3,520 research outputs found
Low Energy Electron and Nuclear Recoil Thresholds in the DRIFT-II Negative Ion TPC for Dark Matter Searches
Understanding the ability to measure and discriminate particle events at the
lowest possible energy is an essential requirement in developing new
experiments to search for weakly interacting massive particle (WIMP) dark
matter. In this paper we detail an assessment of the potential sensitivity
below 10 keV in the 1 m^3 DRIFT-II directionally sensitive, low pressure,
negative ion time projection chamber (NITPC), based on event-by-event track
reconstruction and calorimetry in the multiwire proportional chamber (MWPC)
readout. By application of a digital smoothing polynomial it is shown that the
detector is sensitive to sulfur and carbon recoils down to 2.9 and 1.9 keV
respectively, and 1.2 keV for electron induced events. The energy sensitivity
is demonstrated through the 5.9 keV gamma spectrum of 55Fe, where the energy
resolution is sufficient to identify the escape peak. The effect a lower energy
sensitivity on the WIMP exclusion limit is demonstrated. In addition to recoil
direction reconstruction for WIMP searches this sensitivity suggests new
prospects for applications also in KK axion searches
A flexible and accurate total variation and cascaded denoisers-based image reconstruction algorithm for hyperspectrally compressed ultrafast photography
Hyperspectrally compressed ultrafast photography (HCUP) based on compressed
sensing and the time- and spectrum-to-space mappings can simultaneously realize
the temporal and spectral imaging of non-repeatable or difficult-to-repeat
transient events passively in a single exposure. It possesses an incredibly
high frame rate of tens of trillions of frames per second and a sequence depth
of several hundred, and plays a revolutionary role in single-shot ultrafast
optical imaging. However, due to the ultra-high data compression ratio induced
by the extremely large sequence depth as well as the limited fidelities of
traditional reconstruction algorithms over the reconstruction process, HCUP
suffers from a poor image reconstruction quality and fails to capture fine
structures in complex transient scenes. To overcome these restrictions, we
propose a flexible image reconstruction algorithm based on the total variation
(TV) and cascaded denoisers (CD) for HCUP, named the TV-CD algorithm. It
applies the TV denoising model cascaded with several advanced deep
learning-based denoising models in the iterative plug-and-play alternating
direction method of multipliers framework, which can preserve the image
smoothness while utilizing the deep denoising networks to obtain more priori,
and thus solving the common sparsity representation problem in local similarity
and motion compensation. Both simulation and experimental results show that the
proposed TV-CD algorithm can effectively improve the image reconstruction
accuracy and quality of HCUP, and further promote the practical applications of
HCUP in capturing high-dimensional complex physical, chemical and biological
ultrafast optical scenes.Comment: 25 pages, 5 figures and 1 tabl
JUNO Conceptual Design Report
The Jiangmen Underground Neutrino Observatory (JUNO) is proposed to determine
the neutrino mass hierarchy using an underground liquid scintillator detector.
