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Ein Ziel der Grundlagenforschung der Festkörperphysik ist das Design quantenmechanischer Zwei-Zustands-Systeme, den sogenannten Qubits, zur Speicherung der Information in künftigen Quantencomputern.In dieser Arbeit konnten durch Kooperation zweier Forschungsbereiche (Tunnelsysteme in amorphen Festkörpern und supraleitende Josephson Qubits) sowohl neue Erkenntnisse über Tunnelsysteme gewonnen werden, als auch ein Werkzeug für die weitere Forschung auf dem Bereich der Qubits demonstriert werden.
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Depuis de nombreuses années, les circuits électriques à jonction Josephson sont au cœur des recherches dans le développement d’ordinateurs quantiques. La non-linéarité induite par la jonction Josephson confère à ces circuits le qualificatif d’atomes artificiels simulant les propriétés quantiques d’un atome tel que la discrétisation du spectre rendant apte à travailler avec seulement l’une ou l’autre transition. Dès lors en limitant le spectre à deux niveaux, les atomes artificiels forment des qubits (bits quantiques). La taille de ces circuits permet également une nouvelle approche dans l’étude fondamentale de l’interaction lumière-matière, car ces qubits peuvent être couplés en plusieurs endroits induisant dès lors des phénomènes d’interférence qui peuvent préserver la cohérence d’un ensemble de qubits. Cela a mené à la naissance du domaine des atomes géants.
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Magnetic nanostructures --- Crystal engineering of magnetic materials --- Magnetic recording --- Magnetocaloric materials --- Qubits --- qubits --- magnetic nanostructures --- magnetic recording --- magnetocaloric materials --- crystal engineering of magnetic materials --- Magnetochemistry --- Molecules --- Magnetochemistry. --- Magnetic properties --- Magnetic properties. --- Electrochemistry --- Magnetism --- Chemistry
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This book is a collection of scientific articles which brings research in Si nanodevices, device processing, and materials. The content is oriented to optoelectronics with a core in electronics and photonics. The issue of current technology developments in the nanodevices towards 3D integration and an emerging of the electronics and photonics as an ultimate goal in nanotechnology in the future is presented. The book contains a few review articles to update the knowledge in Si-based devices and followed by processing of advanced nano-scale transistors. Furthermore, material growth and manufacturing of several types of devices are presented. The subjects are carefully chosen to critically cover the scientific issues for scientists and doctoral students.
Technology: general issues --- silicon --- yolk−shell structure --- anode --- lithium-ion batteries --- in-plane nanowire --- site-controlled --- epitaxial growth --- germanium --- nanowire-based quantum devices --- HfO2/Si0.7Ge0.3 gate stack --- ozone oxidation --- Si-cap --- interface state density --- passivation --- GOI --- photodetectors --- dark current --- responsivity --- prussian blue nanoparticles --- organotrialkoxysilane --- silica beads --- arsenite --- arsenate --- water decontamination --- vertical gate-all-around (vGAA) --- digital etch --- quasi-atomic-layer etching (q-ALE) --- selective wet etching --- HNO3 concentration --- doping effect --- vertical Gate-all-around (vGAA) --- p+-Ge0.8Si0.2/Ge stack --- dual-selective wet etching --- atomic layer etching (ALE) --- stacked SiGe/Si --- epitaxial grown --- Fin etching --- FinFET --- short-term potentiation (STP) --- long-term potentiation (LTP) --- charge-trap synaptic transistor --- band-to-band tunneling --- pattern recognition --- neural network --- neuromorphic system --- Si-MOS --- quantum dot --- spin qubits --- quantum computing --- GeSn --- CVD --- lasers --- detectors --- transistors --- III-V on Si --- heteroepitaxy --- threading dislocation densities (TDDs) --- anti-phase boundaries (APBs) --- selective epitaxial growth (SEG) --- n/a
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Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields.
