arXiv subjects

Cheng Liu

Publications and source records attributed to Cheng Liu.

At least 145 records · Page 8Linked to original sources

arXiv2023

Variation Enhanced Attacks Against RRAM-based Neuromorphic Computing System

The RRAM-based neuromorphic computing system has amassed explosive interests for its superior data processing capability and energy efficiency than traditional architectures, and thus being widely used in many data-centric applications. The reliability and security issues of the NCS therefore become an essential problem. In this paper, we systematically investigated the adversarial threats to the RRAM-based NCS and observed that the RRAM hardware feature can be leveraged to strengthen the attack effect, which has not been granted sufficient attention by previous algorithmic attack methods. Thus, we proposed two types of hardware-aware attack methods with respect to different attack scenarios and objectives. The first is adversarial attack, VADER, which perturbs the input samples to mislead the prediction of neural networks. The second is fault injection attack, EFI, which perturbs the network parameter space such that a specified sample will be classified to a target label, while maintaining the prediction accuracy on other samples. Both attack methods leverage the RRAM properties to improve the performance compared with the conventional attack methods. Experimental results show that our hardware-aware attack methods can achieve nearly 100% attack success rate with extremely low operational cost, while maintaining the attack stealthiness.

cs.CR↗

arXiv2023

Low-dimensional metal-organic magnets as a route towards the S=2 Haldane phase

Metal-organic magnets (MOMs), modular magnetic materials where metal atoms are connected by organic linkers, are promising candidates for next-generation quantum technologies. MOMs readily form low-dimensional structures, and so are ideal systems to realise physical examples of key quantum models, including the Haldane phase, where a topological excitation gap occurs in integer-spin antiferromagnetic (AFM) chains. Thus far the Haldane phase has only been identified for $S=1$, with $S \geq 2$ still unrealised because the larger spin imposes more stringent requirements on the magnetic interactions. Here, we report the structure and magnetic properties of CrCl$_2$(pym) (pym=pyrimidine), a new quasi-1D $S=2$ AFM MOM. We show, using X-ray and neutron diffraction, bulk property measurements, density-functional theory calculations and inelastic neutron spectroscopy (INS) that CrCl$_2$(pym) consists of AFM CrCl$_2$ spin chains ($J_1=-1.13(4)\;$meV) which are weakly ferromagnetically coupled through bridging pym ($J_2=0.10(2)\;$meV), with easy-axis anisotropy ($D=-0.15(3)\;$meV). We find that although small compared to $J_1$, these additional interactions are sufficient to prevent observation of the Haldane phase in this material. Nevertheless, the proximity to the Haldane phase together with the modularity of MOMs suggests that layered Cr(II) MOMs are a promising family to search for the elusive $S=2$ Haldane phase.

cond-mat.str-el↗

arXiv2022

SeaDroneSim: Simulation of Aerial Images for Detection of Objects Above Water

Unmanned Aerial Vehicles (UAVs) are known for their fast and versatile applicability. With UAVs' growth in availability and applications, they are now of vital importance in serving as technological support in search-and-rescue(SAR) operations in marine environments. High-resolution cameras and GPUs can be equipped on the UAVs to provide effective and efficient aid to emergency rescue operations. With modern computer vision algorithms, we can detect objects for aiming such rescue missions. However, these modern computer vision algorithms are dependent on numerous amounts of training data from UAVs, which is time-consuming and labor-intensive for maritime environments. To this end, we present a new benchmark suite, SeaDroneSim, that can be used to create photo-realistic aerial image datasets with the ground truth for segmentation masks of any given object. Utilizing only the synthetic data generated from SeaDroneSim, we obtain 71 mAP on real aerial images for detecting BlueROV as a feasibility study. This result from the new simulation suit also serves as a baseline for the detection of BlueROV.

cs.CV↗

arXiv2022

Deep Fusion Prior for Plenoptic Super-Resolution All-in-Focus Imaging

Multi-focus image fusion (MFIF) and super-resolution (SR) are the inverse problem of imaging model, purposes of MFIF and SR are obtaining all-in-focus and high-resolution 2D mapping of targets. Though various MFIF and SR methods have been designed; almost all the them deal with MFIF and SR separately. This paper unifies MFIF and SR problems in the physical perspective as the multi-focus image super resolution fusion (MFISRF), and we propose a novel unified dataset-free unsupervised framework named deep fusion prior (DFP) based-on deep image prior (DIP) to address such MFISRF with single model. Experiments have proved that our proposed DFP approaches or even outperforms those state-of-art MFIF and SR method combinations. To our best knowledge, our proposed work is a dataset-free unsupervised method to simultaneously implement the multi-focus fusion and super-resolution task for the first time. Additionally, DFP is a general framework, thus its networks and focus measurement tactics can be continuously updated to further improve the MFISRF performance. DFP codes are open source available at http://github.com/GuYuanjie/DeepFusionPrior.

