Merge remote-tracking branch 'upstream/master'

Author: nonhermitian

.github/CODEOWNERS

@@ -1,26 +1,56 @@
 # Fallback codeowners for all files that do not have an explicit rule.
-* @jaygambetta
+* @jaygambetta @ajavadia
 
 # Codeowners for individual folders
-qiskit/* @jaygambetta
-qiskit/aer/* @chriseclectic @jaygambetta
-qiskit/ignis/* @dcmckayibm @jaygambetta
+qiskit/* @jaygambetta @ajavadia
+qiskit/aer/* @chriseclectic @jaygambetta @ajavadia
+qiskit/ignis/* @dcmckayibm @jaygambetta @ajavadia
+qiskit/terra/* @nonhermitian @jaygambetta @ajavadia
 
-community/hello_world/* @quantumjim @aasfaw
-community/hello_world/*/* @quantumjim @aasfaw
-community/games/* @quantumjim @aasfaw
-community/games/*/* @quantumjim @aasfaw
+community/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/aer/* @chriseclectic @attp @aasfaw @quantumjim @rraymondhp
+
+community/algorithms/* @attp @aasfaw @quantumjim @rraymondhp
+community/algorithms/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/arts/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/aqua/* @chunfuchen @pistoia @aasfaw
+community/aqua/*/* @chunfuchen @pistoia @aasfaw
+community/aqua/*/*/* @chunfuchen @pistoia @aasfaw
+
+community/artificial_intelligence/* @chunfuchen @pistoia @aasfaw
+community/artificial_intelligence/*/* @chunfuchen @pistoia @aasfaw
+community/artificial_intelligence/*/*/* @chunfuchen @pistoia @aasfaw
 
-community/terra/* @attp @ajavadia @aasfaw
-community/terra/*/* @attp @ajavadia @aasfaw
-community/algorithms/* @attp @ajavadia @aasfaw
+community/chemistry/* @chunfuchen @pistoia @aasfaw
+community/chemistry/*/* @chunfuchen @pistoia @aasfaw
+community/chemistry/*/*/* @chunfuchen @pistoia @aasfaw
 
-community/aqua/* @chunfuchen @pistoia
-community/aqua/*/* @chunfuchen @pistoia
-community/aqua/*/*/* @chunfuchen @pistoia
+community/finance/* @chunfuchen @pistoia @aasfaw
+community/finance/*/* @chunfuchen @pistoia @aasfaw
+community/finance/*/*/* @chunfuchen @pistoia @aasfaw
+
+community/optimization/* @chunfuchen @pistoia @aasfaw
+community/optimization/*/* @chunfuchen @pistoia @aasfaw
+community/optimization/*/*/* @chunfuchen @pistoia @aasfaw
+
+community/awards/teach_me_qiskit_2018/* @attp @aasfaw @quantumjim @rraymondhp
+community/awards/teach_me_qiskit_2018/*/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/awards/teach_me_quantum_2018/* @attp @aasfaw @quantumjim @rraymondhp
+community/awards/teach_me_quantum_2018/*/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/games/* @attp @aasfaw @quantumjim @rraymondhp
+community/games/*/* @attp @aasfaw @quantumjim @rraymondhp
+community/games/*/*/* @attp @aasfaw @quantumjim @rraymondhp
+community/games/*/*/*/* @attp @aasfaw @quantumjim @rraymondhp
+
+community/hello_world/* @quantumjim @aasfaw
+community/hello_world/*/* @quantumjim @aasfaw
 
-community/awards/teach_me_qiskit_2018/* @rraymondhp @aasfaw
-community/awards/teach_me_qiskit_2018/*/* @rraymondhp @aasfaw
+community/ignis/* @dcmckayibm @yehuda-naveh @attp @aasfaw @quantumjim @rraymondhp
 
-community/ignis/* @dcmckayibm @aasfaw
-community/aer/* @chriseclectic @aasfaw
+community/terra/* @nonhermitian @attp @aasfaw @quantumjim @rraymondhp
+community/terra/*/* @nonhermitian @attp @aasfaw @quantumjim @rraymondhp

.gitignore

@@ -30,3 +30,5 @@ qiskit/basics/Qconfig_IBMQ_experience_staging.py
 
 qiskit/basics/Qconfig_IBMQ_network-dev.py
 .DS_Store
+
+qiskit/.ipynb_checkpoints/start_here-checkpoint.ipynb

INSTALL.md

@@ -20,13 +20,13 @@ At least [Python 3.5 or later](https://www.python.org/downloads/) is required to
 When there are no issues with dependencies, Qiskit can be simply installed using
 
 ```
-pip install qiskit qiskit-aqua qiskit-chemistry
+pip install qiskit
 ```
 
 Or, pre-installed qiskit can be updated using
 
 ```
-pip install -U qiskit qiskit-aqua qiskit-chemistry
+pip install -U qiskit
 ```
 
 However, in case of issues with dependencies, we recommend the following installation procedure:

README.md

@@ -10,7 +10,7 @@ In this repository, we've put together a collection of Jupyter notebooks aimed a
 
 The notebooks for these tutorials can be viewed here on GitHub. But for the full experience, you'll want to interact with them!
 
