arXiv subjects

Liang Li

Publications and source records attributed to Liang Li.

At least 361 records · Page 20Linked to original sources

arXiv2018

A Large Catalogue of Multi-wavelength GRB Afterglows I: Color Evolution And Its Physical Implication

The spectrum of gamma-ray burst (GRB) afterglows can be studied with color indices. Here we present a large comprehensive catalogue of 70 GRBs with multi-wavelength optical transient data on which we perform a systematic study to find the temporal evolution of color indices. We categorize them into two samples based on how well the color indices are evaluated. The Golden sample includes 25 bursts mostly observed by GROND, and the Silver sample includes 45 bursts observed by other telescopes. For the Golden sample, we find that 95\% of the color indices do not vary over time. However, the color indices do vary during short periods in most bursts. The observed variations are consistent with effects of (i) the cooling frequency crossing the studied energy bands in a wind medium (43\%) and in a constant density medium (30\%), (ii) early dust extinction (12\%), (iii) transition from reverse shock to forward shock emission (5\%), or (iv) an emergent supernova emission (10\%). We also study the evolutionary properties of the mean color indices for different emission episodes. We find that 86\% of the color indices in the 70 bursts show constancy between consecutive ones. The color index variations occur mainly during the late GRB-SN bump, the flare and early reversed-shock emission components. We further perform a statistical analysis of various observational properties and model parameters (spectral index $β_{o}^{\rm CI}$, electron spectral indices $p^{\rm CI}$, etc.) using color indices. Overall, we conclude that $\sim$ 90\% of colors are constant in time and can be accounted for by the simplest external forward shock model, while the varying color indices call for more detailed modeling.

astro-ph.HE↗

arXiv2018

Fast OBDD Reordering using Neural Message Passing on Hypergraph

Ordered binary decision diagrams (OBDDs) are an efficient data structure for representing and manipulating Boolean formulas. With respect to different variable orders, the OBDDs' sizes may vary from linear to exponential in the number of the Boolean variables. Finding the optimal variable order has been proved a NP-complete problem. Many heuristics have been proposed to find a near-optimal solution of this problem. In this paper, we propose a neural network-based method to predict near-optimal variable orders for unknown formulas. Viewing these formulas as hypergraphs, and lifting the message passing neural network into 3-hypergraph (MPNN3), we are able to learn the patterns of Boolean formula. Compared to the traditional methods, our method can find a near-the-best solution with an extremely shorter time, even for some hard examples.To the best of our knowledge, this is the first work on applying neural network to OBDD reordering.

cs.AI↗

arXiv2018

A Letter of Intent for MATHUSLA: a dedicated displaced vertex detector above ATLAS or CMS

In this Letter of Intent (LOI) we propose the construction of MATHUSLA (MAssive Timing Hodoscope for Ultra-Stable neutraL pArticles), a dedicated large-volume displaced vertex detector for the HL-LHC on the surface above ATLAS or CMS. Such a detector, which can be built using existing technologies with a reasonable budget in time for the HL-LHC upgrade, could search for neutral long-lived particles (LLPs) with up to several orders of magnitude better sensitivity than ATLAS or CMS, while also acting as a cutting-edge cosmic ray telescope at CERN to explore many open questions in cosmic ray and astro-particle physics. We review the physics motivations for MATHUSLA and summarize its LLP reach for several different possible detector geometries, as well as outline the cosmic ray physics program. We present several updated background studies for MATHUSLA, which help inform a first detector-design concept utilizing modular construction with Resistive Plate Chambers (RPCs) as the primary tracking technology. We present first efficiency and reconstruction studies to verify the viability of this design concept, and we explore some aspects of its total cost. We end with a summary of recent progress made on the MATHUSLA test stand, a small-scale demonstrator experiment currently taking data at CERN Point 1, and finish with a short comment on future work.

physics.ins-det↗

arXiv2018

A Comparative Study of Consistent Snapshot Algorithms for Main-Memory Database Systems

