Bøker i Springer Theses-serien

Time, space and entanglement are the main characters in this book. Their nature is still a great mystery in physics and we study here the possibility that these three phenomena are closely connected, showing how entanglement can be at the basis of the emergence of time and space within closed quantum systems. We revisit and extend the Page and Wootters theory that was originally introduced in order to describe the emergence of time through entanglement between subsystems in a globally static, quantum Universe. In the book, after providing a complete review of the salient aspects of the theory, we establish a connection with recent research on the foundations of statistical mechanics and we provide a new understanding of the thermalization process. Furthermore, we generalize the framework in order describe the spatial degree of freedom and we provide a model of 3+1 dimensional, quantum spacetime emerging from entanglement among different subsystems in a globally "timeless" and "positionless" Universe. Finally, via the Page and Wootters theory, the evolution of quantum clocks within a gravitational field is treated and a time dilation effect is obtained in agreement with the Schwarzschild solution.

In recent decades, twistor theory has grown into an irreplaceable tool for the study of scattering amplitudes in gauge theory and gravity. This book introduces the reader to cutting-edge advances in twistor theory and its applications to general relativity. The problem of graviton scattering in four dimensions is shown to be dual to dramatically simpler computations in a two-dimensional CFT known as a twistor sigma model. Twistor sigma models are the first step toward a holographic description of gravity in asymptotically flat space-times. They underpin the infinitely many asymptotic symmetries of flat space physics discovered in celestial holography, and extend them to exciting new arenas like curved space-times. They also yield intrinsically mathematical results in the field of hyperkähler manifolds. This volume will be of broad interest to students and researchers looking for an accessible entry point into twistor geometry, scattering amplitudes, and celestial holography. It will also provide an invaluable reference for specialists by bringing together results from a host of different disciplines.

This thesis describes how the rich internal degrees of freedom of molecules can be exploited to construct the first ¿clock¿ based on ultracold molecules, rather than atoms. By holding the molecules in an optical lattice trap, the vibrational clock is engineered to have a high oscillation quality factor, facilitating the full characterization of frequency shifts affecting the clock at the hertz level. The prototypical vibrational molecular clock is shown to have a systematic fractional uncertainty at the 14th decimal place, matching the performance of the earliest optical atomic lattice clocks. As part of this effort, deeply bound strontium dimers are coherently created, and ultracold collisions of these Van der Waals molecules are studied for the first time, revealing inelastic losses at the universal rate. The thesis reports one of the most accurate measurements of a molecule¿s vibrational transition frequency to date. The molecular clock lays the groundwork for explorations into terahertz metrology, quantum chemistry, and fundamental interactions at atomic length scales.

This book describes the development of novel protein¿RNA-binding assays and their applications in a high-throughput manner for the identification of small-molecule modulators of protein¿RNA interactions to treat cancer and COVID-19.Modulating protein¿RNA interactions with small molecules is expected to provide novel biological insights of the interrelation of diseases with the protein¿RNA interactome. The modulations may also be exploited therapeutically. For these reasons, the development of a simple, reliable, and sensitive protein¿RNA-binding assay is necessary for high-throughput screening to discover new effective chemical entities capable of acting on diverse protein¿RNA interactions. This book discusses the discovery of small-molecule modulators targeting protein¿RNA interactions that are potentially valuable to treat cancer and COVID-19 by constructing novel high-throughput screening methods. The results of this dissertation provide valuable insights into the regulation of protein¿RNA interactions in chemical biology and drug development.

This thesis outlines the principles, device physics, and technological applications of electronics based on the ultra-wide bandgap semiconductor aluminum nitride. It discusses the basic principles of electrostatics and transport properties of polarization-induced two-dimensional electron and hole channels in semiconductor heterostructures based on aluminum nitride. It explains the discovery of high-density two-dimensional hole gases in undoped heterojunctions, and shows how these high conductivity n- and p-type channels are used for high performance nFETs and pFETs, along with wide bandgap RF, mm-wave, and CMOS applications. The thesis goes on to discuss how the several material advantages of aluminum nitride, such as its high thermal conductivity and piezoelectric coefficient, enable not just high performance of transistors, but also monolithic integration of passive elements such as high frequency filters, enabling a new form factor for integrated RF electronics.

This thesis makes significant advances in the use of microspheres in optical traps as highly precise sensing platforms. While optically trapped microspheres have recently proven their dominance in aqueous and vacuum environments, achieving state-of-the-art measurements of miniscule forces and torques, their sensitivity to perturbations in air has remained relatively unexplored. This thesis shows that, by uniquely operating in air and measuring its thermally-fluctuating instantaneous velocity, an optically trapped microsphere is an ultra-sensitive probe of both mass and sound. The mass of the microsphere is determined with similar accuracy to competitive methods but in a fraction of the measurement time and all while maintaining thermal equilibrium, unlike alternative methods. As an acoustic transducer, the air-based microsphere is uniquely sensitive to the velocity of sound, as opposed to the pressure measured by a traditional microphone. By comparison to state-of-the-art commercially-available velocity and pressure sensors, including the world¿s smallest measurement microphone, the microsphere sensing modality is shown to be both accurate and to have superior sensitivity at high frequencies. Applications for such high-frequency acoustic sensing include dosage monitoring in proton therapy for cancer and event discrimination in bubble chamber searches for dark matter. In addition to reporting these scientific results, the thesis is pedagogically organized to present the relevant history, theory, and technology in a straightforward way.

