Google Launches TensorFlow Quantum: Open Source Library for Quantum Machine LearningMar 11, 2020 | 1270 views
Google on Monday announced the launch of TensorFlow Quantum, an open source library for rapid prototyping of quantum Machine Learning (ML) models. The structure can build quantum data sets, prototype hybrid and classic quantum models of ML.
According to the company's announcement, TensorFlow Quantum (TFQ) provides the tools necessary to bring together quantum computing and ML research communities to control and model natural or artificial quantum systems, for example, NISQ (Noisy Intermediate Scale Quantum) processors with approximately 50 to 100 qubits.
The structure was developed in collaboration with the University of Waterloo, Alphabet's division for innovative projects - the X and Volkswagen.
As explained by Google, TFQ integrates Cirq with TensorFlow and offers high-level abstractions for the development and implementation of classic quantum models, both discriminative and generative, providing primitive quantum computing compatible with existing TensorFlow APIs, in addition to circuit simulators high-performance quantum.
"We believe that the bridge between the ML and Quantum communities will lead to exciting new discoveries and accelerate the discovery of new quantum algorithms to solve the world's most challenging problems," said the statement published on the AI Google blog.
The launch of TensorFlow Quantum takes place in the same week as the TensorFlow Dev Summit, an annual meeting of Machine Learning professionals who use the structure at Google offices in Silicon Valley. Due to the strain on the coronavirus, the physical event was canceled.
“Today, TensorFlow Quantum is mainly focused on the execution of quantum circuits in classic quantum circuit simulators. In the future, TFQ will be able to run quantum circuits on real quantum processors supported by Cirq, including Sycamore itself, Google's processor, ”said the technology giant.