This library implements a variety of different proposals for memory for quantum computers, also commonly called qRAM. Want to learn more about what qRAM is? Check out the primer on memory for quantum computers in our docs!

There are many different proposals for qRAM in quantum computing that each have different tradeoffs, and currently come up a lot in quantum machine learning applications. We want to better understanding the costs and benefits of different qRAM implementations in quantum machine learning as well as quantum computing more generally. This library will help achieve these goals by giving us a concrete way to measure the resources each approach takes; choosing to do this in Q# allows us to leverage the built-in resource estimator to quickly iterate profiling the qRAM implementations and optimizing the circuits.

Example of a Bucket Brigade qRAM circuit:

TODO: Include logo/demo screenshot etc.

Built with:

• Quantum Development Kit
• .NET Core SDK 3.1
• Python
• Visual Studio Code and Visual Studio
• Jupyter Notebook

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TODO: Add more! Fix syntax highlighting

operation QueryAndMeasureQRAM(memory : QRAM, queryAddress : Int) : Int {
        using ((addressRegister, targetRegister) = (Qubit[memory::AddressSize], Qubit[memory::DataSize])) {
            ApplyPauliFromBitString (PauliX, true, IntAsBoolArray(queryAddress, memory::AddressSize), addressRegister);
            memory::Lookup(LittleEndian(addressRegister), targetRegister);
            ResetAll(addressRegister);
            return MeasureInteger(LittleEndian(targetRegister));
        }
    }

TODO:

• Docker
• Binder
• Codespaces
• Remote dev env
• local install

TODO: Complete once compiler extension is finalized for scraping API docs

TODO: Describe and show how to run the tests with code examples.

TODO: Link to user manual in docs

Please see our contributing guidelines and our code of conduct before working on a contribution, thanks!

• Primary developers: @glassnotes, @shikharsingh3, @crazy4pi314
• Code review and API design assistance: @RolfHuisman, @cgranade

• WIQCA talk on qRAM by @glassnotes
• Live development of this library with @crazy4pi314 on Twitch

MIT © qsharp-community