An improvement of isochronous mass spectrometry: Velocity measurements using two time-of-flight detectors

Isochronous mass spectrometry (IMS) in storage rings is a powerful tool for mass measurements of exotic nuclei with very short half-lives down to several tens of microseconds, using a multicomponent secondary beam separated in-flight without cooling. However, the inevitable momentum spread of secondary ions limits the precision of nuclear masses determined by using IMS. Therefore, the momentum measurement in addition to the revolution period of stored ions is crucial to reduce the influence of the momentum spread on the standard deviation of the revolution period, which would lead to a much improved mass resolving power of IMS. One of the proposals to upgrade IMS is that the velocity of secondary ions could be directly measured by using two time-of-flight (double TOF) detectors installed in a straight section of a storage ring. In this paper, we outline the principle of IMS with double TOF detectors and the method to correct the momentum spread of stored ions.Comment: Accepted by Nuclear Inst. and Methods in Physics Research,

A Concept for an STJ-based Spectrograph

We describe a multi-order spectrograph concept suitable for 8m-class telescopes, using the intrinsic spectral resolution of Superconducting Tunneling Junction detectors to sort the spectral orders. The spectrograph works at low orders, 1-5 or 1-6, and provides spectral coverage with a resolving power of R~8000 from the atmospheric cutoff at 320 nm to the long wavelength end of the infrared H or K band at 1800 nm or 2400 nm. We calculate that the spectrograph would provide substantial throughput and wavelength coverage, together with high time resolution and sufficient dynamic range. The concept uses currently available technology, or technologies with short development horizons, restricting the spatial sampling to two linear arrays; however an upgrade path to provide more spatial sampling is identified. All of the other challenging aspects of the concept - the cryogenics, thermal baffling and magnetic field biasing - are identified as being feasible.Comment: Accepted in Monthly Notices of the Royal Astronomical Society, 12 pages with 10 figure

Distantly Labeling Data for Large Scale Cross-Document Coreference

Cross-document coreference, the problem of resolving entity mentions across multi-document collections, is crucial to automated knowledge base construction and data mining tasks. However, the scarcity of large labeled data sets has hindered supervised machine learning research for this task. In this paper we develop and demonstrate an approach based on ``distantly-labeling'' a data set from which we can train a discriminative cross-document coreference model. In particular we build a dataset of more than a million people mentions extracted from 3.5 years of New York Times articles, leverage Wikipedia for distant labeling with a generative model (and measure the reliability of such labeling); then we train and evaluate a conditional random field coreference model that has factors on cross-document entities as well as mention-pairs. This coreference model obtains high accuracy in resolving mentions and entities that are not present in the training data, indicating applicability to non-Wikipedia data. Given the large amount of data, our work is also an exercise demonstrating the scalability of our approach.Comment: 16 pages, submitted to ECML 201