arXiv subjects

Yilin Wang

Publications and source records attributed to Yilin Wang.

At least 145 records · Page 8Linked to original sources

arXiv2023

Origin of the exotic electronic states in antiferromagnetic NdSb

Using angle resolved photoemission spectroscopy measurements and first principle calculations, we report that the possible unconventional 2q antiferromagnetic (AFM) order in NdSb can induce unusual modulation on its electronic structure. The obvious extra bands observed in the AFM phase of NdSb are well reproduced by theoretical calculations, in which the Fermi-arc-like structures and sharp extra bands are originated from the in-gap surface states. However, they are demonstrated to be topological trivial. By tuning the chemical potential, the AFM phase of NdSb would go through a topological phase transition, realizing a magnetic topological insulator phase. Hence, our study sheds new light on the rare earth monopnictides for searching unusual AFM structure and the potential of intrinsic magnetic topological materials.

cond-mat.mtrl-sci↗

arXiv2023

Complete One-loop Renormalization-group Equations in the Seesaw Effective Field Theories

In this paper, we derive the complete set of one-loop renormalization-group equations (RGEs) for the operators up to dimension-six (dim-6) in the seesaw effective field theories (SEFTs). Two kinds of contributions to those RGEs are identified, one from double insertions of the dimension-five (dim-5) Weinberg operator and the other from single insertions of the tree-level dim-6 operators in the SEFTs. A number of new results are presented. First, as the dim-5 Weinberg operator is unique in the standard model effective field theory (SMEFT), its contributions to the RGEs for the SEFTs are equally applicable to the SMEFT. We find the full contributions from the Weinberg operator to one-loop RGEs in the SMEFT, correcting the results existing in previous works, and confirm that those from dim-6 operators are consistent with the results in the literature. Second, in the type-I SEFT, we give the explicit expressions of the RGEs of all the physical parameters involved in the charged- and neutral-current interactions of leptons. Third, the RGEs are numerically solved to illustrate the running behaviors of the non-unitary parameters, mixing angles and CP-violating phases in the non-unitary leptonic flavor mixing matrix. Together with the one-loop matching results of the dim-5 and dim-6 operators and their Wilson coefficients, the present work has established a self-consistent framework up to dim-6 to investigate low-energy phenomena of three types of seesaw models at the one-loop level.

hep-ph↗

arXiv2023

Enhanced Spin-polarization via Partial Ge1-dimerization as the Driving Force of the 2$\times$2$\times$2 CDW in FeGe

A $2\times2\times2$ charge density wave (CDW) was recently observed deep inside the antiferromagnetic phase of a Kagome metal FeGe. A key question is whether the CDW in FeGe is driven by its electronic correlation and magnetism. Here, we address this problem using density functional theory and its combination with $U$ as well as dynamical mean-field theory. Our calculations show that large dimerization ($\sim 1.3 \overset{\lower.5em\circ}{\mathrm{A}}$) of Ge1-sites along $c$-axis will enhance electronic correlation of the Fe-$3d$ orbitals and, as a result, it enhances the spin-polarization and saves more magnetic exchange energies. We find that the balance between magnetic energy saving and structural energy cost via partially dimerizing Ge1-sites in an enlarged superstructure, could induce a new local minimum in total energies. The response to the large partial Ge1-dimerization will induce additional small modulations ($<0.05 \overset{\lower.5em\circ}{\mathrm{A}}$) of other sites in the Kagome and honeycomb layers, which further reduces the total energy and leads to a stable $2\times 2\times 2$ CDW ground state in FeGe. Our results are in good agreement with the existing experiments and reveal a novel CDW mechanism driven by the interplay of structure, electronic correlation and magnetism.

cond-mat.str-el↗

arXiv2023

Invisible Neutrino Decays as Origin of TeV Gamma Rays from GRB221009A

Recently, the LHAASO collaboration has observed the gamma rays of energies up to ten TeV from the gamma-ray burst GRB221009A, which has stimulated the community of astronomy, particle physics and astrophysics to propose various possible interpretations. In this paper, we put forward a viable scenario that neutrinos are produced together with TeV photons in the gamma-ray burst and gradually decay into the axion-like particles, which are then converted into gamma rays in the galactic magnetic fields. In such a scenario, the tension between previous axion-like particle interpretations and the existing observational constraints on the relevant coupling constant and mass can be relaxed.

