Simulation of images of CDMAM phantom and the estimation of measurement uncertainties of threshold gold thickness

2017 ◽  
Vol 39 ◽  
pp. 137-146 ◽  
Author(s):  
Alistair Mackenzie ◽  
Timothy D Eales ◽  
Hannah L Dunn ◽  
Mary Yip Braidley ◽  
David R. Dance ◽  
...  
2020 ◽  
Vol 9 (5) ◽  
pp. 305-312
Author(s):  
Ryan Cardman ◽  
Luís F. Gonçalves ◽  
Rachel E. Sapiro ◽  
Georg Raithel ◽  
David A. Anderson

AbstractWe present electric field measurements and imaging of a Yagi–Uda antenna near-field using a Rydberg atom–based radio frequency electric field measurement instrument. The instrument uses electromagnetically induced transparency with Rydberg states of cesium atoms in a room-temperature vapor and off-resonant RF-field–induced Rydberg-level shifts for optical SI-traceable measurements of RF electric fields over a wide amplitude and frequency range. The electric field along the antenna boresight is measured using the atomic probe at a spatial resolution of ${\lambda }_{RF}/2$ with electric field measurement uncertainties below 5.5%, an improvement to RF measurement uncertainties provided by existing antenna standards.


2020 ◽  
Vol 494 (4) ◽  
pp. 5293-5297
Author(s):  
Duncan A Forbes ◽  
Bililign T Dullo ◽  
Jonah Gannon ◽  
Warrick J Couch ◽  
Enrichetta Iodice ◽  
...  

ABSTRACT Using deep g, r, i imaging from the VST Early-type GAlaxy Survey (VEGAS), we have searched for ultradiffuse galaxies (UDGs) in the IC 1459 group. Assuming they are group members, we identify nine galaxies with physical sizes and surface brightnesses that match the UDG criteria within our measurement uncertainties. They have mean colours of g − i = 0.6 and stellar masses of ∼108 M⊙. Several galaxies appear to have associated systems of compact objects, e.g. globular clusters. Two UDGs contain a central bright nucleus, with a third UDG revealing a remarkable double nucleus. This appears to be the first reported detection of a double nucleus in a UDG – its origin is currently unclear.


2015 ◽  
Vol 8 (4) ◽  
pp. 1673-1684 ◽  
Author(s):  
G. E. Bodeker ◽  
S. Kremser

Abstract. The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).


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