Kicking electrons

The concept of dominant interaction hamiltonians is introduced and applied to classical planar electron-atom scattering. Each trajectory is governed in different time intervals by two variants of a separable approximate hamiltonian. Switching between them results in exchange of energy between the two electrons. A second mechanism condenses the electron-electron interaction to instants in time and leads to an exchange of energy and angular momentum among the two electrons in form of kicks. We calculate the approximate and full classical deflection functions and show that the latter can be interpreted in terms of the switching sequences of the approximate one. Finally, we demonstrate that the quantum results agree better with the approximate classical dynamical results than with the full ones.Comment: version 2: references adde

Dissection of Bitcoin's Multiscale Bubble History from January 2012 to February 2018

We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market decrease (drawdowns). In combination with the Lagrange Regularisation Method for detecting the beginning of a new market regime, we identify 3 major peaks and 10 additional smaller peaks, that have punctuated the dynamics of Bitcoin price during the analyzed time period. We explain this classification of long and short bubbles by a number of quantitative metrics and graphs to understand the main socio-economic drivers behind the ascent of Bitcoin over this period. Then, a detailed analysis of the growing risks associated with the three long bubbles using the Log-Periodic Power Law Singularity (LPPLS) model is based on the LPPLS Confidence Indicators, defined as the fraction of qualified fits of the LPPLS model over multiple time windows. Furthermore, for various fictitious 'present' times $t_2$ before the crashes, we employ a clustering method to group the predicted critical times $t_c$ of the LPPLS fits over different time scales, where $t_c$ is the most probable time for the ending of the bubble. Each cluster is proposed as a plausible scenario for the subsequent Bitcoin price evolution. We present these predictions for the three long bubbles and the four short bubbles that our time scale of analysis was able to resolve. Overall, our predictive scheme provides useful information to warn of an imminent crash risk

Dissection of Bitcoin's Multiscale Bubble History from January 2012 to February 2018

We present a detailed bubble analysis of the Bitcoin to US Dollar price dynamics from January 2012 to February 2018. We introduce a robust automatic peak detection method that classifies price time series into periods of uninterrupted market growth (drawups) and regimes of uninterrupted market decrease (drawdowns). In combination with the Lagrange Regularisation Method for detecting the beginning of a new market regime, we identify 3 major peaks and 10 additional smaller peaks, that have punctuated the dynamics of Bitcoin price during the analyzed time period. We explain this classification of long and short bubbles by a number of quantitative metrics and graphs to understand the main socio-economic drivers behind the ascent of Bitcoin over this period. Then, a detailed analysis of the growing risks associated with the three long bubbles using the Log-Periodic Power Law Singularity (LPPLS) model is based on the LPPLS Confidence Indicators, defined as the fraction of qualified fits of the LPPLS model over multiple time windows. Furthermore, for various fictitious 'present' times $t_2$ before the crashes, we employ a clustering method to group the predicted critical times $t_c$ of the LPPLS fits over different time scales, where $t_c$ is the most probable time for the ending of the bubble. Each cluster is proposed as a plausible scenario for the subsequent Bitcoin price evolution. We present these predictions for the three long bubbles and the four short bubbles that our time scale of analysis was able to resolve. Overall, our predictive scheme provides useful information to warn of an imminent crash risk

Detection of small bunches of ions using image charges

A concept for detection of charged particles in a single fly-by, e.g. within an ion optical system for deterministic implantation, is presented. It is based on recording the image charge signal of ions moving through a detector, comprising a set of cylindrical electrodes. This work describes theoretical and practical aspects of image charge detection (ICD) and detector design and its application in the context of real time ion detection. It is shown how false positive detections are excluded reliably, although the signal-to-noise ratio is far too low for time-domain analysis. This is achieved by applying a signal threshold detection scheme in the frequency domain, which - complemented by the development of specialised low-noise preamplifier electronics - will be the key to developing single ion image charge detection for deterministic implantation

Nanoscale ion implantation using focussed highly charged ions

We introduce a focussed ion beam (FIB) based ion implanter equipped with an electron beam ion source (EBIS), able to produce highly charged ions. As an example of its utilisation, we demonstrate the direct writing of nitrogen-vacancy centres in diamond using focussed, mask-less irradiation with Ar8+ ions with sub-micron three dimensional placement accuracy. The ion optical system was optimised and is characterised via secondary electron imaging. The smallest measured foci are below 200 nm, using objective aperture diameters of 5 and 10 µm, showing that nanoscale ion implantation using an EBIS is feasible. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft

Assessing Non-Invasive Liver Function in Patients With Intestinal Failure Receiving Total Parenteral Nutrition-Results From the Prospective PNLiver Trial

Liver abnormalities in intestinal failure (IF) patients receiving parenteral nutrition (PN) can progress undetected by standard laboratory tests to intestinal failure associated liver disease (IFALD). The aim of this longitudinal study is to evaluate the ability of non-invasive liver function tests to assess liver function following the initiation of PN. Twenty adult patients with IF were prospectively included at PN initiation and received scheduled follow-up assessments after 6, 12, and 24 months between 2014 and 2019. Each visit included liver assessment (LiMAx [Liver Maximum Capacity] test, ICG [indocyanine green] test, FibroScan), laboratory tests (standard laboratory test, NAFLD [non-alcoholic fatty liver disease] score, FIB-4 [fibrosis-4] score), nutritional status (bioelectrical impedance analysis, indirect calorimetry), and quality of life assessment. The patients were categorized post-hoc based on their continuous need for PN into a reduced parenteral nutrition (RPN) group and a stable parenteral nutrition (SPN) group. While the SPN group (n = 9) had significantly shorter small bowel length and poorer nutritional status at baseline compared to the RPN group (n = 11), no difference in liver function was observed between the distinct groups. Over time, liver function determined by LiMAx did continuously decrease from baseline to 24 months in the SPN group but remained stable in the RPN group. This decrease in liver function assessed with LiMAx in the SPN group preceded deterioration of all other investigated liver function tests during the study period. Our results suggest that the liver function over time is primarily determined by the degree of intestinal failure. Furthermore, the LiMAx test appeared more sensitive in detecting early changes in liver function in comparison to other liver function tests

Image charge detection statistics relevant for deterministic ion implantation

Image charge detection is a non-perturbative pre-detection approach for deterministic ion implantation. Using low energy ion bunches as a model system for highly charged single ions, we experimentally studied the error and detection rates of an image charge detector setup. The probability density functions of the signal amplitudes in the Fourier spectrum can be modelled with a generalised gamma distribution to predict error and detection rates. It is shown that the false positive error rate can be minimised at the cost of detection rate, but this does not impair the fidelity of a deterministic implantation process. Independent of the ion species, at a signal to-noise ratio of 2, a false positive error rate of 0.1% is achieved, while the detection rate is about 22

The Quest for Stability: the macro view

On September 3-4, 2009 SUERF and Utrecht University School of Economicsorganized the Colloquium "The Quest for Stability" in Utrecht, the Netherlands. The papers included in this SUERF Study are based on contributions to the Colloquium.asset prices, bubbles, financial institutions, global recession, interest rates, liquidity, monetary policy, regulation, stability, supervision.