arXiv subjects

Jun Cao

Publications and source records attributed to Jun Cao.

At least 91 records · Page 5Linked to original sources

arXiv2021

Calibration Strategy of the JUNO Experiment

We present the calibration strategy for the 20 kton liquid scintillator central detector of the Jiangmen Underground Neutrino Observatory (JUNO). By utilizing a comprehensive multiple-source and multiple-positional calibration program, in combination with a novel dual calorimetry technique exploiting two independent photosensors and readout systems, we demonstrate that the JUNO central detector can achieve a better than 1% energy linearity and a 3% effective energy resolution, required by the neutrino mass ordering determination.

physics.ins-det↗

arXiv2020

A liquid scintillator for a neutrino Detector working at -50 degree

A liquid scintillator (LS) is developed for the Taishan Antineutrino Observatory (TAO), a ton-level neutrino detector to measure the reactor antineutrino spectrum with sub-percent energy resolution by adopting Silicon Photomultipliers (SiPMs) as photosensor. To reduce the dark noise of SiPMs to an acceptable level, the LS has to work at -50 degree or lower. A customized apparatus based on a charge-coupled device (CCD) is developed to study the transparency of the liquid samples in a cryostat. We find that the water content in LS results in transparency degradation at low temperature, which can be cured by bubbling dry nitrogen to remove water. Adding 0.05% ethanol as co-solvent cures the solubility decrease problem of the fluors PPO and bis-MSB at low temperature. Finally, a Gadoliniumdoped liquid scintillator (GdLS), with 0.1% Gd by weight, 2 g/L PPO, 1 mg/L bis-MSB, and 0.05% ethanol by weight in the solvent LAB, shows good transparency at -50 degree and also good light yield.

physics.ins-det↗

arXiv2020

Gaussian Estimates for Heat Kernels of Higher Order Schrödinger Operators with Potentials in Generalized Schechter Classes

Let $m\in\mathbb N$, $P(D):=\sum_{|α|=2m}(-1)^m a_αD^α$ be a $2m$-order homogeneous elliptic operator with real constant coefficients on $\mathbb{R}^n$, and $V$ a measurable function on $\mathbb{R}^n$. In this article, the authors introduce a new generalized Schechter class concerning $V$ and show that the higher order Schrödinger operator $\mathcal{L}:=P(D)+V$ possesses a heat kernel that satisfies the Gaussian upper bound and the Hölder regularity when $V$ belongs to this new class. The Davies--Gaffney estimates for the associated semigroup and their local versions are also given. These results pave the way for many further studies on the analysis of $\mathcal{L}$.

math.AP↗

arXiv2020

The replacement system of the JUNO liquid scintillator pilot experiment at Daya Bay

The Jiangmen Underground Neutrino Observatory (JUNO), a multi-purpose neutrino experiment, will use 20 kt liquid scintillator (LS). To achieve the physics goal of determining the neutrino mass ordering, 3$\%$ energy resolution at 1 MeV is required. This puts strict requirements on the LS light yield and the transparency. Four LS purification steps have been designed and mid-scale plants have been built at Daya Bay. To examine the performance of the purified LS and find the optimized LS composition, the purified LS was injected to the antineutrino detector 1 in the experimental hall 1 (EH1-AD1) of the Daya Bay neutrino experiment. To pump out the original gadolinium loaded LS and fill the new LS, a LS replacement system has been built in EH1 in 2017. By replacing the Gd-LS with purified water, then replacing the water with purified LS, the replacement system successfully achieved the designed goal. Subsequently, the fluorescence and the wavelength shifter were added to higher concentrations via the replacement system. The data taken at various LS compositions helped JUNO determine the final LS cocktail. Details of the design, the construction, and the operation of the replacement system are reported in this paper.

physics.ins-det↗

arXiv2020

Volctrans Parallel Corpus Filtering System for WMT 2020

In this paper, we describe our submissions to the WMT20 shared task on parallel corpus filtering and alignment for low-resource conditions. The task requires the participants to align potential parallel sentence pairs out of the given document pairs, and score them so that low-quality pairs can be filtered. Our system, Volctrans, is made of two modules, i.e., a mining module and a scoring module. Based on the word alignment model, the mining module adopts an iterative mining strategy to extract latent parallel sentences. In the scoring module, an XLM-based scorer provides scores, followed by reranking mechanisms and ensemble. Our submissions outperform the baseline by 3.x/2.x and 2.x/2.x for km-en and ps-en on From Scratch/Fine-Tune conditions, which is the highest among all submissions.

