21,139 research outputs found
Possible observables for the chiral electric separation effect in Cu + Au collisions
The quark-gluon plasma (QGP) generated in relativistic heavy-ion collisions
could be locally parity-odd. In parity-odd QGP, the electric field may induce a
chiral current which is called the chiral electric separation effect (CESE). We
propose two possible observables for CESE in Cu + Au collisions: The first one
is the correlation ; the second one is the
charge-dependent event-plane angle with being charge.
Nonzero and
may signal the CESE in Cu + Au
collisions. Within a multiphase transport model, we study how the final state
interaction affects these observables. We find that the correlation
is sensitive to the out-of-plane charge separation caused by the
chiral magnetic effect and to the in-plane charge separation caused by the
in-plane electric field, but it is not sensitive to the CESE. On the other
hand, and are sensitive to the CESE. Therefore, we
suggest that the future experiments measure the above observables in Cu+Au
collisions in order to disentangle different chiral and charge separation
mechanisms.Comment: 6 pages, 6 figures, final published versio
Lattice Boltzmann simulation of separation phenomenon in a binary gaseous flow through a microchannel
Gas separation of a binary gaseous mixture is one of characteristic phenomena
in the micro-scale flows that differ from the conventional size flows. In this
work, the separation in a binary gas mixture flows through a microchannel is
investigated by the lattice Boltzmann method with a diffuse-bounce-back (DBB)
boundary condition. The separation degree and rate are measured in the He--Ar
and Ne--Ar systems for different mole fractions, pressure ratios, and Knudsen
numbers. The results show that the separation phenomenon in the He--Ar mixture
is more obvious than that in the Ne--Ar mixture at the same mole fraction owing
to the larger molecular mass ratio. In addition, the increase in the pressure
ratio reduces the difference in the molecular velocities between the two
species, and the separation phenomenon becomes weaker. However, the gas
separation is enhanced with an increase in the Knudsen number. This is because
the resulting rarefaction effect reduces the interactions between the gas
molecules of the two species, and thus increases the difference in the
molecular velocity.Comment: 19pages,15figure
DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval
This paper concerns a deep learning approach to relevance ranking in
information retrieval (IR). Existing deep IR models such as DSSM and CDSSM
directly apply neural networks to generate ranking scores, without explicit
understandings of the relevance. According to the human judgement process, a
relevance label is generated by the following three steps: 1) relevant
locations are detected, 2) local relevances are determined, 3) local relevances
are aggregated to output the relevance label. In this paper we propose a new
deep learning architecture, namely DeepRank, to simulate the above human
judgment process. Firstly, a detection strategy is designed to extract the
relevant contexts. Then, a measure network is applied to determine the local
relevances by utilizing a convolutional neural network (CNN) or two-dimensional
gated recurrent units (2D-GRU). Finally, an aggregation network with sequential
integration and term gating mechanism is used to produce a global relevance
score. DeepRank well captures important IR characteristics, including
exact/semantic matching signals, proximity heuristics, query term importance,
and diverse relevance requirement. Experiments on both benchmark LETOR dataset
and a large scale clickthrough data show that DeepRank can significantly
outperform learning to ranking methods, and existing deep learning methods.Comment: Published as a conference paper at CIKM 2017, CIKM'17, November
6--10, 2017, Singapore TextNet (https://github.com/pl8787/textnet-release)
PyTorch (https://github.com/pl8787/DeepRank_PyTorch
Locally Smoothed Neural Networks
Convolutional Neural Networks (CNN) and the locally connected layer are
limited in capturing the importance and relations of different local receptive
fields, which are often crucial for tasks such as face verification, visual
question answering, and word sequence prediction. To tackle the issue, we
propose a novel locally smoothed neural network (LSNN) in this paper. The main
idea is to represent the weight matrix of the locally connected layer as the
product of the kernel and the smoother, where the kernel is shared over
different local receptive fields, and the smoother is for determining the
importance and relations of different local receptive fields. Specifically, a
multi-variate Gaussian function is utilized to generate the smoother, for
modeling the location relations among different local receptive fields.
Furthermore, the content information can also be leveraged by setting the mean
and precision of the Gaussian function according to the content. Experiments on
some variant of MNIST clearly show our advantages over CNN and locally
connected layer.Comment: In Proceedings of 9th Asian Conference on Machine Learning (ACML2017
A Study of MatchPyramid Models on Ad-hoc Retrieval
Deep neural networks have been successfully applied to many text matching
tasks, such as paraphrase identification, question answering, and machine
translation. Although ad-hoc retrieval can also be formalized as a text
matching task, few deep models have been tested on it. In this paper, we study
a state-of-the-art deep matching model, namely MatchPyramid, on the ad-hoc
retrieval task. The MatchPyramid model employs a convolutional neural network
over the interactions between query and document to produce the matching score.