History of engineering & technology --- light emitting diode --- nonlinearity estimation and compensation --- probabilistic Bayesian learning --- visible light communication --- digital signal processing --- support vector machines --- BCSVM --- nonlinear equalization --- coherent detection --- k-nearest neighbor algorithm --- modulation format identification --- OSNR monitoring --- neural networks --- optical communications --- optimization --- equalizer --- tap estimation --- optical Fast-OFDM --- nonlinearity compensation --- optical fiber communications --- chromatic dispersion --- short-reach communication --- neural network --- hybrid signal processing --- fiber optics communications --- coherent communications --- machine learning --- clustering --- nonlinearity cancellation --- entanglement --- charge qubit --- position-based semiconductor qubits --- cryogenic technologies --- semiconductor photon communication --- Jaynes–Cummings–Hubbard formalism --- deep neural networks --- volterra equalization --- nonlinear systems --- coherent optical communication --- passive optical networks --- nonlinear compensation --- optical transmission --- optical networks --- artificial intelligence --- quality of transmission --- optical performance monitoring --- failure management --- artificial neural networks --- deep neural network --- image classification --- photonic integrated circuits --- semiconductor optical amplifiers --- photonic neural network --- n/a --- Jaynes-Cummings-Hubbard formalism
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This book is a collection of scientific articles which brings research in Si nanodevices, device processing, and materials. The content is oriented to optoelectronics with a core in electronics and photonics. The issue of current technology developments in the nanodevices towards 3D integration and an emerging of the electronics and photonics as an ultimate goal in nanotechnology in the future is presented. The book contains a few review articles to update the knowledge in Si-based devices and followed by processing of advanced nano-scale transistors. Furthermore, material growth and manufacturing of several types of devices are presented. The subjects are carefully chosen to critically cover the scientific issues for scientists and doctoral students.
silicon --- yolk−shell structure --- anode --- lithium-ion batteries --- in-plane nanowire --- site-controlled --- epitaxial growth --- germanium --- nanowire-based quantum devices --- HfO2/Si0.7Ge0.3 gate stack --- ozone oxidation --- Si-cap --- interface state density --- passivation --- GOI --- photodetectors --- dark current --- responsivity --- prussian blue nanoparticles --- organotrialkoxysilane --- silica beads --- arsenite --- arsenate --- water decontamination --- vertical gate-all-around (vGAA) --- digital etch --- quasi-atomic-layer etching (q-ALE) --- selective wet etching --- HNO3 concentration --- doping effect --- vertical Gate-all-around (vGAA) --- p+-Ge0.8Si0.2/Ge stack --- dual-selective wet etching --- atomic layer etching (ALE) --- stacked SiGe/Si --- epitaxial grown --- Fin etching --- FinFET --- short-term potentiation (STP) --- long-term potentiation (LTP) --- charge-trap synaptic transistor --- band-to-band tunneling --- pattern recognition --- neural network --- neuromorphic system --- Si-MOS --- quantum dot --- spin qubits --- quantum computing --- GeSn --- CVD --- lasers --- detectors --- transistors --- III-V on Si --- heteroepitaxy --- threading dislocation densities (TDDs) --- anti-phase boundaries (APBs) --- selective epitaxial growth (SEG) --- n/a
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Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields.
light emitting diode --- nonlinearity estimation and compensation --- probabilistic Bayesian learning --- visible light communication --- digital signal processing --- support vector machines --- BCSVM --- nonlinear equalization --- coherent detection --- k-nearest neighbor algorithm --- modulation format identification --- OSNR monitoring --- neural networks --- optical communications --- optimization --- equalizer --- tap estimation --- optical Fast-OFDM --- nonlinearity compensation --- optical fiber communications --- chromatic dispersion --- short-reach communication --- neural network --- hybrid signal processing --- fiber optics communications --- coherent communications --- machine learning --- clustering --- nonlinearity cancellation --- entanglement --- charge qubit --- position-based semiconductor qubits --- cryogenic technologies --- semiconductor photon communication --- Jaynes–Cummings–Hubbard formalism --- deep neural networks --- volterra equalization --- nonlinear systems --- coherent optical communication --- passive optical networks --- nonlinear compensation --- optical transmission --- optical networks --- artificial intelligence --- quality of transmission --- optical performance monitoring --- failure management --- artificial neural networks --- deep neural network --- image classification --- photonic integrated circuits --- semiconductor optical amplifiers --- photonic neural network --- n/a --- Jaynes-Cummings-Hubbard formalism
Choose an application
This book is a collection of scientific articles which brings research in Si nanodevices, device processing, and materials. The content is oriented to optoelectronics with a core in electronics and photonics. The issue of current technology developments in the nanodevices towards 3D integration and an emerging of the electronics and photonics as an ultimate goal in nanotechnology in the future is presented. The book contains a few review articles to update the knowledge in Si-based devices and followed by processing of advanced nano-scale transistors. Furthermore, material growth and manufacturing of several types of devices are presented. The subjects are carefully chosen to critically cover the scientific issues for scientists and doctoral students.
