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The double neutron star PSR J1846-0513 is discovered by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in Commensal Radio Astronomy FAST Survey. The pulsar is revealed to be harbored in an eccentric orbit with $e=0.208$ and orbital period of 0.613 days. The total mass of the system is constrained to be $2.6287(35)\rm{M}_{\odot}$, with a mass upper limit of $1.3455{\rm~M}_{\odot}$ for the pulsar and a mass lower limit of $1.2845{\rm~M}_{\odot}$ for the companion star. To reproduce its evolution history, we perform a 1D model for the formation of PSR J1846-0513 whose progenitor is assumed to be neutron star - helium (He) star system via MESA code. Since the large eccentricity is widely believed to originate from an asymmetric supernova explosion, we also investigate the dynamical effects of the supernova explosion. Our simulated results show that the progenitor of PSR J1846-0513 could be a binary system consisting of a He star of $3.3-4.0{\rm~M}_\odot$ and a neutron star in a circular orbit with an initial period of $\sim0.5$ days., Comment: 15 pages, 7 figures, Accepted to be published on RAA

Since the discovery of cosmic rays (CRs) over a century ago, their origin has remained a mystery and a key research question. Recently, the LHAASO experiment identified the first CR super-acceleration source, the Cygnus bubble, which can accelerate CRs to energies exceeding 10 PeV. A pertinent question is: how much does the Cygnus bubble contribute to the CR spectrum observed on Earth? With the aim of answering that question, a 3D propagation analysis was conducted on CRs in this study. The Cygnus bubble was incorporated into our propagation model in order to determine its contributions to the observed spectra. First, we calculated the spectrum and spatial morphology of the Cygnus bubble to reproduce the observed LHAASO data. Subsequently, we calculated the diffuse $\gamma$-ray emissions produced by the CRs from the Cygnus bubble and the energy spectrum of the cosmic ray particles near Earth after propagation. Finally, we utilized a CR spatial-dependent propagation model to calculate the large-scale CR energy spectrum and the resulting diffuse $\gamma$-ray emissions. Our results indicate that: (1) the Cygnus bubble contributes minimally to the CR spectrum observed on Earth, (2) the emissions produced by the CR particles from the Cygnus bubble dominates the diffuse $\gamma$-ray emissions in that region, (3) the structural fluctuations of the diffuse $\gamma$-ray emissions observed by LHAASO are likely due to the local CR halo. We anticipate that LHAASO will identify more CR halo sources to validate our model.

Aircraft target detection in SAR images is a challenging task due to the discrete scattering points and severe background clutter interference. Currently, methods with convolution-based or transformer-based paradigms cannot adequately address these issues. In this letter, we explore diffusion models for SAR image aircraft target detection for the first time and propose a novel \underline{Diff}usion-based aircraft target \underline{Det}ection network \underline{for} \underline{SAR} images (DiffDet4SAR). Specifically, the proposed DiffDet4SAR yields two main advantages for SAR aircraft target detection: 1) DiffDet4SAR maps the SAR aircraft target detection task to a denoising diffusion process of bounding boxes without heuristic anchor size selection, effectively enabling large variations in aircraft sizes to be accommodated; and 2) the dedicatedly designed Scattering Feature Enhancement (SFE) module further reduces the clutter intensity and enhances the target saliency during inference. Extensive experimental results on the SAR-AIRcraft-1.0 dataset show that the proposed DiffDet4SAR achieves 88.4\% mAP$_{50}$, outperforming the state-of-the-art methods by 6\%. Code is availabel at \href{https://github.com/JoyeZLearning/DiffDet4SAR}., Comment: accepted by IEEE GRSL

We describe DeepMachining, a deep learning-based AI system for online prediction of machining errors of lathe machine operations. We have built and evaluated DeepMachining based on manufacturing data from factories. Specifically, we first pretrain a deep learning model for a given lathe machine's operations to learn the salient features of machining states. Then, we fine-tune the pretrained model to adapt to specific machining tasks. We demonstrate that DeepMachining achieves high prediction accuracy for multiple tasks that involve different workpieces and cutting tools. To the best of our knowledge, this work is one of the first factory experiments using pre-trained deep-learning models to predict machining errors of lathe machines.