In-memory databases (IMDBs) are gaining increasing popularity in big data applications, where clients commit updates intensively. Specifically, it is necessary for IMDBs to have efficient snapshot performance to support certain special applications (e.g., consistent checkpoint, HTAP). Formally, the in-memory consistent snapshot problem refers to taking an in-memory consistent time-in-point snapshot with the constraints that 1) clients can read the latest data items and 2) any data item in the snapshot should not be overwritten. Various snapshot algorithms have been proposed in academia to trade off throughput and latency, but industrial IMDBs such as Redis adhere to the simple fork algorithm. To understand this phenomenon, we conduct comprehensive performance evaluations on mainstream snapshot algorithms. Surprisingly, we observe that the simple fork algorithm indeed outperforms the state-of-the-arts in update-intensive workload scenarios. On this basis, we identify the drawbacks of existing research and propose two lightweight improvements. Extensive evaluations on synthetic data and Redis show that our lightweight improvements yield better performance than fork, the current industrial standard, and the representative snapshot algorithms from academia. Finally, we have opensourced the implementation of all the above snapshot algorithms so that practitioners are able to benchmark the performance of each algorithm and select proper methods for different application scenarios.

cs.DB↗

arXiv2018

Log-periodic quantum magneto-oscillations and discrete scale invariance in topological material HfTe5

Discrete scale invariance (DSI) is a phenomenon featuring intriguing log-periodicity which can be rarely observed in quantum systems. Here we report the log-periodic quantum oscillations in the magnetoresistance (MR) and the Hall traces of HfTe5 crystals, which reveals the appearance of DSI. The oscillations show the same logB-periodicity in the behavior of MR and Hall, indicating an overall effect of the DSI on the transport properties. Moreover, the DSI feature in the Hall resistance signals its close relation to the carriers. Combined with theoretical simulations, we further clarify the origin of the log-periodic oscillations and the DSI in the topological materials. Our work evidences the universality of the DSI in the Dirac materials and paves way for the full understanding of the novel phenomenon.

cond-mat.mtrl-sci↗

arXiv2018

Design and characterization of high energy micro-CT with a laser-based X-ray source

The increasingly demand for machining accuracy and product quality excites a great interest in high-resolution non-destructive testing (NDT) methods, but spatial resolution of conventional high-energy computed tomography (CT) is limited to sub-millimeter because of large X-ray spot size. Therefore, we propose a novel high-resolution high-energy CT based on laser-driven X-ray source and prove its feasibility to allow high-spatial-resolution tomographic imaging of dense objects. A numerical model is developed with a consideration of realistic factors including parameter fluctuations, statistical noise and detecting efficiency. By using modulation transfer functions, the system performance is quantitatively characterized and optimized in terms of source characteristics, detector aperture, geometrical configuration and projection parameters. As a result, the simulated tomography for a high-density object (up to 19.35g/cm3) achieves a basic spatial resolution of 64.9μm. This concept expands the prospects of laser-based compact X-ray sources and shows a great potential to achieve high-perspectivity micro-CT imaging for various industrial applications.

physics.ins-det↗

arXiv2018

Discovery of Log-Periodic Oscillations in Ultra-Quantum Topological Materials

Quantum oscillations are usually the manifestation of the underlying physical nature in condensed matter systems. Here we report a new type of log-periodic quantum oscillations in ultra-quantum three-dimensional topological materials. Beyond the quantum limit (QL), the log-periodic oscillations involving up to five oscillating cycles (5 peaks and 5 dips) are observed on the magnetoresistance (MR) of high quality single-crystal ZrTe5, virtually showing the clearest feature of discrete scale invariance (DSI). Further theoretical analyses show that the two-body quasi-bound states can be responsible for the DSI feature. Our work provides a new perspective on the ground state of topological materials beyond the QL.

cond-mat.mtrl-sci↗

arXiv2018

High harmonic generation with circularly polarized fields in solid: a quantum trajectory perspective

We investigate the high harmonic generation (HHG) in solids driven by laser fields with different ellipticities. The HHG spectra show a two-plateau structure within the energy gap between the valence band and the first conduction band. These two plateaus depend distinctly on the laser ellipticity. The first plateau is decreased while the second plateau is enhanced with increasing the laser ellipticity. To understand these phenomena, we develop an intuitive Reciprocal-Space- Trajectory (RST) method, with which HHG in solids is explained by a trajectory-ensemble from different initial states and different ionization times in the reciprocal space. In the framework of RST, we can not only quantitatively reproduce the HHG spectra, but also well understand the underlying physics of these phenomena, providing a deep insight into the mechanism of HHG in solids.

physics.optics↗

arXiv2018

Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version)

