arXiv subjects

Tianxing Jiang

Publications and source records attributed to Tianxing Jiang.

16 recordsLinked to original sources

arXiv2026

Dimensional crossover and local strain induced deflection of the spin spiral state in multiferroic NiI2

Low-dimensional multiferroics hold great promise for integrated magnetoelectric devices. Spin spiral state has recently been shown to induce ferroelectricity in single-layer van der Waals (vdW) material NiI2. However, how this state evolves and can be tuned towards the two-dimensional limit remain unclear. Here, we combine spin-polarized scanning tunneling microscopy, layer-by-layer film growth, and multi-scale theoretical modeling to investigate the spin spirals in NiI2 thin films. As the film thickness increases from 1 to 7 monolayers, we observed a continuous increase of spin-spiral wavelength and a rotation of wavevector from near [110] to [1-10] direction, which evidences a dimensional crossover primarily driven by enhanced interlayer exchange energy. Moreover, we find that the film wrinkles can cause deflection of the spin spiral wavevector, which is caused by local curvature induced modification of exchange interactions. Our findings establish thickness and local strain as two tuning methods for engineering non-collinear helical magnetism and accompanied electric polarization in vdW multiferroics.

cond-mat.mes-hall↗

arXiv2026

Microscopic evidence of spin-driven multiferroicity and topological spin textures in monolayer NiI2

In type II multiferroics, noncollinear spin textures are expected to induce electric polarization directly, leading to strong magnetoelectric coupling. Realizing such spin driven multiferroicity in two-dimensional systems, and elucidating the interplay between local spins and electric polarization, are of both fundamental and technological importance. Here, using vectorial spin polarized scanning tunneling microscopy, we investigated the spin-driven multiferroicity in monolayer NiI2 at atomic scale. We identify a canted spin-spiral state with fully determined spin rotation plane, accompanied by a 2Q charge modulation. At spin spiral domain walls, we discover topological spin textures that composed of meron/antimeron pairs. These textures are associated with distinct charge pattern and notable band shifts, indicating local bound charges induced by variations of ferroelectricity at domain wall. Our observations are well captured by a realistic spin model incorporating Kitaev interactions and generalized spin-current model of type II multiferroicity. The findings provide microscopic evidence of spin-driven multiferroicity in an extreme 2D system and establish a platform for low-dissipation, electric-field control of topological spin textures.

cond-mat.mes-hall↗

arXiv2023

Surface structure and multigap superconductivity of V3Si (111) revealed by scanning tunneling microscopy

V3Si, a classical silicide superconductor with relatively high TC (~16 K), is promising for constructing silicon-based superconducting devices and hetero-structures. However, real space characterization on its surfaces and superconducting properties are still limited. Here we report the first low-temperature scanning tunnelling microscopy (STM) study on cleaned V3Si (111) single crystal surface. We observed a r3 by r3 superstructure which displays mirror symmetry between adjacent terraces, indicating the surface is V-terminated and reconstructed. The tunneling spectrum shows full superconducting gap with double pairs of coherence peaks, but has a relatively small gap size with comparing to bulk TC. Impurity induced in-gap state is absent on surface defects but present on introduced magnetic adatoms. Upon applying magnetic field, a hexagonal vortex lattice is visualized. Interestingly, the vortex size is found to be field dependent, and the coherence length measured from single vortex at low field is significantly larger than estimated value from bulk H_c2. These results reflect V3Si is a multi-band, s- wave superconductor.

cond-mat.supr-con↗

arXiv2022

AntFuzzer: A Grey-Box Fuzzing Framework for EOSIO Smart Contracts

In the past few years, several attacks against the vulnerabilities of EOSIO smart contracts have caused severe financial losses to this prevalent blockchain platform. As a lightweight test-generation approach, grey-box fuzzing can open up the possibility of improving the security of EOSIO smart contracts. However, developing a practical grey-box fuzzer for EOSIO smart contracts from scratch is time-consuming and requires a deep understanding of EOSIO internals. In this work, we proposed AntFuzzer, the first highly extensible grey-box fuzzing framework for EOSIO smart contracts. AntFuzzer implements a novel approach that interfaces AFL to conduct AFL-style grey-box fuzzing on EOSIO smart contracts. Compared to black-box fuzzing tools, AntFuzzer can effectively trigger those hard-to-cover branches. It achieved an improvement in code coverage on 37.5% of smart contracts in our benchmark dataset. AntFuzzer provides unified interfaces for users to easily develop new detection plugins for continually emerging vulnerabilities. We have implemented 6 detection plugins on AntFuzzer to detect major vulnerabilities of EOSIO smart contracts. In our large-scale fuzzing experiments on 4,616 real-world smart contracts, AntFuzzer successfully detected 741 vulnerabilities. The results demonstrate the effectiveness and efficiency of AntFuzzer and our detection pl

cs.CR↗

arXiv2022

Observation of robust zero-energy state and enhanced superconducting gap in a tri-layer heterostructure of MnTe/Bi2Te3/Fe(Te, Se)

