Local Probing of a Superconductor’s Quasiparticles and Bosonic Excitations with a Scanning Tunnelling Microscope

Complementary to scattering techniques, scanning tunnelling microscopy provides atomic-scale real space information about a material\u27s electronic state of matter. State-of-the-art designs of a scanning tunnelling microscope (STM) allow measurements at millikelvin temperatures with unprecedented energy resolution. Therefore, this instrument excels in probing the superconducting state at low temperatures and especially its local quasiparticle excitations as well as bosonic degrees of freedom

Laser Ranging Interferometry for Future Gravity Missions : Instrument Design, Link Acquisition and Data Calibration

The presented study aims to improve the design solution adopted for the Laser Ranging Instrument of the GRACE Follow-On mission in terms of instrument layout, algorithms for the laser link acquisition and techniques for mitigating the range measurement noise. The first part of this work describes viable layout solutions of a heterodyne interferometer employed for intra-satellite range metrology and the major noise contributions which degrade the overall accuracy of the instrument. Together with the optical layout of the instrument, novel design concepts of the instrumenta s subsystems are also analyzed and tested. Precisely, a phasemeter designed to autonomously acquire and track a heterodyne signal with low signal-to-noise ratio in a frequency band that spans from 1MHz to 25MHz is presented. Particular attention is also dedicated to the mathematical modeling of the steering mirror dynamics and to the enhancement of its pointing performance by means of feedforward control. In the second part of this work, solutions for autonomously acquiring a laser signal buried in noise are analyzed and put in relation with the boundary constraints of the acquisition problem. The acquisition algorithms presented and the robustness of their design is verified mainly using numerical simulations. Experimental tests have also been performed for validating the simulation hypothesis and verifying their compliancy to a realistic mission scenario. The last part of this work describes a calibration algorithm which has been developed for minimizing, during data post-processing, the noise due to the tilt-to-piston coupling which represents one of the highest contributors to the overall measurement noise

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma

Digital control networks for virtual creatures

Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments were carried out in a simulated physically realistic 3D world. The performance of evolved controllers was evaluated on two well known control tasks—pole balancing, and locomotion of evolved morphologies. The performance of evolved digital controllers was compared to evolved floating-point neural networks. The results show that the digital implementations are competitive with floating-point designs on both of the benchmark problems. In addition, the first reported evolution from scratch of a biped walker is presented, demonstrating that when all parameters are left open to evolutionary optimisation complex behaviour can result from simple components