Zobrazeno 1 - 10
of 12 594
pro vyhledávání: '"GRAHAM, E."'
We explore the theory of illfounded and cyclic proofs for the propositional {modal $\mu$-calculus}. A fine analysis of {provability} for classical and intuitionistic modal logic provides a novel bridge between finitary, cyclic and illfounded concepti
Externí odkaz:
http://arxiv.org/abs/2401.01096
Autor:
Hu, Fangjun, Khan, Saeed A., Bronn, Nicholas T., Angelatos, Gerasimos, Rowlands, Graham E., Ribeill, Guilhem J., Türeci, Hakan E.
Publikováno v:
Nature Communications 15, 7491 (2024)
Practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a machine learning algorithm, NISQRC, for qubit-based quantum systems that
Externí odkaz:
http://arxiv.org/abs/2312.16165
Autor:
Hu, Fangjun, Angelatos, Gerasimos, Khan, Saeed A., Vives, Marti, Türeci, Esin, Bello, Leon, Rowlands, Graham E., Ribeill, Guilhem J., Türeci, Hakan E.
Publikováno v:
Phys. Rev. X 13, 041020 (2023)
The expressive capacity of physical systems employed for learning is limited by the unavoidable presence of noise in their extracted outputs. Though present in physical systems across both the classical and quantum regimes, the precise impact of nois
Externí odkaz:
http://arxiv.org/abs/2307.16083
Publikováno v:
EvoDevo, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract Background Spiders evolved different types of eyes, a pair of primary eyes that are usually forward pointing, and three pairs of secondary eyes that are typically situated more posterior and lateral on the spider’s head. The best understan
Externí odkaz:
https://doaj.org/article/11747eda499c45cd9f4304146ee24cab
Autor:
Fangjun Hu, Saeed A. Khan, Nicholas T. Bronn, Gerasimos Angelatos, Graham E. Rowlands, Guilhem J. Ribeill, Hakan E. Türeci
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract The practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a machine learning algorithm, NISQRC, for qubit-based quantum
Externí odkaz:
https://doaj.org/article/a3038c2f947a48bb89a0a06f2048753a