arXiv subjects

Tong Liu

Publications and source records attributed to Tong Liu.

At least 271 records · Page 15Linked to original sources

arXiv2021

Fate of Majorana zero modes by a modified real-space-Pfaffian method and mobility edges in a one-dimensional quasiperiodic lattice

We aim to study a one-dimensional $p$-wave superconductor with quasiperiodic on-site potentials. A modified real-space-Pfaffian method is applied to calculate the topological invariants. We confirm that the Majorana zero mode is protected by the nontrivial topology the topological phase transition is accompanied by the energy gap closing and reopening. In addition, we numerically find that there are mobility edges which originate from the competition between the extended $p$-wave pairing and the localized quasi-disorder. We qualitatively analyze the influence of superconducting pairing parameters and on-site potential strength on the mobility edge. In general, our work enriches the research on the $p$-wave superconducting models with quasiperiodic potentials.

cond-mat.dis-nn↗

arXiv2021

Neutrino-dominated accretion flows: second nucleosynthesis factory in core-collapse supernovae and regulation of iron markets in galaxies

Cosmic metals are widely believed to be produced by supernovae (SNe) and compact object mergers. Here, we discuss the nucleosynthesis of neutrino-dominated accretion flows (NDAFs) with outflows in the core-collapse SNe (CCSNe), and show that the outflows from NDAFs can have a significant contribution to the $^{56}$Ni abundance in the faint explosions if the masses of the progenitor stars are within about $25-50$ $M_\odot$. Less massive progenitor stars can produce more $^{56}$Ni than their more massive counterparts in the NDAF outflow nucleosynthesis channel. Therefore, we find that the total (i.e., CCSNe and NDAF outflows) $^{56}$Ni mass per CCSN depends only weakly upon the mass of progenitor stars. In the metallicity evolution, the ratio of $^{56}$Fe (decayed by $^{56}$Ni) mass to the initial total gas mass can increase by $\sim$ 1.95 times if the upper limits of the nucleosynthesis yields from NDAF outflows and CCSNe are considered. Our results might have significant implication for chemical evolution of the the solar neighborhood, galaxies, and active galactic nuclei.

astro-ph.HE↗

arXiv2021

Co-doping effects on magnetism and superconductivity in the 112-type EuFeAs2 system

The discovery of EuFeAs2, currently the only charge-neutral parent phase of the 112-type iron-pnictide system, provides a new platform for the study of elemental doping effects on magnetism and superconductivity (SC). In this study, a series of polycrystalline EuFe1-yCoyAs2 and Eu0.9Pr0.1Fe1-yCoyAs2 samples are synthesized through solid-state reaction, and the evolutions of SC and magnetism with Co doping in EuFeAs2 and Eu0.9Pr0.1FeAs2 are investigated by electrical transport and magnetic susceptibility measurements. For EuFe1-yCoyAs2, the Eu-related antiferromagnetic (AFM) transition around 40 K is barely affected by Co doping, while the Fe-related spin density wave (SDW) transition temperature drops rapidly. Meanwhile, SC is induced by a trace amount of Co doping, with a highest transition temperature Tc ~ 28 K found in EuFe0.9Co0.1As2. For the Eu0.9Pr0.1Fe1-yCoyAs2 series, the magnetism and superconductivity show similar evolutions upon Co doping, and the highest Tc is enhanced to 30.6 K with an optimum doping level y ~ 0.07. Our results shed light on the competition between SC and SDW with Co doping in the 112-type EuFeAs2 system.

cond-mat.supr-con↗

arXiv2021

Coexistence of ferromagnetism, antiferromagnetism, and superconductivity in magnetically anisotropic (Eu,La)FeAs2

Materials with exceptional magnetism and superconductivity usually conceive emergent physical phenomena. Here, we investigate the physical properties of the (Eu,La)FeAs2 system with double magnetic sublattices. The parent EuFeAs2 shows anisotropy-associated magnetic behaviors, such as Eu-related moment canting and exchange bias. Through La doping, the magnetic anisotropy is enhanced with ferromagnetism of Eu2+ realized in the overdoped region, and a special exchange bias of the superposed ferromagnetic/superconducting loop revealed in Eu0.8La0.2FeAs2. Meanwhile, the Fe-related antiferromagnetism shows unusual robustness against La doping. Theoretical calculation and 57Fe Mössbauer spectroscopy investigation reveal a doping-tunable dual itinerant/localized nature of the Fe-related antiferromagnetism. Coexistence of the Eu-related ferromagnetism, Fe-related robust antiferromagnetism, and superconductivity is further revealed in Eu0.8La0.2FeAs2, providing a platform for further exploration of potential applications and emergent physics. Finally, an electronic phase diagram is established for (Eu,La)FeAs2 with the whole superconducting dome adjacent to the Fe-related antiferromagnetic phase, which is of benefit for seeking underlying clues to high-temperature superconductivity.

