arXiv subjects

Zhiyuan Li

Publications and source records attributed to Zhiyuan Li.

At least 307 records · Page 17Linked to original sources

arXiv2021

Discovery of Galaxy Clusters and a Head-Tail Radio Galaxy in the Direction of Globular Cluster NGC 6752

We report the discovery of CXOU J191100-595621 and CXOU J191012-595619, two galaxy clusters serendipitously detected in the direction of globular cluster NGC 6752, based on archival {\it Chandra} observations with a total exposure time of $\sim 344$ ks. The deep {\it Chandra} X-ray data enabled us to measure properties of both systems, which result in a redshift of $z=0.239\pm0.013$ and $z=0.375\pm0.016$, a temperature of $kT=3.32^{+0.57}_{-0.46}$ keV and $kT=3.71^{+1.18}_{-0.86}$ keV, an iron abundance of $Z_{\rm Fe}=0.64^{+0.34}_{-0.29}Z_{\rm Fe\odot}$ and $Z_{\rm Fe}=1.29^{+0.97}_{-0.65}Z_{\rm Fe\odot}$, and a rest-frame full band (0.5-7 keV) luminosity of $L_{\rm X}=9.2^{+1.2}_{-1.1}\times 10^{43} {\rm \, erg\, s^{-1}}$ and $L_{\rm X}=9.9^{+2.7}_{-2.2}\times 10^{43} {\rm \, erg\, s^{-1}}$ for CXOU J191100-595621 and CXOU J191012-595619, respectively. The temperature profile of CXOU J191100-595621 is found to decreases with decreasing radius, indicating a cool core in this cluster. The hydrostatic equilibrium estimation suggests the clusters are moderately weighted, with $M_{500}=(1.3\pm0.4)\times 10^{14}\, M_{\odot}$ and $M_{500}=(2.0\pm1.5)\times 10^{14}\, M_{\odot}$, respectively. We search for optical and radio counterparts of X-ray point sources in the clusters. Three active galactic nuclei are found, among which one is identified with a narrow-angle-tail radio galaxy, and one is found to associated with the brightest central galaxy (BCG) of CXOU J191100-595621.

astro-ph.HE↗

arXiv2021

Upcycling Low-Nickel Polycrystalline Cathodes from Retired Electric Vehicle Batteries into Single-Crystal Nickel-Rich Cathodes

The electrification revolution in automobile industry and others demands annual production capacity of batteries at least on the order of 102 gigawatts hours, which presents a twofold challenge to supply of key materials such as cobalt and nickel and to recycling when the batteries retire. Pyrometallurgical and hydrometallurgical recycling are currently used in industry but suffer from complexity, high costs, and secondary pollution. Here we report a direct-recycling method in molten salts (MSDR) that is environmentally benign and value-creating based on a techno-economic analysis using real-world data and price information. We also experimentally demonstrate the feasibility of MSDR by upcycling a low-nickel polycrystalline LiNi0.5Mn0.3Co0.2O2 (NMC) cathode material that is widely used in early-year electric vehicles into Ni-rich (Ni > 65%) single-crystal NMCs with increased energy-density (>10% increase) and outstanding electrochemical performance (>94% capacity retention after 500 cycles in pouch-type full cells). This work opens up new opportunities for closed-loop recycling of electric vehicle batteries and manufacturing of next-generation NMC cathode materials.

physics.app-ph↗

arXiv2021

DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection

Few-shot object detection, which aims at detecting novel objects rapidly from extremely few annotated examples of previously unseen classes, has attracted significant research interest in the community. Most existing approaches employ the Faster R-CNN as basic detection framework, yet, due to the lack of tailored considerations for data-scarce scenario, their performance is often not satisfactory. In this paper, we look closely into the conventional Faster R-CNN and analyze its contradictions from two orthogonal perspectives, namely multi-stage (RPN vs. RCNN) and multi-task (classification vs. localization). To resolve these issues, we propose a simple yet effective architecture, named Decoupled Faster R-CNN (DeFRCN). To be concrete, we extend Faster R-CNN by introducing Gradient Decoupled Layer for multi-stage decoupling and Prototypical Calibration Block for multi-task decoupling. The former is a novel deep layer with redefining the feature-forward operation and gradient-backward operation for decoupling its subsequent layer and preceding layer, and the latter is an offline prototype-based classification model with taking the proposals from detector as input and boosting the original classification scores with additional pairwise scores for calibration. Extensive experiments on multiple benchmarks show our framework is remarkably superior to other existing approaches and establishes a new state-of-the-art in few-shot literature.

