Formation of Compressed Flat Electron Beams with High Transverse-Emittance Ratios

Flat beams -- beams with asymmetric transverse emittances -- have important applications in novel light-source concepts, advanced-acceleration schemes and could possibly alleviate the need for damping rings in lepton colliders. Over the last decade, a flat-beam-generation technique based on the conversion of an angular-momentum-dominated beam was proposed and experimentally tested. In this paper we explore the production of compressed flat beams. We especially investigate and optimize the flat-beam transformation for beams with substantial fractional energy spread. We use as a simulation example the photoinjector of the Fermilab's Advanced Superconducting Test Accelerator (ASTA). The optimizations of the flat beam generation and compression at ASTA were done via start-to-end numerical simulations for bunch charges of 3.2 nC, 1.0 nC and 20 pC at ~37 MeV. The optimized emittances of flat beams with different bunch charges were found to be 0.25 {\mu}m (emittance ratio is ~400), 0.13 {\mu}m, 15 nm before compression, and 0.41 {\mu}m, 0.20 {\mu}m, 16 nm after full compression, respectively with peak currents as high as 5.5 kA for a 3.2-nC flat beam. These parameters are consistent with requirements needed to excite wakefields in asymmetric dielectric-lined waveguides or produce significant photon flux using small-gap micro-undulators.Comment: 17

Exploratory Analysis of Highly Heterogeneous Document Collections

We present an effective multifaceted system for exploratory analysis of highly heterogeneous document collections. Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework. Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing. As one of our key tagging strategies, we introduce the KERA algorithm (Keyword Extraction for Reports and Articles). KERA extracts topic-representative terms from individual documents in a purely unsupervised fashion and is revealed to be significantly more effective than state-of-the-art methods. Finally, we evaluate our system in its ability to help users locate documents pertaining to military critical technologies buried deep in a large heterogeneous sea of information.Comment: 9 pages; KDD 2013: 19th ACM SIGKDD Conference on Knowledge Discovery and Data Minin

Amp\`ere-Class Pulsed Field Emission from Carbon-Nanotube Cathodes in a Radiofrequency Resonator

Pulsed field emission from cold carbon-nanotube cathodes placed in a radiofrequency resonant cavity was observed. The cathodes were located on the backplate of a conventional $1+\frac{1}{2}$-cell resonant cavity operating at 1.3-GHz and resulted in the production of bunch train with maximum average current close to 0.7 Amp\`ere. The measured Fowler-Nordheim characteristic, transverse emittance, and pulse duration are presented and, when possible, compared to numerical simulations. The implications of our results to high-average-current electron sources are briefly discussed.Comment: 5 pages, 6 figures; submitted to Applied Physics Letter

Detecting Singleton Review Spammers Using Semantic Similarity

Online reviews have increasingly become a very important resource for consumers when making purchases. Though it is becoming more and more difficult for people to make well-informed buying decisions without being deceived by fake reviews. Prior works on the opinion spam problem mostly considered classifying fake reviews using behavioral user patterns. They focused on prolific users who write more than a couple of reviews, discarding one-time reviewers. The number of singleton reviewers however is expected to be high for many review websites. While behavioral patterns are effective when dealing with elite users, for one-time reviewers, the review text needs to be exploited. In this paper we tackle the problem of detecting fake reviews written by the same person using multiple names, posting each review under a different name. We propose two methods to detect similar reviews and show the results generally outperform the vectorial similarity measures used in prior works. The first method extends the semantic similarity between words to the reviews level. The second method is based on topic modeling and exploits the similarity of the reviews topic distributions using two models: bag-of-words and bag-of-opinion-phrases. The experiments were conducted on reviews from three different datasets: Yelp (57K reviews), Trustpilot (9K reviews) and Ott dataset (800 reviews).Comment: 6 pages, WWW 201