Technology: general issues --- silicon --- yolk−shell structure --- anode --- lithium-ion batteries --- in-plane nanowire --- site-controlled --- epitaxial growth --- germanium --- nanowire-based quantum devices --- HfO2/Si0.7Ge0.3 gate stack --- ozone oxidation --- Si-cap --- interface state density --- passivation --- GOI --- photodetectors --- dark current --- responsivity --- prussian blue nanoparticles --- organotrialkoxysilane --- silica beads --- arsenite --- arsenate --- water decontamination --- vertical gate-all-around (vGAA) --- digital etch --- quasi-atomic-layer etching (q-ALE) --- selective wet etching --- HNO3 concentration --- doping effect --- vertical Gate-all-around (vGAA) --- p+-Ge0.8Si0.2/Ge stack --- dual-selective wet etching --- atomic layer etching (ALE) --- stacked SiGe/Si --- epitaxial grown --- Fin etching --- FinFET --- short-term potentiation (STP) --- long-term potentiation (LTP) --- charge-trap synaptic transistor --- band-to-band tunneling --- pattern recognition --- neural network --- neuromorphic system --- Si-MOS --- quantum dot --- spin qubits --- quantum computing --- GeSn --- CVD --- lasers --- detectors --- transistors --- III-V on Si --- heteroepitaxy --- threading dislocation densities (TDDs) --- anti-phase boundaries (APBs) --- selective epitaxial growth (SEG) --- silicon --- yolk−shell structure --- anode --- lithium-ion batteries --- in-plane nanowire --- site-controlled --- epitaxial growth --- germanium --- nanowire-based quantum devices --- HfO2/Si0.7Ge0.3 gate stack --- ozone oxidation --- Si-cap --- interface state density --- passivation --- GOI --- photodetectors --- dark current --- responsivity --- prussian blue nanoparticles --- organotrialkoxysilane --- silica beads --- arsenite --- arsenate --- water decontamination --- vertical gate-all-around (vGAA) --- digital etch --- quasi-atomic-layer etching (q-ALE) --- selective wet etching --- HNO3 concentration --- doping effect --- vertical Gate-all-around (vGAA) --- p+-Ge0.8Si0.2/Ge stack --- dual-selective wet etching --- atomic layer etching (ALE) --- stacked SiGe/Si --- epitaxial grown --- Fin etching --- FinFET --- short-term potentiation (STP) --- long-term potentiation (LTP) --- charge-trap synaptic transistor --- band-to-band tunneling --- pattern recognition --- neural network --- neuromorphic system --- Si-MOS --- quantum dot --- spin qubits --- quantum computing --- GeSn --- CVD --- lasers --- detectors --- transistors --- III-V on Si --- heteroepitaxy --- threading dislocation densities (TDDs) --- anti-phase boundaries (APBs) --- selective epitaxial growth (SEG)
Choose an application
Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields.
History of engineering & technology --- light emitting diode --- nonlinearity estimation and compensation --- probabilistic Bayesian learning --- visible light communication --- digital signal processing --- support vector machines --- BCSVM --- nonlinear equalization --- coherent detection --- k-nearest neighbor algorithm --- modulation format identification --- OSNR monitoring --- neural networks --- optical communications --- optimization --- equalizer --- tap estimation --- optical Fast-OFDM --- nonlinearity compensation --- optical fiber communications --- chromatic dispersion --- short-reach communication --- neural network --- hybrid signal processing --- fiber optics communications --- coherent communications --- machine learning --- clustering --- nonlinearity cancellation --- entanglement --- charge qubit --- position-based semiconductor qubits --- cryogenic technologies --- semiconductor photon communication --- Jaynes-Cummings-Hubbard formalism --- deep neural networks --- volterra equalization --- nonlinear systems --- coherent optical communication --- passive optical networks --- nonlinear compensation --- optical transmission --- optical networks --- artificial intelligence --- quality of transmission --- optical performance monitoring --- failure management --- artificial neural networks --- deep neural network --- image classification --- photonic integrated circuits --- semiconductor optical amplifiers --- photonic neural network --- light emitting diode --- nonlinearity estimation and compensation --- probabilistic Bayesian learning --- visible light communication --- digital signal processing --- support vector machines --- BCSVM --- nonlinear equalization --- coherent detection --- k-nearest neighbor algorithm --- modulation format identification --- OSNR monitoring --- neural networks --- optical communications --- optimization --- equalizer --- tap estimation --- optical Fast-OFDM --- nonlinearity compensation --- optical fiber communications --- chromatic dispersion --- short-reach communication --- neural network --- hybrid signal processing --- fiber optics communications --- coherent communications --- machine learning --- clustering --- nonlinearity cancellation --- entanglement --- charge qubit --- position-based semiconductor qubits --- cryogenic technologies --- semiconductor photon communication --- Jaynes-Cummings-Hubbard formalism --- deep neural networks --- volterra equalization --- nonlinear systems --- coherent optical communication --- passive optical networks --- nonlinear compensation --- optical transmission --- optical networks --- artificial intelligence --- quality of transmission --- optical performance monitoring --- failure management --- artificial neural networks --- deep neural network --- image classification --- photonic integrated circuits --- semiconductor optical amplifiers --- photonic neural network
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