This book focuses on proposing a tsunami early warning system using data assimilation of offshore data. First, Green's Function-based Tsunami Data Assimilation (GFTDA) is proposed to reduce the computation time for assimilation. It can forecast the waveform at Points of Interest (PoIs) by superposing Green's functions between observational stations and PoIs. GFTDA achieves an equivalently high accuracy of tsunami forecasting to the previous approaches, while saving sufficient time to achieve an early warning. Second, a modified tsunami data assimilation method is explored for regions with a sparse observation network. The method uses interpolated waveforms at virtual stations to construct the complete wavefront for tsunami propagation. Its application to the 2009 Dusky Sound, New Zealand earthquake, and the 2015 Illapel earthquake revealed that adopting virtual stations greatly improved the tsunami forecasting accuracy for regions without a dense observation network. Finally, a real-time tsunami detection algorithm using Ensemble Empirical Mode Decomposition (EEMD) is presented. The tsunami signals of the offshore bottom pressure gauge can be automatically separated from the tidal components, seismic waves, and background noise. The algorithm could detect tsunami arrival with a short detection delay and accurately characterize the tsunami amplitude. Furthermore, the tsunami data assimilation approach is combined with the real-time tsunami detection algorithm, which is applied to the tsunami of the 2016 Fukushima earthquake. The proposed tsunami data assimilation approach can be put into practice with the help of the real-time tsunami detection algorithm.

This thesis investigates the detection efficiency of field-resolved measurements of ultrashort mid-infrared waves via electro-optic sampling for the first time. Employing high-power gate pulses and phase-matched upconversion in thick nonlinear crystals, unprecedented efficiencies are achieved for octave-spanning fields in this wavelength range. In combination with state-of-the art, high-power, ultrashort mid-infrared sources, this allows to demonstrate a new regime of linear detection dynamic range for field strengths from mV/cm to MV/cm-levels. These results crucially contribute to the development of field-resolved spectrometers for early disease detection, as fundamental vibrational modes of (bio-)molecules lie in the investigated spectral range.The results are discussed and compared with previous sensitivity records for electric-field measurements and reference is made to related implementations of the described characterization technique. Including a detailed theoretical description and simulation results, the work elucidates crucial scaling laws, characteristics and limitations. The thesis will thus serve as an educational introduction to the topic of field-resolved measurements using electro-optic sampling, giving detailed instructions on simulations and experimental implementations. At the same time, it showcases the state-of-the-art in terms of detection sensitivity for characterizing mid-infrared waves.

The thesis presents a systematic study of the Mpemba effect in a colloidal system with a micron-sized particle diffusing in a water bath. While the Mpemba effect, where a system's thermal relaxation time is a non-monotonic function of the initial temperature, has been observed in water since Aristotle's era, the underlying mechanism of the effect is still unknown. Recent studies indicate that the effect is not limited to water and has been studied both experimentally and numerically in a wide variety of systems. By carefully designing a double-well potential using feedback-based optical tweezers, the author demonstrates that an initially hot system can sometimes cool faster than an initially warm system. The author also presents the first observation in any system of another counterintuitive effect-the inverse Mpemba effect-where the colder of the two samples reaches the thermal equilibrium at a hot temperature first. The results for both the observations agree with theoretical predictions based on the Fokker-Planck equation. The experiments reveal that, for carefully chosen conditions, a strong version of both of the effects are observed where a system can relax to the bath temperature exponentially faster than under typical conditions.

This thesis presents the first realization of non-reciprocal energy transfer between two cantilevers by quantum vacuum fluctuations. According to quantum mechanics, vacuum is not empty but full of fluctuations due to zero-point energy. Such quantum vacuum fluctuations can lead to an attractive force between two neutral plates in vacuum ¿ the so-called Casimir effect ¿ which has attracted great attention as macroscopic evidence of quantum electromagnetic fluctuations, and can dominate the interaction between neutral surfaces at small separations. The first experimental demonstration of diode-like energy transport in vacuum reported in this thesis is a breakthrough in Casimir-based devices. It represents an efficient and robust way of regulating phonon transport along one preferable direction in vacuum. In addition, the three-body Casimir effects investigated in this thesis were used to realize a transistor-like three-terminal device with quantum vacuum fluctuations. These two breakthroughs pave the way for exploring and developing advanced Casimir-based devices with potential applications in quantum information science. This thesis also includes a study of the non-contact Casimir friction, which will enrich the understanding of quantum vacuum fluctuations.

Line intensity mapping (LIM) is an observational technique that probes the large-scale structure of the Universe by collecting light from a wide field of the sky. This book demonstrates a novel analysis method for LIM using machine learning (ML) technologies. The author develops a conditional generative adversarial network that separates designated emission signals from sources at different epochs. It thus provides, for the first time, an efficient way to extract signals from LIM data with foreground noise. The method is complementary to conventional statistical methods such as cross-correlation analysis. When applied to three-dimensional LIM data with wavelength information, high reproducibility is achieved under realistic conditions. The book further investigates how the trained machine extracts the signals, and discusses the limitation of the ML methods. Lastly an application of the LIM data to a study of cosmic reionization is presented. This book benefits students and researchers who are interested in using machine learning to multi-dimensional data not only in astronomy but also in general applications.