cond-mat.supr-con↗

arXiv2021

Multi-Level Graph Contrastive Learning

Graph representation learning has attracted a surge of interest recently, whose target at learning discriminant embedding for each node in the graph. Most of these representation methods focus on supervised learning and heavily depend on label information. However, annotating graphs are expensive to obtain in the real world, especially in specialized domains (i.e. biology), as it needs the annotator to have the domain knowledge to label the graph. To approach this problem, self-supervised learning provides a feasible solution for graph representation learning. In this paper, we propose a Multi-Level Graph Contrastive Learning (MLGCL) framework for learning robust representation of graph data by contrasting space views of graphs. Specifically, we introduce a novel contrastive view - topological and feature space views. The original graph is first-order approximation structure and contains uncertainty or error, while the $k$NN graph generated by encoding features preserves high-order proximity. Thus $k$NN graph generated by encoding features not only provide a complementary view, but is more suitable to GNN encoder to extract discriminant representation. Furthermore, we develop a multi-level contrastive mode to preserve the local similarity and semantic similarity of graph-structured data simultaneously. Extensive experiments indicate MLGCL achieves promising results compared with the existing state-of-the-art graph representation learning methods on seven datasets.

cs.LG↗

arXiv2021

MCMC Confidence Intervals and Biases

The recent paper "Simple confidence intervals for MCMC without CLTs" by J.S. Rosenthal, showed the derivation of a simple MCMC confidence interval using only Chebyshev's inequality, not CLT. That result required certain assumptions about how the estimator bias and variance grow with the number of iterations $n$. In particular, the bias is $o(1/\sqrt{n})$. This assumption seemed mild. It is generally believed that the estimator bias will be $O(1/n)$ and hence $o(1/\sqrt{n})$. However, questions were raised by researchers about how to verify this assumption. Indeed, we show that this assumption might not always hold. In this paper, we seek to simplify and weaken the assumptions in the previously mentioned paper, to make MCMC confidence intervals without CLTs more widely applicable.

math.ST↗

arXiv2021

Final compact remnants in core-collapse supernovae from 20 to 40 $M_\odot$: the lower mass gap

A mass paucity of compact objects in the range of $\sim 2-5 ~M_\odot$ has been suggested by X-ray binary observations, namely, the "lower mass gap". Gravitational wave detections have unlocked another mass measurement method, and aLIGO/Virgo has observed some candidates in the gap. We revisit the numerical simulations on the core-collapse supernovae (CCSNe) for $\sim 20-40~M_\odot$ progenitor stars with differently initial explosion energies. As a result, the lower explosion energy naturally causes more efficient fallback accretion for low-metallicity progenitors, and then the newborn black holes (BHs) in the center of the CCSNe can escape from the gap, but neutron stars cannot easily collapse into BHs in the gap; nevertheless, the final remnants of the solar-metallicity progenitors stick to the gap. If we consider that only drastic CCSNe can be observed and that those with lower explosion energies are universal, the lower mass gap can be reasonably built. The width and depth of the gap are mainly determined by the typical CCSN initial explosion energy and metallicity. One can expect that the future multi-messenger observations of compact objects delineate the shape of the gap, which might constrain the properties of the CCSNe and their progenitors.

astro-ph.HE↗

arXiv2021

Energy injection driven by precessing jets in gamma-ray burst afterglows

Jet precession is considered to universally exist in different-scale astronomical phenomena, including gamma-ray bursts (GRBs). For the long-lived GRB central engine, the relativistical precessing jets will periodically inject kinetic energy into the external shocks, then significantly modulate the shapes of the light curves (LCs) in GRB afterglows. In this paper, we adopt the standard external shock model to investigate the effects of jet precession on GRB X-ray afterglows in cases with different parameters, i.e., the steady or time-dependent jet powers, precession periods, precession angles, and viewing angles. In the case where the jet powers are in steady or slow decay and the jet can sweep across the line of sight, shallow decay (or plateau) segments should appear; otherwise, a giant bump will emerge in the GRB afterglow LCs. We show that jet precession is a new plausible mechanism of the energy injection in GRBs. Moreover, some observed X-ray transients without GRB associations might be powered by the precessing jets.

