working mqtt connection

source/vqe.py

@@ -0,0 +1,45 @@
+from pennylane import numpy as np
+import pennylane as qml
+import os
+from multiprocessing import Queue
+
+os.environ["OMP_NUM_THREADS"] = '16'
+
+def get_sctructure_from_xyz_path(path: str):
+    return qml.qchem.read_structure("methane.xyz")
+
+def run_vqe(q: Queue, symbols, coordinates, active_electrons, active_orbitals, max_iterations, conv_tol, step_size):
+    molecule = qml.qchem.Molecule(symbols, coordinates, load_data=True)
+    H, qubits = qml.qchem.molecular_hamiltonian(molecule, active_electrons=active_electrons,
+        active_orbitals=active_orbitals)
+    dev = qml.device("lightning.qubit", wires=qubits)
+
+
+
+    singles, doubles = qml.qchem.excitations(active_electrons, qubits)
+    params =  np.array(np.zeros(len(singles) + len(doubles)), requires_grad=True)
+    @qml.qnode(dev)
+    def circuit(param, wires):
+            # Map excitations to the wires the UCCSD circuit will act on
+        s_wires, d_wires = qml.qchem.excitations_to_wires(singles, doubles)
+        qml.UCCSD(param, wires, s_wires=s_wires, d_wires=d_wires, init_state=qml.qchem.hf_state(active_electrons, qubits))
+        return qml.expval(H)
+
+    def cost_fn(param):
+        return circuit(param, wires=range(qubits))
+    
+    opt = qml.GradientDescentOptimizer(stepsize=step_size)
+    
+    for n in range(max_iterations):
+        # Take step
+        params, prev_energy = opt.step_and_cost(cost_fn, params)
+
+        energy = cost_fn(params)
+
+        # Calculate difference between new and old energies
+        conv = np.abs(energy - prev_energy)
+
+        q.put([n, energy,params])
+
+        if conv <= conv_tol:
+            break