Co

app.py

@@ -10,6 +10,9 @@ import matplotlib.pyplot as plt
 from PIL import Image
 import pennylane as qml
 
+# Define a device
+dev = qml.device('default.qubit', wires=10)
+
 # Hugging Face and DuckDB function placeholders
 def store_in_hf_dataset(data):
     # Implement storing data in the Hugging Face dataset
@@ -19,6 +22,13 @@ def load_from_hf_dataset():
     # Implement loading data from the Hugging Face dataset
     return []
 
+# Function to buffer the plot and return as PIL image
+def buffer_plot_and_get(fig):
+    buf = io.BytesIO()
+    fig.savefig(buf, format='png')
+    buf.seek(0)
+    return PIL.Image.open(buf)
+
 # Store image in bytes for DuckDB
 def pil_image_to_bytes(image):
     img_byte_arr = io.BytesIO()
@@ -35,6 +45,47 @@ def generate_random_hamiltonian(num_qubits):
         terms.append(term)
     return " + ".join(terms)
 
+# Function to convert Hamiltonian to QASM code
+def hamiltonian_to_qasm(hamiltonian, num_qubits):
+    qasm_code = f"OPENQASM 2.0;\ninclude \"qelib1.inc\";\nqreg q[{num_qubits}];\n"
+    rotations = {i: 0.0 for i in range(num_qubits)}
+    terms = hamiltonian.split(" + ")
+    
+    for term in terms:
+        coeff, paulis = term.split(" * ")
+        paulis = paulis.split()
+        coeff = float(coeff)
+
+        for i, pauli in enumerate(paulis):
+            if pauli == "X":
+                qasm_code += f"x q[{i}];\n"
+            elif pauli == "Y":
+                qasm_code += f"ry(pi/2) q[{i}];\n"
+            elif pauli == "Z":
+                rotations[i] += coeff
+
+    for i, angle in rotations.items():
+        if angle != 0:
+            angle_degrees = round(angle * 180 / math.pi, 2)
+            qasm_code += f"rz({angle_degrees}) q[{i}];\n"
+    
+    return qasm_code
+
+# Function for Trotter decomposition
+def trotter_decomposition(hamiltonian, order):
+    terms = hamiltonian.split(" + ")
+    trotter_steps = []
+    
+    for term in terms:
+        coeff, *pauli_ops = term.split(" * ")
+        coeff = float(coeff)
+        for _ in range(order):
+            trotter_steps.append(f"exp({coeff / order}) * ({' * '.join(pauli_ops)})")
+        for _ in range(order):
+            trotter_steps.append(f"exp({-coeff / order}) * ({' * '.join(pauli_ops)})")
+    
+    return " + ".join(trotter_steps)
+
 # Store data in DuckDB
 def store_in_duckdb(data, db_file='quantum_hamiltonians.duckdb'):
     conn = duckdb.connect(database=db_file)
@@ -91,9 +142,9 @@ def generate_hamiltonians(num_hamiltonians, selected_qubits, selected_order, wri
 # Function to load results from either DuckDB or Hugging Face dataset
 def load_results(load_from_hf, load_from_duckdb):
     if load_from_hf:
-        return load_from_hf_dataset()  # Load from HF dataset
+        return load_from_hf_dataset()
     if load_from_duckdb:
-        return load_from_duckdb()  # Load from DuckDB
+        return load_from_duckdb()
 
 # Gradio app
 with gr.Blocks() as app: