Finite volume corrections to pi-pi scattering

Lattice QCD studies of hadron-hadron interactions are performed by computing the energy levels of the system in a finite box. The shifts in energy levels proportional to inverse powers of the volume are related to scattering parameters in a model independent way. In addition, there are non-universal exponentially suppressed corrections that distort this relation. These terms are proportional to exp(-m_pi L) and become relevant as the chiral limit is approached. In this paper we report on a one-loop chiral perturbation theory calculation of the leading exponential corrections in the case of I=2 pi-pi scattering near threshold.Comment: 17 pages, 2 figures, 1 table. Version published in PR

Policy gradients using variational quantum circuits

Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised and generative learning tasks. However, when applied to reinforcement learning, less is known. In this work, we considered a variational quantum circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a reinforcement learning agent. We show that an epsilon-approximation of the policy gradient can be obtained using a logarithmic number of samples concerning the total number of parameters. We empirically verify that such quantum models behave similarly to typical classical neural networks used in standard benchmarking environments and quantum control, using only a fraction of the parameters. Moreover, we study the barren plateau phenomenon in quantum policy gradients using the Fisher information matrix spectrum.Open access funding provided by FCT-FCCN (b-on). This work is financed by National Funds through the Portuguese funding agency, FCT - Fundacao para a Ciencia e a Tecnologia, within grants LA/P/0063/2020, UI/BD/152698/2022 and project IBEX, with reference PTDC/CCI-COM/4280/2021

Automatic allocation of safety requirements to components of a software product line

Safety critical systems developed as part of a product line must still comply with safety standards. Standards use the concept of Safety Integrity Levels (SILs) to drive the assignment of system safety requirements to components of a system under design. However, for a Software Product Line (SPL), the safety requirements that need to be allocated to a component may vary in different products. Variation in design can indeed change the possible hazards incurred in each product, their causes, and can alter the safety requirements placed on individual components in different SPL products. Establishing common SILs for components of a large scale SPL by considering all possible usage scenarios, is desirable for economies of scale, but it also poses challenges to the safety engineering process. In this paper, we propose a method for automatic allocation of SILs to components of a product line. The approach is applied to a Hybrid Braking System SPL design

Generalised quantum tree search

This extended abstract reports on on-going research on quantum algorithmic approaches to the problem of generalised tree search that may exhibit effective quantum speedup, even in the presence of non-constant branching factors. Two strategies are briefly summarised and current work outlined.This research is financed by the ERDF through the Opera tional Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT, within project POCI-01- 0145-FEDER-03094

Enhancement of optical absorption by modulation of the oxygen flow of TiO2 films deposited by reactive sputtering

Oxygen-deficient TiO2 films with enhanced visible and near-infrared optical absorption have been deposited by reactive sputtering using a planar diode radio frequency magnetron configuration. It is observed that the increase in the absorption coefficient is more effective when the O2 gas supply is periodically interrupted rather than by a decrease of the partial O2 gas pressure in the deposition plasma. The optical absorption coefficient at 1.5 eV increases from about 1 102 cm 1 to more than 4 103 cm 1 as a result of the gas flow discontinuity. A red-shift of 0.24 eV in the optical absorption edge is also observed. High resolution transmission electron microscopy with composition analysis shows that the films present a dense columnar morphology, with estimated mean column width of 40 nm. Moreover, the interruptions of the O2 gas flow do not produce detectable variations in the film composition along its growing direction. X-ray diffraction and micro-Raman experiments indicate the presence of the TiO2 anatase, rutile, and brookite phases. The anatase phase is dominant, with a slight increment of the rutile and brookite phases in films deposited under discontinued O2 gas flow. The increase of optical absorption in the visible and near-infrared regions has been attributed to a high density of defects in the TiO2 films, which is consistent with density functional theory calculations that place oxygen-related vacancy states in the upper third of the optical bandgap. The electronic structure calculation results, along with the adopted deposition method and experimental data, have been used to propose a mechanism to explain the formation of the observed oxygen-related defects in TiO2 thin films. The observed increase in sub-bandgap absorption and the modeling of the corresponding changes in the electronic structure are potentially useful concerning the optimization of efficiency of the photocatalytic activity and the magnetic doping of TiO2 films

Microstructure identification via detrended fluctuation analysis of ultrasound signals

We describe an algorithm for simulating ultrasound propagation in random one-dimensional media, mimicking different microstructures by choosing physical properties such as domain sizes and mass densities from probability distributions. By combining a detrended fluctuation analysis (DFA) of the simulated ultrasound signals with tools from the pattern-recognition literature, we build a Gaussian classifier which is able to associate each ultrasound signal with its corresponding microstructure with a very high success rate. Furthermore, we also show that DFA data can be used to train a multilayer perceptron which estimates numerical values of physical properties associated with distinct microstructures.Comment: Submitted to Phys. Rev.

The use of vasopressors during anaesthesia for caesarean section: a retrospective observational study

info:eu-repo/semantics/publishedVersio

Epidural top-up for caesarean section: a retrospective observational study

info:eu-repo/semantics/publishedVersio