Merge pull request #541 from Avimita-amc8313/hamlib-changes

Hamlib with varying paramaters

hamlib/_common/hamiltonian_simulation_exact.py

@@ -8,6 +8,8 @@
 from qiskit import QuantumCircuit 
 from qiskit.quantum_info import SparsePauliOp
 from qiskit_algorithms import TimeEvolutionProblem, SciPyRealEvolver
+from qiskit_aer import Aer
+from qiskit import transpile
 import numpy as np
 np.random.seed(0)
 import execute as ex
@@ -171,3 +173,38 @@ def HamiltonianSimulationExact(n_spins: int):
     #   print (result)
 
     return result.evolved_state.probabilities_dict()
+
+def HamiltonianSimulationExact_Noiseless(n_spins: int):
+    """
+    Simulate a quantum Hamiltonian circuit for a specified number of spins using a noiseless quantum simulator.
+    
+    This function creates a quantum circuit, transpiles it for optimal execution, and runs it on a quantum simulator.
+    It simulates the circuit with a specified number of shots and collects the results to compute the probability 
+    distribution of measurement outcomes, normalized to represent probabilities.
+    
+    Args:
+        n_spins (int): The number of spins (qubits) to simulate in the circuit.
+    
+    Returns:
+        dict: A dictionary with keys representing the outcomes and values representing the probabilities of these outcomes.
+    
+    Note:
+        This function uses the 'qasm_simulator' backend from Qiskit's Aer module, which simulates a quantum circuit 
+        that measures qubits and returns a count of the measurement outcomes. The function assumes that the circuit 
+        creation and the simulator are perfectly noiseless, meaning there are no errors during simulation.
+    """
+    qc, _, _ = create_circuit(n_spins)
+    num_shots = 100000
+    backend = Aer.get_backend("qasm_simulator")
+    # Transpile and run the circuits
+    transpiled_qc = transpile(qc, backend, optimization_level=0)
+    job = backend.run(transpiled_qc, shots=num_shots)
+    result = job.result()
+    counts = result.get_counts(qc)
+    # Normalize probabilities for Heisenberg model circuit 
+    dist = {}
+    for key in counts.keys():
+        prob = counts[key] / num_shots
+        dist[key] = prob
+
+    return dist

hamlib/qiskit/hamlib_parameter_use_input.json

@@ -0,0 +1,30 @@
+{
+    "FH_D-1.hdf5": {
+      "fh": "graph-1D-grid-nonpbc-qubitnodes",
+      "Lx": "{n_qubits/2}",
+      "U": "0",
+      "enc": "jw"
+    },
+    "tfim.hdf5": {
+      "graph": "1D-grid-nonpbc-qubitnodes",
+      "Lx": "{n_qubits}",
+      "h": "0.1"
+    },
+    "random_max3sat-hams.hdf5": {
+      "max3sat_n": "{n_qubits}",
+      "ratio": "2",
+      "rinst": "00"
+    },
+    "heis.hdf5": {
+      "graph": "1D-grid-nonpbc-qubitnodes",
+      "Lx": "{n_qubits}",
+      "h": "0"
+    },
+    "BH_D-1_d-4.hdf5": {
+      "bh_graph": "1D-grid-nonpbc-qubitnodes",
+      "Lx": "{n_qubits/2}",
+      "U": "10",
+      "enc": "gray",
+      "d": "4"
+    }
+  }

hamlib/qiskit/hamlib_simulation_benchmark.py

@@ -28,7 +28,7 @@
 import metrics as metrics
 
 from hamlib_simulation_kernel import HamiltonianSimulation, kernel_draw, create_circuit, get_valid_qubits
-from hamiltonian_simulation_exact import HamiltonianSimulationExact
+from hamiltonian_simulation_exact import HamiltonianSimulationExact, HamiltonianSimulationExact_Noiseless
 # from hamlib_test import create_circuit, HamiltonianSimulationExact
 from qiskit_algorithms import TimeEvolutionProblem, SciPyRealEvolver
 
@@ -87,6 +87,8 @@ def analyze_and_print_result(qc, result, num_qubits: int,
         correct_dist = precalculated_data[f"TFIM - Qubits{num_qubits}"]
     elif method == 2 and hamiltonian == "tfim":
         correct_dist = precalculated_data[f"Exact TFIM - Qubits{num_qubits}"]
+    elif method == 1 and hamiltonian == "hamlib":
+        correct_dist = HamiltonianSimulationExact_Noiseless(num_qubits)
     elif method == 2 and hamiltonian == "hamlib":
         if verbose:
             print(f"... begin exact computation ...")
@@ -289,7 +291,7 @@ def execution_handler(qc, result, num_qubits, type, num_shots):
     ##########
 
     # draw a sample circuit
-    kernel_draw(hamiltonian, use_XX_YY_ZZ_gates, method)
+    # kernel_draw(hamiltonian, use_XX_YY_ZZ_gates, method)
 
     # Plot metrics for all circuit sizes
     options = {"ham": hamiltonian, "method":method, "shots": num_shots, "reps": max_circuits}

hamlib/qiskit/hamlib_simulation_kernel.py

@@ -16,6 +16,7 @@
 import os
 import requests
 import zipfile
+import json
 from qiskit.quantum_info import SparsePauliOp, Pauli
 from qiskit.circuit import QuantumCircuit
 from qiskit.circuit.library import PauliEvolutionGate
@@ -86,8 +87,57 @@ def sparse_pauliop(terms, num_qubits):
     hamiltonian = SparsePauliOp.from_list(pauli_list, num_qubits=num_qubits)
     return hamiltonian
 