astro-ph.HE↗

arXiv2021

Mobility edges in $\mathcal{PT}$-symmetric cross-stitch flat band lattices

We study the cross-stitch flat band lattice with a $\mathcal{PT}$-symmetric on-site potential and uncover mobility edges with exact solutions. Furthermore, we study the relationship between the $\mathcal{PT}$ symmetry broken point and the localization-delocalization transition point, and verify that mobility edges in this non-Hermitian model is available to signal the $\mathcal{PT}$ symmetry breaking.

cond-mat.dis-nn↗

arXiv2021

Invariable mobility edge in a quasiperiodic lattice

In this paper, we study a one-dimensional tight-binding model with tunable incommensurate potentials. Through the analysis of the inverse participation rate, we uncover that the wave functions corresponding to the energies of the system exhibit different properties. There exists a critical energy under which the wave functions corresponding to all energies are extended. On the contrary, the wave functions corresponding to all energies above the critical energy are localized. However, we are surprised to find that the critical energy is a constant independent of the potentials. We use the self-dual relation to solve the critical energy, namely the mobility edge, and then we verify the analytical results again by analyzing the spatial distributions of the wave functions. Finally, we give a brief discussion on the possible experimental observation of the invariable mobility edge in the system of ultracold atoms in optical lattices.

cond-mat.dis-nn↗

arXiv2021

An Iterative Weighting Method to Apply ISR Correction to $e^+e^-$ Hadronic Cross-section Measurements

Initial state radiation (ISR) plays an important role in $e^+$$e^-$ collision experiments such as the BESIII. To correct the ISR effects in measurements of hadronic cross-sections of $e^+e^-$ annihilation, an iterative method that weights simulated ISR events is proposed here to assess the efficiency of event selection and the ISR correction factor for the observed cross-section. The simulated ISR events were generated only once, and the obtained cross-sectional line shape was used iteratively to weigh the same simulated ISR events to evaluate the efficiency and corrections until the results converge. Compared with the method of generating ISR events iteratively, the proposed weighting method provides consistent results, and reduces the computational time and disk space required by a factor of five or more, thus speeding-up $e^+e^-$ hadronic cross-section measurements.

hep-ex↗

arXiv2021

Chaotic Time-Delay Signature Suppression and Entropy Growth Enhancement Using Frequency-Band Extractor

By frequency-band extracting, we experimentally and theoretically investigate time-delay signature (TDS) suppression and entropy growth enhancement of a chaotic optical-feedback semiconductor laser under different injection currents and feedback strengths. The TDS and entropy growth are quantified by the peak value of autocorrelation function and the difference of permutation entropy at the feedback delay time. At the optimal extracting bandwidth, the measured TDS is suppressed up to 96% compared to the original chaos, and the entropy growth is higher than the noise-dominated threshold indicating that the dynamical process is noisy. The effects of extracting bandwidth and radio frequencies on the TDS and entropy growth are also clarified experimentally and theoretically. The experimental results are in good agreements with the theoretical results. The skewness of the laser intensity distribution is effectively improved to 0.001 with the optimal extracting bandwidth. This technique provides a promising tool to extract randomness and prepare desired entropy sources for chaotic secure communication and random number generation.

physics.optics↗

arXiv2021

Faint AGNs Favor Unexpectedly Long Inter-band Time Lags

Inconsistent conclusions are obtained from recent active galactic nuclei (AGNs) accretion disk inter-band time-lag measurements. While some works show that the measured time lags are significantly larger (by a factor of $\sim 3$) than the theoretical predictions of the Shakura \& Sunyaev disk (SSD) model, others find that the time-lag measurements are consistent with (or only slightly larger than) that of the SSD model. These conflicting observational results might be symptoms of our poor understanding of AGN accretion physics. Here we show that sources with larger-than-expected time lags tend to be less-luminous AGNs. Such a dependence is unexpected if the inter-band time lags are attributed to the light-travel-time delay of the illuminating variable X-ray photons to the static SSD. If, instead, the measured inter-band lags are related not only to the static SSD but also to the outer broad emission-line regions (BLRs; e.g., the blended broad emission lines and/or diffuse continua), our result indicates that the contribution of the non-disk BLR to the observed UV/optical continuum decreases with increasing luminosity ($L$), i.e., an anti-correlation resembling the well-known Baldwin effect. Alternatively, we argue that the observed dependence might be a result of coherent disk thermal fluctuations as the relevant thermal timescale, $τ_{\mathrm{TH}}\propto L^{0.5}$. With future accurate measurements of inter-band time lags, the above two scenarios can be distinguished by inspecting the dependence of inter-band time lags upon either the BLR components in the variable spectra or the timescales.