-The easiest way to do this is using [the Binder image](https://mybinder.org/v2/gh/qiskit/qiskit-tutorials/master?filepath=index.ipynb), which lets you use the notebooks via the web. This means that you don't need to download or install anything, but it also means that you should not insert any private information into the notebooks (such as your API key). We recommend as pointed out in [issue #231](https://github.com/Qiskit/qiskit-tutorials/issues/231) that after you are done using mybinder that you regenerate your token.
+The easiest way to do this is using [the Binder image](https://mybinder.org/v2/gh/qiskit/qiskit-tutorials/master?filepath=./qiskit/start_here.ipynb), which lets you use the notebooks via the web. This means that you don't need to download or install anything, but it also means that you should not insert any private information into the notebooks (such as your API key). We recommend as pointed out in [issue #231](https://github.com/Qiskit/qiskit-tutorials/issues/231) that after you are done using mybinder that you regenerate your token.
 
 Please refer to this [installation guide](INSTALL.md) for setting up Qiskit and the tutorials on your own machine (this is the recommended way).
 
@@ -28,17 +28,20 @@ We've collected a core reference set of notebooks in this section outlining the
 - [Aqua](qiskit/aqua) is meant for those who want to develop applications on NISQ computers.
 - [Jupyter](qiskit/jupyter) is meant to highlight some cool Juypter features.
 
+To go through the official qiskit examples load up the [start_here.ipynb](qiskit/start_here.ipynb) notebook and start seeing how qiskit works.
+
 ### 2. [Community notebooks](community/)<a id='community'></a>
 
 Teaching quantum computing and qiskit has many different paths of learning. We love our community, and we love the contributions so keep them coming. Because Qiskit is changing so much, at the moment we cant keep this updated, but there are some great notebooks in here. See:
 - [Hello, Quantum World](community/hello_world/) learn from the community how to write your first quantum program.
 - [Quantum Games](community/games/), learn quantum computing by having fun.
 - [Quantum Information Science with Terra](community/terra/), learn about quantum information science with Qiskit Terra.
+- [Investigate Quantum Noise with Ignis](community/ignis/), learn about quantum noise  with Qiskit Ignis.
 - [Textbook Quantum Algorithms](community/algorithms/), learn Qiskit from the textbook algorithms.
 - [Quantum Algorithms](community/aqua/), learn about quantum algorithms for noisy near-term devices with Qiskit Aqua.
 - [IBM Q Awards](community/awards/), learn from the great contributions to the [IBM Q Awards](https://qe-awards.mybluemix.net/), [Teach Me Qiskit 2018](community/awards/teach_me_qiskit_2018/index.ipynb) and [Teach Me Quantum 2018](community/awards/teach_me_quantum_2018/index.ipynb).
 
-To go through the tutorials, load up the [index.ipynb](index.ipynb) notebook and start learning.
+To go through the community driven tutorials, load up the [index.ipynb](community/index.ipynb) notebook and start learning.
 
 ## Contribution Guidelines
 

community/aqua/README.md

@@ -1,17 +1,29 @@
-# Qiskit Aqua Tutorials
+# Qiskit Aqua Tutorials 
 
 Qiskit Algorithms for QUantum Applications (Qiskit Aqua) is a library of algorithms for quantum computing
 that uses [Qiskit Terra](https://qiskit.org/terra) to build out and run quantum circuits.
 
-## Contents
+This folder contains some Jupyter Notebook examples showing how to run algorithms in Qiskit Aqua.
+There are also Python code files too.
+
+For more detail see the main [index](../index.ipynb#aqua)
+
+## Input files
+
+The folder [input_files](../input_files) contains a number of example json input files that can be loaded 
+and run by the Qiskit Aqua [GUI](https://github.com/Qiskit/aqua/README.md#gui) or by the Qiskit Aqua
+[command line](https://github.com/Qiskit/aqua/README.md#command-line) tool.
+
+
+## Domains
 
 Aqua provides a library of cross-domain algorithms upon which domain-specific applications and stacks can be
 built. Tutorials, sample code and sample input files may be found here for:
 
-* [General](general)
-* [Qiskit Chemistry](chemistry)
-* [Aqua Optimization](optimization)
-* [Aqua Artificial Intelligence](artificial_intelligence)
-* [Aqua Finance](finance)
+* [Qiskit Chemistry](../chemistry)
+* [Qiskit Optimization](../optimization)
+* [Qiskit Artificial Intelligence](../artificial_intelligence)
+* [Qiskit Finance](../finance)
 
 More information may be found the [main index notebook](index.ipynb).
+