22,390 research outputs found
Proposal of the Readout Electronics for the WCDA in LHAASO Experiment
The LHAASO (Large High Altitude Air Shower Observatory) experiment is
proposed for very high energy gamma ray source survey, in which the WCDA (Water
Cherenkov Detector Array) is the one of the major components. In the WCDA, a
total of 3600 PMTs are placed under water in four ponds, each with a size of
150 m x 150 m. Precise time and charge measurement is required for the PMT
signals, over a large signal amplitude range from single P.E. (photo electron)
to 4000 P.E. To fulfill the high requirement of signal measurement in so many
front end nodes scattered in a large area, special techniques are developed,
such as multiple gain readout, hybrid transmission of clocks, commands, and
data, precise clock phase alignment, and new trigger electronics. We present
the readout electronics architecture for the WCDA and several prototype
modules, which are now under test in the laboratory.Comment: 8 pages, 8 figure
Deep Bayesian Multi-Target Learning for Recommender Systems
With the increasing variety of services that e-commerce platforms provide,
criteria for evaluating their success become also increasingly multi-targeting.
This work introduces a multi-target optimization framework with Bayesian
modeling of the target events, called Deep Bayesian Multi-Target Learning
(DBMTL). In this framework, target events are modeled as forming a Bayesian
network, in which directed links are parameterized by hidden layers, and
learned from training samples. The structure of Bayesian network is determined
by model selection. We applied the framework to Taobao live-streaming
recommendation, to simultaneously optimize (and strike a balance) on targets
including click-through rate, user stay time in live room, purchasing behaviors
and interactions. Significant improvement has been observed for the proposed
method over other MTL frameworks and the non-MTL model. Our practice shows that
with an integrated causality structure, we can effectively make the learning of
a target benefit from other targets, creating significant synergy effects that
improve all targets. The neural network construction guided by DBMTL fits in
with the general probabilistic model connecting features and multiple targets,
taking weaker assumption than the other methods discussed in this paper. This
theoretical generality brings about practical generalization power over various
targets distributions, including sparse targets and continuous-value ones.Comment: 7 pages, Deep Learning, Probabilistic Machine Learning, Recommender
System, Multi-task Learnin
Hybrid metric-Palatini brane system
It is known that the metric and Palatini formalisms of gravity theories have
their own interesting features but also suffer from some different drawbacks.
Recently, a novel gravity theory called hybrid metric-Palatini gravity was put
forward to cure or improve their individual deficiencies. The action of this
gravity theory is a hybrid combination of the usual Einstein-Hilbert action and
a term constructed by the Palatini formalism. Interestingly,
it seems that the existence of a light and long-range scalar field in this
gravity may modify the cosmological and galactic dynamics without conflicting
with the laboratory and Solar System tests. In this paper we focus on the
tensor perturbation of thick branes in this novel gravity theory. We consider
two models as examples, namely, the thick branes constructed by a background
scalar field and by pure gravity. The thick branes in both models have no inner
structure. However, the graviton zero mode in the first model has inner
structure when the parameter in this model is larger than its critical value.
We find that the effective four-dimensional gravity can be reproduced on the
brane for both models. Moreover, the stability of both brane systems against
the tensor perturbation can also be ensured.Comment: 7 pages, 4 figure
Testing dark energy models with data
is a diagnostic approach to distinguish dark energy models. However,
there are few articles to discuss what is the distinguishing criterion. In this
paper, firstly we smooth the latest observational data using a
model-independent method -- Gaussian processes, and then reconstruct the
and its fist order derivative . Such
reconstructions not only could be the distinguishing criteria, but also could
be used to estimate the authenticity of models. We choose some popular models
to study, such as CDM, generalized Chaplygin gas (GCG) model,
Chevallier-Polarski-Linder (CPL) parametrization and Jassal-Bagla-Padmanabhan
(JBP) parametrization. We plot the trajectories of and
with confidence level of these models, and
compare them to the reconstruction from data set. The result indicates
that the data does not favor the CPL and JBP models at
confidence level. Strangely, in high redshift range, the reconstructed
has a tendency of deviation from theoretical value, which
demonstrates these models are disagreeable with high redshift data. This
result supports the conclusions of Sahni et al. \citep{sahni2014model} and Ding
et al. \citep{ding2015there} that the CDM may not be the best
description of our universe
Observational constraint on the varying speed of light theory
The varying speed of light (VSL) theory is controversial. It succeeds in
explaining some cosmological problems, but on the other hand it is excluded by
mainstream physics because it will shake the foundation of physics. In the
present paper, we devote ourselves to test whether the speed of light is
varying from the observational data of the type Ia Supernova, Baryon Acoustic
Oscillation, Observational data and Cosmic Microwave Background (CMB).