We conducted extensive experiments to study the impact of different pooling
sizes, interaction functions and kernel sizes on the retrieval performance.
Finally, we show that the MatchPyramid models can significantly outperform
several recently introduced deep matching models on the retrieval task, but
still cannot compete with the traditional retrieval models, such as BM25 and
language models.Comment: Neu-IR '16 SIGIR Workshop on Neural Information Retrieva
Optical Spectroscopy of Four Young Radio Sources
We report the optical spectroscopy of four young radio sources which are
observed with the Lijiang 2.4m telescope. The Eddington ratios of these sources
are similar with those of narrow-line Seyfert 1 galaxies (NLS1s). Their Fe {\sc
ii} emission is strong while [O {\sc iii}] strength is weak. These results
confirm the NLS1 features of young radio sources, except that the width of
broad H of young radio sources is larger than that of NLS1s. We thus
suggest that the young radio sources are the high black hole mass counterparts
of steep-spectrum radio-loud NLS1s. In addition, the broad H component
of \astrobj{4C 12.50} is the blue wing of the narrow component, but not from
the broad line region.Comment: 11 pages, 5 Figures, 2 Tables, accepted by New Astronom
Filtration and Extraction of Quantum States from Classical Inputs
We propose using nonlinear Mach-Zehnder interferometer (NMZI) to efficiently
prepare photonic quantum states from a classical input. We first analytically
investigate the simple NMZI that can filtrate single photon state from weak
coherent state by preferrentially blocking two-photon component. As a
generalization, we show that the cascaded NMZI can deterministically extract
arbitrary quantum state from a strong coherent state. Finally, we numerically
demonstrate that the cascaded NMZI can be very efficient in both the input
power and the level of cascade. The protocol of quantum state preparation with
NMZI can be extended to various systems of bosonic modes.Comment: 5 pages, 3 figure
Chiral magnetic effect in isobaric collisions
We give a numerical simulation of the generation of the magnetic field and
the charge-separation signal due to the chiral magnetic effect (CME) --- the
induction of an electric current by the magnetic field in a parity-odd matter
--- in the collisions of isobaric nuclei, Ru + Ru and
Zr + Zr, at GeV. We show that
such collisions provide an ideal tool to disentangle the CME signal from the
possible elliptic-flow driven background effects. We also discuss some other
effects that can be tested by using the isobaric collisions.Comment: Proceedings of XXVIth International Conference on Ultrarelativistic
Nucleus-Nucleus Collisions (Quark Matter 2017
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dbCoRC: a database of core transcriptional regulatory circuitries modeled by H3K27ac ChIP-seq signals.
Core transcription regulatory circuitry (CRC) is comprised of a small group of self-regulated transcription factors (TFs) and their interconnected regulatory loops. Studies from embryonic stem cells and other cellular models have revealed the elementary roles of CRCs in transcriptional control of cell identity and cellular fate. Systematic identification and subsequent archiving of CRCs across diverse cell types and tissues are needed to explore both cell/tissue type-specific and disease-associated transcriptional networks. Here, we present a comprehensive and interactive database (dbCoRC, http://dbcorc.cam-su.org) of CRC models which are computationally inferred from mapping of super-enhancer and prediction of TF binding sites. The current version of dbCoRC contains CRC models for 188 human and 50 murine cell lines/tissue samples. In companion with CRC models, this database also provides: (i) super enhancer, typical enhancer, and H3K27ac landscape for individual samples, (ii) putative binding sites of each core TF across the super-enhancer regions within CRC and (iii) expression of each core TF in normal or cancer cells/tissues. The dbCoRC will serve as a valuable resource for the scientific community to explore transcriptional control and regulatory circuitries in biological processes related to, but not limited to lineage specification, tissue homeostasis and tumorigenesis
Test the chiral magnetic effect with isobaric collisions
The quark-gluon matter produced in relativistic heavy-ion collisions may
contain local domains in which P and CP symmetries are not preserved. When
coupled with an external magnetic field, such P- and CP-odd domains will
generate electric currents along the magnetic field --- a phenomenon called the
chiral magnetic effect (CME). Recently, the STAR Collaboration at RHIC and the
ALICE Collaboration at the LHC released data of charge-dependent
azimuthal-angle correlators with features consistent with the CME expectation.
However, the experimental observable is contaminated with significant
background contributions from elliptic-flow-driven effects, which makes the
interpretation of the data ambiguous. In this Letter, we show that the
collisions of isobaric nuclei, Ru + Ru and
Zr + Zr, provide an ideal tool to disentangle the CME
signal from the background effects. Our simulation demonstrates that the two
collision types at GeV have more than difference
in the CME signal and less than difference in the elliptic-flow-driven
backgrounds for the centrality range of .Comment: V1: 4 pages, 4 figure
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