cs.CV↗

arXiv2021

A reduced model for compressible viscous heat-conducting multicomponent flows

In the present paper we propose a reduced temperature non-equilibrium model for simulating multicomponent flows with inter-phase heat transfer, diffusion processes (including the viscosity and the heat conduction) and external energy sources. We derive three equivalent formulations for the proposed model. All the three formulations assume velocity and pressure equilibrium across the material interface. These equivalent forms provide different physical perspectives and numerical conveniences. Temperature equilibration and continuity across the material interfaces are achieved with the instantaneous thermal relaxation. Temperature equilibrium is maintained during the heat conduction process. The proposed models are proved to respect the thermodynamical laws. For numerical solution, the model is split into a hyperbolic partial differential equation (PDE) system and parabolic PDE systems. The former is solved with the high-order Godunov finite volume method that ensures the pressure-velocity-temperature (PVT) equilibrium conduction. The parabolic PDEs are solved with both the implicit and the explicit locally iterative method (LIM) based on Chebyshev parameters. Numerical results are presented for several multicomponent flow problems with diffusion processes. Furthermore, we apply the proposed model to simulate the target ablation problem that is of significance to inertial confinement fusion. Comparisons with one-temperature models in literature demonstrate the ability to maintain the PVT property and superior convergence performance of the proposed model in solving multicomponent problems with diffusions.

math.NA↗

arXiv2021

Realizing discrete time crystal in an one-dimensional superconducting qubit chain

Floquet engineering, i.e. driving the system with periodic Hamiltonians, not only provides great flexibility in analog quantum simulation, but also supports phase structures of great richness. It has been proposed that Floquet systems can support a discrete time-translation symmetry (TTS) broken phase, dubbed the discrete time crystal (DTC). This proposal, as well as the exotic phase, has attracted tremendous interest among the community of quantum simulation. Here we report the observation of the DTC in an one-dimensional superconducting qubit chain. We experimentally realize long-time stroboscopic quantum dynamics of a periodically driven spin system consisting of 8 transmon qubits, and obtain a lifetime of the DTC order limited by the coherence time of the underlying physical platform. We also explore the crossover between the discrete TTS broken and unbroken phases via various physical signatures. Our work extends the usage of superconducting circuit systems in quantum simulation of many-body physics, and provides an experimental tool for investigating non-equilibrium dynamics and phase structures.

quant-ph↗

arXiv2021

When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?

Particle filtering is a popular method for inferring latent states in stochastic dynamical systems, whose theoretical properties have been well studied in machine learning and statistics communities. In many control problems, e.g., partially observed linear dynamical systems (POLDS), oftentimes the inferred latent state is further used for planning at each step. This paper initiates a rigorous study on the efficiency of particle filtering for sequential planning, and gives the first particle complexity bounds. Though errors in past actions may affect the future, we are able to bound the number of particles needed so that the long-run reward of the policy based on particle filtering is close to that based on exact inference. In particular, we show that, in stable systems, polynomially many particles suffice. Key in our proof is a coupling of the ideal sequence based on the exact planning and the sequence generated by approximate planning based on particle filtering. We believe this technique can be useful in other sequential decision-making problems.

cs.LG↗

arXiv2021

X-ray Constraints on the Hot Gas Content of Early-type Galaxies in Virgo

We present a systematic study of the diffuse hot gas around early-type galaxies (ETGs) residing in the Virgo cluster, based on archival {\it Chandra} observations. Our representative sample consists of 79 galaxies with low-to-intermediate stellar masses ($M_* \approx 10^{9-11}\rm~M_\odot$), a mass range that has not been extensively explored with X-ray observations thus far. We detect diffuse X-ray emission in only eight galaxies and find that in five cases a substantial fraction of the detected emission can be unambiguously attributed to truly diffuse hot gas, based on their spatial distribution and spectral properties. For the individually non-detected galaxies, we constrain their average X-ray emission by performing a stacking analysis, finding a specific X-ray luminosity of $L_{\rm X}/M_* \sim 10^{28}{\rm~erg~s^{-1}~M_{\odot}^{-1}}$, which is consistent with unresolved stellar populations. The apparent paucity of truly diffuse hot gas in these low- and intermediate-mass ETGs may be the result of efficient ram pressure stripping by the hot intra-cluster medium. However, we also find no significant diffuse hot gas in a comparison sample of 57 field ETGs of similar stellar masses, for which archival {\it Chandra} observations with similar sensitivity are available. This points to the alternative possibility that galactic winds evacuate the hot gas from the inner region of low- and intermediate-mass ETGs, regardless of the galactic environment. Nevertheless, we do find strong morphological evidence for on-going ram pressure stripping in two galaxies (NGC 4417 and NGC 4459). A better understanding of the roles of ram pressure stripping and galactic winds in regulating the hot gas content of ETGs, invites sensitive X-ray observations for a large galaxy sample.

astro-ph.GA↗

arXiv2021

Strong positivity property and a related inverse source problem for multi-term time-fractional diffusion equations

In this article, we consider the diffusion equation with multi-term time-fractional derivatives. We first derive that the solution is positive when the source term is nonpositive by a subordination principle for the solution. As an application, we prove that the uniqueness of the inverse problem on the determination of the temporally varying source term by integral type information in a subdomain. Finally, several numerical experiments are presented to show the accuracy and efficiency of the algorithm.

math.AP↗

arXiv2021

On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs)

It is generally recognized that finite learning rate (LR), in contrast to infinitesimal LR, is important for good generalization in real-life deep nets. Most attempted explanations propose approximating finite-LR SGD with Ito Stochastic Differential Equations (SDEs), but formal justification for this approximation (e.g., (Li et al., 2019)) only applies to SGD with tiny LR. Experimental verification of the approximation appears computationally infeasible. The current paper clarifies the picture with the following contributions: (a) An efficient simulation algorithm SVAG that provably converges to the conventionally used Ito SDE approximation. (b) A theoretically motivated testable necessary condition for the SDE approximation and its most famous implication, the linear scaling rule (Goyal et al., 2017), to hold. (c) Experiments using this simulation to demonstrate that the previously proposed SDE approximation can meaningfully capture the training and generalization properties of common deep nets.

cs.LG↗

arXiv2021

An Energetic Hot Wind from the Low-luminosity Active Galactic Nucleus M81*

For most of their lifetime, super-massive black holes (SMBHs) commonly found in galactic nuclei obtain mass from the ambient at a rate well below the Eddington limit, which is mediated by a radiatively inefficient, hot accretion flow. Both theory and numerical simulations predict that a strong wind must exist in such hot accretion flows. The wind is of special interest not only because it is an indispensable ingredient of accretion, but perhaps more importantly, it is believed to play a crucial role in the evolution of the host galaxy via the so-called kinetic mode AGN feedback. Observational evidence for this wind, however, remains scarce and indirect. Here we report the detection of a hot outflow from the low-luminosity active galactic nucleus in M81, based on {\it Chandra} high-resolution X-ray spectroscopy. The outflow is evidenced by a pair of Fe XXVI Ly$α$ lines redshifted and blueshifted at a bulk line-of-sight velocity of $\pm2.8\times10^3 \rm~km~s^{-1}$ and a high Fe XXVI Ly$α$-to-Fe XXV K$α$ line ratio implying a plasma temperature of $1.3\times10^8$ Kelvin. This high-velocity, hot plasma cannot be produced by stellar activity or the accretion inflow onto the SMBH. Our magnetohydrodynamical simulations show, instead, it is naturally explained by a wind from the hot accretion flow, propagating out to $\gtrsim10^6$ times the gravitational radius of the SMBH. The kinetic energy and momentum of this wind can significantly affect the evolution of the circumnuclear environment and beyond.

astro-ph.HE↗

arXiv2021

Vacuum-gap transmon qubits realized using flip-chip technology

Significant progress has been made in building large-scale superconducting quantum processors based on flip-chip technology. In this work, we use the flip-chip technology to realize a modified transmon qubit, donated as the "flipmon", whose large shunt capacitor is replaced by a vacuum-gap parallel plate capacitor. To further reduce the qubit footprint, we place one of the qubit pads and a single Josephson junction on the bottom chip and the other pad on the top chip which is galvanically connected with the single Josephson junction through an indium bump. The electric field participation ratio can arrive at nearly 53% in air when the vacuum-gap is about 5 microns, and thus potentially leading to a lower dielectric loss. The coherence times of the flipmons are measured in the range of 30-60 microseconds, which are comparable with that of traditional transmons with similar fabrication processes. The electric field simulation indicates that the metal-air interface's participation ratio increases significantly and may dominate the qubit's decoherence. This suggests that more careful surface treatment needs to be considered. No evidence shows that the indium bumps inside the flipmons cause significant decoherence. With well-designed geometry and good surface treatment, the coherence of the flipmons can be further improved.

quant-ph↗

arXiv2021

Tautological classes of hyper-Kähler manifolds. Erratum

This note is an erratum to the paper "Tautological classes on moduli spaces of hyper-Kähler manifolds." Thorsten Beckman and Mirko Mauri have pointed to us a gap in the proof of \cite[Theorem 8.2.1]{Duke}. We do not know how to correct the proof. We can only recover a partial statement. This gap affects the proof of one of the two main results of \cite{Duke}, we explain how to correct it.

math.AG↗

arXiv2021

Identity-Free Facial Expression Recognition using conditional Generative Adversarial Network

A novel Identity-Free conditional Generative Adversarial Network (IF-GAN) was proposed for Facial Expression Recognition (FER) to explicitly reduce high inter-subject variations caused by identity-related facial attributes, e.g., age, race, and gender. As part of an end-to-end system, a cGAN was designed to transform a given input facial expression image to an "average" identity face with the same expression as the input. Then, identity-free FER is possible since the generated images have the same synthetic "average" identity and differ only in their displayed expressions. Experiments on four facial expression datasets, one with spontaneous expressions, show that IF-GAN outperforms the baseline CNN and achieves state-of-the-art performance for FER.

cs.CV↗

arXiv2021

Transmon qubit with relaxation time exceeding 0.5 milliseconds

By using the dry etching process of tantalum (Ta) film, we had obtained transmon qubit with the best lifetime (T1) 503 us, suggesting that the dry etching process can be adopted in the following multi-qubit fabrication with Ta film. We also compared the relaxation and coherence times of transmons made with different materials (Ta, Nb and Al) with the same design and fabrication processes of Josephson junction, we found that samples prepared with Ta film had the best performance, followed by those with Al film and Nb film. We inferred that the reason for this difference was due to the different loss of oxide materials located at the metal-air interface.

quant-ph↗

arXiv2021

Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?

Convolutional neural networks often dominate fully-connected counterparts in generalization performance, especially on image classification tasks. This is often explained in terms of 'better inductive bias'. However, this has not been made mathematically rigorous, and the hurdle is that the fully connected net can always simulate the convolutional net (for a fixed task). Thus the training algorithm plays a role. The current work describes a natural task on which a provable sample complexity gap can be shown, for standard training algorithms. We construct a single natural distribution on $\mathbb{R}^d\times\{\pm 1\}$ on which any orthogonal-invariant algorithm (i.e. fully-connected networks trained with most gradient-based methods from gaussian initialization) requires $Ω(d^2)$ samples to generalize while $O(1)$ samples suffice for convolutional architectures. Furthermore, we demonstrate a single target function, learning which on all possible distributions leads to an $O(1)$ vs $Ω(d^2/\varepsilon)$ gap. The proof relies on the fact that SGD on fully-connected network is orthogonal equivariant. Similar results are achieved for $\ell_2$ regression and adaptive training algorithms, e.g. Adam and AdaGrad, which are only permutation equivariant.