cs.CL↗

arXiv2020

Xiaomingbot: A Multilingual Robot News Reporter

This paper proposes the building of Xiaomingbot, an intelligent, multilingual and multimodal software robot equipped with four integral capabilities: news generation, news translation, news reading and avatar animation. Its system summarizes Chinese news that it automatically generates from data tables. Next, it translates the summary or the full article into multiple languages, and reads the multilingual rendition through synthesized speech. Notably, Xiaomingbot utilizes a voice cloning technology to synthesize the speech trained from a real person's voice data in one input language. The proposed system enjoys several merits: it has an animated avatar, and is able to generate and read multilingual news. Since it was put into practice, Xiaomingbot has written over 600,000 articles, and gained over 150,000 followers on social media platforms.

eess.AS↗

arXiv2020

Feasibility and physics potential of detecting $^8$B solar neutrinos at JUNO

The Jiangmen Underground Neutrino Observatory~(JUNO) features a 20~kt multi-purpose underground liquid scintillator sphere as its main detector. Some of JUNO's features make it an excellent experiment for $^8$B solar neutrino measurements, such as its low-energy threshold, its high energy resolution compared to water Cherenkov detectors, and its much large target mass compared to previous liquid scintillator detectors. In this paper we present a comprehensive assessment of JUNO's potential for detecting $^8$B solar neutrinos via the neutrino-electron elastic scattering process. A reduced 2~MeV threshold on the recoil electron energy is found to be achievable assuming the intrinsic radioactive background $^{238}$U and $^{232}$Th in the liquid scintillator can be controlled to 10$^{-17}$~g/g. With ten years of data taking, about 60,000 signal and 30,000 background events are expected. This large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter, which will shed new light on the tension between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation framework. If $Δm^{2}_{21}=4.8\times10^{-5}~(7.5\times10^{-5})$~eV$^{2}$, JUNO can provide evidence of neutrino oscillation in the Earth at the about 3$σ$~(2$σ$) level by measuring the non-zero signal rate variation with respect to the solar zenith angle. Moveover, JUNO can simultaneously measure $Δm^2_{21}$ using $^8$B solar neutrinos to a precision of 20\% or better depending on the central value and to sub-percent precision using reactor antineutrinos. A comparison of these two measurements from the same detector will help elucidate the current tension between the value of $Δm^2_{21}$ reported by solar neutrino experiments and the KamLAND experiment.

hep-ex↗

arXiv2020

Spin-Induced Linear Polarization of Excitonic Emission in Antiferromagnetic van der Waals Crystals

Antiferromagnets display enormous potential in spintronics owing to its intrinsic nature, including terahertz resonance, multilevel states, and absence of stray fields. Combining with the layered nature, van der Waals (vdW) antiferromagnets hold the promise in providing new insights and new designs in two-dimensional (2D) spintronics. The zero net magnetic moments of vdW antiferromagnets strengthens the spin stability, however, impedes the correlation between spin and other excitation elements, like excitons. Such coupling is urgently anticipated for fundamental magneto-optical studies and potential opto-spintronic devices. Here, we report an ultra-sharp excitonic emission with excellent monochromaticity in antiferromagnetic nickel phosphorus trisulfides (NiPS3) from bulk to atomically thin flakes. We prove that the linear polarization of the excitonic luminescence is perpendicular to the ordered spin orientation in NiPS3. By applying an in-plane magnetic field to alter the spin orientation, we further manipulate the excitonic emission polarization. Such strong correlation between exciton and spins provides new insights for the study of magneto-optics in 2D materials, and hence opens a path for developing opto-spintronic devices and antiferromagnet-based quantum information technologies.

cond-mat.mes-hall↗

arXiv2020

TAO Conceptual Design Report: A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to provide a reference spectrum for future reactor neutrino experiments, and to provide a benchmark measurement to test nuclear databases. A spherical acrylic vessel containing 2.8 ton gadolinium-doped liquid scintillator will be viewed by 10 m^2 Silicon Photomultipliers (SiPMs) of >50% photon detection efficiency with almost full coverage. The photoelectron yield is about 4500 per MeV, an order higher than any existing large-scale liquid scintillator detectors. The detector operates at -50 degree C to lower the dark noise of SiPMs to an acceptable level. The detector will measure about 2000 reactor antineutrinos per day, and is designed to be well shielded from cosmogenic backgrounds and ambient radioactivities to have about 10% background-to-signal ratio. The experiment is expected to start operation in 2022.

