Adds more examples

README.md

@@ -3,16 +3,10 @@
 <img src="https://github.com/oqc-community/rasqal/blob/develop/logo.png#gh-light-mode-only" align="right" width="160px">
 <img src="https://github.com/oqc-community/rasqal/blob/develop/logo_mono.png#gh-dark-mode-only" align="right" width="160px"/>
 
-Rasqal is a quantum-classical hybrid runtime which runs QIR in a fully dynamic fashion, building up quantum circuits on the fly and executing them against a provided quantum backend.
-It uses symbolic execution and heavily deferred execution to perform code transformations, optimizations and lowering to power the circuit synthesis.
+Rasqal is a quantum-classical solver runtime that takes heavy inspiration from static analysis tools and SAT solvers to power optimization, transformation and circuit splice/weaving.
+Its internal structures and concepts are also evolving towards a more high-level abstract representation of hybrid algorithms, so automated tools can process them better and potentially use such models to help uninitiatied developers get an intuitive understanding of quantum computing.
 
-Some of the key things this approach enables:
-
-1. Unrestricted QIR and LLVM instructions fully interwoven. You can throw whatever form of IR you want at it and it'll process all classical bits locally (or lower them).
-2. Enabling hybrid algorithms to be run on machines and tools with only a gate-level API available. This includes QASM API's if you use its simulation framework.
-3. Lots of optimization potential when passed large amounts of classical context that a quantum algorithm uses to accentuate its own execution.
-
-We also have a [full feature list and quick intro to its concepts](https://github.com/oqc-community/rasqal/blob/develop/docs/features_and_concepts.md) as well as a [draft paper](https://github.com/oqc-community/rasqal/blob/develop/docs/papers/Rasqal%20Draft%20v3.pdf) that covers its internals in excruciating detail.
+The details about its various ideas and components can be found in the [papers](https://github.com/oqc-community/rasqal/tree/develop/docs/papers) folder, while a quick introduction of them and current capabilities can be found [here](https://github.com/oqc-community/rasqal/blob/develop/docs/features_and_concepts.md).
 
 If you have any features or ideas you'd like to see implemented feel free to raise a [feature request](https://github.com/oqc-community/Rasqal/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.md&title=)!
 

examples/README.md

@@ -1,12 +1,15 @@
 ## Examples
 
-All dependencies to run the examples are installed into the Rasqal venv if you are building normally.
-If you can't run the full build, use `./bulid.ps1 -t "initialize-examples"` to install a Rasqal versio from pypi as a replacement.
+**Running examples without building Rasqal:** Install [poetry](https://python-poetry.org/) and do `poetry install` in `rasqal/examples` or pip install the dependencies listed in the .toml file.
 
-All files can be run directly.
+If you've already built Rasqal via its build script its venv will have all the dependencies necessary so re-use that.
 
-**Examples.py** holds examples of how to use Rasqals Python APIs to run QIR.
+Note: all our examples are built using the old Q# compiler as Rasqal can exploit its fully interwoven classical LLVM instructions. 
 
-**Sandbox.py** runs the sandbox Q# project in `qsharp/src`.
-Modify the project as you need and then run the Python file to see how Rasqal reacts.
-Currently restricted to adaptive profile QIR.
+**Examples.py** holds runnable examples 
+
+
+runnable examples of many of Rasqals internal test projects showing how you set up and run things, including backend and argument definition. Shows the Q# that the QIR was generated from for each example, along with tertiary information. 
+Source for most examples can be found in `src/tests/qsharp` and can be modified from there and re-built. 
+
+**Sandbox.py** runs the sandbox Q# project in `qsharp/src`. This uses the new Q# compiler so instruction set is limited.