cs.LG↗

arXiv2021

A Supernova-driven, Magnetically-collimated Outflow as the Origin of the Galactic Center Radio Bubbles

A pair of non-thermal radio bubbles recently discovered in the inner few hundred parsecs of the Galactic center bears a close spatial association with elongated, thermal X-ray features called the X-ray chimneys. While their morphology, position, and orientation vividly point to an outflow from the Galactic center, the physical processes responsible for the outflow remain to be understood. We use three-dimensional magnetohydrodynamic simulations to test the hypothesis that the radio bubbles/X-ray chimneys are the manifestation of an energetic outflow driven by multiple core-collapsed supernovae in the nuclear stellar disk, where numerous massive stars are known to be present. Our simulations are run with different combinations of two main parameters, the supernova birth rate and the strength of a global magnetic field being vertically oriented with respect to the disk. The simulation results show that a hot gas outflow can naturally form and acquire a vertically elongated shape due to collimation by the magnetic pressure. In particular, the simulation with an initial magnetic field strength of 80 $μ$G and a supernova rate of 1 $kyr^{-1}$ can well reproduce the observed morphology, internal energy and X-ray luminosity of the bubbles after an evolutionary time of 330 kyr. On the other hand, a magnetic field strength of 200 $μ$G gives rise to an overly elongated outflow that is inconsistent with the observed bubbles. The simulations also reveal that, inside the bubbles, mutual collisions between the shock waves of individual supernovae produce dense filaments of locally amplified magnetic field. Such filaments may account for a fraction of the synchrotron-emitting radio filaments known to exist in the Galactic center.

astro-ph.GA↗

arXiv2021

Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning

Matrix factorization is a simple and natural test-bed to investigate the implicit regularization of gradient descent. Gunasekar et al. (2017) conjectured that Gradient Flow with infinitesimal initialization converges to the solution that minimizes the nuclear norm, but a series of recent papers argued that the language of norm minimization is not sufficient to give a full characterization for the implicit regularization. In this work, we provide theoretical and empirical evidence that for depth-2 matrix factorization, gradient flow with infinitesimal initialization is mathematically equivalent to a simple heuristic rank minimization algorithm, Greedy Low-Rank Learning, under some reasonable assumptions. This generalizes the rank minimization view from previous works to a much broader setting and enables us to construct counter-examples to refute the conjecture from Gunasekar et al. (2017). We also extend the results to the case where depth $\ge 3$, and we show that the benefit of being deeper is that the above convergence has a much weaker dependence over initialization magnitude so that this rank minimization is more likely to take effect for initialization with practical scale.

cs.LG↗

arXiv2021

Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning

This paper considers batch Reinforcement Learning (RL) with general value function approximation. Our study investigates the minimal assumptions to reliably estimate/minimize Bellman error, and characterizes the generalization performance by (local) Rademacher complexities of general function classes, which makes initial steps in bridging the gap between statistical learning theory and batch RL. Concretely, we view the Bellman error as a surrogate loss for the optimality gap, and prove the followings: (1) In double sampling regime, the excess risk of Empirical Risk Minimizer (ERM) is bounded by the Rademacher complexity of the function class. (2) In the single sampling regime, sample-efficient risk minimization is not possible without further assumptions, regardless of algorithms. However, with completeness assumptions, the excess risk of FQI and a minimax style algorithm can be again bounded by the Rademacher complexity of the corresponding function classes. (3) Fast statistical rates can be achieved by using tools of local Rademacher complexity. Our analysis covers a wide range of function classes, including finite classes, linear spaces, kernel spaces, sparse linear features, etc.

cs.LG↗