Topological Semimetal-Insulator Quantum Phase Transition in Zintl Compounds Ba2X (X=Si, Ge)

By first-principles calculations, we find that Ba2X(X=Si, Ge) hosts a topological semimetal phase with one nodal ring in the kx=0 plane, which is protected by the glide mirror symmetry when spin-orbit coupling (SOC) is ignored. The corresponding drumheadlike surface flat band appears on the (100) surface in surface Green function calculation. Furthermore, a topological-semimetal-to-insulator transition (TSMIT) is found. The nodal line semimetal would evolve into topological insulator as SOC is turned on. The topologically protected metallic surface states emerge around the Gamma=0 point, which could be tuned into topologically-trivial insulator state by more than 3% hydrostatic strain. These results reveal a new category of materials showing quantum phase transition between topological semimetal and insulator, and tunability through elastic strain engineering.Comment: 14 pages. 4 figure

The Non-Perturbative Quantum Nature of the Dislocation-Phonon Interaction

Despite the long history of dislocation-phonon interaction studies, there are many problems that have not been fully resolved during this development. These include an incompatibility between a perturbative approach and the long-range nature of a dislocation, the relation between static and dynamic scattering, and the nature of dislocation-phonon resonance. Here by introducing a fully quantized dislocation field, the "dislon"[1], a phonon is renormalized as a quasi-phonon, with shifted quasi-phonon energy, and accompanied by a finite quasi-phonon lifetime that is reducible to classical results. A series of outstanding legacy issues including those above can be directly explained within this unified phonon renormalization approach. In particular, a renormalized phonon naturally resolves the decades-long debate between dynamic and static dislocation-phonon scattering approaches.Comment: 5 pages main text, 3 figures, 10 pages supplemental material

Tunable THz Surface Plasmon Polariton based on Topological Insulator-Layered Superconductor Hybrid Structure

We theoretically investigate the surface plasmon polariton (SPP) at the interface between 3D strong topological insulator (TI) and layered superconductor-magnetic insulator structure. The tunability of SPP through electronic doping can be enhanced when the magnetic permeability of the layered structure becomes higher. When the interface is gapped by superconductivity or perpendicular magnetism, SPP dispersion is further distorted, accompanied by a shift of group velocity and penetration depth. Such a shift of SPP reaches maximum when the magnitude of Fermi level approaches the gap value, and may lead to observable effects. The tunable SPP at the interface between layered superconductor and magnetism materials in proximity to TI surface may provide new insight in the detection of Majorana Fermions.Comment: 6 pages, 4 figure

VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency

The role of data in building AI systems has recently been emphasized by the emerging concept of data-centric AI. Unfortunately, in the real-world, datasets may contain dirty samples, such as poisoned samples from backdoor attack, noisy labels in crowdsourcing, and even hybrids of them. The presence of such dirty samples makes the DNNs vunerable and unreliable.Hence, it is critical to detect dirty samples to improve the quality and realiability of dataset. Existing detectors only focus on detecting poisoned samples or noisy labels, that are often prone to weak generalization when dealing with dirty samples from other domains.In this paper, we find a commonality of various dirty samples is visual-linguistic inconsistency between images and associated labels. To capture the semantic inconsistency between modalities, we propose versatile data cleanser (VDC) leveraging the surpassing capabilities of multimodal large language models (MLLM) in cross-modal alignment and reasoning.It consists of three consecutive modules: the visual question generation module to generate insightful questions about the image; the visual question answering module to acquire the semantics of the visual content by answering the questions with MLLM; followed by the visual answer evaluation module to evaluate the inconsistency.Extensive experiments demonstrate its superior performance and generalization to various categories and types of dirty samples.Comment: 22 pages,5 figures,17 table

Boosting Backdoor Attack with A Learnable Poisoning Sample Selection Strategy

Data-poisoning based backdoor attacks aim to insert backdoor into models by manipulating training datasets without controlling the training process of the target model. Existing attack methods mainly focus on designing triggers or fusion strategies between triggers and benign samples. However, they often randomly select samples to be poisoned, disregarding the varying importance of each poisoning sample in terms of backdoor injection. A recent selection strategy filters a fixed-size poisoning sample pool by recording forgetting events, but it fails to consider the remaining samples outside the pool from a global perspective. Moreover, computing forgetting events requires significant additional computing resources. Therefore, how to efficiently and effectively select poisoning samples from the entire dataset is an urgent problem in backdoor attacks.To address it, firstly, we introduce a poisoning mask into the regular backdoor training loss. We suppose that a backdoored model training with hard poisoning samples has a more backdoor effect on easy ones, which can be implemented by hindering the normal training process (\ie, maximizing loss \wrt mask). To further integrate it with normal training process, we then propose a learnable poisoning sample selection strategy to learn the mask together with the model parameters through a min-max optimization.Specifically, the outer loop aims to achieve the backdoor attack goal by minimizing the loss based on the selected samples, while the inner loop selects hard poisoning samples that impede this goal by maximizing the loss. After several rounds of adversarial training, we finally select effective poisoning samples with high contribution. Extensive experiments on benchmark datasets demonstrate the effectiveness and efficiency of our approach in boosting backdoor attack performance