astro-ph.HE↗

arXiv2021

Model Reference Adaptive Control of Piecewise Affine Systems with State Tracking Performance Guarantees

In this paper, we investigate the model reference adaptive control approach for uncertain piecewise affine systems with performance guarantees. The proposed approach ensures the error metric, defined as the weighted Euclidean norm of the state tracking error, to be confined within a user-defined time-varying performance bound. We introduce an auxiliary performance function to construct a barrier Lyapunov function. This auxiliary performance signal is reset at each switching instant, which prevents the transgression of the barriers caused by the jumps of the error metric at switching instants. The dwell time constraints are derived based on the parameters of the user-defined performance bound and the auxiliary performance function. We also prove that the Lyapunov function is non-increasing even at the switching instants and thus does not impose extra dwell time constraints. Furthermore, we propose the robust modification of the adaptive controller for the uncertain piecewise affine systems subject to unmatched disturbances. A Numerical example validates the correctness of the proposed approach.

eess.SY↗

arXiv2021

Dual-mapping and quantum criticality in off-diagonal Aubry-André models

We study a class of off-diagonal quasiperiodic hopping models described by one-dimensional Su-Schrieffer-Heeger chain with quasiperiodic modulations. We unveil a general dual-mapping relation in parameter space of the dimerization strength $λ$ and the quasiperiodic modulation strength $V$, regardless of the specific details of the quasiperiodic modulation. Moreover, we demonstrated semi-analytically and numerically that under the specific quasiperiodic modulation, quantum criticality can emerge and persist in a wide parameter space. These unusual properties provides a distinctive paradigm compared with the diagonal quasiperiodic systems.

cond-mat.dis-nn↗

arXiv2020

Testing Blandford-Znajek mechanism in black hole hyperaccretion flows for long-duration gamma-ray bursts

Long-duration gamma-ray bursts (GRBs) are generally related to the core-collapse of massive stars. In the collapsar scenario, a rotating stellar-mass black hole (BH) surrounded by a hyperaccretion disk has been considered as one of the plausible candidates of GRB central engines. In this paper, we work on a sample including 146 long GRBs with significant jet break features in the multi-band afterglows. The jet opening angles can be then obtained by the jet break time. By asumming GRB jets powered by Blandford-Znajek (BZ) mechanism in the BH hyperaccretion system, we analyze the distributions of the long GRB luminosities and durations in the samples, and constrain the accretion rates for the different BH spins. As the results, we find that the BZ mechanism is so powerful making it possible to interpret the long GRB prompt emissions within the reasonably accretion rates.

astro-ph.HE↗

arXiv2020

Tucker decomposition-based Temporal Knowledge Graph Completion

Knowledge graphs have been demonstrated to be an effective tool for numerous intelligent applications. However, a large amount of valuable knowledge still exists implicitly in the knowledge graphs. To enrich the existing knowledge graphs, recent years witness that many algorithms for link prediction and knowledge graphs embedding have been designed to infer new facts. But most of these studies focus on the static knowledge graphs and ignore the temporal information that reflects the validity of knowledge. Developing the model for temporal knowledge graphs completion is an increasingly important task. In this paper, we build a new tensor decomposition model for temporal knowledge graphs completion inspired by the Tucker decomposition of order 4 tensor. We demonstrate that the proposed model is fully expressive and report state-of-the-art results for several public benchmarks. Additionally, we present several regularization schemes to improve the strategy and study their impact on the proposed model. Experimental studies on three temporal datasets (i.e. ICEWS2014, ICEWS2005-15, GDELT) justify our design and demonstrate that our model outperforms baselines with an explicit margin on link prediction task.

cs.AI↗

arXiv2020

Self-supervised Graph Representation Learning via Bootstrapping

Graph neural networks~(GNNs) apply deep learning techniques to graph-structured data and have achieved promising performance in graph representation learning. However, existing GNNs rely heavily on enough labels or well-designed negative samples. To address these issues, we propose a new self-supervised graph representation method: deep graph bootstrapping~(DGB). DGB consists of two neural networks: online and target networks, and the input of them are different augmented views of the initial graph. The online network is trained to predict the target network while the target network is updated with a slow-moving average of the online network, which means the online and target networks can learn from each other. As a result, the proposed DGB can learn graph representation without negative examples in an unsupervised manner. In addition, we summarize three kinds of augmentation methods for graph-structured data and apply them to the DGB. Experiments on the benchmark datasets show the DGB performs better than the current state-of-the-art methods and how the augmentation methods affect the performances.

cs.LG↗