H-hat

$\hat{H}$ (H-hat) is a high abstraction quantum programming language.

Disclaimer: This is a work still in early stages and may be seeing as such. So errors, inconsistencies, tons of experimentation, modifications and trials will happen.

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Note: Documentation is in progress and can be found here.

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Contents

• Summary
• Objectives
• Features
• Installation
• Executing Code
• Progress
• Got an error?
• License
• Credits

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Summary

• A (high level) quantum algorithms builder
• Handling output quantum data with contextualized meaning
• Quantum and classical variables are arrays of data
• No qubit approach: it will be handled by the language as operations (quantum) on indexes; The interpreter/compiler will be responsible to transpile it to low level QASM instructions
• Convert high level languages commands and procedures into low level quantum instructions for quantum languages such as openQASM, cQASM, NetQASM, Q1ASM to be executed on their respective hardware/simulator
• Debugging results and quantum processes through post-measurement analysis (probably)

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Objectives

• Provide an intermediate picture between classical high-level and QASM (or QIR)-like programming languages
• Make use of basic and complex quantum instructions and procedures in a qubit-free environment
• Bring light to measurement results and their analysis
• Be simples enough to be used by software developers with little knowledge on quantum computing
• Prepare the path for quantum devices with hundreds or thousands of qubits
• Integrate with common programming languages through function calls
• Integrate with quantum hardware and compilers
• Debugging through (partial) quantum analysis of measurement results for results and inner processes comparing them to simulated ones (using fisher information, linear entropy, entanglement measurements, etc)

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Features

• simple syntax
• array-like programming approach
• quantum functions for quantum data
• quantum commands and quantum data are referred with @ before the word, i.e. @init, @sync, @q1
• measurements automatically made after executing quantum variable content through interaction with classical functions and classical data
• measurement result contextualized according to the data type it is interacting with

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Installation

• Install Python 3.10+.
• Set up a virtual environment, such as anaconda or venv.
• Install the package, via PYPI (instructions below) or in development mode.

Setting up a virtual environment

In case you don't know how to set up a virtual environment, see the examples below (choose only one):

Using conda

• Install anaconda.
• Create an environment for h-hat and activate it: conda activate <name_of_the_env>

Using venv

• Create a venv: python3.10 -m venv .venv (the venv will be located in the folder .venv inside the hhat_lang root folder)
• Deactivate any other environment you might have active, i.e. conda: conda deactivate, until you have no environment
• Activate our new venv through: source .venv/bin/activate

PYPI installation

After setting up your virtual environment, simply use:

python3 -m pip install hhat-lang

Development mode

In the root folder, run:

python3 -m pip install -e .

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Executing Code

After proceeding on your preferred installation method, it's time to run some code. Just type hhat in the terminal followed by the file containing your code (.hat extension).

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Progress

You can follow the progress in the TODOs list.

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Got an error?

Open an issue!

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License

MIT

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Credits

Code is being developed by Doomsk. The author thanks Kaonan, T1t0, Anneriet, Penguim and Lucasczpnk for great discussions and help on developing the first language concepts.