Proximity Driven Enhanced Magnetic Order at Ferromagnetic Insulator / Magnetic Topological Insulator Interface

Magnetic exchange driven proximity effect at a magnetic insulator / topological insulator (MI/TI) interface provides a rich playground for novel phenomena as well as a way to realize low energy dissipation quantum devices. Here we report a dramatic enhancement of proximity exchange coupling in the MI / magnetic-TI EuS / Sb$_{2-x}$V$_x$Te$_3$ hybrid heterostructure, where V doping is used to drive the TI (Sb$_{2}$Te$_3$) magnetic. We observe an artificial antiferromagnetic-like structure near the MI/TI interface, which may account for the enhanced proximity coupling. The interplay between the proximity effect and doping provides insights into controllable engineering of magnetic order using a hybrid heterostructure.Comment: 5 pages, 4 figure

Spin Transitions and Compressibility of ε‐Fe7N3 and γ′‐Fe4N: Implications for Iron Alloys in Terrestrial Planet Cores

Iron nitrides are possible constituents of the cores of Earth and other terrestrial planets. Pressure‐induced magnetic changes in iron nitrides and effects on compressibility remain poorly understood. Here we report synchrotron X‐ray emission spectroscopy (XES) and X‐ray diffraction (XRD) results for ε‐Fe7N3 and γ′‐Fe4N up to 60 GPa at 300 K. The XES spectra reveal completion of high‐ to low‐spin transition in ε‐Fe7N3 and γ′‐Fe4N at 43 and 34 GPa, respectively. The completion of the spin transition induces stiffening in bulk modulus of ε‐Fe7N3 by 22% at ~40 GPa, but has no resolvable effect on the compression behavior of γ′‐Fe4N. Fitting pressure‐volume data to the Birch‐Murnaghan equation of state yields V0 = 83.29 ± 0.03 (Å3), K0 = 232 ± 9 GPa, K0′ = 4.1 ± 0.5 for nonmagnetic ε‐Fe7N3 above the spin transition completion pressure, and V0 = 54.82 ± 0.02 (Å3), K0 = 152 ± 2 GPa, K0′ = 4.0 ± 0.1 for γ′‐Fe4N over the studied pressure range. By reexamining evidence for spin transition and effects on compressibility of other candidate components of terrestrial planet cores, Fe3S, Fe3P, Fe7C3, and Fe3C based on previous XES and XRD measurements, we located the completion of high‐ to low‐spin transition at ~67, 38, 50, and 30 GPa at 300 K, respectively. The completion of spin transitions of Fe3S, Fe3P, and Fe3C induces elastic stiffening, whereas that of Fe7C3 induces elastic softening. Changes in compressibility at completion of spin transitions in iron‐light element alloys may influence the properties of Earth’s and planetary cores.Key PointsSpin transition in ε‐Fe7N3 and γ′‐Fe4N at 300 K completes at 43 and 34 GPa, respectivelyThe completion of spin transition leads to stiffening in bulk modulus of ε‐Fe7N3, but not in γ′‐Fe4NEvidence for spin transitions in Fe‐light‐element alloys and their effects are reexaminedPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163586/2/jgrb54505_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163586/1/jgrb54505.pd

Dirac-Electrons-Mediated Magnetic Proximity Effect in Topological Insulator / Magnetic Insulator Heterostructures

The possible realization of dissipationless chiral edge current in a topological insulator / magnetic insulator heterostructure is based on the condition that the magnetic proximity exchange coupling at the interface is dominated by the Dirac surface states of the topological insulator. Here we report a polarized neutron reflectometry observation of Dirac electrons mediated magnetic proximity effect in a bulk-insulating topological insulator (Bi$_{0.2}$Sb$_{0.8}$)$_{2}$Te$_{3}$ / magnetic insulator EuS heterostructure. We are able to maximize the proximity induced magnetism by applying an electrical back gate to tune the Fermi level of topological insulator to be close to the charge neutral point. A phenomenological model based on diamagnetic screening is developed to explain the suppressed proximity induced magnetism at high carrier density. Our work paves the way to utilize the magnetic proximity effect at the topological insulator/magnetic insulator hetero-interface for low-power spintronic applications.Comment: 5 pages main text with 4 figures; 2 pages supplemental materials; suggestions and discussions are welcome