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[ 500 ], "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#center": 500.0, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#halfrange": 0.0, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#max": 500, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#mean": 500.0, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#min": 500, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#range": 0, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#range_percent": 0.0, "##characteristics#run#report#iterations@9#shots_per_individual_q_run@0#repeats": 3, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#all": [ 0.035665273666381836, 0.03963732719421387, 0.039835214614868164 ], "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#all_unique": [ 0.035665273666381836, 0.03963732719421387, 0.039835214614868164 ], "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#center": 0.037750244140625, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#halfrange": 0.002084970474243164, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#max": 0.039835214614868164, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#mean": 0.038379271825154625, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#min": 0.035665273666381836, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#range": 0.004169940948486328, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#range_percent": 0.11691879859082431, "##characteristics#run#report#iterations@9#total_q_seconds_per_c_iteration#repeats": 3, "##characteristics#run#report#iterations@9#total_q_shots_per_c_iteration#all": [ 500, 500, 500 ], 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"##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#all_unique": [ 0.03567218780517578, 0.03964400291442871, 0.03984332084655762 ], "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#center": 0.0377577543258667, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#halfrange": 0.002085566520690918, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#max": 0.03984332084655762, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#mean": 0.03838650385538737, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#min": 0.03567218780517578, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#range": 0.004171133041381836, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#range_percent": 0.11692955487234327, "##characteristics#run#report#iterations@9#total_seconds_per_c_iteration#repeats": 3, 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"##characteristics#run#report#total_q_shots#center": 40000.0, "##characteristics#run#report#total_q_shots#halfrange": 0.0, "##characteristics#run#report#total_q_shots#max": 40000, "##characteristics#run#report#total_q_shots#mean": 40000.0, "##characteristics#run#report#total_q_shots#min": 40000, "##characteristics#run#report#total_q_shots#range": 0, "##characteristics#run#report#total_q_shots#range_percent": 0.0, "##characteristics#run#report#total_q_shots#repeats": 3, "##characteristics#run#report#total_seconds#all": [ 3.1947646141052246, 3.2669856548309326, 3.4222259521484375 ], "##characteristics#run#report#total_seconds#all_unique": [ 3.1947646141052246, 3.2669856548309326, 3.4222259521484375 ], "##characteristics#run#report#total_seconds#center": 3.308495283126831, "##characteristics#run#report#total_seconds#halfrange": 0.11373066902160645, "##characteristics#run#report#total_seconds#max": 3.4222259521484375, "##characteristics#run#report#total_seconds#mean": 3.2946587403615317, "##characteristics#run#report#total_seconds#min": 3.1947646141052246, "##characteristics#run#report#total_seconds#range": 0.2274613380432129, "##characteristics#run#report#total_seconds#range_percent": 0.07119815245196687, "##characteristics#run#report#total_seconds#repeats": 3, "##characteristics#run#return_code#all": [ 0, 0, 0 ], "##characteristics#run#return_code#all_unique": [ 0 ], "##characteristics#run#return_code#center": 0.0, "##characteristics#run#return_code#halfrange": 0.0, "##characteristics#run#return_code#max": 0, "##characteristics#run#return_code#mean": 0.0, "##characteristics#run#return_code#min": 0, "##characteristics#run#return_code#range": 0, "##characteristics#run#return_code#repeats": 3, "##characteristics#run#run_success#all": [ "yes", "yes", "yes" ], "##characteristics#run#run_success#all_unique": [ "yes" ], "##characteristics#run#run_success#min": "yes", "##characteristics#run#run_success#repeats": 3, "##characteristics#run#run_success_bool#all": [ true, true, true ], "##characteristics#run#run_success_bool#all_unique": [ true ], "##characteristics#run#run_success_bool#min": true, "##characteristics#run#run_success_bool#repeats": 