The interface between magnetic material and superconductors has long been predicted to host unconventional superconductivity, such as spin-triplet pairing and topological nontrivial pairing state, particularly when spin-orbital coupling (SOC) is incorporated. To identify these novel pairing states, fabricating homogenous heterostructures which contain such various properties are preferred, but often challenging. Here we synthesized a tri-layer type van-der Waals heterostructure of MnTe/Bi2Te3/Fe(Te, Se), which combined s-wave superconductivity, thickness dependent magnetism and strong SOC. Via low-temperature scanning tunneling microscopy (STM), we observed robust zero-energy states with notably nontrivial properties and an enhanced superconducting gap size on single unit-cell (UC) MnTe surface. In contrast, no zero-energy state was observed on 2UC MnTe. First-principle calculations further suggest the 1UC MnTe has large interfacial Dzyaloshinskii-Moriya interaction (DMI) and a frustrated AFM state, which could promote non-collinear spin textures. It thus provides a promising platform for exploring topological nontrivial superconductivity.

cond-mat.supr-con↗

arXiv2022

Finding Peas in the Early Universe with JWST

The Early Release Observations (EROs) of JWST beautifully demonstrate the promise of JWST in characterizing the universe at cosmic dawn. We analyze the ERO spectra of three $z \sim 8$ galaxies to determine their metallicities, gas temperatures and ionization. These galaxies offer the first opportunity to understand the physical properties of epoch-of-reionization galaxies through detailed rest-optical emission line spectroscopy. We show that these objects have metal abundances $12+\log[O/H] \approx 6.9 - 8.2$, based on both the $T_e$ method and on a recent calibration of the $R_{23}$ metallicity indicator. Since the spectra are some of the earliest science data from JWST, we compare several line ratios with values expected from robust physics, to validate our measurement procedures. We compare the abundances and emission line ratios to a nearby sample of Green Pea galaxies -- a population of nearby emission line galaxies whose UV properties resemble epoch-of-reionization galaxies, and which often have large Lyman continuum escape fractions. The JWST data show striking further similarities between these high redshift galaxies and nearby Green Peas. The $z\sim 8$ galaxies span the metallicity range covered by Green Peas. They also show the compact morphology that is typical of emission line dominated galaxies at all redshifts. Based on these similarities with Green Peas, it is likely that these are the first rest-optical spectra of galaxies that are actively driving cosmological reionization

astro-ph.GA↗

arXiv2022

Evidence for Black Holes in Green Peas from WISE colors and variability

We explore the presence of active galactic nuclei (AGN)/black holes (BH) in Green Pea galaxies (GPs), motivated by the presence of high ionization emission lines such as HeII and [NeIII] in their optical spectra. In order to identify AGN candidates, we used mid-infrared (MIR) photometric observations from the all-sky Wide-field Infrared Survey Explorer (WISE) mission for a sample of 1004 GPs. Considering only $>5σ$ detections with no contamination from neighboring sources in AllWISE, we select 31 GPs out of 134 as candidate AGN based on a stringent 3-band WISE color diagnostic. Using multi-epoch photometry in W1 and W2 bands based on time-resolved unWISE coadd images, we find two sources exhibiting variability in both the WISE bands among 112 GPs with W1$\leqslant16$ mag and no contamination from neighboring sources in unWISE. These two variable sources were selected as AGN by the WISE 3-band color diagnostic as well. Compared to variable AGN fractions observed among low-mass galaxy samples in previous studies, we find a higher fraction ($\sim1.8\%$) of MIR variable sources among GPs, which demonstrates the uniqueness and importance of studying these extreme objects. Through this work, we demonstrate that MIR diagnostics are promising tools to select AGN that may be missed by other selection techniques (including optical emission-line ratios and X-ray emission) in star-formation dominated, low-mass, low-metallicity galaxies.