Optical excitation of chiral phonons plays a vital role in studying the phonon-driven magnetic phenomena in solids. Transition metal dichalcogenides host chiral phonons at high symmetry points of the Brillouin zone, providing an ideal platform to explore the interplay between chiral phonons and valley degree of freedom. Here, we investigate the helicity-resolved magneto-Raman response of monolayer MoS2 and identify a doubly degenerate Brillouin-zone-center chiral phonon mode at ~270 cm-1. Our wavelength- and temperature-dependent measurements show that this chiral phonon is activated through the resonant excitation of A exciton. Under an out-of-plane magnetic field, the chiral phonon exhibits giant Zeeman splitting, which corresponds to an effective magnetic moment of ~2.5mu_B. Moreover, we carry out theoretical calculations based on the morphic effects in nonmagnetic crystals, which reproduce the linear Zeeman splitting and Raman cross-section of the chiral phonon. Our study provides important insights into lifting the chiral phonon degeneracy in an achiral covalent material, paving a new route to excite and control chiral phonons.

Co-based materials have recently been explored due to potential to realise complex bond-dependent anisotropic magnetism. Prominent examples include Na$_2$Co$_2$TeO$_6$, BaCo$_2$(AsO$_4$)$_2$, Na$_2$BaCo(PO$_4$)$_2$, and CoX$_2$ (X = Cl, Br, I). In order to provide insight into the magnetic interactions in these compounds, we make a comparative analysis of their local crystal electric field excitations spectra via Raman scattering measurements. Combining these measurements with theoretical analysis confirms the validity of $j_{\rm eff} = 1/2$ single-ion ground states for all compounds, and provides accurate experimental estimates of the local crystal distortions, which play a prominent role in the magnetic couplings between spin-orbital coupled Co moments., Comment: 11 pages, 7 figures

The detection of GW170817/GRB170817A implied the strong association between short gamma-ray bursts (SGRBs) and binary neutron star (BNS) mergers which produce gravitational waves (GWs). More evidence is needed to confirm the association and reveal the physical processes of BNS mergers. The upcoming High Altitude Detection of Astronomical Radiation (HADAR) experiment, excelling in a wide field of view (FOV) and a large effective area above tens of GeV, is a hope for the prompt detection of very-high-energy (VHE; > 10 GeV) SGRBs. The aim of this paper is to simulate and analyse GW/SGRB joint detections by future GW detector networks in synergy with HADAR, including the second generation LIGO, Virgo and KAGRA and the third generation ET and CE. We provide a brief introduction of the HADAR experiment for SGRB simulations and its expected SGRB detections. For GW simulations, we adopt a phenomenological model to describe GWs produced by BNS mergers and introduce the signal-noise ratios (SNRs) as detector responses. Following a theoretical analysis we compute the redshift-dependent efficiency functions of GW detector networks. We then construct the simulation of GW detection by Monte Carlo sampling. We compare the simulated results of LIGO-Virgo O2 and O3 runs with their actual detections as a check. The combination of GW and SGRB models is then discussed for joint detection, including parameter correlations, triggered SNRs and efficiency skymaps. The estimated joint detection rates are 0.09-2.52 per year for LHVK network with HADAR under different possible configurations, and approximately 0.27-7.89 per year for ET+CE network with HADAR.

Vehicle-to-Everything (V2X) collaborative perception has recently gained significant attention due to its capability to enhance scene understanding by integrating information from various agents, e.g., vehicles, and infrastructure. However, current works often treat the information from each agent equally, ignoring the inherent domain gap caused by the utilization of different LiDAR sensors of each agent, thus leading to suboptimal performance. In this paper, we propose DI-V2X, that aims to learn Domain-Invariant representations through a new distillation framework to mitigate the domain discrepancy in the context of V2X 3D object detection. DI-V2X comprises three essential components: a domain-mixing instance augmentation (DMA) module, a progressive domain-invariant distillation (PDD) module, and a domain-adaptive fusion (DAF) module. Specifically, DMA builds a domain-mixing 3D instance bank for the teacher and student models during training, resulting in aligned data representation. Next, PDD encourages the student models from different domains to gradually learn a domain-invariant feature representation towards the teacher, where the overlapping regions between agents are employed as guidance to facilitate the distillation process. Furthermore, DAF closes the domain gap between the students by incorporating calibration-aware domain-adaptive attention. Extensive experiments on the challenging DAIR-V2X and V2XSet benchmark datasets demonstrate DI-V2X achieves remarkable performance, outperforming all the previous V2X models. Code is available at https://github.com/Serenos/DI-V2X, Comment: aaai2024