physics.ins-det↗

arXiv2020

Improving the Energy Resolution of the Reactor Antineutrino Energy Reconstruction with Positron Direction

The energy resolution is crucial for the reactor neutrino experiments which aims to determine neutrino mass ordering by precise measurement of the reactor antineutrino energy spectrum. A non-negligible effect in the antineutrino energy resolution is the spread of the kinetic energy of the recoiled neutron and the corresponding positron when detecting the antineutrinos via Inverse Beta-Decay (IBD) reaction. The emission direction of the produced positron in IBD reaction can be used to estimate the kinetic energy of neutron and thus the reconstructed antineutrino energy resolution can be improved. To demonstrate the feasibility, a simple positron direction reconstruction method is implemented in a toy liquid scintillator detector like the Taishan Antineutrino Observatory (TAO) with 4500 photoelectron yield per MeV. A 4% to 26% improvement of energy resolution can be achieved for 5 MeV reactor antineutrinos at TAO.

physics.ins-det↗

arXiv2020

Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency

Obtaining accurate information about future traffic flows of all links in a traffic network is of great importance for traffic management and control applications. This research studies two particular problems in traffic forecasting: (1) capture the dynamic and non-local spatial correlation between traffic links and (2) model the dynamics of temporal dependency for accurate multiple steps ahead predictions. To address these issues, we propose a deep learning framework named Spatial-Temporal Sequence to Sequence model (STSeq2Seq). This model builds on sequence to sequence (seq2seq) architecture to capture temporal feature and relies on graph convolution for aggregating spatial information. Moreover, STSeq2Seq defines and constructs pattern-aware adjacency matrices (PAMs) based on pair-wise similarity of the recent traffic patterns on traffic links and integrate it into graph convolution operation. It also deploys a novel seq2sesq architecture which couples a convolutional encoder and a recurrent decoder with attention mechanism for dynamic modeling of long-range dependence between different time steps. We conduct extensive experiments using two publicly-available large-scale traffic datasets and compare STSeq2Seq with other baseline models. The numerical results demonstrate that the proposed model achieves state-of-the-art forecasting performance in terms of various error measures. The ablation study verifies the effectiveness of PAMs in capturing dynamic non-local spatial correlation and the superiority of proposed seq2seq architecture in modeling non-stationary temporal dependency for multiple steps ahead prediction. Furthermore, qualitative analysis is conducted on PAMs as well as the attention weights for model interpretation.

cs.LG↗

arXiv2019

Realization of 2D Crystalline Metal Nitrides via Selective Atomic Substitution

Two-dimensional (2D) transition metal nitrides (TMNs) are new members in the 2D materials family with a wide range of applications. Particularly, highly crystalline and large area thin films of TMNs are potentially promising for applications in electronic and optoelectronic devices; however, the synthesis of such TMNs has not yet been achieved. Here, we report the synthesis of few-nanometer thin Mo5N6 crystals with large area and high quality via in situ chemical conversion of layered MoS2 crystals. The structure and quality of the ultrathin Mo5N6 crystal are confirmed using transmission electron microscopy, Raman spectroscopy and X-ray photoelectron spectroscopy. The large lateral dimensions of Mo5N6 crystals are inherited from the MoS2 crystals that are used for the conversion. Atomic force microscopy characterization reveals the thickness of Mo5N6 crystals is reduced to about 1/3 of the MoS2 crystal. Electrical measurements show the obtained Mo5N6 samples are metallic with high electrical conductivity (~ 100 Ω sq-1), which is comparable to graphene. The versatility of this general approach is demonstrated by expanding the method to synthesize W5N6 and TiN. Our strategy offers a new direction for preparing 2D TMNs with desirable characteristics, opening a door for studying fundamental physics and facilitating the development of next generation electronics.