hep-ph↗

arXiv2023

MRET: Multi-resolution Transformer for Video Quality Assessment

No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA tasks are sensitive to changes in input resolution. Since large amounts of UGC videos nowadays are 720p or above, the fixed and relatively small input used in conventional NR-VQA methods results in missing high-frequency details for many videos. In this paper, we propose a novel Transformer-based NR-VQA framework that preserves the high-resolution quality information. With the multi-resolution input representation and a novel multi-resolution patch sampling mechanism, our method enables a comprehensive view of both the global video composition and local high-resolution details. The proposed approach can effectively aggregate quality information across different granularities in spatial and temporal dimensions, making the model robust to input resolution variations. Our method achieves state-of-the-art performance on large-scale UGC VQA datasets LSVQ and LSVQ-1080p, and on KoNViD-1k and LIVE-VQC without fine-tuning.

cs.CV↗

arXiv2023

LightPainter: Interactive Portrait Relighting with Freehand Scribble

Recent portrait relighting methods have achieved realistic results of portrait lighting effects given a desired lighting representation such as an environment map. However, these methods are not intuitive for user interaction and lack precise lighting control. We introduce LightPainter, a scribble-based relighting system that allows users to interactively manipulate portrait lighting effect with ease. This is achieved by two conditional neural networks, a delighting module that recovers geometry and albedo optionally conditioned on skin tone, and a scribble-based module for relighting. To train the relighting module, we propose a novel scribble simulation procedure to mimic real user scribbles, which allows our pipeline to be trained without any human annotations. We demonstrate high-quality and flexible portrait lighting editing capability with both quantitative and qualitative experiments. User study comparisons with commercial lighting editing tools also demonstrate consistent user preference for our method.

cs.CV↗

arXiv2023

Electronic Correlation Effects on Stabilizing a Perfect Kagome Lattice and Ferromagnetic Fluctuation in LaRu$_3$Si$_2$

A perfect Kagome lattice features flat bands that usually lead to strong electronic correlation effects, but how electronic correlation, in turn, stabilizes a perfect Kagome lattice has rarely been explored. Here, we study such effect in a superconducting ($T_c \sim 7.8$ K) Kagome metal LaRu$_3$Si$_2$ with a distorted Kagome plane consisting of pure Ru ions, using density functional theory plus $U$ and plus dynamical mean-field theory. We find that increasing electronic correlation can stabilize a perfect Kagome lattice and induce substantial ferromagnetic fluctuations in LaRu$_3$Si$_2$. By comparing the calculated magnetic susceptibilities to experimental data, LaRu$_3$Si$_2$ is found to be on the verge of becoming a perfect Kagome lattice. It thus shows moderate but non-negligible electronic correlations and ferromagnetic fluctuations, which are crucial to understanding the experimentally observed non-Fermi-liquid behavior and the pretty high superconducting $T_c$ of LaRu$_3$Si$_2$.

cond-mat.str-el↗

arXiv2023

Large deviations of multichordal SLE$_{0+}$, real rational functions, and zeta-regularized determinants of Laplacians

We prove a strong large deviation principle (LDP) for multiple chordal SLE$_{0+}$ curves with respect to the Hausdorff metric. In the single-chord case, this result strengthens an earlier partial result by the second author. We also introduce a Loewner potential, which in the smooth case has a simple expression in terms of zeta-regularized determinants of Laplacians. This potential differs from the LDP rate function by an additive constant depending only on the boundary data, that satisfies PDEs arising as a semiclassical limit of the Belavin-Polyakov-Zamolodchikov equations of level two in conformal field theory with central charge $c \to -\infty$. Furthermore, we show that every multichord minimizing the potential in the upper half-plane for given boundary data is the real locus of a rational function and is unique, thus coinciding with the $κ\to 0+$ limit of the multiple SLE$_κ$. As a by-product, we provide an analytic proof of the Shapiro conjecture in real enumerative geometry, first proved by Eremenko and Gabrielov: if all critical points of a rational function are real, then the function is real up to post-composition by a Möbius transformation.

math-ph↗

arXiv2023

Orientation-dependent electron-phonon coupling in interfacial superconductors LaAlO3/KTaO3

The emergent superconductivity at the LaAlO3/KTaO3 interfaces exhibits a mysterious dependence on the KTaO3 crystallographic orientations. Here we show, by soft X-ray angle-resolved photoemission spectroscopy, that the interfacial superconductivity is contributed by mobile electrons with unexpected quasi-three-dimensional character, beyond the "two-dimensional electron gas" scenario in describing oxide interfaces. At differently-oriented interfaces, the quasi-three-dimensional electron gas ubiquitously exists and spatially overlaps with the small q Fuchs-Kliewer surface phonons. Intriguingly, electrons and the Fuchs-Kliewer phonons couple with different strengths depending on the interfacial orientations, and the stronger coupling correlates with the higher superconducting transition temperature. Our results provide a natural explanation for the orientation-dependent superconductivity, and the first evidence that interfacial orientations can affect electron-phonon coupling strength over several nanometers, which may have profound implications for the applications of oxide interfaces in general.

