5,084 research outputs found
Solar Neutrino Results from the Sudbury Neutrino Observatory
We describe here the measurement of the flux of neutrinos created by the
decay of solar ^8B by the Sudbury Neutrino Observatory (SNO). The neutrinos
were detected via the charged current (CC) reaction on deuterium and by the
elastic scattering (ES) of electrons. The CC reaction is sensitive exclusively
to 's, while the ES reaction also has a small sensitivity to
's and 's.
The flux of 's from ^8B decay measured by the CC reaction rate is
. Assuming no flavor transformation, the flux
inferred from the ES reaction rate is .
Comparison of to the Super-Kamiokande Collaboration's
precision value of yields a difference, assuming
the systematic uncertainties are normally distributed, providing evidence that
there is a non-electron flavor active neutrino component in the solar flux. The
total flux of active ^8B neutrinos is thus determined to be , in close agreement with the predictions of solar
models.Comment: Talk given at the XX International Symposium on Lepton and Photon
Interactions at High Energie
Towards precision distances and 3D dust maps using broadband Period--Magnitude relations of RR Lyrae stars
We determine the period-magnitude relations of RR Lyrae stars in 13
photometric bandpasses from 0.4 to 12 {\mu}m using timeseries observations of
134 stars. The Bayesian formalism, extended from our previous work to include
the effects of line-of-sight dust extinction, allows for the simultaneous
inference of the posterior distribution of the mean absolute magnitude, slope
of the period-magnitude power-law, and intrinsic scatter about a perfect
power-law for each bandpass. In addition, the distance modulus and
line-of-sight dust extinction to each RR Lyrae star in the calibration sample
is determined, yielding a sample median fractional distance error of 0.66%. The
intrinsic scatter in all bands appears to be larger than the photometric
errors, except in WISE W1 (3.4 {\mu}m) and W2 (4.6 {\mu}m) where the
photometric error ( mag) is to be comparable or larger
than the intrinsic scatter. Additional observations at these wavelengths could
improve the inferred distances to these sources further. As an application of
the methodology, we infer the distance to the RRc-type star RZCep at low
Galactic latitude () to be mag
( pc) with colour excess mag. This
distance, equivalent to a parallax of microarcsec, is consistent
with the published HST parallax measurement but with an uncertainty that is 13
times smaller than the HST measurement. If our measurements (and methodology)
hold up to scrutiny, the distances to these stars have been determined to an
accuracy comparable to those expected with Gaia. As RR Lyrae are one of the
primary components of the cosmic distance ladder, the achievement of sub-1%
distance errors within a formalism that accounts for dust extinction may be
considered a strong buttressing of the path to eventual 1% uncertainties in
Hubble's constant.Comment: 21 pages, 29 figures, 2 tables, abstract abridged for arXiv. Comments
solicited on referee report (received June 9, 2014) linked:
https://gist.github.com/profjsb/c6c4e2f3a20ea02f1762 . Public archive of code
used to generate results and figures:
https://github.com/ckleinastro/period_luminosity_relation_fittin
Prototype Detector for Ultrahigh Energy Neutrino Detection
Necessary technical experience is being gained from successful construction
and deployment of current prototype detectors to search for UHE neutrinos in
Antarctica, Lake Baikal in Russia, and the Mediterranean. The prototype
detectors have also the important central purpose of determining whether or not
UHE neutrinos do in fact exist in nature by observation of at least a few UHE
neutrino-induced leptons with properties that are not consistent with expected
backgrounds. We discuss here the criteria for a prototype detector to
accomplish that purpose in a convincing way even if the UHE neutrino flux is
substantially lower than predicted at present.Comment: 18 pages, 8 figures, submitted to Astroparticle Physic
Nucleus: A Pilot Project
Early in 2016, an environmental scan was conducted by the Research Library
Data Working Group for three purposes:
1.) Perform a survey of the data management landscape at Los Alamos National
Laboratory in order to identify local gaps in data management services.
2.) Conduct an environmental scan of external institutions to benchmark
budgets, infrastructure, and personnel dedicated to data management.
3.) Draft a research data infrastructure model that aligns with the current
workflow and classification restrictions at Los Alamos National Laboratory.
This report is a summary of those activities and the draft for a pilot data
management project.Comment: 13 pages, repor
Electoral Recall in Washington State and California: California Needs Stricter Standards to Protect Elected Officials from Harassment
This article highlights the weaknesses of the electoral recall mechanisms in California and the way in which the Washington recall process has avoided such weaknesses. Part II provides general background information on the development of recall mechanisms. Part III explores how the United States Supreme Court has ruled on recall attempts and the specific guidance the Court has provided for states in developing adequately protective recall processes. Part IV analyzes the strengths and weaknesses of the California recall provisions by examining the recall-related opinions of California courts and the complexities of Governor Davis\u27s recall. Part V provides a solution to the California dilemma by exploring an alternative form of recall established in Washington, examines both the constitutional and statutory provisions of Washington\u27s recall mechanism, and analyzes Washington courts\u27 interpretation of these provisions. After comparing the two recall regimes, Part V argues that the Washington mechanism is superior to California\u27s process. Finally, Part VI urges California legislators to promote the true purposes of recall by ensuring government accountability and public participation while minimizing the risks of hindering the government functioning that such harassment of elected officials tends to elicit
Algorithms for integrated analysis of glycomics and glycoproteomics by LC-MS/MS
The glycoproteome is an intricate and diverse component of a cell, and it plays a key role in the definition of the interface between that cell and the rest of its world. Methods for studying the glycoproteome have been developed for released glycan glycomics and site-localized bottom-up glycoproteomics using liquid chromatography-coupled mass spectrometry and tandem mass spectrometry (LC-MS/MS), which is itself a complex problem.
Algorithms for interpreting these data are necessary to be able to extract biologically meaningful information in a high throughput, automated context. Several existing solutions have been proposed but may be found lacking for larger glycopeptides, for complex samples, different experimental conditions, different instrument vendors, or even because they simply ignore fundamentals of glycobiology. I present a series of open algorithms that approach the problem from an instrument vendor neutral, cross-platform fashion to address these challenges, and integrate key concepts from the underlying biochemical context into the interpretation process.
In this work, I created a suite of deisotoping and charge state deconvolution algorithms for processing raw mass spectra at an LC scale from a variety of instrument types. These tools performed better than previously published algorithms by enforcing the underlying chemical model more strictly, while maintaining a higher degree of signal fidelity. From this summarized, vendor-normalized data, I composed a set of algorithms for interpreting glycan profiling experiments that can be used to quantify glycan expression. From this I constructed a graphical method to model the active biosynthetic pathways of the sample glycome and dig deeper into those signals than would be possible from the raw data alone. Lastly, I created a glycopeptide database search engine from these components which is capable of identifying the widest array of glycosylation types available, and demonstrate a learning algorithm which can be used to tune the model to better understand the process of glycopeptide fragmentation under specific experimental conditions to outperform a simpler model by between 10% and 15%. This approach can be further augmented with sample-wide or site-specific glycome models to increase depth-of-coverage for glycoforms consistent with prior beliefs
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