The HADAR experiment, which will be constructed in Tibet, China, combines the wide-angle advantages of traditional EAS array detectors with the high sensitivity advantages of focused Cherenkov detectors. Its physics objective is to observe transient sources such as gamma-ray bursts and counterparts of gravitational waves. The aim of this study is to utilize the latest AI technology to enhance the sensitivity of the HADAR experiment. We have built training datasets and models with distinctive creativity by incorporating relevant physical theories for various applications. They are able to determine the kind, energy, and direction of incident particles after careful design. We have obtained a background identification accuracy of 98.6%, a relative energy reconstruction error of 10.0%, and an angular resolution of 0.22-degrees in a test dataset at 10 TeV. These findings demonstrate the enormous potential for enhancing the precision and dependability of detector data analysis in astrophysical research. Thanks to deep learning techniques, the HADAR experiment's observational sensitivity to the Crab Nebula has surpassed that of MAGIC and H.E.S.S. at energies below 0.5 TeV and remains competitive with conventional narrow-field Cherenkov telescopes at higher energies. Additionally, our experiment offers a fresh approach to dealing with strongly connected scattered data.

Vertical Federated Learning (VFL) attracts increasing attention because it empowers multiple parties to jointly train a privacy-preserving model over vertically partitioned data. Recent research has shown that applying zeroth-order optimization (ZOO) has many advantages in building a practical VFL algorithm. However, a vital problem with the ZOO-based VFL is its slow convergence rate, which limits its application in handling modern large models. To address this problem, we propose a cascaded hybrid optimization method in VFL. In this method, the downstream models (clients) are trained with ZOO to protect privacy and ensure that no internal information is shared. Meanwhile, the upstream model (server) is updated with first-order optimization (FOO) locally, which significantly improves the convergence rate, making it feasible to train the large models without compromising privacy and security. We theoretically prove that our VFL framework converges faster than the ZOO-based VFL, as the convergence of our framework is not limited by the size of the server model, making it effective for training large models with the major part on the server. Extensive experiments demonstrate that our method achieves faster convergence than the ZOO-based VFL framework, while maintaining an equivalent level of privacy protection. Moreover, we show that the convergence of our VFL is comparable to the unsafe FOO-based VFL baseline. Additionally, we demonstrate that our method makes the training of a large model feasible., Comment: Under Review

Using optical magneto-spectroscopy, we investigate the magnetic excitations of Na$_2$Co$_2$TeO$_6$ in a broad magnetic field range ($0\ \rm{T}\leq B\leq 17.5\ \rm{T}$) at low temperature. Our measurements reveal rich spectra of in-plane magnetic excitations with a surprisingly large number of modes, even in the high-field spin-polarized state. Theoretical calculations find that the Na-occupation disorder in \NCTO plays a crucial role in generating these modes. Our work demonstrates the necessity to consider disorder in the spin environment in the search for Kitaev quantum spin liquid states in practicable materials.

The observation of short gamma ray bursts (SGRBs) in the TeV energy range plays an important role in understanding the radiation mechanism and probing new areas of physics such as Lorentz invariance violation. However, no SGRB has been observed in this energy range due to the short duration of SGRBs and the weakness of current experiments. New experiments with new technology are required to detect sub-TeV SGRBs. In this work, we observe the very high energy (VHE) $\gamma$-ray emissions from SGRBs and calculate the annual detection rate with the High Altitude Detection of Astronomical Radiation HADAR (HADAR) experiment. First, a set of pseudo-SGRB samples is generated and checked using the observations of Fermi-GBM, Fermi-LAT, and SWIFT measurements. The annual detection rate is calculated from these SGRB samples based on the performance of the HADAR instrument. As a result, the HADAR experiment can detect 0.5 SGRB per year if the spectral break-off of $\gamma$-rays caused by the internal absorption is larger than 100 GeV. For a GRB09010-like GRB in HADAR's view, it should be possible to detect approximately 2000 photons considering the internal absorption. With a time delay assumption due to the Lorentz invariance violation effects, a simulated light curve of GRB090510 has evident energy dependence. We hope that the HADAR experiment can perform the SGRB observations and test our calculations in the future.