cond-mat.supr-con↗

arXiv2023

The Loewner Energy via the Renormalised Energy of Moving Frames

We obtain a new formula for the Loewner energy of Jordan curves on the sphere, which is a Kähler potential for the essentially unique Kähler metric on the Weil-Petersson universal Teichmüller space, as the renormalised energy of moving frames on the two domains of the sphere delimited by the given curve.

math.DG↗

arXiv2022

Distinguishing thixotropy, anti-thixotropy, and viscoelasticity using hysteresis

Thixotropy, anti-thixotropy, and viscoelasticity are three types of time-dependent dynamics that involve fundamentally different underlying physical processes. Yet distinguishing them can be very challenging, which hinders the understanding of structure-property relations. Here we show that hysteresis is a promising technique to contrast the three dynamics by exploring signatures of the most basic thixotropic, anti-thixotropic, and nonlinear viscoelastic models. From these signatures, using shear-rate controlled ramps that begin and end at high shear rates, we identify two distinguishing features in hysteresis loops. The first is the direction of the hysteresis loops: clockwise for thixotropy, but counterclockwise for viscoelasticity and anti-thixotropy. A second feature is achieved at high ramping rates where all responses lose hysteresis: the viscoelastic response shows a stress plateau at low shear rates (lack of stress relaxation), whereas the thixotropic and anti-thixotropic responses are purely viscous with minimal shear thinning or thickening. The features are observed independent of the model details. We establish further evidence for these signatures by experimentally measuring the hysteresis of thixotropic Laponite suspensions, anti-thixotropic carbon black suspensions, and viscoelastic poly (ethylene oxide) solutions. The protocols explored here can be used to distinguish thixotropy, anti-thixotropy, and viscoelasticity, which helps reveal the underlying microstructural physics of complex fluids.

cond-mat.soft↗

arXiv2022

Accidental symmetries in the scalar potential of the Standard Model extended with two Higgs triplets

The two-Higgs-triplet model (2HTM) provides us with an attractive way to simultaneously account for tiny neutrino masses and the observed matter-antimatter asymmetry in our Universe. In this talk, we study the accidental symmetries of the scalar potential in the 2HTM using the bilinear-field formalism. Based on the group-theoretical arguments, we prove that the maximal symmetry group is ${\rm SO(4)}$. We carefully analyze all the subgroups of ${\rm SO(4)}$, and find that there are eight distinct kinds of accidental symmetries in the scalar potential of the 2HTM.

hep-ph↗

arXiv2022

IDM-Follower: A Model-Informed Deep Learning Method for Long-Sequence Car-Following Trajectory Prediction

Model-based and learning-based methods are two major types of methodologies to model car following behaviors. Model-based methods describe the car-following behaviors with explicit mathematical equations, while learning-based methods focus on getting a mapping between inputs and outputs. Both types of methods have advantages and weaknesses. Meanwhile, most car-following models are generative and only consider the inputs of the speed, position, and acceleration of the last time step. To address these issues, this study proposes a novel framework called IDM-Follower that can generate a sequence of following vehicle trajectory by a recurrent autoencoder informed by a physical car-following model, the Intelligent Driving Model (IDM).We implement a novel structure with two independent encoders and a self-attention decoder that could sequentially predict the following trajectories. A loss function considering the discrepancies between predictions and labeled data integrated with discrepancies from model-based predictions is implemented to update the neural network parameters. Numerical experiments with multiple settings on simulation and NGSIM datasets show that the IDM-Follower can improve the prediction performance compared to the model-based or learning-based methods alone. Analysis on different noise levels also shows good robustness of the model.

eess.SY↗

arXiv2022

Quasiparticle characteristics of the weakly ferromagnetic Hund's metal MnSi

Hund's metals are multi-orbital systems with $3d$ or $4d$ electrons exhibiting both itinerant character and local moments, and they feature Kondo-like screenings of local orbital and spin moments, with suppressed coherence temperature driven by Hund's coupling $J_H$. They often exhibit magnetic order at low temperature, but how the interaction between the Kondo-like screening and long-range magnetic order is manifested in the quasiparticle spectrum remains an open question. Here we present spectroscopic signature of such interaction in a Hund's metal candidate MnSi exhibiting weak ferromagnetism. Our photoemission measurements reveal renormalized quasiparticle bands near the Fermi level with strong momentum dependence: the ferromagnetism manifests through possibly exchange-split bands (Q1) below $T_C$ , while the spin/orbital screenings lead to gradual development of quasiparticles (Q2) upon cooling. Our results demonstrate how the characteristic spin/orbital coherence in a Hund's metal could coexist and compete with the magnetic order to form a weak itinerant ferromagnet, via quasiparticle bands that are well separated in momentum space and exhibit distinct temperature dependence. Our results imply that the competition between the spin/orbital screening and the magnetic order in a Hund's metal bears intriguing similarity to the Kondo lattice systems.

