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"##characteristics#run#total_execution_time#range": 0.0, "##characteristics#run#total_execution_time#repeats": 3, "##characteristics#run#vqe_input#classical_energy#all": [ -2.8077839575399746, -2.8077839575399746, -2.8077839575399746 ], "##characteristics#run#vqe_input#classical_energy#all_unique": [ -2.8077839575399746 ], "##characteristics#run#vqe_input#classical_energy#center": -2.8077839575399746, "##characteristics#run#vqe_input#classical_energy#exp": -2.8077839575399746, "##characteristics#run#vqe_input#classical_energy#exp_allx": [ -2.8077839575399746 ], "##characteristics#run#vqe_input#classical_energy#exp_ally": [ 100.0 ], "##characteristics#run#vqe_input#classical_energy#exp_warning": "no", "##characteristics#run#vqe_input#classical_energy#halfrange": 0.0, "##characteristics#run#vqe_input#classical_energy#max": -2.8077839575399746, "##characteristics#run#vqe_input#classical_energy#mean": -2.8077839575399746, "##characteristics#run#vqe_input#classical_energy#min": -2.8077839575399746, "##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#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#exp": 80.0, "##characteristics#run#vqe_input#minimizer_options#maxiter#exp_allx": [ 80.0 ], "##characteristics#run#vqe_input#minimizer_options#maxiter#exp_ally": [ 100.0 ], "##characteristics#run#vqe_input#minimizer_options#maxiter#exp_warning": "no", "##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_src#all": [ "def my_cobyla( func, x0, my_args=(), my_options=None ): # another non-stochastic minimizer for comparison\n \"COBYLA optimizer from SciPy library\"\n\n return minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", "def my_cobyla( func, x0, my_args=(), my_options=None ): # another non-stochastic minimizer for comparison\n \"COBYLA optimizer from SciPy library\"\n\n return minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", "def my_cobyla( func, x0, my_args=(), my_options=None ): # another non-stochastic minimizer for comparison\n \"COBYLA optimizer from SciPy library\"\n\n return 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 ): # another non-stochastic minimizer for comparison\n \"COBYLA optimizer from SciPy library\"\n\n return 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 ): # another non-stochastic minimizer for comparison\n \"COBYLA optimizer from SciPy library\"\n\n return minimize( func, x0, method='COBYLA', options=my_options, args=my_args )\n", 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0.27329070519808357, 0.21833972115019554 ], "##characteristics#run#vqe_output#fun_validated#exp_warning": "yes", "##characteristics#run#vqe_output#fun_validated#halfrange": 1.0529189840774904, "##characteristics#run#vqe_output#fun_validated#max": -0.7019459893849936, "##characteristics#run#vqe_output#fun_validated#mean": -1.8718559716933163, "##characteristics#run#vqe_output#fun_validated#min": -2.8077839575399746, "##characteristics#run#vqe_output#fun_validated#range": 2.105837968154981, "##characteristics#run#vqe_output#fun_validated#range_percent": -0.75, "##characteristics#run#vqe_output#fun_validated#repeats": 3, "##characteristics#run#vqe_output#maxcv#all": [ 0.0, 0.0, 0.0 ], "##characteristics#run#vqe_output#maxcv#all_unique": [ 0.0 ], "##characteristics#run#vqe_output#maxcv#center": 0.0, "##characteristics#run#vqe_output#maxcv#exp": 0.0, "##characteristics#run#vqe_output#maxcv#exp_allx": [ 0.0 ], "##characteristics#run#vqe_output#maxcv#exp_ally": [ 100.0 ], "##characteristics#run#vqe_output#maxcv#exp_warning": "no", "##characteristics#run#vqe_output#maxcv#halfrange": 0.0, "##characteristics#run#vqe_output#maxcv#max": 0.0, "##characteristics#run#vqe_output#maxcv#mean": 0.0, "##characteristics#run#vqe_output#maxcv#min": 0.0, "##characteristics#run#vqe_output#maxcv#range": 0.0, "##characteristics#run#vqe_output#maxcv#repeats": 3, "##characteristics#run#vqe_output#message#all": [ "Optimization terminated successfully.", "Optimization terminated successfully.", "Optimization terminated successfully." ], "##characteristics#run#vqe_output#message#all_unique": [ "Optimization terminated successfully." ], "##characteristics#run#vqe_output#message#min": "Optimization terminated successfully.", "##characteristics#run#vqe_output#message#repeats": 3, "##characteristics#run#vqe_output#nfev#all": [ 16, 19, 29 ], "##characteristics#run#vqe_output#nfev#all_unique": [ 16, 19, 29 ], "##characteristics#run#vqe_output#nfev#center": 22.5, 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