astro-ph.GA↗

arXiv2021

Robustness and Generalization via Generative Adversarial Training

While deep neural networks have achieved remarkable success in various computer vision tasks, they often fail to generalize to new domains and subtle variations of input images. Several defenses have been proposed to improve the robustness against these variations. However, current defenses can only withstand the specific attack used in training, and the models often remain vulnerable to other input variations. Moreover, these methods often degrade performance of the model on clean images and do not generalize to out-of-domain samples. In this paper we present Generative Adversarial Training, an approach to simultaneously improve the model's generalization to the test set and out-of-domain samples as well as its robustness to unseen adversarial attacks. Instead of altering a low-level pre-defined aspect of images, we generate a spectrum of low-level, mid-level and high-level changes using generative models with a disentangled latent space. Adversarial training with these examples enable the model to withstand a wide range of attacks by observing a variety of input alterations during training. We show that our approach not only improves performance of the model on clean images and out-of-domain samples but also makes it robust against unforeseen attacks and outperforms prior work. We validate effectiveness of our method by demonstrating results on various tasks such as classification, segmentation and object detection.

cs.CV↗

arXiv2020

Fine-grained Synthesis of Unrestricted Adversarial Examples

We propose a novel approach for generating unrestricted adversarial examples by manipulating fine-grained aspects of image generation. Unlike existing unrestricted attacks that typically hand-craft geometric transformations, we learn stylistic and stochastic modifications leveraging state-of-the-art generative models. This allows us to manipulate an image in a controlled, fine-grained manner without being bounded by a norm threshold. Our approach can be used for targeted and non-targeted unrestricted attacks on classification, semantic segmentation and object detection models. Our attacks can bypass certified defenses, yet our adversarial images look indistinguishable from natural images as verified by human evaluation. Moreover, we demonstrate that adversarial training with our examples improves performance of the model on clean images without requiring any modifications to the architecture. We perform experiments on LSUN, CelebA-HQ and COCO-Stuff as high resolution datasets to validate efficacy of our proposed approach.

cs.CV↗

arXiv2020

Self-supervised Learning of Point Clouds via Orientation Estimation

Point clouds provide a compact and efficient representation of 3D shapes. While deep neural networks have achieved impressive results on point cloud learning tasks, they require massive amounts of manually labeled data, which can be costly and time-consuming to collect. In this paper, we leverage 3D self-supervision for learning downstream tasks on point clouds with fewer labels. A point cloud can be rotated in infinitely many ways, which provides a rich label-free source for self-supervision. We consider the auxiliary task of predicting rotations that in turn leads to useful features for other tasks such as shape classification and 3D keypoint prediction. Using experiments on ShapeNet and ModelNet, we demonstrate that our approach outperforms the state-of-the-art. Moreover, features learned by our model are complementary to other self-supervised methods and combining them leads to further performance improvement.

cs.CV↗

arXiv2020

A comprehensive study of H$α$ emitters at $z \sim$ 0.62 in the DAWN survey: the need for deep and wide regions

We present new estimates of the luminosity function (LF) and star formation rate density (SFRD) for an H$α$ selected sample at $z\sim0.62$ from the Deep And Wide Narrow-band (DAWN) survey. Our results are based on a new H$α$ sample in the extended COSMOS region (compared to Coughlin et al. 2018) with the inclusion of flanking fields, resulting in a total area coverage of $\sim$1.5 deg$^2$. A total of 241 H$α$ emitters were selected based on robust selection criteria using spectro-photometric redshifts and broadband color-color classification. We explore the effect of different dust correction prescriptions by calculating the LF and SFRD using a constant dust extinction correction, A{$_{\textrm{H}α}=1$} mag, a luminosity-dependent correction, and a stellar-mass dependent correction. The resulting H$α$ LFs are well fitted using Schechter functions with best-fit parameters: L$^*=10^{42.24}$ erg s$^{-1}$, $ϕ^*=10^{-2.85}$ Mpc$^{-3}$, $α= -1.62$ for constant dust correction, L$^*=10^{42.31}$ erg s$^{-1}$, $ϕ^*=10^{-2.8}$ Mpc$^{-3}$, $α=-1.39$ for luminosity-dependent dust correction, and L$^*=10^{42.36}$ erg s$^{-1}$, $ϕ^*=10^{-2.91}$ Mpc$^{-3}$, $α= -1.48$, for stellar mass-dependent dust correction. The deep and wide nature of the DAWN survey effectively samples H$α$ emitters over a wide range of luminosities, thereby providing better constraints on both the faint and bright end of the LF. Also, the SFRD estimates $ρ_{\textrm{SFR}}=10^{-1.39}$ M$_{\odot}$yr$^{-1}$Mpc$^{-3}$ (constant dust correction), $ρ_{\textrm{SFR}}=10^{-1.47}$ M$_{\odot}$yr$^{-1}$Mpc$^{-3}$ (luminosity-dependent dust correction), and $ρ_{\textrm{SFR}}=10^{-1.49}$ M$_{\odot}$yr$^{-1}$Mpc$^{-3}$ (stellar mass-dependent dust correction) are in good agreement with the evolution of SFRD across redshifts ($0 < z < 2$) seen from previous H$α$ surveys.

