I am working on a Grover’s algorithm in Qiskit with two oracles. Each oracle marks a different state as “good”. I want to add a few more oracles to mark specific states as “bad”, in order to decrease their probability relative to other states. Could someone advise on how to write such oracles..? Thank you

Here’s my current implementation:

from qiskit import QuantumCircuit, transpile, execute
from qiskit_aer import AerSimulator
import numpy as np

def oracle127(qc):
    n = 10
    qc.x([0, 1, 2])
    qc.mcx([i for i in range(n)], n)
    qc.x([0, 1, 2])
    return qc

def oracle896(qc):
    n = 10
    qc.x([3, 4, 5, 6, 7, 8, 9])
    qc.mcx([i for i in range(n)], n)
    qc.x([3, 4, 5, 6, 7, 8, 9])
    return qc

def main():
    n = 10  # Number of qubits
    qc = QuantumCircuit(n + 1, n)
    qc.x(n)
    qc.h(range(n + 1))
    k = 2  # Number of oracles
    r = int(np.pi * np.sqrt(2**n/k) / 4)  # Number of iterations
    for _ in range(r):
        qc = oracle127(qc)  # Apply first oracle
        qc = oracle896(qc)  # Apply second oracle
        # Diffusion operation
        qc.h(range(n))
        qc.x(range(n))
        qc.h(n - 1)
        qc.mcx([i for i in range(n-1)], n - 1)
        qc.h(n - 1)
        qc.x(range(n))
        qc.h(range(n))
    qc.measure(range(n), range(n))

    backend = AerSimulator()
    compiled_circuit = transpile(qc, backend)
    job = backend.run(compiled_circuit, shots=1000)
    counts = job.result().get_counts()
    print(counts)

main()