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Researcher profile

Yulin Chen

Yulin Chen contributes to research discovery and scholarly infrastructure.

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cond-mat.mtrl-scicond-mat.supr-concond-mat.str-elArtificial IntelligenceComputation and Languagecond-mat.mes-hallMachine LearningCryptography and Securityeess.IVNeurons and Cognitionphysics.data-anphysics.optics

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Published work

25 published item(s)

preprint2026arXiv

Experimental Realization of All-Optical Terahertz Attoclock

The attoclock is a powerful tool for probing ultrafast electron dynamics with attosecond precision.Here, we demonstrate an all-optical terahertz (THz) attoclock that reconstructs photoionization dynamics by detecting the THz radiation emitted from Ar atoms ionized by two-color (800 nm/400 nm) laser fields. In this approach, the polarization direction of the emitted THz field reflects the direction of the photoelectron drift velocity and thus serves as a direct observable that encodes the effective ionization delay, analogous to the angular deflection of photoelectrons in conventional attoclocks. By precisely tailoring the relative phase and ellipticity of the driving fields, we observe intensity-dependent rotations of the THz polarization. These rotations, which reveal changes of the effective delay, are consistent with both conventional attoclock measurements and time-dependent Schrödinger equation simulations. Our experiment establishes the feasibility of the THz attoclock as a vacuum-free and contactless probe of tunneling dynamics, offering a transformative alternative for investigating condensed-matter systems where photoelectron detection is challenging.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Meow-Omni 1: A Multimodal Large Language Model for Feline Ethology

Deciphering animal intent is a fundamental challenge in computational ethology, largely because of semantic aliasing, the phenomenon where identical external signals (e.g., a cat's purr) correspond to radically different internal states depending on physiological context. Existing Multimodal Large Language Models (MLLMs) are blind to high-frequency biological time-series data, restricting them to superficial behavioural pattern matching rather than genuine latent-state reasoning. To bridge this gap, we introduce Meow-Omni 1, the first open-source, quad-modal MLLM purpose-built for computational ethology. It natively fuses video, audio, and physiological time-series streams with textual reasoning. Through targeted architectural adaptation, we integrate specialized scientific encoders into a unified backbone and formalize intent inference via physiologically grounded cross-modal alignment. Evaluated on MeowBench, a novel, expert-verified quad-modal benchmark, Meow-Omni 1 achieves state-of-the-art intent-recognition accuracy (71.16%), substantially outperforming leading vision-language and omni-modal baselines. We release the complete open-source pipeline including model weights, training framework, and the Meow-10K dataset, to establish a scalable paradigm for inter-species intent understanding and to advance foundation models toward real-world veterinary diagnostics and wildlife conservation.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

TACT: Mitigating Overthinking and Overacting in Coding Agents via Activation Steering

When language model agents tackle complex software engineering tasks, they often degrade over long trajectories, which we define as *agent drift*. We focus on two recurring failure modes *overthinking* and *overacting*, i.e., where the agent repeatedly reasons over information it already has, and where it issues tool calls without integrating recent observations or acquiring new evidence. In this paper, we introduce TACT (Think-Act Calibration via activation Steering), to detect and mitigate agent drift in the residual stream before it surfaces as a behavioral failure. In specific, we label trajectory steps as overthinking, overacting, or calibrated, and find that their hidden states can separate linearly along two *drift axes*, pointing from calibrated behavior toward each failure mode (AUC $\approx$ 0.9). To mitigate agent drift, we project each step's activation onto these axes at test time and pull drifted ones back toward the calibrated region. Experiments show that TACT outperforms unsteered baselines across SWE-bench Verified, Terminal-Bench 2.0, and CLAW-Eval, lifting average resolve rate by $+5.8$ pp on Qwen3.5-27B and $+4.8$ pp on Gemma-4-26B-A4B-it while cutting steps-to-resolve by up to $26\%$. These gains frame agent drift as a steerable direction in the residual stream, and position TACT as a viable handle for reliable long-horizon agents.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

