In this paper, classical and continuous variable (CV) quantum neural network hybrid multi-classifiers are presented using the MNIST dataset. Currently available classifiers can classify only up to two classes. The pro...In this paper, classical and continuous variable (CV) quantum neural network hybrid multi-classifiers are presented using the MNIST dataset. Currently available classifiers can classify only up to two classes. The proposed architecture allows networks to classify classes up to n<sup>m</sup> classes, where n represents cutoff dimension and m the number of qumodes on photonic quantum computers. The combination of cutoff dimension and probability measurement method in the CV model allows a quantum circuit to produce output vectors of size n<sup>m</sup>. They are then interpreted as one-hot encoded labels, padded with n<sup>m</sup> - 10 zeros. The total of seven different classifiers is built using 2, 3, …, 6, and 8-qumodes on photonic quantum computing simulators, based on the binary classifier architecture proposed in “Continuous variable quantum neural networks” [1]. They are composed of a classical feed-forward neural network, a quantum data encoding circuit, and a CV quantum neural network circuit. On a truncated MNIST dataset of 600 samples, a 4-qumode hybrid classifier achieves 100% training accuracy.展开更多
Let there be light-to change the world we want to be!Over the past several decades,and ever since the birth of the first laser,mankind has witnessed the development of the science of light,as light-based technologies ...Let there be light-to change the world we want to be!Over the past several decades,and ever since the birth of the first laser,mankind has witnessed the development of the science of light,as light-based technologies have revolutionarily changed our lives.Needless to say,photonics has now penetrated into many aspects of science and technology,turning into an important and dynamically changing field of increasing interdisciplinary interest.In this inaugural issue of eLight,we highlight a few emerging trends in photonics that we think are likely to have major impact at least in the upcoming decade,spanning from integrated quantum photonics and quantum computing,through topological/non-Hermitian photonics and topological insulator lasers,to AI-empowered nanophotonics and photonic machine learning.This Perspective is by no means an attempt to summarize all the latest advances in photonics,yet we wish our subjective vision could fuel inspiration and foster excitement in scientific research especially for young researchers who love the science of light.展开更多
In recent years,quantum computing has made significant strides,particularly in light-based technology.The introduction of quantum photonic chips has ushered in an era marked by scalability,stability,and cost-effective...In recent years,quantum computing has made significant strides,particularly in light-based technology.The introduction of quantum photonic chips has ushered in an era marked by scalability,stability,and cost-effectiveness,paving the way for innovative possibilities within compact footprints.This article provides a comprehensive exploration of photonic quantum computing,covering key aspects such as encoding information in photons,the merits of photonic qubits,and essential photonic device components including light squeezers,quantum light sources,interferometers,photodetectors,and wave-guides.The article also examines photonic quantum communication and internet,and its implications for secure systems,detailing implementations such as quantum key distribution and long-distance communication.Emerging trends in quantum communication and essential reconfigurable elements for advancing photonic quantum internet are discussed.The review further navigates the path towards establishing scalable and fault-tolerant photonic quantum computers,highlighting quantum computational advantages achieved using photons.Additionally,the discussion extends to programmable photonic circuits,integrated photonics and transformative applications.Lastly,the review addresses prospects,implications,and challenges in photonic quantum computing,offering valuable insights into current advancements and promising future directions in this technology.展开更多
文摘In this paper, classical and continuous variable (CV) quantum neural network hybrid multi-classifiers are presented using the MNIST dataset. Currently available classifiers can classify only up to two classes. The proposed architecture allows networks to classify classes up to n<sup>m</sup> classes, where n represents cutoff dimension and m the number of qumodes on photonic quantum computers. The combination of cutoff dimension and probability measurement method in the CV model allows a quantum circuit to produce output vectors of size n<sup>m</sup>. They are then interpreted as one-hot encoded labels, padded with n<sup>m</sup> - 10 zeros. The total of seven different classifiers is built using 2, 3, …, 6, and 8-qumodes on photonic quantum computing simulators, based on the binary classifier architecture proposed in “Continuous variable quantum neural networks” [1]. They are composed of a classical feed-forward neural network, a quantum data encoding circuit, and a CV quantum neural network circuit. On a truncated MNIST dataset of 600 samples, a 4-qumode hybrid classifier achieves 100% training accuracy.
基金support from the National Key R&D Program of China under Grant(No.2017YFA0303800).MS acknowledges support from the Israel Science Foundation.
文摘Let there be light-to change the world we want to be!Over the past several decades,and ever since the birth of the first laser,mankind has witnessed the development of the science of light,as light-based technologies have revolutionarily changed our lives.Needless to say,photonics has now penetrated into many aspects of science and technology,turning into an important and dynamically changing field of increasing interdisciplinary interest.In this inaugural issue of eLight,we highlight a few emerging trends in photonics that we think are likely to have major impact at least in the upcoming decade,spanning from integrated quantum photonics and quantum computing,through topological/non-Hermitian photonics and topological insulator lasers,to AI-empowered nanophotonics and photonic machine learning.This Perspective is by no means an attempt to summarize all the latest advances in photonics,yet we wish our subjective vision could fuel inspiration and foster excitement in scientific research especially for young researchers who love the science of light.
文摘In recent years,quantum computing has made significant strides,particularly in light-based technology.The introduction of quantum photonic chips has ushered in an era marked by scalability,stability,and cost-effectiveness,paving the way for innovative possibilities within compact footprints.This article provides a comprehensive exploration of photonic quantum computing,covering key aspects such as encoding information in photons,the merits of photonic qubits,and essential photonic device components including light squeezers,quantum light sources,interferometers,photodetectors,and wave-guides.The article also examines photonic quantum communication and internet,and its implications for secure systems,detailing implementations such as quantum key distribution and long-distance communication.Emerging trends in quantum communication and essential reconfigurable elements for advancing photonic quantum internet are discussed.The review further navigates the path towards establishing scalable and fault-tolerant photonic quantum computers,highlighting quantum computational advantages achieved using photons.Additionally,the discussion extends to programmable photonic circuits,integrated photonics and transformative applications.Lastly,the review addresses prospects,implications,and challenges in photonic quantum computing,offering valuable insights into current advancements and promising future directions in this technology.