Understanding melting in metals is a hot topic of present research. This may be accomplished by pumping the system with infrared (IR) laser radiation, and probing it with hard X-rays produced by an X-ray Free-Electron Laser (XFEL). In this work we studied nanostructured polycrystalline thin films of platinum that were illuminated by IR radiation of increasing fluences. We characterized the structural response as well as the nucleation and propagation of the liquid phase as a function of time delay between the IR pump and X-ray probe. We observed partial melting of the samples for IR fluences higher than 200 mJ$\cdot$cm$^{-2}$. To fit the contribution of the liquid phase to the scattering pattern in platinum we applied a model of liquid metal. The two-temperature model simulations were performed to understand the solid-state fraction of the sample heating process as a function of time delay and fluence.

Inspired by the success of recent vision transformers and large kernel design in convolutional neural networks (CNNs), in this paper, we analyze and explore essential reasons for their success. We claim two factors that are critical for 3D large-scale scene understanding: a larger receptive field and operations with greater non-linearity. The former is responsible for providing long range contexts and the latter can enhance the capacity of the network. To achieve the above properties, we propose a simple yet effective long range pooling (LRP) module using dilation max pooling, which provides a network with a large adaptive receptive field. LRP has few parameters, and can be readily added to current CNNs. Also, based on LRP, we present an entire network architecture, LRPNet, for 3D understanding. Ablation studies are presented to support our claims, and show that the LRP module achieves better results than large kernel convolution yet with reduced computation, due to its nonlinearity. We also demonstrate the superiority of LRPNet on various benchmarks: LRPNet performs the best on ScanNet and surpasses other CNN-based methods on S3DIS and Matterport3D. Code will be made publicly available.

Occlusion issue is the biggest challenge in pedestrian detection. RCNN-based detectors extract instance features by cropping rectangle regions of interest in the feature maps. However, the visible pixels of the occluded objects are limited, making the rectangle instance feature mixed with a lot of instance-irrelevant noise information. Besides, by counting the number of instances with different degrees of overlap of CrowdHuman dataset, we find that the number of severely overlapping objects and the number of slightly overlapping objects are unbalanced, which may exacerbate the challenges posed by occlusion issues. Regarding to the noise issue, from the perspective of denoising, an iterable dynamic instance noise filter (DINF) is proposed for the RCNN-based pedestrian detectors to improve the signal-noise ratio of the instance feature. Simulating the wavelet denoising process, we use the instance feature vector to generate dynamic convolutional kernels to transform the RoIs features to a domain in which the near-zero values represent the noise information. Then, soft thresholding with channel-wise adaptive thresholds is applied to convert the near-zero values to zero to filter out noise information. For the imbalance issue, we propose an IoU-Focal factor (IFF) to modulate the contributions of the well-regressed boxes and the bad-regressed boxes to the loss in the training process, paying more attention to the minority severely overlapping objects. Extensive experiments conducted on CrowdHuman and CityPersons demonstrate that our methods can help RCNN-based pedestrian detectors achieve state-of-the-art performance., Comment: 15 pages, 8 figures

This paper describes our winning system on SemEval 2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts. A replaced token detection pre-trained model is utilized with minorly different task-specific heads for SubTask-A: Multi-class Classification and SubTask-B: Ranking. Incorporating a pattern-aware ensemble method, our system achieves a 68.90% accuracy score and 0.8070 spearman's rank correlation score surpassing the 2nd place with a large margin by 2.7 and 2.2 percent points for SubTask-A and SubTask-B, respectively. Our approach is simple and easy to implement, and we conducted ablation studies and qualitative and quantitative analyses for the working strategies used in our system., Comment: Accepted at the 16th International Workshop on Semantic Evaluation (SemEval-2022), NAACL

The structural characterization and electrical transport measurements at ambient and applied pressures of the compounds of the La(Ag1-xAux)Sb2 family are presented. Up to two charge density wave (CDW) transitions could be detected upon cooling from room temperature and an equivalence of the effects of chemical and physical pressure on the CDW ordering temperatures was observed with the unit cell volume being a salient structural parameter. As such La(Ag1-xAux)Sb2 is a rare example of a non-cubic system that exhibits good agreement between the effects of applied, physical, pressure and changes in unit cell volume from steric changes induced by isovalent substitution. Additionally, for La(Ag0.54Au0.46)Sb2 anomalies in low temperature electrical transport were observed in the pressure range where the lower charge density wave is completely suppressed.