We study the Combinatorial Pure Exploration problem with Continuous and Separable reward functions (CPE-CS) in the stochastic multi-armed bandit setting. In a CPE-CS instance, we are given several stochastic arms with unknown distributions, as well as a collection of possible decisions. Each decision has a reward according to the distributions of arms. The goal is to identify the decision with the maximum reward, using as few arm samples as possible. The problem generalizes the combinatorial pure exploration problem with linear rewards, which has attracted significant attention in recent years. In this paper, we propose an adaptive learning algorithm for the CPE-CS problem, and analyze its sample complexity. In particular, we introduce a new hardness measure called the consistent optimality hardness, and give both the upper and lower bounds of sample complexity. Moreover, we give examples to demonstrate that our solution has the capacity to deal with non-linear reward functions.

cs.LG↗

arXiv2017

Nematic superconducting state in iron pnictide superconductors

Nematic order often breaks the tetragonal symmetry of iron-based superconductors. It arises from regular structural transition or electronic instability in the normal phase. Here, we report the observation of a nematic superconducting state, by measuring the angular dependence of the in-plane and out-of-plane magnetoresistivity of Ba0.5K0.5Fe2As2 single crystals. We find large twofold oscillations in the vicinity of the superconducting transition, when the direction of applied magnetic field is rotated within the basal plane. To avoid the influences from sample geometry or current flow direction, the sample was designed as Corbino-shape for in-plane and mesa-shape for out-of-plane measurements. Theoretical analysis shows that the nematic superconductivity arises from the weak mixture of the quasi-degenerate s-wave and d-wave components of the superconducting condensate, most probably induced by a weak anisotropy of stresses inherent to single crystals.

cond-mat.supr-con↗

arXiv2017

Scaling law of high harmonic generation in the framework of photon channel

Photon channel perspective on high harmonic generation (HHG) is proposed by quantizing both the driving laser and high harmonics. It is shown that the HHG yield can be expressed as a sum of the contribution of all the photon channels. From this perspective, the contribution of a specific photon channel follows a simple scaling law and the competition between the channels is well interpreted. Our prediction is shown to be in good agreement with the simulations by solving the time-dependent Schrodinger equation. It also can well explains the experimental results of the HHG in the noncollinear two-color field and bicicular laser field.

physics.atom-ph↗

arXiv2017

High-order harmonic generation of doped semiconductor

We investigate the high-order harmonic generation (HHG) in doped semiconductors. The HHG is simulated with the single-electron time-dependent Schrödinger equation (TDSE). The results show that the high-order harmonics in the second plateau generated from the doped semiconductors is about 1 to 3 orders of magnitude higher than those from the undoped semiconductor. The results are explained based on the analysis of the energy band structure and the time-dependent population imaging. Our work indicates that doping can effectively control the HHG in semiconductor.

physics.optics↗

arXiv2017

Demonstration of Laser-produced Neutron Diagnostic by Radiative Capture Gamma-rays

We report a new scenario of time-of-flight (TOF) technique in which fast neutrons and delayed gamma-ray signals were both recorded in a millisecond time window in harsh environments induced by high-intensity lasers. The delayed gamma signals, arriving far later than the original fast neutron and often being ignored previously, were identified to be the results of radiative captures of thermalized neutrons. The linear correlation between gamma photon number and the fast neutron yield shows that these delayed gamma events can be employed for neutron diagnosis. This method can reduce the detecting efficiency dropping problem caused by prompt high-flux gamma radiation, and provides a new way for neutron diagnosing in high-intensity laser-target interaction experiments.

physics.ins-det↗

arXiv2017

Variable Version Lovász Local Lemma: Beyond Shearer's Bound

A tight criterion under which the abstract version Lovász Local Lemma (abstract-LLL) holds was given by Shearer decades ago. However, little is known about that of the variable version LLL (variable-LLL) where events are generated by independent random variables, though this model of events is applicable to almost all applications of LLL. We introduce a necessary and sufficient criterion for variable-LLL, in terms of the probabilities of the events and the event-variable graph specifying the dependency among the events. Based on this new criterion, we obtain boundaries for two families of event-variable graphs, namely, cyclic and treelike bigraphs. These are the first two non-trivial cases where the variable-LLL boundary is fully determined. As a byproduct, we also provide a universal constructive method to find a set of events whose union has the maximum probability, given the probability vector and the event-variable graph. Though it is #P-hard in general to determine variable-LLL boundaries, we can to some extent decide whether a gap exists between a variable-LLL boundary and the corresponding abstract-LLL boundary. In particular, we show that the gap existence can be decided without solving Shearer's conditions or checking our variable-LLL criterion. Equipped with this powerful theorem, we show that there is no gap if the base graph of the event-variable graph is a tree, while gap appears if the base graph has an induced cycle of length at least 4. The problem is almost completely solved except when the base graph has only 3-cliques, in which case we also get partial solutions. A set of reduction rules are established that facilitate to infer gap existence of an event-variable graph from known ones. As an application, various event-variable graphs, in particular combinatorial ones, are shown to be gapful/gapless.

