Broadband quantum-dot frequency-modulated comb laser

Frequency-modulated (FM) laser combs, which offer a periodic quasi-continuous-wave output and a flat-topped optical spectrum, are emerging as a promising solution for wavelength-division multiplexing applications, precision metrology, and ultrafast optical ranging. The generation of FM combs relies on spatial hole burning, group velocity dispersion (GVD), Kerr nonlinearity, and four-wave mixing (FWM). While FM combs have been widely observed in quantum cascade Fabry-Perot (FP) lasers, the requirement for a low-dispersion FP cavity can be a challenge in platforms where the waveguide dispersion is mainly determined by the material. Here we report a 60 GHz quantum-dot (QD) mode-locked laser in which both the amplitude-modulated (AM) and the FM comb can be generated independently. The high FWM efficiency of -5 dB allows the QD laser to generate an FM comb efficiently. We also demonstrate that the Kerr nonlinearity can be practically engineered to improve the FM comb bandwidth without the need for GVD engineering. The maximum 3-dB bandwidth that our QD platform can deliver is as large as 2.2 THz. This study gives novel insights into the improvement of FM combs and paves the way for small-footprint, electrically-pumped, and energy-efficient frequency combs for silicon photonic integrated circuits (PICs)

Automatic RADAR Target Recognition System at THz Frequency Band. A Review

The development of technology for communication in the THz frequency band has seen rapid progress recently. Due to the wider bandwidth a THz frequency RADAR provides the possibility of higher precision imaging compared to conventional RADARs. A high resolution RADAR operating at THz frequency can be used for automatically detecting and segmenting concealed objects. Recent advancements in THz circuit integration have opened up a wide range of possibilities for on chip applications, like of security and surveillance. The development of various sources and detectors for generation and detection of THz frequency has been driven by other techniques such as spectroscopy, imaging and impulse ranging. One of the central vision of this type of security system aims at ambient intelligence: the computation and communication carried out intelligently. The need for higher mobility with limited size and power consumption has led to development of nanotechnology based THz generators. In addition to this some of the soft computing tools are used for detection of radar target automatically based on some algorithms named as ANN, RNN, Neuro-Fuzzy and Genetic algorithms. This review article includes UWB radar for THz signal, its characteristics and application, Nanotechnology for THz generation and issues related to ATR

Approche industrielle aux boîtes quantiques dans des dispositifs de silicium sur isolant complètement déplété pour applications en information quantique

La mise en oeuvre des qubits de spin électronique à base de boîtes quantiques réalisés en utilisant une technologie avancée de métal-oxyde-semiconducteur complémentaire (en anglais: CMOS ou Complementary Metal-Oxide-Semiconductor) fonctionnant à des températures cryogéniques permet d’envisager la fabrication industrielle reproductible et à haut rendement de systèmes de qubits de spin à grande échelle. Le développement d’une architecture de boîtes quantiques à base de silicium fabriquées en utilisant exclusivement des techniques de fabrication industrielle CMOS constitue une étape majeure dans cette direction. Dans cette thèse, le potentiel de la technologie UTBB (en anglais: Ultra-Thin Body and Buried oxide) silicium sur isolant complétement déplété (en anglais: FD-SOI ou Fully Depleted Silicon-On-Insulator) 28 nm de STMicroelectronics (Crolles, France) a été étudié pour la mise en oeuvre de boîtes quantiques bien définies, capables de réaliser des systèmes de qubit de spin. Dans ce contexte, des mesures d’effet Hall ont été réalisées sur des microstructures FD-SOI à 4.2 K afin de déterminer la qualité du noeud technologique pour les applications de boîtes quantiques. De plus, un flot du processus d’intégration, optimisé pour la mise en oeuvre de dispositifs quantiques utilisant exclusivement des méthodes de fonderie de silicium pour la production de masse est présenté, en se concentrant sur la réduction des risques de fabrication et des délais d’exécution globaux. Enfin, deux géométries différentes de dispositifs à boîtes quantiques FD-SOI de 28nm ont été conçues et leurs performances ont été étudiées à 1.4 K. Dans le cadre d’une collaboration entre Nanoacademic Technologies, Institut quantique et STMicroelectronics, un modèle QTCAD (en anglais: Quantum Technology Computer-Aided Design) en 3D a été développé pour la modélisation de dispositifs à boîtes quantiques FD-SOI. Ainsi, en complément de la caractérisation expérimentale des structures de test via des mesures de transport et de spectroscopie de blocage de Coulomb, leur performance est modélisée et analysée à l’aide du logiciel QTCAD. Les résultats présentés ici démontrent les avantages de la technologie FD-SOI par rapport à d’autres approches pour les applications de calcul quantique, ainsi que les limites identifiées du noeud 28 nm dans ce contexte. Ce travail ouvre la voie à la mise en oeuvre des nouvelles générations de dispositifs à boîtes quantiques FD-SOI basées sur des noeuds technologiques inférieurs.Abstract: Electron spin qubits based on quantum dots implemented using advanced Complementary Metal-Oxide-Semiconductor (CMOS) technology functional at cryogenic temperatures promise to enable reproducible high-yield industrial manufacturing of large-scale spin qubit systems. A milestone in this direction is to develop a silicon-based quantum dot structure fabricated using exclusively CMOS industrial manufacturing techniques. In this thesis, the potential of the industry-standard process 28 nm Ultra-Thin Body and Buried oxide (UTBB) Fully Depleted Silicon-On-Insulator (FD-SOI) technology of STMicroelectronics (Crolles, France) was investigated for the implementation of well-defined quantum dots capable to realize spin qubit systems. In this context, Hall effect measurements were performed on FD-SOI microstructures at 4.2 K to determine the quality of the technology node for quantum dot applications. Moreover, an optimized integration process flow for the implementation of quantum devices, using exclusively mass-production silicon-foundry methods is presented, focusing on reducing manufacturing risks and overall turnaround times. Finally, two different geometries of 28 nm FD-SOI quantum dot devices were conceived, and their performance was studied at 1.4 K. In the framework of a collaboration between Nanoacademic Technologies, Institut quantique, and STMicroelectronics, a 3D Quantum Technology Computer-Aided Design (QTCAD) model was developed for FD-SOI quantum dot device modeling. Therefore, along with the experimental characterization of the test structures via transport and Coulomb blockade spectroscopy measurements, their performance is modeled and analyzed using the QTCAD software. The results reported here demonstrate the advantages of the FD-SOI technology over other approaches for quantum computing applications, as well as the identified limitations of the 28 nm node in this context. This work paves the way for the implementation of the next generations of FD-SOI quantum dot devices based on lower technology nodes