We select the common form with the contribution of dark energy
and matter, where is the current value of speed of light, is a
constant, and consequently construct a varying speed of light dark energy model
(VSLDE). The combined observational data show a much trivial constraint
at 68.3\% confidence level, which indicates that the
speed of light may be a constant with high significance. By reconstructing the
time-variable , we find that the speed of light almost has no variation
for redshift . For high- observations, they are more sensitive
to the VSLDE model, but the variation of speed of light is only in order of
. We also introduce the geometrical diagnostic to show the
difference between the VSLDE and CDM model. The result shows that the
current data are difficult to differentiate them. All the results show that the
observational data favor the constant speed of light
Application of Real-time Digitization Technique in Beam Measurement for Accelerators
Beam measurement is very important for accelerators. With the development of
analog-to-digital conversion techniques, digital beam measurement becomes a
research hot spot. IQ (In-phase & Quadrature-phase) analysis based method is an
important beam measurement approach, the principle of which is presented and
discussed in this paper. The State Key Laboratory of Particle Detection and
Electronics in University of Science and Technology of China has devoted
efforts to the research of digital beam measurement based on high-speed
high-resolution analog-to-digital conversion, and a series of beam measurement
instruments were designed for China Spallation Neutron Source (CSNS), Shanghai
Synchrotron Radiation Facility (SSRF), and Accelerator Driven Sub-critical
system (ADS)
A New All-Digital Background Calibration Technique for Time-Interleaved ADC Using First Order Approximation FIR Filters
This paper describes a new all-digital technique for calibration of the
mismatches in time-interleaved analog-to-digital converters (TIADCs) to reduce
the circuit area. The proposed technique gives the first order approximation of
the gain mismatches and sample-time mismatches, and employs first order
approximation FIR filter banks to calibrate the sampled signal, which do not
need large number of FIR taps. In the case of a two-channel 12-bit TIADC, the
proposed technique improves SINAD of simulated data from 45dB to 69dB, and
improves SINAD of measured data from 47dB to 53dB, while the number of FIR taps
is only 30. In the case of slight mismatches, 24-bit FIR coefficient is
sufficient to correct 12-bit signals, which makes it easy to implement this
technique in hardware. In addition, this technique is not limited by the number
of sub-ADC channels and can be calculated in parallel in hardware, these
features enable this technique to be versatile and capable of real-time
calibration
A new method of waveform digitization based on time-interleaved A/D conversion
Time interleaved analog-to-digital conversion (TIADC) based on parallelism is
an effective way to meet the requirement of the ultra-fast waveform digitizer
beyond Gsps. Different methods to correct the mismatch errors among different
analog-to-digital conversion channels have been developed previously. To
overcome the speed limitation in hardware design and to implement the mismatch
correction algorithm in real time, this paper proposes a fully parallel
correction algorithm. A 12-bit 1-Gsps waveform digitizer with ENOB around 10.5
bit from 5 MHz to 200 MHz is implemented based on the real-time correction
algorithm.Comment: 11 pages, 15 figure
One-Shot Coherence Dilution
Manipulation and quantification of quantum resources are fundamental problems
in quantum physics. In the asymptotic limit, coherence distillation and
dilution have been proposed by manipulating infinite identical copies of
states. In the non-asymptotic setting, finite data-size effects emerge, and the
practically relevant problem of coherence manipulation using finite resources
has been left open. This letter establishes the one-shot theory of coherence
dilution, which involves converting maximally coherent states into an arbitrary
quantum state using maximally incoherent operations, dephasing-covariant
incoherent operations, incoherent operations, or strictly incoherent
operations. We introduce several coherence monotones with concrete operational
interpretations that estimate the one-shot coherence cost --- the minimum
amount of maximally coherent states needed for faithful coherence dilution.
Furthermore, we derive the asymptotic coherence dilution results with maximally
incoherent operations, incoherent operations, and strictly incoherent
operations as special cases. Our result can be applied in the analyses of
quantum information processing tasks that exploit coherence as resources, such
as quantum key distribution and random number generation.Comment: 12 pages, 1 figure, comments are welcome
Matching the Quasi Meson Distribution Amplitude in RI/MOM scheme
The -dependence of light-cone distribution amplitude (LCDA) can be
directly calculated from a quasi distribution amplitude (DA) in lattice QCD
within the framework of large-momentum effective theory (LaMET). In this paper,
we study the one-loop renormalization of the quasi-DA in the
regularization-independent momentum subtraction (RI/MOM) scheme. The
renormalization factor for the quasi parton distribution function can be used
to renormalize the quasi-DA provided that they are implemented on lattice and
in perturbation theory in the same manner. We derive the one-loop matching
coefficient that matches quasi-DA in the RI/MOM scheme onto LCDA in the
scheme. Our result provides the crucial step to extract the
LCDAs from lattice matrix elements of quasi-DAs.Comment: 7 pages, 0 figure
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