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What is Google Cirq?

Cirq is a Python library specifically crafted for the creation, modification, and optimization of quantum circuits that can be run on both quantum computers and simulators. It provides essential abstractions that cater to the present generation of noisy intermediate-scale quantum computers, emphasizing the importance of understanding hardware specifics to achieve the best performance. This library features built-in simulators that can handle both wave function and density matrix representations, and it is adept at simulating noisy quantum channels using techniques like Monte Carlo methods or complete density matrix approaches. Furthermore, Cirq seamlessly integrates with an advanced wavefunction simulator named qsim, enabling users to experience quantum hardware through a virtual quantum machine. By leveraging Cirq, researchers can perform experiments on Google's quantum processors, thus offering a robust platform for groundbreaking investigations in the realm of quantum computing. For those keen on further exploration, a wealth of resources is readily available to study recent experiments and acquire the necessary code to independently replicate these findings, enhancing the overall understanding of quantum technology. This accessibility promotes a collaborative environment where enthusiasts and professionals alike can contribute to the rapidly evolving field of quantum research.

What is Bayesforge?

Bayesforgeâ„¢ is a meticulously crafted Linux machine image aimed at equipping data scientists with high-quality open source software and offering essential tools for those engaged in quantum computing and computational mathematics who seek to leverage leading quantum computing frameworks. It seamlessly integrates popular machine learning libraries such as PyTorch and TensorFlow with the open source resources provided by D-Wave, Rigetti, IBM Quantum Experience, and Google's pioneering quantum programming language Cirq, along with a variety of advanced quantum computing tools. Notably, it includes the quantum fog modeling framework and the Qubiter quantum compiler, which can efficiently cross-compile to various major architectures. Users benefit from a straightforward interface to access all software via the Jupyter WebUI, which features a modular design that supports coding in languages like Python, R, and Octave, thus creating a flexible environment suitable for a wide array of scientific and computational projects. This extensive setup not only boosts efficiency but also encourages collaboration among professionals from various fields, ultimately leading to innovative solutions and advancements in research. As a result, users can expect an integrated experience that significantly enhances their analytical capabilities.

Media

Media

Integrations Supported

Python
AWS Marketplace
Bayesforge
D-Wave
Google Cirq
IBM Quantum
Octave
PyTorch
R
Rigetti Quantum Cloud Services (QCS)
Superstaq
TensorFlow

Integrations Supported

Python
AWS Marketplace
Bayesforge
D-Wave
Google Cirq
IBM Quantum
Octave
PyTorch
R
Rigetti Quantum Cloud Services (QCS)
Superstaq
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

quantumai.google/cirq

Company Facts

Organization Name

Quantum Programming Studio

Company Website

artiste-qb.net/bayesforge/

Categories and Features

Categories and Features

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