The Unlearnability Phenomenon in RLVR for Language Models

Reinforcement Learning with Verifiable Reward (RLVR) has proven effective in improving Large Language Model's (LLM) reasoning ability. However, the learning dynamics of RLVR remain underexplored. In this paper, we reveal a counterintuitive phenomenon: among hard examples that the model initially struggles with, a substantial subset remains unlearnable even when correct rollouts are present. To understand the phenomenon, we first demonstrate that existing optimization and sampling techniques fail to resolve unlearnability. With cross-example gradient analysis, we show that unlearnable examples have fundamental representation issue, characterized by low gradient similarity with the rest of the examples and ungeneralizable reasoning patterns. We further show that representation flaws are difficult to mitigate in RL, as data augmentation does not improve gradient similarity. Our study provides the first systematic characterization of unlearnable data in RLVR training and reveals fundamental limitations in current RL approaches for reasoning tasks. Code and data are available at \url{https://github.com/yulinchen99/unlearnability-rlvr}.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections

Web agents can autonomously complete online tasks by interacting with websites, but their exposure to open web environments makes them vulnerable to prompt injection attacks embedded in HTML content or visual interfaces. Existing guard models still suffer from limited generalization to unseen domains and attack patterns, high false positive rates on benign content, reduced deployment efficiency due to added latency at each step, and vulnerability to adversarial attacks that evolve over time or directly target the guard itself. To address these limitations, we propose WARD (Web Agent Robust Defense against Prompt Injection), a practical guard model for secure and efficient web agents. WARD is built on WARD-Base, a large-scale dataset with around 177K samples collected from 719 high-traffic URLs and platforms, and WARD-PIG, a dedicated dataset designed for prompt injection attacks targeting the guard model. We further introduce A3T, an adaptive adversarial attack training framework that iteratively strengthens WARD through a memory-based attacker and guard co-evolution process. Extensive experiments show that WARD achieves nearly perfect recall on out-of-distribution benchmarks, maintains low false positive rates to preserve agent utility, remains robust against guard-targeted and adaptive attacks under substantial distribution shifts, and runs efficiently in parallel with the agent without introducing additional latency.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Pressure-Induced Superconductivity in Topological Heterostructure (PbSe)5(Bi2Se3)6

Recently, the natural heterostructure of (PbSe)5(Bi2Se3)6 has been theoretically predicted and experimentally confirmed as a topological insulator. In this work, we induce superconductivity in (PbSe)5(Bi2Se3)6 by implementing high pressure. As increasing pressure up to 10 GPa, superconductivity with Tc ~ 4.6 K suddenly appears, followed by an abrupt decrease. Remarkably, upon further compression above 30 GPa, a new superconducting state arises, where pressure raises the Tc to an unsaturated 6.0 K within the limit of our research. Combining XRD and Raman spectroscopies, we suggest that the emergence of two distinct superconducting states occurs concurrently with the pressure-induced structural transition in this topological heterostructure (PbSe)5(Bi2Se3)6.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Approaching a Minimal Topological Electronic Structure in Antiferromagnetic Topological Insulator MnBi2Te4 via Surface Modification