cs.CV↗

arXiv2022

Statistical Modeling of Soft Error Influence on Neural Networks

Soft errors in large VLSI circuits pose dramatic influence on computing- and memory-intensive neural network (NN) processing. Understanding the influence of soft errors on NNs is critical to protect against soft errors for reliable NN processing. Prior work mainly rely on fault simulation to analyze the influence of soft errors on NN processing. They are accurate but usually specific to limited configurations of errors and NN models due to the prohibitively slow simulation speed especially for large NN models and datasets. With the observation that the influence of soft errors propagates across a large number of neurons and accumulates as well, we propose to characterize the soft error induced data disturbance on each neuron with normal distribution model according to central limit theorem and develop a series of statistical models to analyze the behavior of NN models under soft errors in general. The statistical models reveal not only the correlation between soft errors and NN model accuracy, but also how NN parameters such as quantization and architecture affect the reliability of NNs. The proposed models are compared with fault simulation and verified comprehensively. In addition, we observe that the statistical models that characterize the soft error influence can also be utilized to predict fault simulation results in many cases and we explore the use of the proposed statistical models to accelerate fault simulations of NNs. According to our experiments, the accelerated fault simulation shows almost two orders of magnitude speedup with negligible simulation accuracy loss over the baseline fault simulations.

cs.LG↗

arXiv2022

Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement Learning

Enabling the capability of assessing risk and making risk-aware decisions is essential to applying reinforcement learning to safety-critical robots like drones. In this paper, we investigate a specific case where a nano quadcopter robot learns to navigate an apriori-unknown cluttered environment under partial observability. We present a distributional reinforcement learning framework to generate adaptive risk-tendency policies. Specifically, we propose to use lower tail conditional variance of the learnt return distribution as intrinsic uncertainty estimation, and use exponentially weighted average forecasting (EWAF) to adapt the risk-tendency in accordance with the estimated uncertainty. In simulation and real-world empirical results, we show that (1) the most effective risk-tendency vary across states, (2) the agent with adaptive risk-tendency achieves superior performance compared to risk-neutral policy or risk-averse policy baselines.

cs.RO↗

arXiv2022

Prospective Study on Observations of γ-Ray Sources in the Galaxy Using the HADAR Experiment

The High Altitude Detection of Astronomical Radiation (HADAR) experiment is a refracting terrestrial telescope array based on the atmospheric Cherenkov imaging technique. It focuses the Cherenkov light emitted by extensive air showers through a large aperture water-lens system for observing very-high-energy-rays and cosmic rays. With the advantages of a large field-of-view (FOV) and low energy threshold, the HADAR experiment operates in a large-scale sky scanning mode to observe galactic sources. This study presents the prospects of using the HADAR experiment for the sky survey of TeV γ-ray sources from TeVCat and provids a one-year survey of statistical significance. Results from the simulation show that a total of 23 galactic point sources, including five supernova remnant sources and superbubbles, four pulsar wind nebula sources, and 14 unidentified sources, were detected in the HADAR FOV with a significance greater than 5 standard deviations (σ). The statistical significance for the Crab Nebula during one year of operation reached 346.0 σ and the one-year integral sensitivity of HADAR above 1TeV was ~1.3%-2.4% of the flux from the Crab Nebula.

astro-ph.HE↗

arXiv2022

Optimal covariance matrix estimation for high-dimensional noise in high-frequency data

We consider high-dimensional measurement errors with high-frequency data. Our objective is on recovering the high-dimensional cross-sectional covariance matrix of the random errors with optimality. In this problem, not all components of the random vector are observed at the same time and the measurement errors are latent variables, leading to major challenges besides high data dimensionality. We propose a new covariance matrix estimator in this context with appropriate localization and thresholding, and then conduct a series of comprehensive theoretical investigations of the proposed estimator. By developing a new technical device integrating the high-frequency data feature with the conventional notion of $α$-mixing, our analysis successfully accommodates the challenging serial dependence in the measurement errors. Our theoretical analysis establishes the minimax optimal convergence rates associated with two commonly used loss functions; and we demonstrate with concrete cases when the proposed localized estimator with thresholding achieves the minimax optimal convergence rates. Considering that the variances and covariances can be small in reality, we conduct a second-order theoretical analysis that further disentangles the dominating bias in the estimator. A bias-corrected estimator is then proposed to ensure its practical finite sample performance. We also extensively analyze our estimator in the setting with jumps, and show that its performance is reasonably robust. We illustrate the promising empirical performance of the proposed estimator with extensive simulation studies and a real data analysis.

