Javascript must be enabled to continue!
Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing
View through CrossRef
We introducePerceval, an open-source software platform for simulating and interfacing with discrete-variable photonic quantum computers, and describe its main features and components. Its Python front-end allows photonic circuits to be composed from basic photonic building blocks like photon sources, beam splitters, phase-shifters and detectors. A variety of computational back-ends are available and optimised for different use-cases. These use state-of-the-art simulation techniques covering both weak simulation, or sampling, and strong simulation. We give examples ofPercevalin action by reproducing a variety of photonic experiments and simulating photonic implementations of a range of quantum algorithms, from Grover's and Shor's to examples of quantum machine learning.Percevalis intended to be a useful toolkit for experimentalists wishing to easily model, design, simulate, or optimise a discrete-variable photonic experiment, for theoreticians wishing to design algorithms and applications for discrete-variable photonic quantum computing platforms, and for application designers wishing to evaluate algorithms on available state-of-the-art photonic quantum computers.
Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
Title: Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing
Description:
We introducePerceval, an open-source software platform for simulating and interfacing with discrete-variable photonic quantum computers, and describe its main features and components.
Its Python front-end allows photonic circuits to be composed from basic photonic building blocks like photon sources, beam splitters, phase-shifters and detectors.
A variety of computational back-ends are available and optimised for different use-cases.
These use state-of-the-art simulation techniques covering both weak simulation, or sampling, and strong simulation.
We give examples ofPercevalin action by reproducing a variety of photonic experiments and simulating photonic implementations of a range of quantum algorithms, from Grover's and Shor's to examples of quantum machine learning.
Percevalis intended to be a useful toolkit for experimentalists wishing to easily model, design, simulate, or optimise a discrete-variable photonic experiment, for theoreticians wishing to design algorithms and applications for discrete-variable photonic quantum computing platforms, and for application designers wishing to evaluate algorithms on available state-of-the-art photonic quantum computers.
Related Results
Advancements in Quantum Computing and Information Science
Advancements in Quantum Computing and Information Science
Abstract: The chapter "Advancements in Quantum Computing and Information Science" explores the fundamental principles, historical development, and modern applications of quantum co...
Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
Advanced frameworks for fraud detection leveraging quantum machine learning and data science in fintech ecosystems
The rapid expansion of the fintech sector has brought with it an increasing demand for robust and sophisticated fraud detection systems capable of managing large volumes of financi...
Two-dimensional function photonic crystal
Two-dimensional function photonic crystal
Photonic crystal is a kind of periodic optical nanostructure consisting of two or more materials with different dielectric constants, which has attracted great deal of attention be...
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
Integrating quantum neural networks with machine learning algorithms for optimizing healthcare diagnostics and treatment outcomes
The rapid advancements in artificial intelligence (AI) and quantum computing have catalyzed an unprecedented shift in the methodologies utilized for healthcare diagnostics and trea...
Revolutionizing multimodal healthcare diagnosis, treatment pathways, and prognostic analytics through quantum neural networks
Revolutionizing multimodal healthcare diagnosis, treatment pathways, and prognostic analytics through quantum neural networks
The advent of quantum computing has introduced significant potential to revolutionize healthcare through quantum neural networks (QNNs), offering unprecedented capabilities in proc...
Quantum information outside quantum information
Quantum information outside quantum information
Quantum theory, as counter-intuitive as a theory can get, has turned out to make predictions of the physical world that match observations so precisely that it has been described a...
Quantum Computing Techniques for Numerical Linear Algebra in Computational Mathematics
Quantum Computing Techniques for Numerical Linear Algebra in Computational Mathematics
Quantum computing is a new and exciting area of computational mathematics that has the ability to solve very hard problems that traditional computing methods have not been able to ...
Quantum metamaterials: Applications in quantum information science
Quantum metamaterials: Applications in quantum information science
Metamaterials are a class of artificially engineered materials with periodic structures possessing exceptional properties not found in conventional materials. This definition can b...