The topological electronic structure plays a central role in the non-trivial physical properties in topological quantum materials. A minimal, hydrogen-atom-like topological electronic structure is desired for researches. In this work, we demonstrate an effort towards the realization of such a system in the intrinsic magnetic topological insulator MnBi2Te4, by manipulating the topological surface state (TSS) via surface modification. Using high resolution laser- and synchrotron-based angle-resolved photoemission spectroscopy (ARPES), we found the TSS in MnBi2Te4 is heavily hybridized with a trivial Rashba-type surface state (RSS), which could be efficiently removed by the in situ surface potassium (K) dosing. By employing multiple experimental methods to characterize K dosed surface, we attribute such a modification to the electrochemical reactions of K clusters on the surface. Our work not only gives a clear band assignment in MnBi2Te4, but also provides possible new routes in accentuating the topological behavior in the magnetic topological quantum materials.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Despite the success, the process of fine-tuning large-scale PLMs brings prohibitive adaptation costs. In fact, fine-tuning all the parameters of a colossal model and retaining separate instances for different tasks are practically infeasible. This necessitates a new branch of research focusing on the parameter-efficient adaptation of PLMs, dubbed as delta tuning in this paper. In contrast with the standard fine-tuning, delta tuning only fine-tunes a small portion of the model parameters while keeping the rest untouched, largely reducing both the computation and storage costs. Recent studies have demonstrated that a series of delta tuning methods with distinct tuned parameter selection could achieve performance on a par with full-parameter fine-tuning, suggesting a new promising way of stimulating large-scale PLMs. In this paper, we first formally describe the problem of delta tuning and then comprehensively review recent delta tuning approaches. We also propose a unified categorization criterion that divide existing delta tuning methods into three groups: addition-based, specification-based, and reparameterization-based methods. Though initially proposed as an efficient method to steer large models, we believe that some of the fascinating evidence discovered along with delta tuning could help further reveal the mechanisms of PLMs and even deep neural networks. To this end, we discuss the theoretical principles underlying the effectiveness of delta tuning and propose frameworks to interpret delta tuning from the perspective of optimization and optimal control, respectively. Furthermore, we provide a holistic empirical study of representative methods, where results on over 100 NLP tasks demonstrate a comprehensive performance comparison of different approaches. The experimental results also cover the analysis of combinatorial, scaling and transferable properties of delta tuning.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Direct Visualization and Manipulation of Tunable Quantum Well State in Semiconducting Nb2SiTe4

Quantum well states (QWSs) can form at the surface or interfaces of materials with confinement potential. They have broad applications in electronic and optical devices such as high mobility electron transistor, photodetector and quantum well laser. The properties of the QWSs are usually the key factors for the performance of the devices. However, direct visualization and manipulation of such states are in general challenging. In this work, by using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy/spectroscopy (STM/STS), we directly probe the QWSs generated on the vacuum interface of a narrow band gap semiconductor Nb2SiTe4. Interestingly, the position and splitting of QWSs could be easily manipulated via potassium (K) dosage onto the sample surface. Our results suggest Nb2SiTe4 to be an intriguing semiconductor system to study and engineer the QWSs, which has great potential in device applications.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Emergent superconductivity in van der Waals Kagome material Pd3P2S8 under high pressure

Kagome lattice systems have been proposed to host rich physics, which provide an excellent platform to explore unusual quantum states. Here, we report on the discovery of superconductivity in van der Waals material Pd3P2S8 under pressure. The superconductivity is observed in Pd3P2S8 for those pressures where the temperature dependence of the resistivity changes from a semiconducting-like behavior to that of a normal metal. The superconducting transition temperature Tc increases with applied pressure and reaches ~ 6.83 K at 79.5 GPa. Combining high-pressure XRD, Raman spectroscopy and theoretical calculations, our results demonstrate that the observed superconductivity induced by high pressure in Pd3P2S8 is closely related to the formation of amorphous phase, which results from the structural instability due to the enhanced coupling between interlayer Pd and S atoms upon compression.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Evolution of the electronic structure of ultrathin MnBi2Te4 Films

Ultrathin films of intrinsic magnetic topological insulator MnBi2Te4 exhibit fascinating quantum properties such as quantum anomalous Hall effect and axion insulator state. In this work, we systematically investigate the evolution of the electronic structure of MnBi2Te4 thin films. With increasing film thickness, the electronic structure changes from an insulator-type with a large energy gap to one with in-gap topological surface states, which is, however, still drastically different from the bulk material. By surface doping of alkali-metal atoms, a Rashba split band gradually emerges and hybridizes with topological surface states, which not only reconciles the puzzling difference between the electronic structures of the bulk and thin film MnBi2Te4 but also provides an interesting platform to establish Rashba ferromagnet that is attractive for (quantum) anomalous Hall effect. Our results provide important insights into the understanding and engineering of the intriguing quantum properties of MnBi2Te4 thin films.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Observation of Coexisting Dirac Bands and Moiré Flat Bands in Magic-Angle Twisted Trilayer Graphene

