fix typos and update license

README.md

@@ -9,7 +9,7 @@
   [![Documentation Status](https://readthedocs.org/projects/el-openqaoa/badge/?version=latest)](https://el-openqaoa.readthedocs.io/en/latest/?badge=latest) <!-- Readthedocs -->
   [![PyPI version](https://badge.fury.io/py/openqaoa.svg)](https://badge.fury.io/py/openqaoa) <!-- PyPI -->
   [![arXiv](https://img.shields.io/badge/arXiv-2210.08695-<COLOR>.svg)](https://arxiv.org/abs/2210.08695) <!-- arXiv -->
-  [![License](https://img.shields.io/badge/%F0%9F%AA%AA%20license-Apache%20License%202.0-lightgrey)](LICENSE.md)<!-- License -->
+  [![License](https://img.shields.io/pypi/l/openqaoa)](LICENSE.md)<!-- License -->
   [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](CODE_OF_CONDUCT.md)<!-- Covenant Code of conduct -->
   [![Downloads](https://pepy.tech/badge/openqaoa)](https://pepy.tech/project/openqaoa)
   [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/entropicalabs/openqaoa.git/main?labpath=%2Fexamples)
@@ -23,6 +23,8 @@ A multi-backend python library for quantum optimization using QAOA on Quantum co
 
 Please, consider [joining our discord](https://discord.gg/ana76wkKBd) if you want to be part of our community and participate in the OpenQAOA's development. 
 
+Check out OpenQAOA website [https://openqaoa.entropicalabs.com/](https://openqaoa.entropicalabs.com/)
+
 ## Installation instructions
 
 You can install the latest version of OpenQAOA directly from PyPi. First, create a virtual environment with python3.8+ and then simply pip install openqaoa with the following command

src/openqaoa-core/algorithms/jobs/managed_job.py

@@ -1,17 +1,3 @@
-#   Copyright 2022 Entropica Labs
-#
-#   Licensed under the Apache License, Version 2.0 (the "License");
-#   you may not use this file except in compliance with the License.
-#   You may obtain a copy of the License at
-#
-#       http://www.apache.org/licenses/LICENSE-2.0
-#
-#   Unless required by applicable law or agreed to in writing, software
-#   distributed under the License is distributed on an "AS IS" BASIS,
-#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#   See the License for the specific language governing permissions and
-#   limitations under the License.
-
 import os
 
 from openqaoa_braket.backends import DeviceAWS

src/openqaoa-core/algorithms/rqaoa/rqaoa_result.py

@@ -73,24 +73,24 @@ def from_dict(
         dictionary:dict
     ):
         """
-        Creates a RQAOAResul object from a dictionary (which is the output of the asdict method).
+        Creates a RQAOAResult object from a dictionary (which is the output of the asdict method).
         Parameters
         ----------
         dictionary : dict
             The input dictionary.
         Returns
         -------
-        RQAOAResul
-            The RQAOAResul object.
+        RQAOAResult
+            The RQAOAResult object.
         """
 
         # deepcopy the dictionary, so that the original dictionary is not changed
         dictionary = copy.deepcopy(dictionary)
 
-        # create a new RQAOAResul object
+        # create a new RQAOAResult object
         results = cls()
 
-        # add the keys of the dictionary to the RQAOAResul object
+        # add the keys of the dictionary to the RQAOAResult object
         for key, value in dictionary.items():
             results[key] = value
 

src/openqaoa-core/algorithms/rqaoa/rqaoa_workflow.py

@@ -51,17 +51,17 @@ class RQAOA(Workflow):
         For a complete list of its parameters and usage please see the method set_circuit_properties
     rqaoa_parameters: `RqaoaParameters`
         Set of parameters containing all the relevant information for the recursive procedure of RQAOA.
-    results: `RQAOAResul`
+    results: `RQAOAResult`
         The results of the RQAOA optimization.
         Dictionary containing all the information about the RQAOA run: the
         solution states and energies (key: 'solution'), the output of the classical
         solver (key: 'classical_output'), the elimination rules for each step
         (key: 'elimination_rules'), the number of eliminations at each step (key: 'schedule'),
         total number of steps (key: 'number_steps'), the intermediate QUBO problems and the
         intermediate QAOA objects that have been optimized in each RQAOA step (key: 'intermediate_problems').
-        This object (`RQAOAResul`) is a dictionary with some custom methods as
-        RQAOAResul.get_hamiltonian_step(i) which get the hamiltonian of reduced problem of the i-th step.
-        To see the full list of methods please see the RQAOAResul class.
+        This object (`RQAOAResult`) is a dictionary with some custom methods as
+        RQAOAResult.get_hamiltonian_step(i) which get the hamiltonian of reduced problem of the i-th step.
+        To see the full list of methods please see the RQAOAResult class.
 
     Examples
     --------

src/openqaoa-core/qaoa_components/ansatz_constructor/baseparams.py

@@ -7,7 +7,6 @@
 from .hamiltonianmapper import HamiltonianMapper
 from .gatemap import RotationGateMap
 
-from .gatemap import RotationGateMap
 
 def _is_iterable_empty(in_iterable):
     if isinstance(in_iterable, Iterable):  # Is Iterable

src/openqaoa-core/utilities.py

@@ -1682,7 +1682,7 @@ def dicke_wavefunction(excitations, n_qubits):
     Returns
     -------
     `np.ndarray`
-        The wavefunction vector for a given cumulative Dicke states with <=k excitations
+        The wavefunction vector for a given cumulative Dicke states with $<=k$ excitations
     """
 
     k_dicke = dicke_basis(excitations, n_qubits)

tests/jobs_test_input/input_data/openqaoa_params.json

@@ -1,19 +1,16 @@
 {
   "header": {
-    "atomic_id": "077777dc-dedb-4d43-8fdd-022a9c1b44fc",
-    "experiment_id": "d831008a-6f69-4c3d-ada5-015a92105825",
+    "atomic_id": "354d0fc2-6c88-46e7-968b-afd1a85ab4fc",
+    "experiment_id": "1eb533d2-1a82-4cc6-bd36-ab452b46cb48",
     "project_id": null,
     "algorithm": "rqaoa",
-    "name": null,
+    "description": null,
     "run_by": null,
     "provider": null,
     "target": null,
     "cloud": null,
     "client": null,
     "qubit_number": 10,
-    "qubit_routing": null,
-    "error_mitigation": null,
-    "error_correction": null,
     "execution_time_start": null,
     "execution_time_end": null,
     "metadata": {
@@ -25,7 +22,7 @@
       "p": 1,
       "rqaoa_type": "custom",
       "rqaoa_n_max": 1,
-      "rqaoa_n_cutoff": 6
+      "rqaoa_n_cutoff": 3
     }
   },
   "data": {
@@ -215,8 +212,8 @@
     },
     "input_parameters": {
       "device": {
-        "device_location": "aws",
-        "device_name": "arn:aws:braket:::device/quantum-simulator/amazon/sv1"
+        "device_location": "local",
+        "device_name": "vectorized"
       },
       "backend_properties": {
         "init_hadamard": true,
@@ -271,16 +268,19 @@
         "rqaoa_type": "custom",
         "n_max": 1,
         "steps": [
-          1,
-          1,
-          1,
-          1
+          2,
+          2,
+          2,
+          2,
+          2,
+          2,
+          2
         ],
-        "n_cutoff": 6,
+        "n_cutoff": 3,
         "original_hamiltonian": null,
         "counter": 0
       }
     },
-    "results": null
+    "result": null
   }
 }