Quantum Information

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and free sign-in (IBMid) required.

The IBM Quantum Platform offers some of the best resources for beginner and more advanced quantum computing I've ever seen. Accessable upon creation of an IBMid, this web-based resource allows users to send quantum programs straight to IBM's quantum processors. They also offer a variety of learning resources, including the Quantum Composer, a beautiful, clean interactive where individuals can toy around with quantum circuitry and immediately generate the corresponding code in Qiskit or OpenQASM 2.0. The platform offers courses in the fundementals of quantum computing (IBM Quantum Learning). If you're an individual interested in experimenting with quantum computing/programming, the IBM Quantum Platform is a must-have. The only drawback is the user is only allotted 10 minutes of runtime on IBM's GPU's per month, which depending on the complexity of your quantum algorithums, may be a lot or too little.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Packages for best implementation of each quantum algorithm listed, most Python-based. Usage Requirements: Internet connection, Python IDE or other quantum computation tools needed for execution of algorithms

It's in the name! Created by Stephen P. Jordan at Google Quantum AI, this site hosts a remarkable catalog of quantum algorithm descriptions and packages for quality implementation. Use it to compare algorithm design and runtime, and explore further using the associated Quantum Map, a visual network of relationships between algorithms.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): C. Usage Requirements: Internet connection, C compiler, GitHub for liboqs

Designed to promote the free use of quantum computer-resistant cryptography algorithms and prepare open cryptography techniques for the post-quantum computing age. Open Quantum Safe hosts liboqs, a library of C-based quantum cryptography algorithms on their GitHub.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Written in Q# and C# (also accessible via Python/Jupyter Notebooks). Usage Requirements: Requires internet connection when using website.

An open-source collection of self-paced interactive tutorials and programming exercises. Katas is designed to teach quantum computing concepts and the Q# programming language hands-on. Each "kata" covers specific topics, like qubits, quantum states, measurements, and quantum algorithms. The collection has automated unit tests that instantly validate the learner's code. It is an excellent tool for beginners wanting to learn quantum programming and Microsoft's Q# language. The link provided goes directly to the Katas learning site, not the GitHub.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Python. Usage Requirements: Python-compatible IDE

Qiskit is the most popular go-to package for quantum computing and simulating/executing quantum algorithms. Providing a suite of add-ons and tools, Qiskit allows for the construction, simulation, and execution of quantum circuitry on IBM quantum or classical computers. Plenty of documentation and example code is available online and functions for specific problem-solving application and optimization.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Python. Usage Requirements: Python-compatible IDE, optional hardware or alternate back-end simulations

Integrate machine learning, simulation, quantum circuitry, and hardware using PennyLane's multifaceted array of capabilities designed to interface between quantum techniques. It is built to support research in QC, ML, and quantum chemistry. The platform provides ample documentation for all its functionalities, including tutorials for getting started with quantum computing and ML.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Primary development in Q#, host scripts can be written in Python, C#, or F#. Also has support for Qiskit and OpenQASM. Usage Requirements: Integrates as an extension for VS Code or Jupyter Notebooks. Runs locally on standard desktop hardware, and connects online via Azure Quantum to execute jobs.

An open-source, domain-specific framework designed by Microsoft for building and executing quantum algorithms. The power from this framework stems from its high-level qubit resource management, and its local simulation and visualization abilities. Microsoft has been recently focusing on QDK for scientific applications, like (quantum) chemistry, so you can see the real-world usage of QDK first-hand. The link provided goes to Microsoft's QDK documentation, not the GitHub.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Requires Python and Python packages (Numpy, Scipy, Cython, and Matplotlib). Works on any desktop/laptop OS.

QuTiP is an open-source software which simulates the dynamics of open quantum systems. It allows for numerical simulations of many Hamiltonians, even those with arbitrary time-dependence. These Hamiltonians have a large range of practical physics applications including quantum optics, trapped ions, quantum nanomechanical resonators, and superconducting surfaces. It being completely free makes it idea for exploring quantum mechanics/dynamics and having no licensing fees makes it a good pick for classrooms too.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Built using Python, requires Python 3.

Cirq is yet another open-source framework for programming qunatum computers. Cirq is a Python library which allows for the writing, manipulation, optimization, and execution of quantum circuits and code on quantum computers and quantum simulators. One advantage of Cirq is its abstractions for dealing with modern noisy intermediate-scale quantum (NISQ) computers.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): C/C++. Usage Requirements: Requires a C/C++ compiler like Clang, GCC, etc., depending on the user's usage. Depending on what the user wants, you may need an MPI compiler and/or a GPU compiler.

QuEST stands for the Quantum Exact Simulation Toolkit. It is a high-performance simulator of quantum circuits, state-vectors, and density matrices too. QuEST also uses multithreading, GPU acceleration, and distribution to run ridiculously fast on laptops, desktops, and supercomputers. The developers pride themselves that "QuEST just works", meaning it is stand-alon, requires no installation, and is incredibly easy to compile and get running.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Requires Python with Python dependencies. Usage Requirements: Runs on local consumer hardware or cluster nodes. Built on open-source quantum computational libraries and works offline.

An open-source Python framework designed to streamline the study of Hamiltonians for fault-tolerant quantum computing. The framework involves Hamiltonian generators from molecule descriptions, analysis of quantum algorithms involving Hamiltonians, and even Julia scripts for Trotter error calculation of time evolution/ground state energy. Also important is the attached academic paper.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Python, Jupyter. Usage Requirements: Python, Jupyter-compatible IDE

Set of 52 open data sets for the use of training and evaluating quantum computing and QC machine learning models, complete with example notebooks. More information in the associated manuscript.

Contributor: Amelia Binau, Indiana University - Bloomington