EuCd$_2$As$_2$ is an antiferromagnetic semimetal, that can host non-trivial topological properties, depending upon its magnetic state and excitations. Here, we report the synthesis and characterization of Eu(Cd$_{1-x}$Ag$_x$)$_2$As$_2$ and Eu$_{1-y}$Na$_y$Cd$_2$As$_2$, and study the evolution and nature of magnetic order with doping. Temperature-substitution phase diagrams are constructed from the electrical resistance and magnetic susceptibility data. We observe a splitting of the magnetic transition into two different transitions, and the gradual increase in one of the transition temperatures with Ag- and Na-substitution. The other transition remains more or less independent of doping. We further show that a magnetic state with a net ferromagnetic moment is stabilized by both Ag and Na doping and this can be explained by considering the changes in band filling due to substitution as suggested by density functional theory (DFT) calculations. We thus show that chemical substitution and the subsequent changes in band filling could be a pathway to tune the magnetic ground state and to stabilize a ferromagnetic phase in EuCd$_2$As$_2$.

Among current anchor-based detectors, a positive anchor box will be intuitively assigned to the object that overlaps it the most. The assigned label to each anchor will directly determine the optimization direction of the corresponding prediction box, including the direction of box regression and category prediction. In our practice of crowded object detection, however, the results show that a positive anchor does not always regress toward the object that overlaps it the most when multiple objects overlap. We name it anchor drift. The anchor drift reflects that the anchor-object matching relation, which is determined by the degree of overlap between anchors and objects, is not always optimal. Conflicts between the fixed matching relation and learned experience in the past training process may cause ambiguous predictions and thus raise the false-positive rate. In this paper, a simple but efficient adaptive two-stage anchor assignment (TSAA) method is proposed. It utilizes the final prediction boxes rather than the fixed anchors to calculate the overlap degree with objects to determine which object to regress for each anchor. The participation of the prediction box makes the anchor-object assignment mechanism adaptive. Extensive experiments are conducted on three classic detectors RetinaNet, Faster-RCNN and YOLOv3 on CrowdHuman and COCO to evaluate the effectiveness of TSAA. The results show that TSAA can significantly improve the detectors' performance without additional computational costs or network structure changes., Comment: 11 pages, 8 figures

Interlayer excitons, or bound electron-hole pairs whose constituent quasiparticles are located in distinct stacked semiconducting layers, are being intensively studied in heterobilayers of two dimensional semiconductors. They owe their existence to an intrinsic type-II band alignment between both layers that convert these into p-n junctions. Here, we unveil a pronounced interlayer exciton (IX) in heterobilayers of metal monochalcogenides, namely gamma-InSe on epsilon-GaSe, whose pronounced emission is adjustable just by varying their thicknesses given their number of layers dependent direct bandgaps. Time-dependent photoluminescense spectroscopy unveils considerably longer interlayer exciton lifetimes with respect to intralayer ones, thus confirming their nature. The linear Stark effect yields a bound electron-hole pair whose separation d is just (3.6 \pm 0.1) {\AA} with d being very close to dSe = 3.4 {\AA} which is the calculated interfacial Se separation. The envelope of IX is twist angle dependent and describable by superimposed emissions that are nearly equally spaced in energy, as if quantized due to localization induced by the small moir\'e periodicity. These heterostacks are characterized by extremely flat interfacial valence bands making them prime candidates for the observation of magnetism or other correlated electronic phases upon carrier doping., Comment: ACS Nano, in press 42 pages plus, 4 figures, plus supplementary information file, containing 21 supplementary figures

Resistance measurements on single crystals of CaK(Fe$_{1-x}$Mn$_x$)$_4$As$_4$ ($x$ = 0.024) were performed under hydrostatic pressure up to 5.15 GPa. The pressure dependence of the magnetic and superconducting transition temperatures and that of the superconducting upper critical field are reported. Our results show that upon increasing pressure, the magnetic transition temperature $T_{N}$ is suppressed, whereas the superconducting transition temperature $T_{c}$ first increases and then decreases, exhibiting a maximum at a pressure $p_c$ corresponding to the intersection of the $T_{N}$($p$) and $T_{c}$($p$) lines. In addition, a minimum in the normalized slope of the superconducting upper critical field as well as a change in the pressure dependence of the inferred superconducting coherence length are observed at $p_c$, suggesting a difference in the Fermi surface of the paramagnetic and antiferromagnetic states. Finally, CaK(Fe$_{1-x}$Mn$_x$)$_4$As$_4$ ($x$ = 0.024) likely goes through a half-collapsed-tetragonal phase transition at $\sim$ 4.3 GPa, further demonstrating that the half-collapsed-tetragonal transition pressure in the CaKFe$_4$As$_4$ system is relatively insensitive to transition metal substitution., Comment: 6 figures