astro-ph.GA↗

arXiv2019

Emission Line Metallicities From The Faint Infrared Grism Survey and VLT/MUSE

We derive direct measurement gas-phase metallicities of $7.4 < 12 + \log(O/H) < 8.4$ for 14 low-mass Emission Line Galaxies (ELGs) at $0.3 < z < 0.8$ identified in the Faint Infrared Grism Survey (FIGS). We use deep slitless G102 grism spectroscopy of the Hubble Ultra Deep Field (HUDF), dispersing light from all objects in the field at wavelengths between 0.85 and 1.15 microns. We run an automatic search routine on these spectra to robustly identify 71 emission line sources, using archival data from VLT/MUSE to measure additional lines and confirm redshifts. We identify 14 objects with $0.3 < z < 0.8$ with measurable O[III]$λ$4363 Å emission lines in matching VLT/MUSE spectra. For these galaxies, we derive direct electron-temperature gas-phase metallicities with a range of $7.4 < 12 + \log(O/H) < 8.4$. With matching stellar masses in the range of $10^{7.9} M_{\odot} < M_{\star} < 10^{10.4} M_{\odot}$, we construct a mass-metallicity (MZ) relation and find that the relation is offset to lower metallicities compared to metallicities derived from alternative methods (e.g.,$R_{23}$, O3N2, N2O2) and continuum selected samples. Using star formation rates (SFR) derived from the $Hα$ emission line, we calculate our galaxies' position on the Fundamental Metallicity Relation (FMR), where we also find an offset toward lower metallicities. This demonstrates that this emission-line-selected sample probes objects of low stellar masses but even lower metallicities than many comparable surveys. We detect a trend suggesting galaxies with higher Specific Star Formation (SSFR) are more likely to have lower metallicity. This could be due to cold accretion of metal-poor gas that drives star formation, or could be because outflows of metal-rich stellar winds and SNe ejecta are more common in galaxies with higher SSFR.

astro-ph.GA↗

arXiv2018

Correlation between SFR surface density and thermal pressure of ionized gas in local analogs of high-redshift galaxies

We explore the relation between the star formation rate surface density ($Σ$SFR) and the interstellar gas pressure for nearby compact starburst galaxies. The sample consists of 17 green peas and 19 Lyman break analogs. Green peas are nearby analogs of Ly$α$ emitters at high redshift and Lyman break analogs are nearby analogs of Lyman break galaxies at high redshift. We measure the sizes for green peas using Hubble Space Telescope Cosmic Origins Spectrograph (COS) NUV images with a spatial resolution of $\sim$ 0.05$^{''}$. We estimate the gas thermal pressure in HII regions by $P = N_{total}Tk{_B} \simeq 2n_{e}Tk{_B}$. The electron density is derived using the [SII] doublet at 6716,6731 Å, and the temperature is calculated from the [OIII] lines. The correlation is characterized by $Σ$ SFR = 2.40$\times$10$^{-3\,}$M$_{\odot\,}$yr$^{-1\,}$kpc$^{-2}$$\left(\frac{P/k_{B}}{10^{4}cm^{-3}K}\right)^{1.33}$. Green peas and Lyman break analogs have high $Σ$SFR up to 1.2 M$_{\odot\,}$yr$^{-1\,}$kpc$^{-2}$ and high thermal pressure in HII region up to P/k$_B$ $\sim$10$^{7.2}{\rm\, K\, cm}^{-3}$. These values are at the highest end of the range seen in nearby starburst galaxies. The high gas pressure and the correlation, are in agreement with those found in star-forming galaxies at z $\sim$ 2.5. These extreme pressures are shown to be responsible for driving galactic winds in nearby starbursts. These outflows may be a crucial in enabling Lyman-$α$ and Lyman-continuum to escape.