Engineered quantum dots for infrared photodetectors

Quantum Dot Infrared Photodetector (QDIP) Focal Plane Arrays (FPAs) have been proposed as an alternative technology for the 3rd generation FPAs. QDIPs are emerging as a competitive technology for infrared detection and imaging especially in the midwave infrared (MWIR) and longwave infrared (LWIR) regime. These detectors are based on intersubband transitions in self-assembled InAs quantum dots (QDs) and offer several advantages such as normal incidence detection, low dark currents and high operating temperatures, while enjoying all the benefits of a mature GaAs fabrication technology. However, due to Stranski-Krastanov (SK) growth mode and the subsequent capping growth, the conventional SK QDs are pancake shaped\u27 with small height to base ratio due to interface diffusion. Thus they cannot fully exploit the 3D \u27artificial atom\u27 properties. This dissertation work investigates two approaches for shape engineered QDs: (1) Selective capping techniques of Stranski-Krastanov QDs, and (2) Growth of Sub-Monolayer (SML) QDs. Using Molecular Beam Epitaxy (MBE) growth, engineered QDs have been demonstrated with improved dot geometry and 3D quantum confinement to more closely resemble the 3D \u27artificial atom\u27. In SK-QDs, the results have demonstrated an increased dot height to base aspect ratio of 0.67 compared with 0.23 for conventional SK-QD using Transmission Electron Microscope (TEM) images, enhanced s-to-p polarized spectral response ratio of 37% compared with 10% for conventional SK-QD, and improved SK-QDIP characterization such as: high operating temperature of 150K under background-limited infrared photodetection (BLIP) condition, photodetectivity of 1x109 cmHz1/2/W at 77K for a peak wavelength of 4.8 μm, and photoconductive gain of 100 (Vb=12V) at 77 K. In SML-QDs, we have demonstrated dots with a small base width of 4~6 nm, height of 8 nm, absence of wetting layer and advantage optical property than the SK-QDs. SML-QD shows adjustable dot height to base aspect ratio of 8nm/6nm, increased s-to-p polarized spectral response ratio of 33%, and a narrower full width at half maximum (FWHM), long wavelength 10.5 μm bound-to-bound intersubband transition, and higher responsivity of 1.2 A/W at -2.2 V at 77K and detectivity of 4x109 cmHz1/2/W at 0.4 V 77K.\u2

Large-Scale Optical Neural Networks based on Photoelectric Multiplication

Recent success in deep neural networks has generated strong interest in hardware accelerators to improve speed and energy consumption. This paper presents a new type of photonic accelerator based on coherent detection that is scalable to large ($N \gtrsim 10^6$) networks and can be operated at high (GHz) speeds and very low (sub-aJ) energies per multiply-and-accumulate (MAC), using the massive spatial multiplexing enabled by standard free-space optical components. In contrast to previous approaches, both weights and inputs are optically encoded so that the network can be reprogrammed and trained on the fly. Simulations of the network using models for digit- and image-classification reveal a "standard quantum limit" for optical neural networks, set by photodetector shot noise. This bound, which can be as low as 50 zJ/MAC, suggests performance below the thermodynamic (Landauer) limit for digital irreversible computation is theoretically possible in this device. The proposed accelerator can implement both fully-connected and convolutional networks. We also present a scheme for back-propagation and training that can be performed in the same hardware. This architecture will enable a new class of ultra-low-energy processors for deep learning.Comment: Text: 10 pages, 5 figures, 1 table. Supplementary: 8 pages, 5, figures, 2 table