Moiré superlattices that consist of two or more layers of two-dimensional materials stacked together with a small twist angle have emerged as a tunable platform to realize various correlated and topological phases, such as Mott insulators, unconventional uperconductivity and quantum anomalous Hall effect. Recently, the magic-angle twisted trilayer graphene (MATTG) has shown both robust superconductivity similar to magic-angle twisted bilayer graphene (MATBG) and other unique properties, including the Pauli-limit violating and re-entrant superconductivity. These rich properties are deeply rooted in its electronic structure under the influence of distinct moiré potential and mirror symmetry. Here, combining nanometer-scale spatially resolved angle-resolved photoemission spectroscopy (nano-ARPES) and scanning tunneling microscopy/spectroscopy (STM/STS), we systematically measure the yet unexplored band structure of MATTG near charge neutrality. Our measurements reveal the coexistence of the distinct dispersive Dirac band with the emergent moiré flat band, showing nice agreement with the theoretical calculations. These results serve as a stepstone for further understanding of the unconventional superconductivity in MATTG.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Observation of Dimension-Crossover of a Tunable 1D Dirac Fermion in Topological Semimetal NbSi$_x$Te$_2$

Condensed matter systems in low dimensions exhibit emergent physics that does not exist in three dimensions. When electrons are confined to one dimension (1D), some significant electronic states appear, such as charge density wave, spin-charge separations and Su-Schrieffer-Heeger (SSH) topological state. However, a clear understanding of how the 1D electronic properties connects with topology is currently lacking. Here we systematically investigated the characteristic 1D Dirac fermion electronic structure originated from the metallic NbTe$_2$ chains on the surface of the composition-tunable layered compound NbSi$_x$Te$_2$ ($x$ = 0.40 and 0.43) using angle-resolved photoemission spectroscopy. We found the Dirac fermion forms a Dirac nodal line structure protected by the combined $\widetilde{\mathcal{M}}{\rm_y}$ and time-reversal symmetry T and proves the NbSi$_x$Te$_2$ system as a topological semimetal, in consistent with the ab-initio calculations. As $x$ decreases, the interaction between adjacent NbTe2 chains increases and Dirac fermion goes through a dimension-crossover from 1D to 2D, as evidenced by the variation of its Fermi surface and Fermi velocity across the Brillouin zone in consistence with a Dirac SSH model. Our findings demonstrate a tunable 1D Dirac electron system, which offers a versatile platform for the exploration of intriguing 1D physics and device applications.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Persistent exchange splitting in a chiral helimagnet Cr1/3NbS2

Using high-resolution angle-resolved photoemission spectroscopy (ARPES) and ab-initio calculation, we systematically investigate the electronic structure of the chiral helimagnet Cr1/3NbS2 and its temperature evolution. The comparison with NbS2 suggests that the electronic structure of Cr1/3NbS2 is strongly modified by the intercalation of Cr atoms. Our ab-initio calculation, consistent with experimental result, suggests strong hybridization between Nb- and Cr-derived states near the Fermi level. In the chiral helimagnetic state (below the Curie temperature Tc), we observe exchange splitting of the energy bands crossing EF, which follows the temperature evolution of the magnetic moment, suggesting an important role of the conduction electrons in the long-range magnetic ordering. Interestingly, the exchange splitting persists far above Tc with negligible temperature dependence, in drastic contrast to the itinerant ferromagnetism described by the Stoner model, indicating the existence of short-range magnetic order. Our results provide important insights into the microscopic mechanism of the chiral helimagnetic ordering in Cr1/3NbS2.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Pressure-Induced Superconductivity and Structural Phase Transitions in Magnetic Topological Insulator Candidate MnSb4Te7

