Tools

49

Frameworks, libraries, and developer tools for building quantum software.

Moving from quantum research and development to production-grade, fault-tolerant quantum workload execution remains one of the most significant challenges facing quantum platform builders. While Python frameworks have enabled an easy entry point for quantum algorithm design, the low-latency requirements for real-time quantum error correction (QEC) demand performance that traditional interpreted environments cannot provide. FPGAs and ASICs play a central role at these layers, but their specialized programming models make development rigid and time-consuming. CPUs, GPUs, and other accelerators introduce a different challenge: as infrastructure becomes increasingly heterogeneous, programming across different devices and their associated abstractions becomes more complex. Allowing researchers to write workloads in high-level languages that map to low-latency execution across diverse distributed target platforms will enable the development of key infrastructure for utility-scale quantum systems. For this, we introduce Backline, a heterogeneous compilation and runtime framework built within PennyLane and Catalyst. Backline allows us to design and build quantum-classical workloads for high-performance and low-latency devices, with compilation directly from a Python interface through MLIR. We demonstrate the compilation and execution of several quantum workloads with low-latency data movement across a mix of CPUs, GPUs, and FPGAs, for both local and distributed remote hardware targets, all from a vendor-agnostic Python frontend. With an AMD VPK120 FPGA board as the controller, issuing each round from its hardware-handshake engine, we measured median steady-state round-trip latencies over RoCE v2 of 2.305 μs to an AMD Ryzen Threadripper PRO CPU and 4.5 μs to an AMD Instinct MI210 GPU across 106−1 rounds per path, demonstrating microsecond-scale synchronous co-processing.

Updated 2 weeks ago

MQT Qudits

A tool for mixed-dimensional qudit quantum computing. It supports circuit design, simulation, and analysis for mixed-dimensional quantum circuits.

Quantum Simulation

Updated 2 months ago

MQT IonShuttler

MQT IonShuttler

A tool for generating shuttling schedules for trapped-ion quantum computers with a grid-type Memory Zone based on the Quantum Charge Coupled Device (QCCD) architecture. Python package, part of the Munich Quantum Toolkit.

Updated 2 months ago

MQT YAQS

Tool for the scalable simulation and characterization of open quantum dynamics, noisy quantum circuits, and hardware-realistic device models. Python package, part of the Munich Quantum Toolkit.

Quantum Simulation

Updated 2 months ago

MQT Bench

A quantum circuit benchmark suite with cross-level support, i.e., providing the same benchmark algorithms for different abstraction levels throughout the quantum computing software stack. MQT Bench is hosted at https://mqt-bench.app/. Python package, part of the Munich Quantum Toolkit (MQT).

Updated 2 months ago

MQT DDSim

A tool for classical quantum circuit simulation. It supports different algorithmic simulation methodologies, noise-aware approaches and more. Implemented in C++20 with Python bindings, part of the Munich Quantum Toolkit.

Quantum Simulation

Updated 2 months ago

Microsoft's Quantum Development Kit centered on the Q# quantum programming language. Ships a compiler, standard library, simulators, resource estimator, VS Code and JupyterLab extensions, language service, and Python and npm packages, and integrates with Azure Quantum for execution on hardware backends. Used for expressing, simulating, and resource-estimating quantum algorithms at scale.

Updated 3 months ago

High-level quantum programming language with a strong static type system, developed by the silq-lang group at ETH Zurich. Designed to let researchers express and simulate quantum algorithms safely and intuitively; the compiler and runtime are implemented in the D programming language. Targets quantum computing research and teaching.

Updated 3 months ago

Open-source SDK from IBM and the Qiskit community for working with quantum computers at the level of extended quantum circuits, operators, and primitives such as Sampler and Estimator. Includes a transpiler for optimizing circuits and a quantum information toolbox for advanced operator manipulation, with execution on both classical simulators and real quantum hardware from multiple vendors.

Updated 3 months ago

Open-source quantum software platform from Xanadu spanning quantum computing, quantum machine learning, and quantum chemistry. Integrates with a wide range of quantum hardware backends, pairs them with high-performance simulators and compilation tools, and exposes a differentiable interface to PyTorch, TensorFlow, JAX, and NumPy. Released under Apache 2.0 and maintained by a broad research and developer community.

Updated 3 months ago

Includes

Topics

Compilation

Benchmarking

Quantum Simulation

Chemistry

State Preparation

Sampling

QML

Cryptography

Linear Algebra

Optimization

QEC

QEM