Analytic calculation of two-loop QCD corrections to b\to s\ell^+\ell^- in the high q^2 region

We present our results for the NNLL virtual corrections to the matrix elements of the operators O_1 and O_2 for the inclusive process b\to s\ell^+\ell^- in the kinematical region q^2>4m_c^2, where q^2 is the invariant mass squared of the lepton-pair. This is the first analytic two-loop calculation of these matrix elements in the high q^2 region. We give the matrix elements as an expansion in m_c/m_b and keep the full analytic dependence on q^2. Making extensive use of differential equation techniques, we fully automatize the expanding of the Feynman integrals in m_c/m_b. In coincidence with an earlier work where the master integrals where calculated numerically (Ghinculov et al.) we find that in the high q^2 region the \alpha_s corrections to the matrix elements calculated in the present paper lead to a decrease of the q^2-spectrum by 10%-15% relative to the NNLL result in which these contributions are put to zero and reduce the renormalization scale uncertainty to ~2%.Comment: 27 pages, 4 figures, 2 tables, mathematica and c++ code attached, minor changes and corrections of typo

Drone radio signal detection with multi-timescale deep neural networks

We develop a multi-timescale deep learning algorithm to detect drones from radio signals. While previous approaches focused on the analysis of high-frequency radio data alone we integrate signals from the higher timescale of the drone communication protocol in an end-to-end architecture. To this end, we develop a new meta-CNN layer, which generalizes the idea of the standard CNN (which slides a single, fully connected kernel along a higher-level input) towards arbitrarily complex kernel models. To detect higher timescale patterns our system uses an LSTM layer in the top layers. As a result, our model is able to extend drone identification abilities significantly toward very small SNRs

Outdoor ranging and positioning based on LoRa modulation

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We present results for outdoor ranging and positioning based on the Long-Range (LoRa) modulation, which is a widespread wireless IoT technology. LoRa systems typically operate in sub-GHz frequency bands with only 125 kHz bandwidth, which restricts the ranging performance due to the limited temporal resolution. The investigated LoRa ranging method operates in the 2.4 GHz ISM frequency band and supports wider bandwidths, achieving for outdoor ranging a mean distance error below 50 m over distances of up to 1400 m. Positioning based on LoRa ranging obtained a measured Distance Root Mean Square (DRMS) error of 30 m, which reduced to 5 m for tracking of a mobile node, making it a suitable method for approximate outdoor positioning and tracking of IoT devices without using Global Navigation Satellite Systems (GNSS)

Robust drone detection and classification from radio frequency signals using convolutional neural networks

As the number of unmanned aerial vehicles (UAVs) in the sky increases, safety issues have become more pressing. In this paper, we compare the performance of convolutional neural networks (CNNs) using first, 1D in-phase and quadrature (IQ) data and second, 2D spectrogram data for detection and classification of UAVs based on their radio frequency (RF) signals. We focus on the robustness of the models to low signal-to-noise ratios (SNRs), as this is the most relevant aspect for a real-world application. Within an input type, either IQ or spectrogram, we found no significant difference in performance between models, even as model complexity increased. In addition, we found an advantage in favor of the 2D spectrogram representation of the data. While there is basically no performance difference at SNRs ≥ 0 dB, we observed a 100% improvement in balanced accuracy at −12 dB, i.e. 0.842 on the spectrogram data compared to 0.413 on the IQ data for the VGG11 model. Together with an easy-to-use benchmark dataset, our findings can be used to develop better models for robust UAV detection systems

Triptycene-terminated thiolate and selenolate monolayers on Au(111)

To study the implications of highly space-demanding organic moieties on the properties of self-assembled monolayers (SAMs), triptycyl thiolates and selenolates with and without methylene spacers on Au(111) surfaces were comprehensively studied using ultra-high vacuum infrared reflection absorption spectroscopy, X-ray photoelectron spectroscopy, near-edge X-ray absorption fine structure spectroscopy and thermal desorption spectroscopy. Due to packing effects, the molecules in all monolayers are substantially tilted. In the presence of a methylene spacer the tilt is slightly less pronounced. The selenolate monolayers exhibit smaller defect densities and therefore are more densely packed than their thiolate analogues. The Se–Au binding energy in the investigated SAMs was found to be higher than the S–Au binding energy

Comparison of DVB-T Passive Radar Simulated and Measured Bistatic RCS Values for a Pilatus PC-12 Aircraft

