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Broad Bandwidth and High Dimensional Quantum Memory Based on Atomic Ensembles [[electronic resource] /] / by Dong-Sheng Ding
| Broad Bandwidth and High Dimensional Quantum Memory Based on Atomic Ensembles [[electronic resource] /] / by Dong-Sheng Ding |
| Autore | Ding Dong-Sheng |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXII, 122 p. 49 illus., 42 illus. in color.) |
| Disciplina | 530.1201514 |
| Collana | Springer Theses, Recognizing Outstanding Ph.D. Research |
| Soggetto topico |
Quantum optics
Quantum computers Spintronics Information storage and retrieval Microwaves Optical engineering Quantum Optics Quantum Information Technology, Spintronics Information Storage and Retrieval Microwaves, RF and Optical Engineering |
| ISBN | 981-10-7476-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Quantum memory of orbital angular momentum and its’ superposition -- Quantum memory single photon’s high-dimensional state -- Two-dimensional orbital angular momentum entanglement storage -- Raman quantum memory of high-dimensional entanglement -- Raman quantum memory polarized entanglement -- Conclusion and Outlook. |
| Record Nr. | UNINA-9910300543603321 |
Ding Dong-Sheng
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| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The Development of Elementary Quantum Theory [[electronic resource] /] / by Herbert Capellmann
| The Development of Elementary Quantum Theory [[electronic resource] /] / by Herbert Capellmann |
| Autore | Capellmann Herbert |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VII, 98 p.) |
| Disciplina | 530.1201514 |
| Collana | SpringerBriefs in History of Science and Technology |
| Soggetto topico |
Physics
Quantum physics History History and Philosophical Foundations of Physics Quantum Physics History of Science |
| ISBN | 3-319-61884-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction and Outline -- The Fundamental Differences Between Classical and Quantum Physics -- Planck’s Quantum Hypothesis and Einstein’s Contributions to the Foundations of Quantum Theory -- The ”Old Quantum Theory -- The Quantum Theory of Born, Heisenberg, and Jordan -- Continuous Representations of the New Quantum Laws -- The Consequences of the Basic Quantum Laws on Wave Phenomena and Quantum Uncertainties -- Early Opposition to the Copenhagen Interpretation -- Orthodox Portrayals of the Development of Quantum Mechanics, Comparison and Differences -- Later Criticism of the Copenhagen Interpretation. |
| Record Nr. | UNINA-9910254590603321 |
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Capellmann Herbert
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Supervised Learning with Quantum Computers [[electronic resource] /] / by Maria Schuld, Francesco Petruccione
| Supervised Learning with Quantum Computers [[electronic resource] /] / by Maria Schuld, Francesco Petruccione |
| Autore | Schuld Maria |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (293 pages) |
| Disciplina | 530.1201514 |
| Collana | Quantum Science and Technology |
| Soggetto topico |
Quantum physics
Quantum computers Pattern recognition Spintronics Physics Artificial intelligence |
| ISBN | 3-319-96424-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Background -- How quantum computers can classify data -- Organisation of the book -- Machine Learning -- Prediction -- Models -- Training -- Methods in machine learning -- Quantum Information -- Introduction to quantum theory -- Introduction to quantum computing -- An example: The Deutsch-Josza algorithm -- Strategies of information encoding -- Important quantum routines -- Quantum advantages -- Computational complexity of learning -- Sample complexity -- Model complexity -- Information encoding -- Basis encoding -- Amplitude encoding -- Qsample encoding -- Hamiltonian encoding -- Quantum computing for inference -- Linear models -- Kernel methods -- Probabilistic models -- Quantum computing for training -- Quantum blas -- Search and amplitude amplification -- Hybrid training for variational algorithms -- Quantum adiabatic machine learning -- Learning with quantum models -- Quantum extensions of Ising-type models -- Variational classifiers and neural networks -- Other approaches to build quantum models -- Prospects for near-term quantum machine learning -- Small versus big data -- Hybrid versus fully coherent approaches -- Qualitative versus quantitative advantages -- What machine learning can do for quantum computing -- References. |
| Record Nr. | UNINA-9910300533803321 |
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Schuld Maria
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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