The magnetic van der Waals crystals (MnX2Te4)m(X2Te3)n (X = Sb, Bi) have drawn significant attention due to their rich topological properties and the tenability by external magnetic field. In this work, we report on the discovery of superconductivity in magnetic topological insulator candidate MnSb4Te7 (m = 1, n = 1) via the application of high pressure. The antiferromagnetic ordering is robust to pressure until 8 GPa and then fully suppressed. The carrier type converts from hole- to electron-type accompanied with structural phase transition at around 15 GPa. Superconductivity emerges near the critical pressure 30 GPa where MnSb4Te7 converted into a simple cubic phase. Interestingly, MnSb4Te7 shows a dome-like phase diagram with a maximum Tc of 2.2 K at 50.7 GPa. The results demonstrate that MnSb4Te7 with nontrivial topology of electronic states display new ground states upon compression.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Pressure-induced Superconductivity in dual-topological semimetal Pt2HgSe3

Recently monolayer jacutingaite (Pt2HgSe3), a naturally occurring exfoliable mineral, discovered in Brazil in 2008, has been theoretically predicted as a candidate quantum spin Hall system with a 0.5 eV band gap, while the bulk form is one of only a few known dual-topological insulators which may host different surface states protected by symmetries. In this work, we systematically investigate both structure and electronic evolution of bulk Pt2HgSe3 under high pressure up to 96 GPa. The nontrivial topology persists up to the structural phase transition observed in the high-pressure regime. Interestingly, we found that this phase transition is accompanied by the appearance of superconductivity at around 55 GPa and the critical transition temperature Tc increases with applied pressure. Our results demonstrate that Pt2HgSe3 with nontrivial topology of electronic states displays new ground states upon compression and raises potentials in application to the next-generation spintronic devices.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Quantum oscillations in Noncentrosymmetric Weyl semimetals RAlSi (R = Sm and Ce)

Weyl semimetal (WSM) as a new type of quantum state of matter hosting low energy relativistic quasiparticles, has attracted significant attention for both scientific community and potential quantum device applications. Here, we report a comprehensive investigation of the structural, magnetic and transport properties of noncentrosymmetric RAlSi (R = Sm, Ce), which have been predicted to be new magnetic WSM candidates. Both samples exhibit non-saturated magnetoresistance (MR), with ~ 900% for SmAlSi and 80% for CeAlSi at 1.8 K, 9 T. The carrier densities of SmAlSi and CeAlSi display remarkable change around magnetic transition temperatures, signifying that the electronic states are sensitive to magnetic ordering of rare earth elements. At low temperatures, SmAlSi reveals prominent Shubnikov-de Haas (SdH) oscillations associated with the nontrivial Berry phase. High pressure experiments demonstrate that the magnetic order is robust and survival under high pressure. Our results would yield valuable insights of WSM physics and potentials in application to the next-generation spintronic devices in RAX family.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Chiral Topological Semimetal with Multifold Band Crossings and Long Fermi arcs

Topological semimetals in crystals with a chiral structure (which possess a handedness due to a lack of mirror and inversion symmetries) are expected to display numerous exotic physical phenomena, including fermionic excitations with large topological charge [1], long Fermi arc surface states [2,3], unusual magnetotransport [4] and lattice dynamics [5], as well as a quantized response to circularly polarized light [6]. To date, all experimentally confirmed topological semimetals exist in crystals that contain mirror operations, meaning that these properties do not appear. Here, we show that AlPt is a structurally chiral topological semimetal that hosts new fourfold and sixfold fermions, which can be viewed as a higher spin eneralization of Weyl fermions without equivalence in elementary particle physics. These multifold fermions are located at high symmetry points and have Chern numbers larger than those in Weyl semimetals, thus resulting in multiple Fermi arcs that span the full diagonal of the surface Brillouin zone. By imaging these long Fermi arcs, we experimentally determine the magnitude and sign of their Chern number, allowing us to relate their dispersion to the handedness of their host crystal.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Electronic Origin for the Enhanced Thermoelectric Efficiency of Cu2Se