The colorectal polyps classification is a critical clinical examination. To improve the classification accuracy, most computer-aided diagnosis algorithms recognize colorectal polyps by adopting Narrow-Band Imaging (NBI). However, the NBI usually suffers from missing utilization in real clinic scenarios since the acquisition of this specific image requires manual switching of the light mode when polyps have been detected by using White-Light (WL) images. To avoid the above situation, we propose a novel method to directly achieve accurate white-light colonoscopy image classification by conducting structured cross-modal representation consistency. In practice, a pair of multi-modal images, i.e. NBI and WL, are fed into a shared Transformer to extract hierarchical feature representations. Then a novel designed Spatial Attention Module (SAM) is adopted to calculate the similarities between the class token and patch tokens %from multi-levels for a specific modality image. By aligning the class tokens and spatial attention maps of paired NBI and WL images at different levels, the Transformer achieves the ability to keep both global and local representation consistency for the above two modalities. Extensive experimental results illustrate the proposed method outperforms the recent studies with a margin, realizing multi-modal prediction with a single Transformer while greatly improving the classification accuracy when only with WL images., Comment: Early Accepted by MICCAI 2022

Objects in aerial images have greater variations in scale and orientation than in typical images, so detection is more difficult. Convolutional neural networks use a variety of frequency- and orientation-specific kernels to identify objects subject to different transformations; these require many parameters. Sampling equivariant networks can adjust sampling from input feature maps according to the transformation of the object, allowing a kernel to extract features of an object under different transformations. Doing so requires fewer parameters, and makes the network more suitable for representing deformable objects, like those in aerial images. However, methods like deformable convolutional networks can only provide sampling equivariance under certain circumstances, because of the locations used for sampling. We propose sampling equivariant self-attention networks which consider self-attention restricted to a local image patch as convolution sampling with masks instead of locations, and design a transformation embedding module to further improve the equivariant sampling ability. We also use a novel randomized normalization module to tackle overfitting due to limited aerial image data. We show that our model (i) provides significantly better sampling equivariance than existing methods, without additional supervision, (ii) provides improved classification on ImageNet, and (iii) achieves state-of-the-art results on the DOTA dataset, without increased computation.

There is no unified definition of Data anomalies, which refers to the specific data operation mode that may violate the consistency of the database. Known data anomalies include Dirty Write, Dirty Read, Non-repeatable Read, Phantom, Read Skew and Write Skew, etc. In order to improve the efficiency of concurrency control algorithms, data anomalies are also used to define the isolation levels, because the weak isolation level can improve the efficiency of transaction processing systems. This paper systematically studies the data anomalies and the corresponding isolation levels. We report twenty-two new data anomalies that other papers have not reported, and all data anomalies are classified miraculously. Based on the classification of data anomalies, two new isolation levels systems with different granularity are proposed, which reveals the rule of defining isolation levels based on data anomalies and makes the cognition of data anomalies and isolation levels more concise.

Single crystals of La2Ni7 have been grown out of a binary, La-Ni melt. Temperature dependent, zero magnetic field, specific heat, electrical resistivity, and low field magnetization measurements indicate that there is a series of antiferromagnetic phase transitions at T1 = 61.0 \pm 0.2 K, T2 = 56.5 \pm 0.2 K and T3 = 42.2 \pm 0.2 K. The three specific heat anomalies found at these temperatures qualitatively have very small entropy changes associated with them and the anisotropic M(H) data saturate at ~ 0.12 {\mu}B/Ni; both observations strongly suggesting the AFM order is associated with very small, itinerant, moments. Anisotropic, H||c and H{\perp}c, {\rho}(H) and M(H) isotherms as well as constant field, {\rho}(T) and M(T) sweeps manifest signatures of multiple phase lines and result in H-T phase diagrams that are clearly anisotropic. Analysis of M(T) and M(H) data allow for the identification of the two lower temperature magnetically ordered states as antiferromagnetically ordered, with the moments aligned along the crystallographic c-axis, and the higher temperature, T2 < T < T1, state as having a finite ferromagnetic component. In addition, the metamagnetic transition at low temperatures, for H applied along the crystallographic c-axis (H||c) appears to be a near classic example of a spin-flop transition, resulting in a field stabilized antiferromagnetic state with the moments ordered perpendicular to the c-axis. Although the small moment ordering, and existence of multiple phase transitions in field and temperature, suggesting an energetic proximity of these states, could foretell a degree of pressure sensitivity, our measurements of R(T) for applied pressures up to 2.0 GPa indicate that there is very little pressure dependence of T1, T2 and T3., Comment: 22 figures

