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Developers searching for an open source framework for programming quantum computers
About Google Cirq
Cirq is a Python software library for writing, manipulating, and optimizing quantum circuits, and then running them on quantum computers and quantum simulators. Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum computers, where details of the hardware are vital to achieving state-of-the-art results. Cirq comes with built-in simulators, both for wave functions and for density matrices. These can handle noisy quantum channels using monte carlo or full density matrix simulations. In addition, Cirq works with a state-of-the-art wavefunction simulator: qsim. These simulators can be used to mock quantum hardware with the quantum virtual machine. Cirq is used to run experiments on Google's quantum processors. Learn more about the latest experiments and access the code to se how to run them yourself.
Other Popular Alternatives & Related Software
Superstaq
Superstaq’s low-level, device-specific optimizations enable users to draw the best performance out of today's hardware across multiple qubit modalities. Qiskit and Cirq open source frontends allow users to submit to leading quantum hardware platforms from IBM, Infleqtion, OQC, Rigetti, and more. Leverage our pre-built library of quantum applications to benchmark the performance on otherwise "impossible" problems with quantum hardware. Superstaq's library of sophisticated compilation and noise mitigation techniques, such as dynamical decoupling, automatically optimizes quantum programs based on the target hardware's native gate set. Whether it's Cirq or Qiskit, Superstaq enables you to write quantum programs that target virtually any quantum computer.
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Bayesforge
Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave.
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Azure Quantum
Use state-of-the-art cloud tools and learning resources to help you build and refine quantum algorithms. Gain access to a diverse portfolio of today’s quantum hardware. Access a diverse portfolio of today’s quantum hardware to build toward the emergence of fault-tolerant quantum systems. Navigate complexity and develop new skills with world-class onboarding and education resources including Microsoft Learn, Quantum katas tutorials, industry case studies, and a university curriculum. Use the Azure Quantum resource estimator tool to estimate the number of logical and physical qubits and runtime required to execute quantum applications on future-scaled quantum computers. Determine the number of qubits needed for a quantum solution and evaluate the differences across qubit technologies. Prepare and refine quantum solutions to run on future-scaled quantum machines.
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QC Ware Forge
Unique and efficient turn-key algorithms for data scientists. Powerful circuit building blocks for quantum engineers. Turn-key algorithm implementations for data scientists, financial analysts, and engineers. Explore problems in binary optimization, machine learning, linear algebra, and monte carlo sampling on simulators and real quantum hardware. No prior experience with quantum computing is required. Use NISQ data loader circuits to load classical data into quantum states to use with your algorithms. Use circuit building blocks for linear algebra with distance estimation and matrix multiplication circuits. Use our circuit building blocks to create your own algorithms. Get a significant performance boost for D-Wave hardware and use the latest improvements for gate-based approaches. Try out quantum data loaders and algorithms with guaranteed speed-ups on clustering, classification, and regression.
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Company Information
Google
Founded: 1998
United States
quantumai.google/cirq
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