Thermoelectric materials (TMs) can uniquely convert waste heat into electricity, which provides a potential solution for the global energy crisis that is increasingly severe. Bulk Cu2Se, with ionic conductivity of Cu ions, exhibits a significant enhancement of its thermoelectric figure of merit zT by a factor of ~3 near its structural transition around 400 K. Here, we show a systematic study of the electronic structure of Cu2Se and its temperature evolution using high-resolution angle-resolved photoemission spectroscopy. Upon heating across the structural transition, the electronic states near the corner of the Brillouin zone gradually disappear, while the bands near the centre of Brillouin zone shift abruptly towards high binding energies and develop an energy gap. Interestingly, the observed band reconstruction well reproduces the temperature evolution of the Seebeck coefficient of Cu2Se, providing an electronic origin for the drastic enhancement of the thermoelectric performance near 400 K. The current results not only bridge among structural phase transition, electronic structures, and thermoelectric properties in a condensed matter system, but also provide valuable insights into the search and design of new generation of thermoelectric materials.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Electronic structure of a Si-containing topological Dirac semimetal CaAl2Si2

There has been an upsurge in the discovery of topological quantum materials, where various topological insulators and semimetals have been theoretically predicted and experimentally observed. However, only very few of them contains silicon, the most widely used element in electronic industry. Recently, ternary compound CaAl2Si2 has been predicted to be a topological Dirac semimetal, hosting Lorentz-symmetry-violating quasiparticles with a strongly tilted conical band dispersion. In this work, by using high-resolution angle-resolved photoemission spectroscopy (ARPES), we investigated the comprehensive electronic structure of CaAl2Si2. A pair of topological Dirac crossings is observed along the kz direction, in good agreement with the ab initio calculations, confirming the topological Dirac semimetal nature of the compound. Our study expands the topological material family on Si-containing compounds, which have great application potential in realizing low-cost, nontoxic electronic device with topological quantum states.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

High-throughput relation extraction algorithm development associating knowledge articles and electronic health records

Objective: Medical relations are the core components of medical knowledge graphs that are needed for healthcare artificial intelligence. However, the requirement of expert annotation by conventional algorithm development processes creates a major bottleneck for mining new relations. In this paper, we present Hi-RES, a framework for high-throughput relation extraction algorithm development. We also show that combining knowledge articles with electronic health records (EHRs) significantly increases the classification accuracy. Methods: We use relation triplets obtained from structured databases and semistructured webpages to label sentences from target corpora as positive training samples. Two methods are also provided for creating improved negative samples by combining positive samples with naïve negative samples. We propose a common model that summarizes sentence information using large-scale pretrained language models and multi-instance attention, which then joins with the concept embeddings trained from the EHRs for relation prediction. Results: We apply the Hi-RES framework to develop classification algorithms for disorder-disorder relations and disorder-location relations. Millions of sentences are created as training data. Using pretrained language models and EHR-based embeddings individually provides considerable accuracy increases over those of previous models. Joining them together further tremendously increases the accuracy to 0.947 and 0.998 for the two sets of relations, respectively, which are 10-17 percentage points higher than those of previous models. Conclusion: Hi-RES is an efficient framework for achieving high-throughput and accurate relation extraction algorithm development.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Magnetism-induced topological transition in EuAs3

The nature of the interaction between magnetism and topology in magnetic topological semimetals remains mysterious, but may be expected to lead to a variety of novel physics. We present $ab$ $initio$ band calculations, electrical transport and angle-resolved photoemission spectroscopy (ARPES) measurements on the magnetic semimetal EuAs$_3$, demonstrating a magnetism-induced topological transition from a topological nodal-line semimetal in the paramagnetic or the spin-polarized state to a topological massive Dirac metal in the antiferromagnetic (AFM) ground state at low temperature, featuring a pair of massive Dirac points, inverted bands and topological surface states on the (010) surface. Shubnikov-de Haas (SdH) oscillations in the AFM state identify nonzero Berry phase and a negative longitudinal magnetoresistance ($n$-LMR) induced by the chiral anomaly, confirming the topological nature predicted by band calculations. When magnetic moments are fully polarized by an external magnetic field, an unsaturated and extremely large magnetoresistance (XMR) of $\sim$ 2$\times10^5$ % at 1.8 K and 28.3 T is observed, likely arising from topological protection. Consistent with band calculations for the spin-polarized state, four new bands in quantum oscillations different from those in the AFM state are discerned, of which two are topologically protected. Nodal-line structures at the $Y$ point in the Brillouin zone (BZ) are proposed in both the spin-polarized and paramagnetic states, and the latter is proven by ARPES. Moreover, a temperature-induced Lifshitz transition accompanied by the emergence of a new band below 3 K is revealed. These results indicate that magnetic EuAs$_3$ provides a rich platform to explore exotic physics arising from the interaction of magnetism with topology.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Pressure-induced Topological and Structural Phase Transitions in an Antiferromagnetic Topological Insulator

