Measuring precise radial velocities and cross-correlation function line-profile variations using a Skew Normal density

Context. Stellar activity is one of the primary limitations to the detection of low-mass exoplanets using the radial-velocity (RV) technique. Stellar activity can be probed by measuring time-dependent variations in the shape of the cross-correlation function (CCF). It is therefore critical to measure with high-precision these shape variations to decorrelate the signal of an exoplanet from spurious RV signals caused by stellar activity. Aims. We propose to estimate the variations in shape of the CCF by fitting a Skew Normal (SN) density which, unlike the commonly employed Normal density, includes a Skewness parameter to capture the asymmetry of the CCF induced by stellar activity and the convective blueshift. Methods. We compared the performances of the proposed method to the commonly employed Normal density using both simulations and real observations with different levels of activity and signal-to-noise ratios. Results. When considering real observations, the correlation between the RV and the asymmetry of the CCF and between the RV and the width of the CCF are stronger when using the parameters estimated with the SN density rather than those obtained with the commonly employed Normal density. In particular, the strongest correlations have been obtained when using the mean of the SN as an estimate for the RV. This suggests that the CCF parameters estimated using a SN density are more sensitive to stellar activity, which can be helpful when estimating stellar rotational periods and when characterizing stellar activity signals. Using the proposed SN approach, the uncertainties estimated on the RV defined as the median of the SN are on average 10% smaller than the uncertainties calculated on the mean of the Normal. The uncertainties estimated on the asymmetry parameter of the SN are on average 15% smaller than the uncertainties measured on the Bisector Inverse Slope Span (BIS SPAN), which is the commonly used parameter to evaluate the asymmetry of the CCF. We also propose a new model to account for stellar activity when fitting a planetary signal to RV data. Based on simple simulations, we were able to demonstrate that this new model improves the planetary detection limits by 12% compared to the model commonly used to account for stellar activity. Conclusions. The SN density is a better model than the Normal density for characterizing the CCF since the correlations used to probe stellar activity are stronger and the uncertainties of the RV estimate and the asymmetry of the CCF are both smaller.Peer reviewe

Machine learning accelerated likelihood-free event reconstruction in dark matter direct detection

Reconstructing the position of an interaction for any dual-phase time projection chamber (TPC) with the best precision is key to directly detecting Dark Matter. Using the likelihood-free framework, a newalgorithm to reconstruct the 2-D (x; y) position and the size of the charge signal (e) of an interaction is presented. The algorithm uses the secondary scintillation light distribution (S2) obtained by simulating events using a waveform generator. To deal with the computational effort required by the likelihood-free approach, we employ the Bayesian Optimization for LikelihoodFree Inference (BOLFI) algorithm. Together with BOLFI, prior distributions for the parameters of interest (x; y; e) and highly informative discrepancy measures to performthe analyses are introduced. We evaluate the quality of the proposed algorithm by a comparison against the currently existing alternative methods using a large-scale simulation study. BOLFI provides a natural probabilistic uncertainty measure for the reconstruction and it improved the accuracy of the reconstruction over the next best algorithm by up to 15% when focusing on events at large radii (R > 30 cm, the outer 37% of the detector). In addition, BOLFI provides the smallest uncertainties among all the tested methods.Peer reviewe

Adaptive Approximate Bayesian Computation Tolerance Selection

Approximate Bayesian Computation (ABC) methods are increasingly used for inference in situations in which the likelihood function is either computationally costly or intractable to evaluate. Extensions of the basic ABC rejection algorithm have improved the computational efficiency of the procedure and broadened its applicability. The ABC - Population Monte Carlo (ABC-PMC) approach has become a popular choice for approximate sampling from the posterior. ABC-PMC is a sequential sampler with an iteratively decreasing value of the tolerance, which specifies how close the simulated data need to be to the real data for acceptance. We propose a method for adaptively selecting a sequence of tolerances that improves the computational efficiency of the algorithm over other common techniques. In addition we define a stopping rule as a by-product of the adaptation procedure, which assists in automating termination of sampling. The proposed automatic ABC-PMC algorithm can be easily implemented and we present several examples demonstrating its benefits in terms of computational efficiency.Peer reviewe

Accounting for stellar activity signals in radial-velocity data by using change point detection techniques star

Context. Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for addressing stellar activity is to assume a linear relationship between the RV observations and the activity indicators along the entire time series, and then remove the estimated contribution of activity from the variation in RV data (overall correction method). However, since active regions evolve on the photosphere over time, correlations between the RV observations and the activity indicators will correspondingly be anisotropic. Aims. We present an approach that recognizes the RV locations where the correlations between the RV and the activity indicators significantly change in order to better account for variations in RV caused by stellar activity. Methods. The proposed approach uses a general family of statistical breakpoint methods, often referred to as change point detection (CPD) algorithms; several implementations of which are available in R and python. A thorough comparison is made between the breakpoint-based approach and the overall correction method. To ensure wide representativity, we use measurements from real stars that have different levels of stellar activity and whose spectra have different signal-to-noise ratios. Results. When the corrections for stellar activity are applied separately to each temporal segment identified by the breakpoint method, the corresponding residuals in the RV time series are typically much smaller than those obtained by the overall correction method. Consequently, the generalized Lomb-Scargle periodogram contains a smaller number of peaks caused by active regions. The CPD algorithm is particularly effective when focusing on active stars with long time series, such as alpha Cen B. In that case, we demonstrate that the breakpoint method improves the detection limit of exoplanets by 74% on average with respect to the overall correction method. Conclusions. CPD algorithms provide a useful statistical framework for estimating the presence of change points in a time series. Since the process underlying the RV measurements generates anisotropic data by its intrinsic properties, it is natural to use CPD to obtain cleaner signals from RV data. We anticipate that the improved exoplanet detection limit may lead to a widespread adoption of such an approach. Our test on the HD 192310 planetary system is encouraging, as we confirm the presence of the two hosted exoplanets and we determine orbital parameters consistent with the literature, also providing much more precise estimates for HD 192310 c.Peer reviewe

