Metadata-Version: 2.1
Name: tweedledum-dev
Version: 1.1.0.dev202103302100
Summary: A library for synthesizing and manipulating quantum circuits
Home-page: https://github.com/boschmitt/tweedledum
Author: Bruno Schmitt
Author-email: bruno.schmitt@epfl.ch
License: MIT
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            /!\ (Warning) If you have used tweedledum before: the master branch history is broken.
            /!\ The new master branch is a completely rewrite of the library. The old version can be found
            /!\ on **alpha** branch. (Sorry for the inconvenience!!---but it is for a great cause)
        
        **tweedledum** is a library for synthesis, compilation, and optimization of
        quantum circuits.  The library is written to be scalable up to problem sizes in
        which quantum circuits outperform classical ones. Also, it is meant to be used
        both independently and alongside established tools.
        
        
        Its design is guided by three mantras:
        
        - __Gotta run fast__: execution-time performance is a priority.
        
        - __Your compiler, your rules__.  You know better. At least, Tweedledum 
        hopes so! The library provides a standard set of operators that can be easily 
        extended (thanks to some type-erasure black magic).  However, the library will 
        leave your operators completely alone if you don't write passes that 
        specifically manipulate them.  Furthermore, Tweedledum will rarely take any
        decision in your behalf, i.e., it does not provide generic methods to optimize
        or synthesize circuits, you need to specifically call the algorithms you want.
        
        - __Opinionated, but not stubborn__.  Many passes and synthesis algorithms have
        many configuration parameters.  Tweedledum comes with reasonable defaults and 
        curated opinions of what value such parameters should take.  But in the end,
        it all up to you.
        
        __Corollary__:  Because of it's flexibility, Tweedledum is capable of accepting
        gates/operators that are defined as python classes.  Indeed, any pythonic 
        framework can use the library as a circuit manager.  Meaning that the library 
        can be used to slowly transition the core and performance sensitive parts of a 
        pythonic framework to C++, while maintaining the capability of users to develop
        passes in python.
        
        # Installation
        
        Tweedledum has two python packages that can be installed using `pip`.  For both,
        you will at least __Python 3.6__.  The `tweedledum` package contains the latest
        stable release.  You can install it from PyPi using:
        
        * Latest stable release (Linux/Mac/Windows)
        
        ```
        pip install tweedledum
        ```
        
        For the developers, users or researchers who are comfortable living on the 
        absolute bleeding edge, `tweedledum-dev` contains that latest developments 
        merged into the master branch.
        
        * Latest (Linux/Mac/Windows)
        
        ```
        pip install tweedledum-dev
        ```
        
        __Warning__: The two packages cannot be installed together.
        
        # Used third-party tools
        
        The library it is built, tested, bind to python, and whatnot using many
        third-party tools and services. Thanks a lot!
        
        - [**abc**](https://github.com/berkeley-abc/abc) - ABC: System for Sequential Logic Synthesis and Formal Verification
        - [**bill**](https://github.com/lsils/bill) - C++ header-only reasoning library
        - [**Catch2**](https://github.com/catchorg/Catch2) test framework for unit-tests, TDD and BDD
        - [**CMake**](https://cmake.org) for build automation
        - [**Eigen**](https://gitlab.com/libeigen/eigen) template library for linear algebra
        - [**{fmt}**](https://github.com/fmtlib/fmt) - A modern formatting library
        - [**kitty**](https://github.com/msoeken/kitty) - truth table library 
        - [**lorina**](https://github.com/hriener/lorina) - C++ parsing library for simple formats used in logic synthesis and formal verification 
        - [**mockturtle**](https://github.com/lsils/mockturtle) - C++ logic network library
        - [**nlohmann/json**](https://github.com/nlohmann/json) - JSON for Modern C++
        - [**parallel_hashmap**](https://github.com/greg7mdp/parallel-hashmap) - A family of header-only, very fast and memory-friendly hashmap and btree containers.
        - [**percy**](https://github.com/lsils/percy) - C++ header-only exact synthesis library
        - [**pybind11**](https://github.com/pybind/pybind11) - Seamless operability between C++11 and Python
        - [**rang**](https://github.com/agauniyal/rang) - A Minimal, Header only Modern c++ library for terminal goodies
        
        ## License
        
        This software is licensed under the MIT licence (see 
        [LICENSE](https://github.com/boschmitt/tweedledum/blob/master/LICENSE)).
        
        ## EPFL logic synthesis libraries
        
        tweedledum is part of the
        [EPFL logic synthesis](https://lsi.epfl.ch/page-138455-en.html) libraries.
        The other libraries and several examples on how to use and integrate the 
        libraries can be found in the 
        [logic synthesis tool showcase](https://github.com/lsils/lstools-showcase).
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