3, "##characteristics#run#total_execution_time#all": [ 0.0, 0.0, 0.0 ], "##characteristics#run#total_execution_time#all_unique": [ 0.0 ], "##characteristics#run#total_execution_time#center": 0.0, "##characteristics#run#total_execution_time#halfrange": 0.0, "##characteristics#run#total_execution_time#max": 0.0, "##characteristics#run#total_execution_time#mean": 0.0, "##characteristics#run#total_execution_time#min": 0.0, "##characteristics#run#total_execution_time#range": 0.0, "##characteristics#run#total_execution_time#repeats": 3, "##characteristics#run#vqe_input#ansatz_method#all": [ "universal_ansatz", "universal_ansatz", "universal_ansatz" ], "##characteristics#run#vqe_input#ansatz_method#all_unique": [ "universal_ansatz" ], "##characteristics#run#vqe_input#ansatz_method#min": "universal_ansatz", "##characteristics#run#vqe_input#ansatz_method#repeats": 3, "##characteristics#run#vqe_input#ansatz_src#all": [ "def universal_ansatz(current_params, entangler_map=None):\n if entangler_map==None:\n # Which qubits to use (0 to 1 best to avoid qiskit bugs)\n entangler_map = {1: [0]}\n\n return qiskit.tools.apps.optimization.trial_circuit_ryrz(num_of_qubits, circuit_depth, current_params, entangler_map, None, False)\n", "def universal_ansatz(current_params, entangler_map=None):\n if entangler_map==None:\n # Which qubits to use (0 to 1 best to avoid qiskit bugs)\n entangler_map = {1: [0]}\n\n return qiskit.tools.apps.optimization.trial_circuit_ryrz(num_of_qubits, circuit_depth, current_params, entangler_map, None, False)\n", "def universal_ansatz(current_params, entangler_map=None):\n if entangler_map==None:\n # Which qubits to use (0 to 1 best to avoid qiskit bugs)\n entangler_map = {1: [0]}\n\n return qiskit.tools.apps.optimization.trial_circuit_ryrz(num_of_qubits, circuit_depth, current_params, entangler_map, None, False)\n" ], "##characteristics#run#vqe_input#ansatz_src#all_unique": [ "def universal_ansatz(current_params, entangler_map=None):\n if entangler_map==None:\n # Which qubits to use (0 to 1 best to avoid qiskit bugs)\n entangler_map = {1: [0]}\n\n return qiskit.tools.apps.optimization.trial_circuit_ryrz(num_of_qubits, circuit_depth, current_params, entangler_map, None, False)\n" ], "##characteristics#run#vqe_input#ansatz_src#min": "def universal_ansatz(current_params, entangler_map=None):\n if entangler_map==None:\n # Which qubits to use (0 to 1 best to avoid qiskit bugs)\n entangler_map = {1: [0]}\n\n return qiskit.tools.apps.optimization.trial_circuit_ryrz(num_of_qubits, circuit_depth, current_params, entangler_map, None, False)\n", "##characteristics#run#vqe_input#ansatz_src#repeats": 3, "##characteristics#run#vqe_input#classical_energy#all": [ -1.8572746704950887, -1.8572746704950887, -1.8572746704950887 ], "##characteristics#run#vqe_input#classical_energy#all_unique": [ -1.8572746704950887 ], "##characteristics#run#vqe_input#classical_energy#center": -1.8572746704950887, "##characteristics#run#vqe_input#classical_energy#halfrange": 0.0, "##characteristics#run#vqe_input#classical_energy#max": -1.8572746704950887, "##characteristics#run#vqe_input#classical_energy#mean": -1.8572746704950884, "##characteristics#run#vqe_input#classical_energy#min": -1.8572746704950887, "##characteristics#run#vqe_input#classical_energy#range": 0.0, "##characteristics#run#vqe_input#classical_energy#range_percent": -0.0, "##characteristics#run#vqe_input#classical_energy#repeats": 3, "##characteristics#run#vqe_input#minimizer_method#all": [ "my_cobyla", "my_cobyla", "my_cobyla" ], "##characteristics#run#vqe_input#minimizer_method#all_unique": [ "my_cobyla" ], "##characteristics#run#vqe_input#minimizer_method#min": "my_cobyla", "##characteristics#run#vqe_input#minimizer_method#repeats": 3, "##characteristics#run#vqe_input#minimizer_options#fatol#all": [ 0.001, 0.001, 0.001 ], "##characteristics#run#vqe_input#minimizer_options#fatol#all_unique": [ 0.001 ], "##characteristics#run#vqe_input#minimizer_options#fatol#center": 0.001, "##characteristics#run#vqe_input#minimizer_options#fatol#halfrange": 0.0, "##characteristics#run#vqe_input#minimizer_options#fatol#max": 0.001, "##characteristics#run#vqe_input#minimizer_options#fatol#mean": 0.001, "##characteristics#run#vqe_input#minimizer_options#fatol#min": 0.001, "##characteristics#run#vqe_input#minimizer_options#fatol#range": 0.0, "##characteristics#run#vqe_input#minimizer_options#fatol#range_percent": 0.0, "##characteristics#run#vqe_input#minimizer_options#fatol#repeats": 3, "##characteristics#run#vqe_input#minimizer_options#maxfev#all": [ 200, 200, 200 ], "##characteristics#run#vqe_input#minimizer_options#maxfev#all_unique": [ 200 ], "##characteristics#run#vqe_input#minimizer_options#maxfev#center": 200.0, "##characteristics#run#vqe_input#minimizer_options#maxfev#halfrange": 