math.ST↗

arXiv2022

Multimode optomechanical cooling via general dark-mode control

The dark-mode effect is a stubborn obstacle for ground-state cooling of multiple degenerate mechanical modes optomechanically coupled to a common cavity-field mode. Here we propose an auxiliary-cavity-mode method for simultaneous ground-state cooling of two degenerate or near-degenerate mechanical modes by breaking the dark mode. We find that the introduction of the auxiliary cavity mode not only breaks the dark-mode effect, but also provides a new cooling channel to extract the thermal excitations stored in the dark mode. Moreover, we study the general physical-coupling configurations for breaking the dark mode in a generalized networkcoupled four-mode optomechanical system consisting of two cavity modes and two mechanical modes. We find the analytical dark-mode-breaking condition in this system. This method is general and it can be generalized to break the dark-mode effect and to realize the simultaneous ground-state cooling in a multiple-mechanicalmode optomechanical system. We also demonstrate the physical mechanism behind the dark-mode breaking by studying the breaking of dark-state effect in the N-type four-level atomic system. Our results not only provide a general method to control various dark-mode and dark-state effects in physics, but also present an opportunity to the study of macroscopic quantum phenomena and applications in multiple-mechanical-resonator systems.

quant-ph↗

arXiv2022

Constraints on self-dual black hole in loop quantum gravity with S0-2 star in the Galactic Center

One of remarkable features of loop quantum gravity (LQG) is that it can provide resolutions to both the black hole and big bang singularities. In the mini-superspace approach based on the polymerization procedure in LQG, a quantum corrected black hole metric is constructed. This metric is also known as self-dual spacetime since the form of the metric is invariant under the exchange $r \to a_0/r$ with $a_0$ being proportional to the minimum area in LQG and $r$ is the standard radial coordinate at asymptotic infinity. It modifies the Schwarzschild spacetime by the polymeric function $P$, purely due to the geometric quantum effects from LQG. Here $P$ is related to the polymeric parameter $δ$ which is introduced to define the paths one integrates the connection along to define the holonomies in the quantum corrected Hamiltonian constraint in the polymerization procedure in LQG. In this paper, we consider its effects on the orbital signatures of S0-2 star orbiting Sgr A* in the central region of our Milky Way, and compare it with the publicly available astrometric and spectroscopic data, including the astrometric positions, the radial velocities, and the orbital precession for the S0-2 star. We perform Monte Carlo Markov Chain (MCMC) simulations to probe the possible LQG effects on the orbit of S0-2 star. No significant evidence of the self-dual spacetime arisIng from LQG is found. We thus place an upper bounds at 95\% confidence level on the polymeric function $P < 0.043$ and $P < 0.056$, for Gaussian and uniform priors on orbital parameters, respectively.

gr-qc↗

arXiv2022

LTD064402+245919, compact binary or subgiant with red star eclipsing binary?

Recently, a single-line spectroscopic binary, LTD064402+245919, has been discovered by Yang et al. Using data from LAMOST and ZTF, the unseen companion is estimated to have a mass of 1-3 $M_{\odot}$, orbiting a subgiant with orbital period of 14.50 days, making it a good compact binary candidate without X-ray emission. However, new light curves from ZTF and ASAS-SN, have shown the depth of one dip increases towards a bluer wavelength, indicating LTD064402+245919 is more likely to be a subgiant with a red star. Using both Wilson-Devinney code and Phoebe, the derived $T_{eff}$ of secondary is about 3400 K, corresponding to a red M2/3 star. Additionally, the 20% error of parallax from Gaia is large. The mass of subgiant will be 1.28 $M_{\odot}$ instead of 2.77 $M_{\odot}$, if the refined distance of 5.0kpc is used. Nevertheless, new multi-colour photometry are warranted for the final confirmation of binary properties.

astro-ph.SR↗

arXiv2022

A spectroscopic study of blue supergiant stars in Local Group spiral galaxies: Andromeda and Triangulum

Low-resolution LAMOST and Keck spectra of blue supergiant stars distributed over the disks of the Local Group spiral galaxies M 31 and M 33 are analyzed to determine stellar effective temperatures, gravities, metallicities, and reddening. Logarithmic metallicities at the center of the galaxies (in solar units) of $0.30\pm0.09$ and $0.11\pm0.04$ and metallicity gradients of $-0.37\pm0.13$ dex/$R_{25}$ and $-0.36\pm0.16$ dex/$R_{25}$ are measured for M 31 and M 33, respectively. For M 33 the 2-dimensional distribution of metallicity indicates a deviation from azimutal symmetry with an off-centre peak. The flux-weighted gravity-luminosity relationship of blue supergiant stars is used to determine a distance modulus of 24.51$\pm$0.13 mag for M 31 and 24.93$\pm$0.07 mag for M 33. For M 31 the flux-weighted gravity--luminosity relationship (FGLR) distance agrees well with other methods. For M 33 the FGLR-based distance is larger than the distances from Cepheids studies but it is in good agreement with work on eclipsing binaries, planetary nebulae , long-period variables, and the tip of the red giant branch.