Passive radar is a technology that has huge potential for airspace monitoring, taking advantage of existing transmissions. However, to predict whether particular targets can be measured in a particular scenario, it is necessary to be able to model the received signal. In this paper, we present the results of a campaign in which a Pilatus PC-12 single-engine aircraft was measured with a passive radar system relying on DVB-T transmission from a single transmitter. We then present our work to simulate the bistatic RCS of the aircraft along its flight track, using both the method of moments and the shooting and bouncing ray solvers, assess the uncertainty in the simulations, and compare against the measurements. We find that our simulated RCS values are useful in predicting whether or not detection occurs. However, we see poor agreement between simulated and measured RCS values where measurements are available, which we attribute primarily to the difficulties in extracting RCS measurements from the data and to unmodeled transmission and received path effects

Mobility of charge carriers in self-assembled monolayers

We present a new approach to study charge transport within 2D layers of organic semi-conductors (OSCs) using atomic force microscopy (AFM)-based lithography applied to self-assembled monolayers (SAMs), fabricated from appropriate organothiols. The extent of lateral charge transport was investigated by insulating pre-defined patches within OSC-based SAMs with regions of insulating SAM made from large band gap alkanethiolates. The new method is demonstrated using a phenyl-linked anthracenethiolate (PAT), 4-(anthracene-2-ylethynyl)benzyl thiolate. I-V characteristics of differently shaped PAT-islands were measured using the AFM tip as a top electrode. We were able to determine a relationship between island size and electrical conductivity, and from this dependence, we could obtain information on the lateral charge transport and charge carrier mobility within the thin OSC layers. Our study demonstrates that AFM nanografting of appropriately functionalized OSC molecules provides a suitable method to determine intrinsic mobilities of charge carriers in OSC thin films. In particular, this method is rather insensitive with regard to influence of grain boundaries and other defects, which hamper the application of conventional methods for the determination of mobilities in macroscopic samples. © 2019 Fu et al

Complete next-to-leading order gluino contributions to b--> s gamma and b--> s g

We present the first complete order alpha_s corrections to the Wilson coefficients (at the high scale) of the various versions of magnetic and chromomagnetic operators which are induced by a squark-gluino exchange. For this matching calculation, we work out the on-shell amplitudes b--> s gamma and b --> s g, both in the full and in the effective theory up to order alpha_s^2. The most difficult part of the calculation is the evaluation of the two-loop diagrams in the full theory; these can be split into two classes: a) diagrams with one gluino and a virtual gluon; b) diagrams with two gluinos or with one gluino and a four-squark vertex. Accordingly, the Wilson coefficients can be split into a part a) and a part b). While part b) of the Wilson coefficients is presented in this paper for the first time, part a) was given in (Bobeth et al.). We checked their results for the coefficients of the magnetic operators and found perfect agreement. Moreover, we work out the renormalization procedure in great detail. Our results for the complete next-to-leading order Wilson coefficients are fully analytic, but far too long to be printed. We therefore publish them in the form of a C++ program. They constitute a crucial building block for the phenomenological next-to-leading logarithmic analysis of the branching ratio Bbar --> X_s gamma in a supersymmetric model beyond minimal flavor violation.Comment: 38 pages, including c++ cod

Triptycene-terminated thiolate and selenolate monolayers on Au(111)

To study the implications of highly space-demanding organic moieties on the properties of self-assembled monolayers (SAMs), triptycyl thiolates and selenolates with and without methylene spacers on Au(111) surfaces were comprehensively studied using ultra-high vacuum infrared reflection absorption spectroscopy, X-ray photoelectron spectroscopy, near-edge X-ray absorption fine structure spectroscopy and thermal desorption spectroscopy. Due to packing effects, the molecules in all monolayers are substantially tilted. In the presence of a methylene spacer the tilt is slightly less pronounced. The selenolate monolayers exhibit smaller defect densities and therefore are more densely packed than their thiolate analogues. The Se–Au binding energy in the investigated SAMs was found to be higher than the S–Au binding energy

Deposition of Metal-Organic Frameworks by Liquid-Phase Epitaxy: The Influence of Substrate Functional Group Density on Film Orientation

The liquid phase epitaxy (LPE) of the metal-organic framework (MOF) HKUST-1 has been studied for three different COOH-terminated templating organic surfaces prepared by the adsorption of self-assembled monolayers (SAMs) on gold substrates. Three different SAMs were used, mercaptohexadecanoic acid (MHDA), 4’-carboxyterphenyl-4-methanethiol (TPMTA) and 9-carboxy-10-(mercaptomethyl)triptycene (CMMT). The XRD data demonstrate that highly oriented HKUST-1 SURMOFs with an orientation along the (100) direction was obtained on MHDA-SAMs. In the case of the TPMTA-SAM, the quality of the deposited SURMOF films was found to be substantially inferior. Surprisingly, for the CMMT-SAMs, a different growth direction was obtained; XRD data reveal the deposition of highly oriented HKUST-1 SURMOFs grown along the (111) direction