Differentiation of colorectal polyps is an important clinical examination. A computer-aided diagnosis system is required to assist accurate diagnosis from colonoscopy images. Most previous studies at-tempt to develop models for polyp differentiation using Narrow-Band Imaging (NBI) or other enhanced images. However, the wide range of these models' applications for clinical work has been limited by the lagging of imaging techniques. Thus, we propose a novel framework based on a teacher-student architecture for the accurate colorectal polyp classification (CPC) through directly using white-light (WL) colonoscopy images in the examination. In practice, during training, the auxiliary NBI images are utilized to train a teacher network and guide the student network to acquire richer feature representation from WL images. The feature transfer is realized by domain alignment and contrastive learning. Eventually the final student network has the ability to extract aligned features from only WL images to facilitate the CPC task. Besides, we release the first public-available paired CPC dataset containing WL-NBI pairs for the alignment training. Quantitative and qualitative evaluation indicates that the proposed method outperforms the previous methods in CPC, improving the accuracy by 5.6%with very fast speed., Comment: Accepted in MICCAI-21

The antiferromagnet and semimetal EuCd$_2$As$_2$ has recently attracted a lot of attention due to a wealth of topological phases arising from the interplay of topology and magnetism. In particular, the presence of a single pair of Weyl points is predicted for a ferromagnetic configuration of Eu spins along the $c$-axis in EuCd$_2$As$_2$. In the search for such phases, we investigate here the effects of hydrostatic pressure in EuCd$_2$As$_2$. For that, we present specific heat, transport and $\mu$SR measurements under hydrostatic pressure up to $\sim\,2.5\,$GPa, combined with {\it ab initio} density functional theory (DFT) calculations. Experimentally, we establish that the ground state of EuCd$_2$As$_2$ changes from in-plane antiferromagnetic (AFM$_{ab}$) to ferromagnetic at a critical pressure of $\,\approx\,$2\,GPa, which is likely characterized by the moments dominantly lying within the $ab$ plane (FM$_{ab}$). The AFM$_{ab}$-FM$_{ab}$ transition at such a relatively low pressure is supported by our DFT calculations. Furthermore, our experimental and theoretical results indicate that EuCd$_2$As$_2$ moves closer to the sought-for FM$_c$ state (moments $\parallel$ $c$) with increasing pressure further. We predict that a pressure of $\approx$\,23\,GPa will stabilize the FM$_c$ state, if Eu remains in a 2+ valence state. Thus, our work establishes hydrostatic pressure as a key tuning parameter that (i) allows for a continuous tuning between magnetic ground states in a single sample of EuCd$_2$As$_2$ and (ii) enables the exploration of the interplay between magnetism and topology and thereby motivates a series of future experiments on this magnetic Weyl semimetal., Comment: 8 figures in main text, 6 figures in Appendix; 14 pages total

PSR J$1946+3417$ is a millisecond pulsar (MSP) with a spin period $P\simeq3.17\rm~ms$. Harbored in a binary with an orbital period $P_{\rm b}\simeq27$ days, the MSP is accompanied by a white dwarf (WD). The masses of the MSP and the WD were determined to be $1.83\rm~M_\odot$ and $0.266\rm~M_\odot$, respectively. Specially, its orbital eccentricity is $e\simeq0.134$, which is challenging the recycling model of MSPs. Assuming that the neutron star in a binary may collapse to a strange star when its mass reaches a critical limit, we propose a phase transition (PT) scenario to account for the origin of the system. The sudden mass loss and the kick induced by asymmetric collapse during the PT may result in the orbital eccentricity. If the PT event takes place after the mass transfer ceases, the eccentric orbit can not be re-circularized in the Hubble time. Aiming at the masses of both components, we simulate the evolution of the progenitor of PSR J$1946+3417$ via \texttt{MESA}. The simulations show that a NS / main sequence star binary with initial masses of $1.4+1.6\rm~M_\odot$ in an initial orbit of 2.59 days will evolve into a binary consisting of a $2.0\rm~M_\odot$ MSP and a $0.27\rm~M_\odot$ WD in an orbit of $\sim21.5$ days. Assuming that the gravitational mass loss fraction during PT is $10\%$, we simulate the effect of PT via the kick program of \texttt{BSE} with a velocity of $\sigma_{\rm PT}=60~{\rm km~s}^{-1}$. The results show that the PT scenario can reproduce the observed orbital period and eccentricity with higher probability then other values., Comment: accepted to be published on RAA