cs.DM↗

arXiv2017

Quantifying and Estimating the Predictive Accuracy for Censored Time-to-Event Data with Competing Risks

This paper focuses on quantifying and estimating the predictive accuracy of prognostic models for time-to-event outcomes with competing events. We consider the time-dependent discrimination and calibration metrics, including the receiver operating characteristics curve and the Brier score, in the context of competing risks. To address censoring, we propose a unified nonparametric estimation framework for both discrimination and calibration measures, by weighting the censored subjects with the conditional probability of the event of interest given the observed data. We demonstrate through simulations that the proposed estimator is unbiased, efficient and robust against model misspecification in comparison to other methods published in the literature. In addition, the proposed method can be extended to time-dependent predictive accuracy metrics constructed from a general class of loss functions. We apply the methodology to a data set from the African American Study of Kidney Disease and Hypertension to evaluate the predictive accuracy of a prognostic risk score in predicting end-stage renal disease (ESRD), accounting for the competing risk of pre-ESRD death.

stat.ME↗

arXiv2017

Dynamic Prediction for Multiple Repeated Measures and Event Time Data: An Application to Parkinson's Disease

In many clinical trials studying neurodegenerative diseases such as Parkinson's disease (PD), multiple longitudinal outcomes are collected to fully explore the multidimensional impairment caused by this disease. If the outcomes deteriorate rapidly, patients may reach a level of functional disability sufficient to initiate levodopa therapy for ameliorating disease symptoms. An accurate prediction of the time to functional disability is helpful for clinicians to monitor patients' disease progression and make informative medical decisions. In this article, we first propose a joint model that consists of a semiparametric multilevel latent trait model (MLLTM) for the multiple longitudinal outcomes, and a survival model for event time. The two submodels are linked together by an underlying latent variable. We develop a Bayesian approach for parameter estimation and a dynamic prediction framework for predicting target patients' future outcome trajectories and risk of a survival event, based on their multivariate longitudinal measurements. Our proposed model is evaluated by simulation studies and is applied to the DATATOP study, a motivating clinical trial assessing the effect of deprenyl among patients with early PD.

stat.AP↗

arXiv2017

Study on space-time structure of Higgs boson decay using HBT correlation Method in e$^+$e$^-$ collision at $\sqrt{s}$=250 GeV

The space-time structure of the Higgs boson decay are carefully studied with the HBT correlation method using e$^+$e$^-$ collision events produced through Monte Carlo generator PYTHIA 8.2 at $\sqrt{s}$=250GeV. The Higgs boson jets (Higgs-jets) are identified by H-tag tracing. The measurement of the Higgs boson radius and decay lifetime are derived from HBT correlation of its decay final state pions inside Higgs-jets in the e$^+$e$^-$ collisions events with an upper bound of $R_H \le 1.03\pm 0.05$ fm and $τ_H \le (1.29\pm0.15)\times 10^{-7}$ fs. This result is consistent with CMS data.

hep-ph↗

arXiv2017

Magnetic tunneling induced Weyl node annihilation in TaP

Weyl nodes are topological objects in three-dimensional metals. Their topological property can be revealed by studying the high-field transport properties of a Weyl semimetal. While the energy of the lowest Landau band (LLB) of a conventional Fermi pocket always increases with magnetic field due to the zero point energy, the LLB of Weyl cones remains at zero energy unless a strong magnetic field couples the Weyl fermions of opposite chirality. In the Weyl semimetal TaP, we achieve such a magnetic coupling between the electron-like Fermi pockets arising from the W1 Weyl fermions. As a result, their LLBs move above chemical potential, leading to a sharp sign reversal in the Hall resistivity at a specific magnetic field corresponding to the W1 Weyl node separation. By contrast, despite having almost identical carrier density, the annihilation is unobserved for the hole-like pockets because the W2 Weyl nodes are much further separated. These key findings, corroborated by other systematic analyses, reveal the nontrivial topology of Weyl fermions in high-field measurements.

cond-mat.str-el↗