astro-ph.GA↗

arXiv2022

Fault-Tolerant Deep Learning: A Hierarchical Perspective

With the rapid advancements of deep learning in the past decade, it can be foreseen that deep learning will be continuously deployed in more and more safety-critical applications such as autonomous driving and robotics. In this context, reliability turns out to be critical to the deployment of deep learning in these applications and gradually becomes a first-class citizen among the major design metrics like performance and energy efficiency. Nevertheless, the back-box deep learning models combined with the diverse underlying hardware faults make resilient deep learning extremely challenging. In this special session, we conduct a comprehensive survey of fault-tolerant deep learning design approaches with a hierarchical perspective and investigate these approaches from model layer, architecture layer, circuit layer, and cross layer respectively.

cs.AR↗

arXiv2022

Thin Accretion Disk onto slowly rotating black holes in Einstein-Æther theory

The accretion disk is formed by particles moving in closed orbits around a compact object, whose physical properties and the electromagnetic radiation characteristics are determined by the space-time geometry around the compact object. In this paper, we study the physical properties and the optical appearance of the electromagnetic radiation emitted from a thin accretion disk around the two types of the black hole solution in Einstein-Æther theory. We investigate in detail the effects of the æther field on the energy flux, temperature distribution, and electromagnetic spectrum of the disk in the two types of slowly rotating Einstein-Æther black holes. Then we plot the ray-traced redshifted image as well as the intensity and polarization profile of a lensed accretion disk around the two types of Einstein-Æther black holes. We found that from the image simulation, the æther field only has a certain effect on the central shadow area of the accretion disk.

gr-qc↗

arXiv2022

Free-spin dominated magnetocaloric effect in dense Gd$^{3+}$ double perovskites

Frustrated lanthanide oxides with dense magnetic lattices are of fundamental interest for their potential in cryogenic refrigeration due to a large ground state entropy and suppressed ordering temperatures, but can often be limited by short-range correlations. Here, we present examples of frustrated fcc oxides, Ba$_2$GdSbO$_6$ and Sr$_2$GdSbO$_6$ and the new site-disordered analog Ca$_2$GdSbO$_6$ ([CaGd]$_A$[CaSb]$_B$O$_6$), in which the magnetocaloric effect is influenced by minimal superexchange ($J_1 \sim 10$ mK). We report on the crystal structures using powder x-ray diffraction and the bulk magnetic properties through low-field susceptibility and isothermal magnetization measurements. The Gd compounds exhibit a magnetic entropy change of up to -15.8 J/K/mol$_\textrm{Gd}$ in a field of 7 T at 2 K, a 20 % excess compared to the value of -13.0 J/K/mol$_\textrm{Gd}$ for a standard in magnetic refrigeration, Gd$_3$Ga$_5$O$_{12}$. Heat capacity measurements indicate a lack of magnetic ordering down to 0.4 K for Ba$_2$GdSbO$_6$ and Sr$_2$GdSbO$_6$, suggesting cooling down through the liquid 4-He regime. A mean-field model is used to elucidate the role of primarily free spin behavior in the magnetocaloric performance of these compounds in comparison to other top-performing Gd-based oxides. The chemical flexibility of the double perovskites raises the possibility of further enhancement of the magnetocaloric effect in the Gd$^{3+}$ fcc lattices.

cond-mat.str-el↗

arXiv2022

Comparative structural evolution under pressure of powder and single crystals of the layered antiferromagnet FePS$_3$

The layered antiferromagnet FePS$_3$ has been shown to undergo a structural transition under pressure linked to an insulator-metal transition, with two incompatible models previously proposed for the highest-pressure structure. We present a study of the high-pressure crystal structures of FePS$_3$ using both single-crystal and powder x-ray diffraction. We show that the highest pressure transition involves a collapse of the inter-planar spacing of this material, along with an increase in symmetry from a monoclinic to a trigonal structure, to the exclusion of other models. The extent of this volume collapse is shown to be sensitive to the presence of a helium pressure medium in the sample environment, indicating that consideration of such experimental factors is important for understanding high-pressure behaviours in this material.

cond-mat.str-el↗

arXiv2022

Displacement calibration of optical tweezers with absolute gravitational acceleration

In recent years, levitated particles of optical traps in vacuum have shown enormous potential in precision sensor development and searching for new physics. The accuracy of the calibration relating the detected signal to absolute displacement of the trapped particle is a critical factor for absolute measurement performance. In this paper, we suggest and experimentally demonstrate a novel calibration method for optical tweezers based on free-falling particles in vacuum, where the gravitational acceleration is introduced as an absolute reference. Our work provides a calibration protocol with great certainty and traceability, which is significant in improving the accuracy of precision sensing based on optically levitated particles.

physics.ins-det↗

arXiv2022

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

astro-ph.HE↗