-dataset_name_template = ""
-filename = ""
+def get_valid_qubits(min_qubits, max_qubits, skip_qubits):
+    """
+    Get an array of valid qubits within the specified range, removing duplicates.
+
+    Returns:
+        list: A list of valid qubits.
+    """
+    global dataset_name_template, filename
+
+    # Create an array with the given min, max, and skip values
+    qubit_candidates = list(range(min_qubits, max_qubits + 1, skip_qubits))
+    valid_qubits_set = set()  # Use a set to avoid duplicates
+
+    for qubits in qubit_candidates:
+        initial_n_spins = qubits // 2 if "{n_qubits/2}" in dataset_name_template else qubits
+        n_spins = initial_n_spins
+
+        # print(f"Starting check for qubits = {qubits}, initial n_spins = {n_spins}")
+
+        found_valid_dataset = False
+
+        while n_spins <= max_qubits:
+            dataset_name = dataset_name_template.replace("{n_qubits}", str(n_spins)).replace("{n_qubits/2}", str(n_spins))
+            # print(f"Checking dataset: {dataset_name}")
+
+            data = process_hamiltonian_file(filename, dataset_name)
+            if data is not None:
+                # print(f"Valid dataset found for n_spins = {n_spins}")
+                if "{n_qubits/2}" in dataset_name_template:
+                    valid_qubits_set.add(n_spins * 2)  # Add the original qubits value
+                else:
+                    valid_qubits_set.add(qubits)
+                found_valid_dataset = True
+                break
+            else:
+                # print(f"Dataset not available for n_spins = {n_spins}. Trying next value...")
+                n_spins += 1
+                if n_spins >= (qubits + skip_qubits) // 2 if "{n_qubits/2}" in dataset_name_template else (qubits + skip_qubits):
+                    print(f"No valid dataset found for qubits = {qubits}")
+                    break
+
+        if found_valid_dataset:
+            continue  # Move to the next candidate in the original skip sequence
+
+    valid_qubits = list(valid_qubits_set)  # Convert set to list to remove duplicates
+    valid_qubits.sort()  # Sorting the qubits for consistent order
+
+    if verbose:
+        print(f"Final valid qubits: {valid_qubits}")
+
+    return valid_qubits  
 
 # In hamiltonian_simulation_kernel.py
 
@@ -108,10 +158,13 @@ def create_circuit(n_spins: int, time: float = 0.2, num_trotter_steps: int = 5):
         tuple: A tuple containing the constructed QuantumCircuit and the Hamiltonian as a SparsePauliOp.
     """
     global dataset_name_template, filename
+    # global filename
     global QCI_
-
+
+    # dataset_name_template = construct_dataset_name(filename)
+    process_data(dataset_name_template)
     # Replace placeholders with actual n_spins value
-    dataset_name = dataset_name_template.replace("{n_spins}", str(n_spins)).replace("{n_spins/2}", str(n_spins // 2))
+    dataset_name = dataset_name_template.replace("{n_qubits}", str(n_spins)).replace("{n_qubits/2}", str(n_spins // 2))
 
     if verbose:
         print(f"Trying dataset: {dataset_name}")  # Debug print
@@ -156,58 +209,6 @@ def create_circuit(n_spins: int, time: float = 0.2, num_trotter_steps: int = 5):
         # print(f"Dataset not available for n_spins = {n_spins}.")
         return None, None, None
 
-def get_valid_qubits(min_qubits, max_qubits, skip_qubits):
-    """
-    Get an array of valid qubits within the specified range, removing duplicates.
-
-    Returns:
-        list: A list of valid qubits.
-    """
-    global dataset_name_template, filename
-
-    # Create an array with the given min, max, and skip values
-    qubit_candidates = list(range(min_qubits, max_qubits + 1, skip_qubits))
-    valid_qubits_set = set()  # Use a set to avoid duplicates
-
-    for qubits in qubit_candidates:
-        initial_n_spins = qubits // 2 if "{n_spins/2}" in dataset_name_template else qubits
-        n_spins = initial_n_spins
-
-        # print(f"Starting check for qubits = {qubits}, initial n_spins = {n_spins}")
-
-        found_valid_dataset = False
-
-        while n_spins <= max_qubits:
-            dataset_name = dataset_name_template.replace("{n_spins}", str(n_spins)).replace("{n_spins/2}", str(n_spins))
-            # print(f"Checking dataset: {dataset_name}")
-
-            data = process_hamiltonian_file(filename, dataset_name)
-            if data is not None:
-                # print(f"Valid dataset found for n_spins = {n_spins}")
-                if "{n_spins/2}" in dataset_name_template:
-                    valid_qubits_set.add(n_spins * 2)  # Add the original qubits value
-                else:
-                    valid_qubits_set.add(qubits)
-                found_valid_dataset = True
-                break
-            else:
-                # print(f"Dataset not available for n_spins = {n_spins}. Trying next value...")
-                n_spins += 1
-                if n_spins >= (qubits + skip_qubits) // 2 if "{n_spins/2}" in dataset_name_template else (qubits + skip_qubits):
-                    print(f"No valid dataset found for qubits = {qubits}")
-                    break
-
-        if found_valid_dataset:
-            continue  # Move to the next candidate in the original skip sequence
-
-    valid_qubits = list(valid_qubits_set)  # Convert set to list to remove duplicates
-    valid_qubits.sort()  # Sorting the qubits for consistent order
-
-    if verbose:
-        print(f"Final valid qubits: {valid_qubits}")
-
-    return valid_qubits  
-
 
 ############### Circuit Definition