p2/shots-17",
        "circuit/asymmetric4/p1-a/shots-512",
        "circuit/asymmetric4/p1-a/shots-17",
        "circuit/asymmetric4/p1-b/shots-512",
        "circuit/asymmetric4/p1-b/shots-17",
        "circuit/asymmetric4/p2/shots-512",
        "circuit/asymmetric4/p2/shots-17",
        "circuit/cycle5/p1-a/shots-512",
        "circuit/cycle5/p1-a/shots-17",
        "circuit/cycle5/p1-b/shots-512",
        "circuit/cycle5/p1-b/shots-17",
        "circuit/cycle5/p2/shots-512",
        "circuit/cycle5/p2/shots-17"
      ],
      "explanation": "The checker reports the actually submitted circuits as not equivalent.",
      "id": "circuit",
      "kind": "circuit",
      "proposal_claim_refs": [],
      "scope_ids": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ],
      "title": "Submitted circuits differ"
    },
    {
      "check_ids": [
        "probability/textbook_cycle4/p1-a/shots-512",
        "probability/textbook_cycle4/p1-a/shots-17",
        "probability/textbook_cycle4/p1-b/shots-512",
        "probability/textbook_cycle4/p1-b/shots-17",
        "probability/textbook_cycle4/p2/shots-512",
        "probability/textbook_cycle4/p2/shots-17",
        "probability/asymmetric4/p1-a/shots-512",
        "probability/asymmetric4/p1-a/shots-17",
        "probability/asymmetric4/p1-b/shots-512",
        "probability/asymmetric4/p1-b/shots-17",
        "probability/asymmetric4/p2/shots-512",
        "probability/asymmetric4/p2/shots-17",
        "probability/cycle5/p1-a/shots-512",
        "probability/cycle5/p1-a/shots-17",
        "probability/cycle5/p1-b/shots-512",
        "probability/cycle5/p1-b/shots-17",
        "probability/cycle5/p2/shots-512",
        "probability/cycle5/p2/shots-17"
      ],
      "explanation": "Exact output probabilities differ beyond tolerance.",
      "id": "probability",
      "kind": "probability",
      "proposal_claim_refs": [],
      "scope_ids": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ],
      "title": "Ideal output distribution differs"
    },
    {
      "check_ids": [
        "exact-objective/textbook_cycle4/p1-a/shots-512",
        "exact-objective/textbook_cycle4/p1-a/shots-17",
        "exact-objective/textbook_cycle4/p1-b/shots-512",
        "exact-objective/textbook_cycle4/p1-b/shots-17",
        "exact-objective/textbook_cycle4/p2/shots-512",
        "exact-objective/textbook_cycle4/p2/shots-17",
        "exact-objective/asymmetric4/p1-a/shots-512",
        "exact-objective/asymmetric4/p1-a/shots-17",
        "exact-objective/asymmetric4/p1-b/shots-512",
        "exact-objective/asymmetric4/p1-b/shots-17",
        "exact-objective/asymmetric4/p2/shots-512",
        "exact-objective/asymmetric4/p2/shots-17",
        "exact-objective/cycle5/p1-a/shots-512",
        "exact-objective/cycle5/p1-a/shots-17",
        "exact-objective/cycle5/p1-b/shots-512",
        "exact-objective/cycle5/p1-b/shots-17",
        "exact-objective/cycle5/p2/shots-512",
        "exact-objective/cycle5/p2/shots-17"
      ],
      "explanation": "Independently computed exact objectives differ beyond tolerance.",
      "id": "exact-objective",
      "kind": "exact-objective",
      "proposal_claim_refs": [],
      "scope_ids": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ],
      "title": "Exact objective differs"
    },
    {
      "check_ids": [
        "shots-request/reference/textbook_cycle4/p1-a/shots-512",
        "shots-preservation/textbook_cycle4/p1-a/shots-512",
        "shots-request/reference/textbook_cycle4/p1-a/shots-17",
        "shots-preservation/textbook_cycle4/p1-a/shots-17",
        "shots-request/reference/textbook_cycle4/p1-b/shots-512",
        "shots-preservation/textbook_cycle4/p1-b/shots-512",
        "shots-request/reference/textbook_cycle4/p1-b/shots-17",
        "shots-preservation/textbook_cycle4/p1-b/shots-17",
        "shots-request/reference/textbook_cycle4/p2/shots-512",
        "shots-preservation/textbook_cycle4/p2/shots-512",
        "shots-request/reference/textbook_cycle4/p2/shots-17",
        "shots-preservation/textbook_cycle4/p2/shots-17",
        "shots-request/reference/asymmetric4/p1-a/shots-512",
        "shots-preservation/asymmetric4/p1-a/shots-512",
        "shots-request/reference/asymmetric4/p1-a/shots-17",
        "shots-preservation/asymmetric4/p1-a/shots-17",
        "shots-request/reference/asymmetric4/p1-b/shots-512",
        "shots-preservation/asymmetric4/p1-b/shots-512",
        "shots-request/reference/asymmetric4/p1-b/shots-17",
        "shots-preservation/asymmetric4/p1-b/shots-17",
        "shots-request/reference/asymmetric4/p2/shots-512",
        "shots-preservation/asymmetric4/p2/shots-512",
        "shots-request/reference/asymmetric4/p2/shots-17",
        "shots-preservation/asymmetric4/p2/shots-17",
        "shots-request/reference/cycle5/p1-a/shots-512",
        "shots-preservation/cycle5/p1-a/shots-512",
        "shots-request/reference/cycle5/p1-a/shots-17",
        "shots-preservation/cycle5/p1-a/shots-17",
        "shots-request/reference/cycle5/p1-b/shots-512",
        "shots-preservation/cycle5/p1-b/shots-512",
        "shots-request/reference/cycle5/p1-b/shots-17",
        "shots-preservation/cycle5/p1-b/shots-17",
        "shots-request/reference/cycle5/p2/shots-512",
        "shots-preservation/cycle5/p2/shots-512",
        "shots-request/reference/cycle5/p2/shots-17",
        "shots-preservation/cycle5/p2/shots-17"
      ],
      "explanation": "The reference and target complete different numbers of shots for the same request. This changes sampling uncertainty even when circuits are equivalent.",
      "id": "shot_policy",
      "kind": "shot_policy",
      "proposal_claim_refs": [],
      "scope_ids": [
        "asymmetric4/p1-a/shots-17",
        "asymmetric4/p1-a/shots-512",
        "asymmetric4/p1-b/shots-17",
        "asymmetric4/p1-b/shots-512",
        "asymmetric4/p2/shots-17",
        "asymmetric4/p2/shots-512",
        "cycle5/p1-a/shots-17",
        "cycle5/p1-a/shots-512",
        "cycle5/p1-b/shots-17",
        "cycle5/p1-b/shots-512",
        "cycle5/p2/shots-17",
        "cycle5/p2/shots-512",
        "textbook_cycle4/p1-a/shots-17",
        "textbook_cycle4/p1-a/shots-512",
        "textbook_cycle4/p1-b/shots-17",
        "textbook_cycle4/p1-b/shots-512",
        "textbook_cycle4/p2/shots-17",
        "textbook_cycle4/p2/shots-512"
      ],
      "title": "Shot setting changed"
    }
  ],
  "limitations": [
    "Checks cover only the declared graphs, angles and shot requests.",
    "Numerical agreement uses floating-point arithmetic with absolute tolerance 1e-10.",
    "No optimizer convergence, hardware, noise, dynamic-circuit or whole-program claim.",
    "The reference is a preservation baseline, not scientific truth.",
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