Recently, natural van der Waals heterostructures of (MnBi2Te4)m(Bi2Te3)n have been theoretically predicted and experimentally shown to host tunable magnetic properties and topologically nontrivial surface states. In this work, we systematically investigate both the structural and electronic responses of MnBi2Te4 and MnBi4Te7 to external pressure. In addition to the suppression of antiferromagnetic order, MnBi2Te4 is found to undergo a metal-semiconductor-metal transition upon compression. The resistivity of MnBi4Te7 changes dramatically under high pressure and a non-monotonic evolution of \r{ho}(T) is observed. The nontrivial topology is proved to persists before the structural phase transition observed in the high-pressure regime. We find that the bulk and surface states respond differently to pressure, which is consistent with the non-monotonic change of the resistivity. Interestingly, a pressure-induced amorphous state is observed in MnBi2Te4, while two high pressure phase transitions are revealed in MnBi4Te7. Our combined theoretical and experimental research establishes MnBi2Te4 and MnBi4Te7 as highly tunable magnetic topological insulators, in which phase transitions and new ground states emerge upon compression.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Super Resolution Convolutional Neural Network for Feature Extraction in Spectroscopic Data

Two dimensional (2D) peak finding is a common practice in data analysis for physics experiments, which is typically achieved by computing the local derivatives. However, this method is inherently unstable when the local landscape is complicated, or the signal-to-noise ratio of the data is low. In this work, we propose a new method in which the peak tracking task is formalized as an inverse problem, thus can be solved with a convolutional neural network (CNN). In addition, we show that the underlying physics principle of the experiments can be used to generate the training data. By generalizing the trained neural network on real experimental data, we show that the CNN method can achieve comparable or better results than traditional derivative based methods. This approach can be further generalized in different physics experiments when the physical process is known.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Epitaxial growth and characterization of high quality Bi2O2Se thin films on SrTiO3 substrates by pulsed laser deposition

Recently, Bi2O2Se is discovered as a promising two-dimensional (2D) semiconductor for next generation electronics, due to its moderate bandgap size, high electron mobility and pronounced ambient stability. Meanwhile, it has been predicted that high quality Bi2O2Se-related heterostructures may possess exotic physical phenomena, such as piezoelectricity and topological superconductivity. Herein, we report the first successful heteroepitaxial growth of Bi2O2Se films on SrTiO3 substrates via pulsed laser deposition (PLD) method. Films obtained under optimal conditions show an epitaxial growth with the c axis perpendicular to the film surface and the a and b axes parallel to the substrate. The growth mode transition to three dimensional (3D) island from quasi-2D layer of the heteroepitaxial Bi2O2Se films on SrTiO3 (001) substrates is observed as prolonging deposition time of films. The maximum value of electron mobility reaches 160 cm2/V-1s-1 at room temperature in a 70nm-thick film. The thickness dependent mobility provides evidence that interface-scattering is likely to be the limiting factor for the relatively low electron mobility at low temperature, implying that the interface engineering as an effective method to tune the low temperature electron mobility. Our work suggests the epitaxial Bi2O2Se films grown by PLD are promising for both fundamental study and practical applications.

0 citations0 reviewsNo code linkedOpen access