Deploy established error-robust quantum control protocols.
Control electronicsQuantum Cloud
Access and deploy established error-robust quantum control protocols. Easily integrate techniques from the literature onto custom hardware, cloud platforms, or Fire Opal.
Intuitive Python programming for diverse quantum backends.
CompilersHigh-level Quantum Programming+1 more
Implement quantum programs in Python with intuitive syntax. Translate code for execution on classical simulators or actual quantum hardware. Open-source framework.
Access and program D-Wave quantum systems with Python.
High-level Quantum ProgrammingHybrid computing+1 more
Provides a comprehensive Python SDK and command-line tools for developing applications on D-Wave quantum computers and hybrid solvers. Includes API, CLI, and package documentation.
Build and train quantum neural networks with a cloud-integrated platform. Offers easy-to-use APIs, comprehensive tutorials, toolkits for chemistry/optimization, and large-scale simulation.
Optimizes Quil programs for specific hardware architectures using advanced compilation techniques. Provides both binary and server interfaces for flexible integration.
Simulate Quil programs efficiently with a high-performance, featureful virtual machine. Model quantum computer characteristics and deploy as a binary or server.
Bridge quantum physics formalisms to classical code
High-level Quantum ProgrammingQuantum Algorithms
QCL is a high-level, architecture-independent quantum programming language with syntax like C/Pascal, enabling full algorithm implementation and simulation.
Provides pure, safe, and standard Rust bindings for the high-performance Qrack quantum simulator. Leverage Qrack's OpenCL acceleration within Rust applications.
High-performance quantum simulation via Python bindings
High-level Quantum ProgrammingSimulators
Access a fast C++11/OpenCL quantum simulator from Python. Supports OpenCL acceleration, zero-copy mode, and integration with PyZX for circuit optimization.
Comprehensive, GPU accelerated framework for developing universal virtual quantum processors
Simulators
Framework for full-stack quantum computing development, via high performance and fundamentally optimized simulation. The intent of "Qrack" is to provide maximum performance for the simulation of an ideal, virtually error-free quantum computer, across the broadest possible set of hardware and operating systems.
A tool for quantum circuit compilation developed as part of the Munich Quantum Toolkit (MQT). It builds upon MQT Core, which forms the backbone of the MQT.
A tool for quantum circuit equivalence checking developed as part of the Munich Quantum Toolkit (MQT). It builds upon MQT Core, which forms the backbone of the MQT.
Quantum circuit simulator based on decision diagrams written in C++
Quantum CircuitsSimulators
A tool for classical quantum circuit simulation developed as part of the Munich Quantum Toolkit (MQT). It builds upon MQT Core, which forms the backbone of the MQT.
MQT DDVis - An installation-free web-tool which visualizes quantum decision diagrams and allows to explore their behavior when used in design tasks such as simulation, synthesis, or verification.
The Quantum Device Management Interface (QDMI) is one of the core components of the Munich Quantum Software Stack (MQSS)—a sophisticated software stack to connect end users to the wide range of possible quantum devices.
General purpose quantum computing library in modern C++
High-level Quantum ProgrammingSimulators
Simulate arbitrary quantum processes with a modern C++ template library. Designed for high performance, portability, and ease of use with minimal dependencies.
Scalable functional language for quantum circuit design.
High-level Quantum ProgrammingQuantum Circuits
Design scalable quantum circuits using a functional language. Features high-level description, automatic reversible synthesis, hierarchical circuits, and programmable transformers.
Qurry (was) a prototype for a functional quantum programming language. It incorporated many aspects of functional programming (Haskell, Clojure), but also took standard design philosophies from C++, Python, and other "traditional" languages.
The package also aims for a more general way of defining control problems with QuTiP and makes switching between the four control algorithms (GOAT, JOPT, and GRAPE and CRAB implemented in qutip-qtrl) very easy.
The qutip-qip package, QuTiP quantum information processing, aims at providing basic tools for quantum computing simulation both for simple quantum algorithm design and for experimental realization.
Simulate open quantum systems dynamics efficiently. Supports various Hamiltonians, time-dependence, and applications in quantum optics, superconducting circuits, and more.
Remove quantum complexity, turn ideas into solutions.
High-level Quantum Programming
Access diverse quantum and advanced compute resources through a single interface. Solve complex problems faster, innovate rapidly, and integrate easily into existing workflows without requiring deep expertise.
High-level Quantum ProgrammingHybrid computing+2 more
Quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. Research in quantum algorithms and applications can leverage Google’s quantum computing frameworks, all from within TensorFlow.
Abstract and optimize quantum algorithms efficiently.
Quantum Algorithms
Develop, differentiate, and optimize quantum algorithms using abstract data structures. Execute on diverse simulators and hardware backends for variational quantum computation.
QUA is an intuitive pulse-level programming language used with Quantum Machines’ OPX hybrid controllers. It is the core of QM’s comprehensive hybrid development platform – which also features automated calibrations via QUAlibrate, and access to a vast library of control applications. QUA seamlessly merges quantum and classical programming. With QUA, quantum builders can easily program complex algorithms that were previously impossible, reaching milestones faster and accelerating the path to breakthrough results.
QUAlibrate simplifies the complex task of quantum calibration, dramatically boosting productivity. Built for scale, it enables parallelized multi-qubit tune-up, with full qubit tune-up in less than a minute. QUAlibrate gives users complete code-level control to program and customize calibration nodes and graphs.
Design, simulate, and optimize fault-tolerant quantum computer architectures. Model over 20 hardware imperfections to accelerate logical qubit experiments.