cond-mat.mtrl-sci↗

arXiv2019

A quantitative approach to select PMTs for large detectors

Photomultiplier tubes (PMTs) are widely used in neutrino and other experiments for the detection of weak light. To date PMTs are the most sensitive single photon detector per unit area. In addition to the quantum efficiency for photon detection, there are a number of other specifications, such as rate and amplitude of after-pulses, dark noise rate, transit time spread, radioactive background of glass, peak-to-valley ratio, etc. All affect the photon detection and hence the physics goals. In addition, cost is another major factor for large experiments. It is important to know how to properly take into account all these parameters and choose the most appropriate PMTs. In this paper, we present an approach to quantify the impact of all parameters on the physics goals, including cost and risk. This method has been successfully used in the JUNO experiment. It can be applied to other experiments with large number of PMTs.

physics.ins-det↗

arXiv2019

Towards the meV limit of the effective neutrino mass in neutrinoless double-beta decays

In this paper, we emphasize why it is important for future neutrinoless double-beta ($0νββ$) decay experiments to reach the sensitivity to the effective neutrino mass $|m^{}_{ββ}| \approx 1~{\rm meV}$. Assuming such a sensitivity and the precisions on neutrino oscillation parameters after the JUNO experiment, we fully explore the constrained regions of the lightest neutrino mass $m^{}_1$ and two Majorana-type CP-violating phases $\{ρ, σ\}$. The implications for the neutrino mass spectrum, the effective neutrino mass $m^{}_β$ in beta decays and the sum of three neutrino masses $Σ\equiv m^{}_1 + m^{}_2 + m^{}_3$ relevant for cosmological observations are also discussed.

hep-ph↗

arXiv2019

Energy Flux in Hierarchical Equations of Motion Method and Its Application to a Three-Level Heat Engine

We derive the formula of energy flux for the hierarchical equations of motion (HEOM) method with the help of stochastic decoupling technique. The resulting expression is a combination of the terms in the first two layers of the hierarchy. The formula is applied to a three-level "heat engine" coupled respectively to three baths, of which two for heat sources and one for work dump. All the three baths are modeled by collections of harmonic oscillators. We illustrate the proper parameterizing to converge the third bath to the "work-dump" limit. As an example, the effect of the engine parameters on working efficiency is studied.

cond-mat.stat-mech↗

arXiv2019

Thermal diffusivity and specific heat capacity of linear alkylbenzene

We report the measurements of the thermal diffusivity and the isobaric specific heat capacity of linear alkylbenzene at about 23$\,^{\circ}\mathrm{C}$ with the standard atmosphere, which are measured for the first time. The conductivity, heat capacity ratio, and speed of sound were derived from our measurements based on thermodynamic relations. The temperature dependence of heat capacity ratio and isobaric specific heat capacity were calculated and relevant results were discussed.

physics.ins-det↗

arXiv2019

A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network

Traffic forecasting is crucial for urban traffic management and guidance. However, existing methods rarely exploit the time-frequency properties of traffic speed observations, and often neglect the propagation of traffic flows from upstream to downstream road segments. In this paper, we propose a hybrid approach that learns the spatio-temporal dependency in traffic flows and predicts short-term traffic speeds on a road network. Specifically, we employ wavelet transform to decompose raw traffic data into several components with different frequency sub-bands. A Motif-based Graph Convolutional Recurrent Neural Network (Motif-GCRNN) and Auto-Regressive Moving Average (ARMA) are used to train and predict low-frequency components and high-frequency components, respectively. In the Motif-GCRNN framework, we integrate Graph Convolutional Networks (GCNs) with local sub-graph structures - Motifs - to capture the spatial correlations among road segments, and apply Long Short-Term Memory (LSTM) to extract the short-term and periodic patterns in traffic speeds. Experiments on a traffic dataset collected in Chengdu, China, demonstrate that the proposed hybrid method outperforms six state-of-art prediction methods.

cs.CV↗

arXiv2019

Topological phase transition based on the attractive Hubbard model

We theoretically investigate the effect of an attractive on-site interaction on the two-band magnetic Dirac fermion model based on a square lattice system. When the attractive fermion interaction is taken into account by the mean-field approximation, a phase diagram is obtained. It is found that a quantum phase transition from a band insulator state to quantum anomalous Hall state occurs with increased attractive interaction. For an existing quantum anomalous Hall state, the attractive interaction enlarges its nontrivial band gap and makes the topological edge states more localized, which protects the transport of linear-dispersive edge states against finite-size and further disorder effects.

cond-mat.mes-hall↗