update qiskit simulator usage, skip test on missing qiskit

qtensor/optimisation/Optimizer.py

@@ -104,7 +104,7 @@ def _get_max_tw(self):
         log.info('Memory available: {}', avail)
         # Cost = 16*2**tw
         # tw = log(cost/16) = log(cost) - 4
-        return np.int(np.log2(avail)) - 4
+        return int(np.log2(avail)) - 4
 
     def _split_graph(self, p_graph, max_tw):
         searcher = GreedyParvars(p_graph)

qtensor/tests/qiskit_qaoa_energy.py

@@ -2,10 +2,6 @@
 import networkx as nx
 from functools import partial
 
-from qiskit import QuantumCircuit, ClassicalRegister, QuantumRegister
-from qiskit import Aer, execute
-from qiskit.circuit import Parameter
-
 
 def maxcut_obj(x, G):
     """
@@ -66,6 +62,7 @@ def create_qaoa_circ(G, theta):
     Returns:
         qc: qiskit circuit
     """
+    from qiskit import QuantumCircuit
     nqubits = len(G.nodes())
     p = len(theta)//2  # number of alternating unitaries
     qc = QuantumCircuit(nqubits)
@@ -94,7 +91,8 @@ def get_expectation(G, shots=512):
         p: int,
            Number of repetitions of unitaries
     """
-    backend = Aer.get_backend('qasm_simulator')
+    from qiskit_aer import AerSimulator
+    backend = AerSimulator(method='statevector')
 
     def execute_circ(theta):
         qc = create_qaoa_circ(G, theta)

qtensor/tests/test_bucket_backends.py

@@ -7,9 +7,6 @@
 
 
 def get_test_problem():
-    w = np.array([[0,1,1,0],[1,0,1,1],[1,1,0,1],[0,1,1,0]])
-    G = nx.from_numpy_matrix(w)
-
     G = nx.random_regular_graph(5, 14)
     gamma, beta = [np.pi/3], [np.pi/2]
     return G, gamma, beta

qtensor/tests/test_composers.py

@@ -10,7 +10,7 @@
 
 def get_test_problem():
     w = np.array([[0,1,1,0],[1,0,1,1],[1,1,0,1],[0,1,1,0]])
-    G = nx.from_numpy_matrix(w)
+    G = nx.from_numpy_array(w)
     gamma, beta = [np.pi/3], [np.pi/2]
     return G, gamma, beta
 

qtensor/tests/test_optimizers.py

@@ -11,8 +11,6 @@
 import pytest
 
 def get_test_problem(n=14, p=2, d=3):
-    w = np.array([[0,1,1,0],[1,0,1,1],[1,1,0,1],[0,1,1,0]])
-    G = nx.from_numpy_matrix(w)
 
     G = nx.random_regular_graph(d, n)
     gamma, beta = [np.pi/3]*p, [np.pi/2]*p

qtensor/tests/test_qaoa_energy.py

@@ -11,6 +11,7 @@
 from qtensor.FeynmanSimulator import FeynmanSimulator
 from qtensor.optimisation.Optimizer import TamakiTrimSlicing, TreeTrimSplitter
 from qtensor.tests.qiskit_qaoa_energy import simulate_qiskit_amps
+qiskit_aer = pytest.importorskip('qiskit_aer')
 
 @lru_cache
 def get_test_problem(n=10, p=2, d=3, type='random'):

qtensor/tests/test_simulators.py

@@ -10,9 +10,6 @@
 
 
 def get_test_problem(n=14, p=2, d=3):
-    w = np.array([[0,1,1,0],[1,0,1,1],[1,1,0,1],[0,1,1,0]])
-    G = nx.from_numpy_matrix(w)
-
     G = nx.random_regular_graph(d, n)
     gamma, beta = [np.pi/3]*p, [np.pi/2]*p
     return G, gamma, beta

setup.py

@@ -7,7 +7,6 @@
     'matplotlib>=3.1.3'
     ,'google-api-core[grpc]<=1.14.0'
     ,'cirq'
-    ,'qiskit'
     ,'qiskit-optimization'
     ,'pyrofiler>=0.1.5'
     ,'loguru'