[Python] how to build a kernel matrix that doesn't recursively call the quantum kernel

from qiskit_ibm_runtime import QiskitRuntimeService, Session
from qiskit_ibm_runtime import Sampler

token = "my ibm token "
cafile = 'Security file'


service = QiskitRuntimeService(channel="ibm_quantum", token=token, verify=cafile)

from qiskit_aer import Aer, AerSimulator
def quantum_kernel(x1,x2):
n = len(x1)
circuit1 = QuantumCircuit(n)
circuit2 = QuantumCircuit(n)

circuit1 = feature_map(circuit1,x1)
circuit2 = feature_map(circuit2,x2)

circuit = QuantumCircuit(2*n + 1,1)

circuit.append(circuit1, range(n))
circuit.append(circuit2, range(n, 2*n))

circuit.h(2*n)
for i in range(n):
circuit.cswap(2*n, i, n+i)
circuit.h(2*n)

circuit.measure(2*n,0)



backend = service.least_busy(operational=True, simulator=False)

transpiled_circuit = transpile(circuit , backend = backend)

sampler = Sampler(backend)
job = sampler.run([transpiled_circuit])
print(f"job id : {job.job_id()}")
result = job.result()
#print(result)

pub_result = result[0]
bit_array = pub_result.data.c


import numpy as np
bit_data = np.array(bit_array._array)


flat_bits = bit_data.flatten()


counts = {'0': 0, '1': 0}


for bit in flat_bits:
if bit == 0:
counts['0'] += 1
elif bit == 1:
counts['1'] += 1


zero_prob = counts.get('0', 0) / 4096


kernel_value = 2 * zero_prob - 1
return kernel_value



num_samples = len(norm_data)

quantum_kernel_matrix = np.zeros((num_samples, num_samples))

for i in range(num_samples):
for j in range(num_samples):
x1 = norm_data
x2 = norm_data[j]
kernel_value = quantum_kernel(x1,x2)
quantum_kernel_matrix[i,j] = kernel_value



print("quantum kernel matrix :")
print(quantum_kernel_matrix)


the above is the code that I have written to compute the kernel value and the matrix but the problem is this code is assigning different quantum jobs for computing each pair (i,j) of the kernel matrix can somebody help me so that the code won't recursively call the quantum kernel but gives me the matrix.

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