High-resolution detection system for time-of-flight electron spectrometry

One of the key components of a time-of-flight (TOF) spectrometer is the detection system. In addition to high timing resolution, accurate two-dimensional imaging substantially broadensthe areas of applications of TOF spectrometers; for example, add a new dimension to angle-resolved photoemission spectroscopy (ARPES). In this paper we report on the recent developments of a high spatial (<50 mm) and timing (<130 ps) resolution imaging system capable of selective detection of electrons, ions and/or photons. Relative to our previously reported results, we have substantially improved the counting rate capabilities of the system especially for cases where the energy range of interest represents a small fraction of the incoming flux at the detector plane. The new system ignores all the events outside of a tunable time window substantially decreasing the dead time required for the event processing. That allows high-resolution TOF measurements within a given energy or momentum range and also can be used for distinguishing (or disabling) detection of photons versus detection of charged particles. The counting rate within a given energy window can be as high as ~;;400KHz at 10percent dead time. The electron detection system reported in the paper was developed for the TOF ARPES experiments at the Advanced Light Source, Lawrence Berkeley National Laboratory

Entropy and Quantum Kolmogorov Complexity: A Quantum Brudno's Theorem

In classical information theory, entropy rate and Kolmogorov complexity per symbol are related by a theorem of Brudno. In this paper, we prove a quantum version of this theorem, connecting the von Neumann entropy rate and two notions of quantum Kolmogorov complexity, both based on the shortest qubit descriptions of qubit strings that, run by a universal quantum Turing machine, reproduce them as outputs.Comment: 26 pages, no figures. Reference to publication added: published in the Communications in Mathematical Physics (http://www.springerlink.com/content/1432-0916/

Reduced right ventricular function on cardiovascular magnetic resonance imaging is associated with uteroplacental impairment in tetralogy of Fallot

BACKGROUND: Maternal right ventricular (RV) dysfunction (measured by echocardiography) is associated with impaired uteroplacental circulation, however echocardiography has important limitations in the assessment of RV function. We therefore aimed to investigate the association of pre-pregnancy RV and left ventricular (LV) function measured by cardiovascular magnetic resonance with uteroplacental Doppler flow parameters in pregnant women with repaired Tetralogy of Fallot (ToF). METHODS: Women with repaired ToF were examined, who had been enrolled in a prospective multicenter study of pregnant women with congenital heart disease. Clinical data and CMR evaluation before pregnancy were compared with uteroplacental Doppler parameters at 20 and 32 weeks gestation. In particular, pulsatility index (PI) of uterine and umbilical artery were studied. RESULTS: We studied 31 women; mean age 30 years, operated at early age. Univariable analyses showed that reduced RV ejection fraction (RVEF; P = 0.037 and P = 0.001), higher RV end-systolic volume (P = 0.004) and higher LV end-diastolic and end-systolic volume (P = 0.001 and P = 0.003, respectively) were associated with higher uterine or umbilical artery PI. With multivariable analyses (corrected for maternal age and body mass index), reduced RVEF before pregnancy remained associated with higher umbilical artery PI at 32 weeks (P = 0.002). RVEF was lower in women with high PI compared to women with normal PI during pregnancy (44% vs. 53%, p = 0.022). LV ejection fraction was not associated with uterine or umbilical artery PI. CONCLUSIONS: Reduced RV function before pregn

Online change detection in exponential families with unknown parameters

International audienceThis paper studies online change detection in exponential families when both the parameters before and after change are unknown. We follow a standard statistical approach to sequential change detection with generalized likelihood ratio test statistics. We interpret these statistics within the framework of information geometry, hence providing a unified view of change detection for many common statistical models and corresponding distance functions. Using results from convex duality, we also derive an efficient scheme to compute the exact statistics sequentially, which allows their use in online settings where they are usually approximated for the sake of tractability. This is applied to real-world datasets of various natures, including onset detection in audio signals