Updating the main doc

Just updating it to be accurate to what the project actually is and noy be coy about its capabilities and goals.

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=)!
 

src/rasqal/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=)!