Propagation of a Gaussian Wigner Function Through a Matrix-Aperture Beamline

A Gaussian Wigner function may be defined in terms of its covariance matrix and centroid. In the framework of statistical optics, a Wigner function represents partially coherent radiation. A Gaussian Wigner function is an equivalent representation to the more commonly used Gaussian Schell model cross spectral density. Starting from the relationship between Gaussian Wigner functions and the Gaussian Schell model, we derive coherence properties of the Gaussian Wigner function including coherence length and degree of coherence. We define a simplified beamline called a matrix-aperture beamline composed of linear transport sections separated by physical apertures. This is an idealized form for a transport beamline in a synchrotron light source or X-ray free electron laser. An envelope model provides a basic foundation to understand the optics of a given beamline in an analogous manner with which linear optics are treated in particle beam dynamics, with corresponding definitions of emittance and Twiss parameters. One major challenge to such an envelope model lies in the hard edge apertures which break the Gaussian condition raising the question as to the adequacy of a Gaussian model. We present a consistent way to construct a Gaussian approximation of the far-field Wigner function following the hard edge aperture. To this end, we introduce the concept of a Gaussian aperture and analyze its effects on the radiation Wigner function. A software implementation of this model is described

Optimization of Magnetized Electron Cooling with JSPEC

The Electron-Ion-Collider (EIC) will be a next-generation facility located at Brookhaven National Laboratory (BNL), built with the goal of accelerating heavy ions up to 275 GeV. To prevent ion beam size growth during the acceleration phase, cooling techniques will be required to keep the beam size from growing due to intra-beam scattering. The JSPEC (JLab Simulation Package for Electron Cooling) $\texttt{C++}$ package is a tool designed to numerically model magnetized and unmagnetized cooling through friction forces between co-propagating electron and ion bunches. Here we describe a feature that has been added to the JSPEC package, which implements a Nelder-Mead Simplex optimization algorithm to allow a user to optimize certain beam parameters in order to achieve a target cooling time

Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages

Pre-trained speech representations like wav2vec 2.0 are a powerful tool for automatic speech recognition (ASR). Yet many endangered languages lack sufficient data for pre-training such models, or are predominantly oral vernaculars without a standardised writing system, precluding fine-tuning. Query-by-example spoken term detection (QbE-STD) offers an alternative for iteratively indexing untranscribed speech corpora by locating spoken query terms. Using data from 7 Australian Aboriginal languages and a regional variety of Dutch, all of which are endangered or vulnerable, we show that QbE-STD can be improved by leveraging representations developed for ASR (wav2vec 2.0: the English monolingual model and XLSR53 multilingual model). Surprisingly, the English model outperformed the multilingual model on 4 Australian language datasets, raising questions around how to optimally leverage self-supervised speech representations for QbE-STD. Nevertheless, we find that wav2vec 2.0 representations (either English or XLSR53) offer large improvements (56-86% relative) over state-of-the-art approaches on our endangered language datasets

Making sense of trifles : data narratives and cumulative data disclosure

The law does not concern itself with trifles. If a risk is deemed minimal, or an infraction negligible, invoking the authority of the law often seems unnecessary. However, there are increasingly fields of human activity where this principle leads to gaps in the protection neces- sary for a flourishing society. This paper reports findings and ideas from a research project in cumulative data disclosure, where an aggregation of in themselves harmless data points can expose the users of social media to significant personal risk