It is located 53 km away from both Yangjiang and Taishan Nuclear Power Plants
in Guangdong, China. The experimental hall, spanning more than 50 meters, is
under a granite mountain of over 700 m overburden. Within six years of running,
the detection of reactor antineutrinos can resolve the neutrino mass hierarchy
at a confidence level of 3-4, and determine neutrino oscillation
parameters , , and to
an accuracy of better than 1%. The JUNO detector can be also used to study
terrestrial and extra-terrestrial neutrinos and new physics beyond the Standard
Model. The central detector contains 20,000 tons liquid scintillator with an
acrylic sphere of 35 m in diameter. 17,000 508-mm diameter PMTs with high
quantum efficiency provide 75% optical coverage. The current choice of
the liquid scintillator is: linear alkyl benzene (LAB) as the solvent, plus PPO
as the scintillation fluor and a wavelength-shifter (Bis-MSB). The number of
detected photoelectrons per MeV is larger than 1,100 and the energy resolution
is expected to be 3% at 1 MeV. The calibration system is designed to deploy
multiple sources to cover the entire energy range of reactor antineutrinos, and
to achieve a full-volume position coverage inside the detector. The veto system
is used for muon detection, muon induced background study and reduction. It
consists of a Water Cherenkov detector and a Top Tracker system. The readout
system, the detector control system and the offline system insure efficient and
stable data acquisition and processing.Comment: 328 pages, 211 figure
An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning
Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study light interception by plant canopies and are used in the retrieval of biophysical variables through model inversion. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. Emulators are advantageous in real practice because of the computational efficiency and excellent accuracy and flexibility for extrapolation. We hereby present an “Emulator toolbox” that enables analysing multi-output machine learning regression algorithms (MO-MLRAs) on their ability to approximate an RTM. The toolbox is included in the free-access ARTMO’s MATLAB suite for parameter retrieval and model inversion and currently contains both linear and non-linear MO-MLRAs, namely partial least squares regression (PLSR), kernel ridge regression (KRR) and neural networks (NN). These MO-MLRAs have been evaluated on their precision and speed to approximate the soil vegetation atmosphere transfer model SCOPE (Soil Canopy Observation, Photochemistry and Energy balance). SCOPE generates, amongst others, sun-induced chlorophyll fluorescence as the output signal. KRR and NN were evaluated as capable of reconstructing fluorescence spectra with great precision. Relative errors fell below 0.5% when trained with 500 or more samples using cross-validation and principal component analysis to alleviate the underdetermination problem. Moreover, NN reconstructed fluorescence spectra about 50-times faster and KRR about 800-times faster than SCOPE. The Emulator toolbox is foreseen to open new opportunities in the use of advanced RTMs, in which both consistent physical assumptions and data-driven machine learning algorithms live together
Roadmap on holography
From its inception holography has proven an extremely productive and attractive area of research. While specific technical applications give rise to 'hot topics', and three-dimensional (3D) visualisation comes in and out of fashion, the core principals involved continue to lead to exciting innovations in a wide range of areas. We humbly submit that it is impossible, in any journal document of this type, to fully reflect current and potential activity; however, our valiant contributors have produced a series of documents that go no small way to neatly capture progress across a wide range of core activities. As editors we have attempted to spread our net wide in order to illustrate the breadth of international activity. In relation to this we believe we have been at least partially successful.This work was supported by Ministerio de Economía, Industria y Competitividad (Spain) under projects FIS2017-82919-R (MINECO/AEI/FEDER, UE) and FIS2015-66570-P (MINECO/FEDER), and by Generalitat Valenciana (Spain) under project PROMETEO II/2015/015
White Light-Informed Optical Properties Improve Ultrasound-Guided Fluorescence Tomography of Photoactive Protoporphyrin IX
Subsurface fluorescence imaging is desirable for medical applications, including protoporphyrin-IX (PpIX)-based skin tumor diagnosis, surgical guidance, and dosimetry in photodynamic therapy. While tissue optical properties and heterogeneities make true subsurface fluorescence mapping an ill-posed problem, ultrasound-guided fluorescence-tomography (USFT) provides regional fluorescence mapping. Here USFT is implemented with spectroscopic decoupling of fluorescence signals (auto-fluorescence, PpIX, photoproducts), and white light spectroscopy-determined bulk optical properties. Segmented US images provide a priori spatial information for fluorescence reconstruction using region-based, diffuse FT. The method was tested in simulations, tissue homogeneous and inclusion phantoms, and an injected-inclusion animal model. Reconstructed fluorescence yield was linear with PpIX concentration, including the lowest concentration used, 0.025 μg/ml . White light spectroscopy informed optical properties, which improved fluorescence reconstruction accuracy compared to the use of fixed, literature-based optical properties, reduced reconstruction error and reconstructed fluorescence standard deviation by factors of 8.9 and 2.0, respectively. Recovered contrast-to-background error was 25% and 74% for inclusion phantoms without and with a 2-mm skin-like layer, respectively. Preliminary mouse-model imaging demonstrated system feasibility for subsurface fluorescence measurement in vivo. These data suggest that this implementation of USFT is capable of regional PpIX mapping in human skin tumors during photodynamic therapy, to be used in dosimetric evaluations
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