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https://hdl.handle.net/10316/112027
Título: | A Quantum-Classical Network for Beat-Making Performance | Autor: | Oshiro, Scott Hamido, Omar Costa |
Data: | 2020 | Editora: | Stony Brook University | Título da revista, periódico, livro ou evento: | Journal of Network Music and Arts | Volume: | 2 | Número: | 1 | Resumo: | In recent years, quantum computing has emerged as the next frontier in computational and infor- mation technologies. Even though it has found potential applications in solving complex problems in fields such as chemistry, machine learning, and cryptography, among other fields, there has been little research conducted on its applications for music and acoustic technologies. This paper will discuss the use of a quantum internet protocol in the context of networked music performance in which quantum computing could play a role in processing musical data via a cloud-based music software application. We also propose an example model for a beat-making performance network using a smart music playlist application deployed on a simulated quantum internet. In the pro- posed system design and architecture, several beat-makers located remotely from each other are connected live over a simulated quantum internet in a distributed networked music performance. Each beat-maker node transmits and receives audio sample time slices of beat patterns from one another to use in their local performances. This model provides a proof of concept for implement- ing quantum algorithms, standards, and protocols in music software and network applications when a quantum internet becomes available. | Descrição: | Oshiro, Scott, and Omar Costa Hamido. "A Quantum-Classical Network for Beat-Making Performance." Journal of Network Music and Arts 2, 1 (2020). https://commons.library.stonybrook.edu/jonma/vol2/ iss1/4 | URI: | https://hdl.handle.net/10316/112027 | ISSN: | 2690-2044 | Direitos: | openAccess |
Aparece nas coleções: | I&D CEIS20 - Artigos em Revistas Internacionais |
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Ficheiro | Descrição | Tamanho | Formato | |
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A Quantum-Classical Network for Beat-Making Performance.pdf | 645.58 kB | Adobe PDF | Ver/Abrir |
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