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Description

Cirq is a Python library designed for creating, modifying, and optimizing quantum circuits, which can be executed on both quantum computers and simulators. It offers valuable abstractions tailored for the current generation of noisy intermediate-scale quantum computers, where understanding the hardware specifics is crucial for achieving optimal outcomes. The library includes integrated simulators that can manage both wave function and density matrix representations, capable of simulating noisy quantum channels through Monte Carlo methods or complete density matrix techniques. Additionally, Cirq is compatible with an advanced wavefunction simulator known as qsim, allowing users to replicate quantum hardware experiences through a quantum virtual machine. By utilizing Cirq, researchers can conduct experiments on Google's quantum processors, providing a platform for innovative exploration in quantum computing. For those interested in delving deeper, resources are available to learn about recent experiments and access the code needed to replicate these experiments independently.

Description

The development of large-scale physical quantum computers is proving to be a formidable task, and in parallel with efforts to create these machines, considerable attention is being directed towards crafting effective quantum algorithms. Without a fully realized large quantum computer, it becomes essential to utilize precise software simulations on classical systems to replicate the execution of these quantum algorithms, allowing researchers to analyze quantum computer behavior and refine their designs. In addition to simulating ideal, error-free quantum circuits on a faultless quantum computer, the QX simulator offers the capability to model realistic noisy executions by incorporating various error models, such as depolarizing noise. Users have the option to activate specific error models and set a physical error probability tailored to mimic a particular target quantum computer. This defined error rate can be based on factors like gate fidelity and qubit decoherence characteristics of the intended platform, ultimately aiding in the realistic assessment of quantum computation capabilities. Thus, these simulations not only inform the design of future quantum computers but also enhance our understanding of the complexities involved in quantum processing.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Bayesforge Yes 
Python Yes 
Superstaq Yes 

Integrations

Bayesforge No 
Python No 
Superstaq No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

quantumai.google/cirq

Vendor Details

Company Name

Quantum Computing Simulation

Website

quantum-studio.net

Product Features

Product Features

Alternatives

QX Simulator Reviews

QX Simulator

Quantum Computing Simulation

Alternatives

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Google Cirq

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