cond-mat.str-el↗

arXiv2022

Interplay of broken symmetry and delocalized excitations in the insulating state of 1$T$-TaS$_2$

Coexistence of localized and extended excitations is central to the macroscopic properties of correlated materials. For 5d transition metal compounds, electron correlations alone generally do not lead to a metal-insulator (Mott) transition, with insulating behavior usually resulting from their coupling with magnetic ordering and/or structural distortions. 1$T$-TaS$_2$ is a prototypical example of such correlated insulating behavior, with a high-symmetry metallic phase transforming into a distorted, charge density wave (CDW) insulating state at low temperatures. The relevance of the localized electron physics at play in 3d compounds to these 5d transition metal compounds remains an open question. We resolved this standing controversy in 1$T$-TaS$_2$ combining resonant inelastic X-ray spectroscopy and first-principles calculations. We observed five electronic excitations arising from the interband transitions of the Ta 5d orbitals and the S 3p ligand state, with none of the excitations on the order of the Mott gap. These excitations cannot be explained within the framework of standard multiplet calculations that assume a localized wavefunction, but instead, are captured by a band theory framework accounting for the low symmetry of the crystal field in the CDW state. Our findings suggest that the electronic property of 1$T$-TaS$_2$ is dominated by both plasmonic quasiparticles and inter-band transitions associated with a Drude-type response, with no resonance associated with a putative Mott transition. Our discovery provides new insights into the electron localization and the onset of insulating behavior in 5d transition metal materials.

cond-mat.mtrl-sci↗

arXiv2022

Probing CP Violation in Neutrino-antineutrino Oscillations with Non-unitary Flavor Mixing

If massive neutrinos are Majorana particles, then the lepton number should be violated and neutrino-antineutrino oscillations will take place. In this talk, we present the properties of CP violation in neutrino-antineutrino oscillations with a non-unitary leptonic flavor mixing matrix, which naturally arises in the type-I seesaw model due to the mixing between light and heavy Majorana neutrinos. Taking into account current experimental bounds on the leptonic unitarity violation, we show that the CP asymmetries induced by the non-unitary mixing parameters can significantly deviate from those in the unitarity limit.

hep-ph↗

arXiv2022

CONVIQT: Contrastive Video Quality Estimator

Perceptual video quality assessment (VQA) is an integral component of many streaming and video sharing platforms. Here we consider the problem of learning perceptually relevant video quality representations in a self-supervised manner. Distortion type identification and degradation level determination is employed as an auxiliary task to train a deep learning model containing a deep Convolutional Neural Network (CNN) that extracts spatial features, as well as a recurrent unit that captures temporal information. The model is trained using a contrastive loss and we therefore refer to this training framework and resulting model as CONtrastive VIdeo Quality EstimaTor (CONVIQT). During testing, the weights of the trained model are frozen, and a linear regressor maps the learned features to quality scores in a no-reference (NR) setting. We conduct comprehensive evaluations of the proposed model on multiple VQA databases by analyzing the correlations between model predictions and ground-truth quality ratings, and achieve competitive performance when compared to state-of-the-art NR-VQA models, even though it is not trained on those databases. Our ablation experiments demonstrate that the learned representations are highly robust and generalize well across synthetic and realistic distortions. Our results indicate that compelling representations with perceptual bearing can be obtained using self-supervised learning. The implementations used in this work have been made available at https://github.com/pavancm/CONVIQT.

eess.IV↗

arXiv2022

On the Role of Generalization in Transferability of Adversarial Examples

Black-box adversarial attacks designing adversarial examples for unseen neural networks (NNs) have received great attention over the past years. While several successful black-box attack schemes have been proposed in the literature, the underlying factors driving the transferability of black-box adversarial examples still lack a thorough understanding. In this paper, we aim to demonstrate the role of the generalization properties of the substitute classifier used for generating adversarial examples in the transferability of the attack scheme to unobserved NN classifiers. To do this, we apply the max-min adversarial example game framework and show the importance of the generalization properties of the substitute NN in the success of the black-box attack scheme in application to different NN classifiers. We prove theoretical generalization bounds on the difference between the attack transferability rates on training and test samples. Our bounds suggest that a substitute NN with better generalization behavior could result in more transferable adversarial examples. In addition, we show that standard operator norm-based regularization methods could improve the transferability of the designed adversarial examples. We support our theoretical results by performing several numerical experiments showing the role of the substitute network's generalization in generating transferable adversarial examples. Our empirical results indicate the power of Lipschitz regularization methods in improving the transferability of adversarial examples.

cs.LG↗