Automatic Restoration of Diacritics for Igbo Language

Igbo is a low-resource African language with orthographic and tonal diacritics, which capture distinctions between words that are important for both meaning and pronunciation, and hence of potential value for a range of language processing tasks. Such diacritics, however, are often largely absent from the electronic texts we might want to process, or assemble into corpora, and so the need arises for effective methods for automatic diacritic restoration for Igbo. In this paper, we experiment using an Igbo bible corpus, which is extensively marked for vowel distinctions, and partially for tonal distinctions, and attempt the task of reinstating these diacritics when they have been deleted. We investigate a number of word-level diacritic restoration methods, based on n-grams, under a closed-world assumption, achieving an accuracy of 98.83 % with our most effective method

Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling

This paper presents a Kernel Entity Salience Model (KESM) that improves text understanding and retrieval by better estimating entity salience (importance) in documents. KESM represents entities by knowledge enriched distributed representations, models the interactions between entities and words by kernels, and combines the kernel scores to estimate entity salience. The whole model is learned end-to-end using entity salience labels. The salience model also improves ad hoc search accuracy, providing effective ranking features by modeling the salience of query entities in candidate documents. Our experiments on two entity salience corpora and two TREC ad hoc search datasets demonstrate the effectiveness of KESM over frequency-based and feature-based methods. We also provide examples showing how KESM conveys its text understanding ability learned from entity salience to search

OpenEssayist: a supply and demand learning analytics tool for drafting academic essays

This paper focuses on the use of a natural language analytics engine to provide feedback to students when preparing an essay for summative assessment. OpenEssayist is a real-time learning analytics tool, which operates through the combination of a linguistic analysis engine that processes the text in the essay, and a web application that uses the output of the linguistic analysis engine to generate the feedback. We outline the system itself and present analysis of observed patterns of activity as a cohort of students engaged with the system for their module assignments. We report a significant positive correlation between the number of drafts submitted to the system and the grades awarded for the first assignment. We can also report that this cohort of students gained significantly higher overall grades than the students in the previous cohort, who had no access to OpenEssayist. As a system that is content free, OpenEssayist can be used to support students working in any domain that requires the writing of essays

Three-Dimensional Analysis of Wakefields Generated by Flat Electron Beams in Planar Dielectric-Loaded Structures

An electron bunch passing through dielectric-lined waveguide generates $\check{C}$erenkov radiation that can result in high-peak axial electric field suitable for acceleration of a subsequent bunch. Axial field beyond Gigavolt-per-meter are attainable in structures with sub-mm sizes depending on the achievement of suitable electron bunch parameters. A promising configuration consists of using planar dielectric structure driven by flat electron bunches. In this paper we present a three-dimensional analysis of wakefields produced by flat beams in planar dielectric structures thereby extending the work of Reference [A. Tremaine, J. Rosenzweig, and P. Schoessow, Phys. Rev. E 56, No. 6, 7204 (1997)] on the topic. We especially provide closed-form expressions for the normal frequencies and field amplitudes of the excited modes and benchmark these analytical results with finite-difference time-domain particle-in-cell numerical simulations. Finally, we implement a semi-analytical algorithm into a popular particle tracking program thereby enabling start-to-end high-fidelity modeling of linear accelerators based on dielectric-lined planar waveguides.Comment: 12 pages, 2 tables, 10 figure

Diffraction effects in coherent transition radiation diagnostics for sub-mm bunch length measurement

Electrons crossing the boundary between different media generate bursts of transition radiation. In the case of bunches of N electrons, the radiation is coherent and has an N-squared enhancement at wavelengths related to the longitudinal bunch distribution. This coherent transition radiation has therefore attracted attention as an interceptive charged particle beam diagnostic technique. Many analytical descriptions have been devised describing the spectral distribution generated by electron bunches colliding with thin metallic foils making different simplifying assumptions. For typical bunches having lengths in the sub-millimeter range, measurable spectra are generated up into the millimeter range. Analysis of this THz radiation is performed using optical equipment tens of millimeters in size. This gives rise to concern that optical diffraction effects may spread the wavefront of interest into regions larger than the optical elements and partially escape detection, generating a wavelength-dependent instrument response. In this paper we present a model implementing vector diffraction theory to analyze these effects in bunch length diagnostics based on coherent transition radiation