astro-ph.GA↗

arXiv2018

Direct T$_e$ metallicity calibration of R23 in strong line emitters

The gas metallicity of galaxies is often estimated using strong emission lines such as the optical lines of [OIII] and [OII]. The most common measure is "R23", defined as ([OII]$λ$$λ$3726, 3729 + [OIII]$λ$$λ$4959,5007)/H$β$. Most calibrations for these strong-line metallicity indicators are for continuum selected galaxies. We report a new empirical calibration of R23 for extreme emission-line galaxies using a large sample of about 800 star-forming green pea galaxies with reliable T$_e$-based gas-phase metallicity measurements. This sample is assembled from Sloan Digital Sky Survey (SDSS) Data Release 13 with the equivalent width of the line [OIII]$λ$5007 $>$ 300 Å or the equivalent width of the line H$β$ $>$ 100 Å in the redshift range 0.011 $<$ z $<$ 0.411. For galaxies with strong emission lines and large ionization parameter (which manifests as log [OIII]$λ$$λ$4959,5007/[OII]$λ$$λ$3726,3729 $\geq$ 0.6), R23 monotonically increases with log(O/H) and the double-value degeneracy is broken. Our calibration provides metallicity estimates that are accurate to within $\sim$ 0.14 dex in this regime. Many previous R23 calibrations are found to have bias and large scatter for extreme emission-line galaxies. We give formulae and plots to directly convert R23 and [OIII]$λ$$λ$4959,5007/[OII]$λ$$λ$3726,3729 to log(O/H). Since green peas are best nearby analogs of high-redshift Lyman-$α$ emitting galaxies, the new calibration offers a good way to estimate the metallicities of both extreme emission-line galaxies and high-redshift Lyman-$α$ emitting galaxies. We also report on 15 galaxies with metallicities less than 1/12 solar, with the lowest metallicities being 12+log(O/H) = 7.25 and 7.26.

astro-ph.GA↗

arXiv2017

Ly$α$ and UV Sizes of Green Pea Galaxies

Green Peas are nearby analogs of high-redshift Ly$α$-emitting galaxies. To probe their Ly$α$ escape, we study the spatial profiles of Ly$α$ and UV continuum emission of 24 Green Pea galaxies using the Cosmic Origins Spectrograph (COS) on Hubble Space Telescope (HST). We extract the spatial profiles of Ly$α$ emission from their 2D COS spectra, and of UV continuum from both the 2D spectra and NUV images. The Ly$α$ emission shows more extended spatial profiles than the UV continuum in most Green Peas. The deconvolved Full Width Half Maximum (FWHM) of the Ly$α$ spatial profile is about 2 to 4 times that of the UV continuum in most cases. Since Green Peas are analogs of high-z LAEs, it suggests that most high-z LAEs likely have larger Ly$α$ sizes than UV sizes. We also compare the spatial profiles of Ly$α$ photons at blueshifted and redshifted velocities in eight Green Peas with sufficient data quality, and find the blue wing of the Ly$α$ line has a larger spatial extent than the red wing in four Green Peas with comparatively weak blue Ly$α$ line wings. We show that Green Peas and MUSE $z=3-6$ LAEs have similar Ly$α$ and UV continuum sizes, which probably suggests starbursts in both low-z and high-z LAEs drive similar gas outflows illuminated by Ly$α$ light. Five Lyman continuum (LyC) leakers in this sample have similar Ly$α$ to UV continuum size ratios (~1.4-4.3) to the other Green Peas, indicating their LyC emission escape through ionized holes in the interstellar medium.

astro-ph.GA↗

arXiv2017

Ly$α$ profile, dust, and prediction of Ly$α$ escape fraction in Green Pea Galaxies

We studied Lyman-$α$ (Ly$α$) escape in a statistical sample of 43 Green Peas with HST/COS Ly$α$ spectra. Green Peas are nearby star-forming galaxies with strong [OIII]$λ$5007 emission lines. Our sample is four times larger than the previous sample and covers a much more complete range of Green Pea properties. We found that about 2/3 of Green Peas are strong Ly$α$ line emitters with rest-frame Ly$α$ equivalent width $>20$ Å. The Ly$α$ profiles of Green Peas are diverse. The Ly$α$ escape fraction, defined as the ratio of observed Ly$α$ flux to intrinsic Ly$α$ flux, shows anti-correlations with a few Ly$α$ kinematic features -- both the blue peak and red peak velocities, the peak separations, and FWHM of the red portion of the Ly$α$ profile. Using properties measured from SDSS optical spectra, we found many correlations -- Ly$α$ escape fraction generally increases at lower dust reddening, lower metallicity, lower stellar mass, and higher [OIII]/[OII] ratio. We fit their Ly$α$ profiles with the HI shell radiative transfer model and found Ly$α$ escape fraction anti-correlates with the best-fit $N_{HI}$. Finally, we fit an empirical linear relation to predict Ly$α$ escape fraction from the dust extinction and Ly$α$ red peak velocity. The standard deviation of this relation is about 0.3 dex. This relation can be used to isolate the effect of IGM scatterings from Ly$α$ escape and to probe the IGM optical depth along the line of sight of each $z>7$ Ly$α$ emission line galaxy in the JWST era.

astro-ph.GA↗