0.0, "##characteristics#run#vqe_input#minimizer_options#maxfev#max": 200, "##characteristics#run#vqe_input#minimizer_options#maxfev#mean": 200.0, "##characteristics#run#vqe_input#minimizer_options#maxfev#min": 200, "##characteristics#run#vqe_input#minimizer_options#maxfev#range": 0, "##characteristics#run#vqe_input#minimizer_options#maxfev#range_percent": 0.0, "##characteristics#run#vqe_input#minimizer_options#maxfev#repeats": 3, "##characteristics#run#vqe_input#minimizer_options#maxiter#all": [ 80, 80, 80 ], "##characteristics#run#vqe_input#minimizer_options#maxiter#all_unique": [ 80 ], "##characteristics#run#vqe_input#minimizer_options#maxiter#center": 80.0, "##characteristics#run#vqe_input#minimizer_options#maxiter#halfrange": 0.0, "##characteristics#run#vqe_input#minimizer_options#maxiter#max": 80, "##characteristics#run#vqe_input#minimizer_options#maxiter#mean": 80.0, "##characteristics#run#vqe_input#minimizer_options#maxiter#min": 80, "##characteristics#run#vqe_input#minimizer_options#maxiter#range": 0, "##characteristics#run#vqe_input#minimizer_options#maxiter#range_percent": 0.0, "##characteristics#run#vqe_input#minimizer_options#maxiter#repeats": 3, "##characteristics#run#vqe_input#minimizer_options#xatol#all": [ 0.001, 0.001, 0.001 ], "##characteristics#run#vqe_input#minimizer_options#xatol#all_unique": [ 0.001 ], "##characteristics#run#vqe_input#minimizer_options#xatol#center": 0.001, "##characteristics#run#vqe_input#minimizer_options#xatol#halfrange": 0.0, "##characteristics#run#vqe_input#minimizer_options#xatol#max": 0.001, "##characteristics#run#vqe_input#minimizer_options#xatol#mean": 0.001, "##characteristics#run#vqe_input#minimizer_options#xatol#min": 0.001, "##characteristics#run#vqe_input#minimizer_options#xatol#range": 0.0, "##characteristics#run#vqe_input#minimizer_options#xatol#range_percent": 0.0, "##characteristics#run#vqe_input#minimizer_options#xatol#repeats": 3, "##characteristics#run#vqe_input#minimizer_src#all": [ "def my_cobyla( func, x0, my_args=(), my_options=None ):\n \"Stock COBYLA optimizer from SciPy library\"\n\n return scipy.optimize.minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", "def my_cobyla( func, x0, my_args=(), my_options=None ):\n \"Stock COBYLA optimizer from SciPy library\"\n\n return scipy.optimize.minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", "def my_cobyla( func, x0, my_args=(), my_options=None ):\n \"Stock COBYLA optimizer from SciPy library\"\n\n return scipy.optimize.minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n" ], "##characteristics#run#vqe_input#minimizer_src#all_unique": [ "def my_cobyla( func, x0, my_args=(), my_options=None ):\n \"Stock COBYLA optimizer from SciPy library\"\n\n return scipy.optimize.minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n" ], "##characteristics#run#vqe_input#minimizer_src#min": "def my_cobyla( func, x0, my_args=(), my_options=None ):\n \"Stock COBYLA optimizer from SciPy library\"\n\n return scipy.optimize.minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", "##characteristics#run#vqe_input#minimizer_src#repeats": 3, "##characteristics#run#vqe_input#q_device_name#all": [ "local_qasm_simulator", "local_qasm_simulator", "local_qasm_simulator" ], "##characteristics#run#vqe_input#q_device_name#all_unique": [ "local_qasm_simulator" ], "##characteristics#run#vqe_input#q_device_name#min": "local_qasm_simulator", "##characteristics#run#vqe_input#q_device_name#repeats": 3, "##characteristics#run#vqe_input#sample_number#all": [ 500, 500, 500 ], "##characteristics#run#vqe_input#sample_number#all_unique": [ 500 ], "##characteristics#run#vqe_input#sample_number#center": 500.0, "##characteristics#run#vqe_input#sample_number#halfrange": 0.0, "##characteristics#run#vqe_input#sample_number#max": 500, "##characteristics#run#vqe_input#sample_number#mean": 500.0, "##characteristics#run#vqe_input#sample_number#min": 500, "##characteristics#run#vqe_input#sample_number#range": 0, "##characteristics#run#vqe_input#sample_number#range_percent": 0.0, "##characteristics#run#vqe_input#sample_number#repeats": 3, "##characteristics#run#vqe_output#fun#all": [ -1.8745878979616577, -1.8719048033774717, -1.8529236485598288 ], "##characteristics#run#vqe_output#fun#all_unique": [ -1.8745878979616577, -1.8719048033774717, -1.8529236485598288 ], "##characteristics#run#vqe_output#fun#center": -1.8637557732607433, "##characteristics#run#vqe_output#fun#halfrange": 0.010832124700914436, "##characteristics#run#vqe_output#fun#max": -1.8529236485598288, "##characteristics#run#vqe_output#fun#mean": -1.866472116632986, "##characteristics#run#vqe_output#fun#min": -1.8745878979616577, "##characteristics#run#vqe_output#fun#range": 0.021664249401828872, 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