Accounting for stellar activity signals in radial-velocity data by using change point detection techniques star

Context. Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for addressing stellar activity is to assume a linear relationship between the RV observations and the activity indicators along the entire time series, and then remove the estimated contribution of activity from the variation in RV data (overall correction method). However, since active regions evolve on the photosphere over time, correlations between the RV observations and the activity indicators will correspondingly be anisotropic. Aims. We present an approach that recognizes the RV locations where the correlations between the RV and the activity indicators significantly change in order to better account for variations in RV caused by stellar activity. Methods. The proposed approach uses a general family of statistical breakpoint methods, often referred to as change point detection (CPD) algorithms; several implementations of which are available in R and python. A thorough comparison is made between the breakpoint-based approach and the overall correction method. To ensure wide representativity, we use measurements from real stars that have different levels of stellar activity and whose spectra have different signal-to-noise ratios. Results. When the corrections for stellar activity are applied separately to each temporal segment identified by the breakpoint method, the corresponding residuals in the RV time series are typically much smaller than those obtained by the overall correction method. Consequently, the generalized Lomb-Scargle periodogram contains a smaller number of peaks caused by active regions. The CPD algorithm is particularly effective when focusing on active stars with long time series, such as alpha Cen B. In that case, we demonstrate that the breakpoint method improves the detection limit of exoplanets by 74% on average with respect to the overall correction method. Conclusions. CPD algorithms provide a useful statistical framework for estimating the presence of change points in a time series. Since the process underlying the RV measurements generates anisotropic data by its intrinsic properties, it is natural to use CPD to obtain cleaner signals from RV data. We anticipate that the improved exoplanet detection limit may lead to a widespread adoption of such an approach. Our test on the HD 192310 planetary system is encouraging, as we confirm the presence of the two hosted exoplanets and we determine orbital parameters consistent with the literature, also providing much more precise estimates for HD 192310 c.Peer reviewe

Exact solution of the Zeeman effect in single-electron systems

Contrary to popular belief, the Zeeman effect can be treated exactly in single-electron systems, for arbitrary magnetic field strengths, as long as the term quadratic in the magnetic field can be ignored. These formulas were actually derived already around 1927 by Darwin, using the classical picture of angular momentum, and presented in their proper quantum-mechanical form in 1933 by Bethe, although without any proof. The expressions have since been more or less lost from the literature; instead, the conventional treatment nowadays is to present only the approximations for weak and strong fields, respectively. However, in fusion research and other plasma physics applications, the magnetic fields applied to control the shape and position of the plasma span the entire region from weak to strong fields, and there is a need for a unified treatment. In this paper we present the detailed quantum-mechanical derivation of the exact eigenenergies and eigenstates of hydrogen-like atoms and ions in a static magnetic field. Notably, these formulas are not much more complicated than the better-known approximations. Moreover, the derivation allows the value of the electron spin gyromagnetic ratio $g_s$ to be different from 2. For completeness, we then review the details of dipole transitions between two hydrogenic levels, and calculate the corresponding Zeeman spectrum. The various approximations made in the derivation are also discussed in details.Comment: 18 pages, 4 figures. Submitted to Physica Script

When assessment defines the content—understanding goals in between teachers and policy

© 2020 The Authors. The Curriculum Journal published by John Wiley & Sons Ltd on behalf of British Educational Research Association.Education policy development internationally reflect a widespread expansion of learning outcome orientation in policy, curricula and assessment. In this paper, teachers’ perceptions about their work are explored, as goals and assessment play a more prominent role driven by the introduction of a learning outcomes‐oriented system. This is investigated through interviews of Norwegian teachers and extensive policy analysis of Norwegian policy documents. The findings indicate that the teachers are finding ways to negotiate and adjust to the language in the policies investigated in this study. Furthermore, the findings show that the teachers have developed their professional language according to the policies. The teachers referred to their self‐made criteria and goal sheets as central tools in explicating what is to be learned. In many ways, the tools for assessment, thus determine the content of education as well as what is valued in the educational system.publishedVersio

Pathophysiology of L-dopa-induced motor and non-motor complications in Parkinson's disease

Involuntary movements, or dyskinesia, represent a debilitating complication of levodopa (L-dopa) therapy for Parkinson's disease (PD). L-dopa-induced dyskinesia (LID) are ultimately experienced by the vast majority of patients. In addition, psychiatric conditions often manifested as compulsive behaviours, are emerging as a serious problem in the management of L-dopa therapy. The present review attempts to provide an overview of our current understanding of dyskinesia and other L-dopa-induced dysfunctions, a field that dramatically evolved in the past twenty years. In view of the extensive literature on LID, there appeared a critical need to re-frame the concepts, to highlight the most suitable models, to review the central nervous system (CNS) circuitry that may be involved, and to propose a pathophysiological framework was timely and necessary. An updated review to clarify our understanding of LID and other L-dopa-related side effects was therefore timely and necessary. This review should help in the development of novel therapeutic strategies aimed at preventing the generation of dyskinetic symptoms

Deregulation, Privatisation and Marketisation of Nordic Comprehensive Education : Social Changes Reflected in Schooling

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Becoming a special educator – Finnish and Swedish students' views of their future profession

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