The observation of very-high-energy (VHE, $\rm >10~GeV$) $\gamma$-ray emission from $\rm \gamma$-ray bursts (GRBs), especially in the prompt phase, will provide critical information for understanding many aspects of their nature including the physical environment, the relativistic bulk motion, the mechanisms of particle acceleration of GRBs and for studying Lorentz invariance violation, etc. For the afterglow phase, the highest energy photons detected to date by the imaging atmospheric Cherenkov telescopes extend to the TeV regime. However, for the prompt phase, years of efforts in searching for the VHE emission has yielded no statistically significant detections. A wide field-of-view (FOV) and large effective area above tens of GeV are essential for detecting the VHE emissions from GRBs in the prompt phase. The High Altitude Detection of Astronomical Radiation (HADAR) experiment has such merits. In this paper, we report the estimates of its expected annual GRB detection rate, which are obtained by combining the performance of the HADAR instrument with the theoretical calculations based on a phenomenological model to generate the pseudo-GRB population. The expected detectable gamma-ray signal from GRBs above the background is then obtained to give the detection rate. In the spectral model, an extra component is assigned to every GRB event in addition to the Band function. The results indicate that if the energy of the cutoff due to internal absorption is higher than 50 GeV, the detection rate for GRBs for the HADAR experiment is approximately two or three GRBs per year, which varies slightly depending upon the characteristics of the extra component., Comment: accepted by ApJ

LaCrGe$_3$ has attracted attention as a paradigm example of the avoidance of ferromagnetic (FM) quantum criticality in an itinerant magnet. By combining thermodynamic, transport, x-ray and neutron scattering as well as $\mu$SR measurements, we refined the temperature-pressure phase diagram of LaCrGe$_3$. We provide thermodynamic evidence (i) for the first-order character of the FM transition when it is suppressed to low temperatures and (ii) for the formation of new phases at high pressures. From our microscopic data, we infer that short-range FM ordered clusters exist in these high-pressure phases. These results suggest that LaCrGe$_3$ is a rare example, which fills the gap between the two extreme limits of avoided FM quantum criticality in clean and strongly disordered metals., Comment: 7 pages, 4 figures plus Supplemental Information

We present the pressure-temperature phase diagram La$_5$Co$_2$Ge$_3$ up to $\sim$ 5\,GPa, which was constructed from magnetization, resistivity and specific heat measurements. At ambient pressure, La$_5$Co$_2$Ge$_3$ is an itinerant ferromagnet with a Curie temperature $T_\textrm C\sim$ 4\,K. Upon increasing pressure up to $\sim$ 1.7\,GPa, $T_\textrm C$ is suppressed down to $\sim$ 3\,K. Upon further increasing pressure, our results suggest that La$_5$Co$_2$Ge$_3$ enters a different low-temperature ground state. The corresponding transition temperature, $T^*$, has a nonmonotonic pressure dependence up to $\sim$ 5\,GPa. Our results demonstrate that the ferromagnetic quantum critical point in La$_5$Co$_2$Ge$_3$ is avoided by the appearance of a different, likely magnetically ordered state that has an antiferromagnetic component., Comment: 7 pages, 7 figures

We report measurements of the temperature- and pressure-dependent resistance, $R(T,p)$, of a manganin manometer in a $^4$He-gas pressure setup from room temperature down to the solidification temperature of $^4$He ($T_\textrm {solid}\sim$ 50 K at 0.8 GPa) for pressures, $p$, between 0 GPa and $\sim$0.8 GPa. The same manganin wire manometer was also measured in a piston-cylinder cell from 300 K down to 1.8 K and for pressures between 0 GPa to $\sim$2 GPa. From these data, we infer the temperature and pressure dependence of the pressure coefficient of manganin, $\alpha(T,p)$, defined by the equation $R_p = (1+\alpha p) R_0$ where $R_0$ and $R_p$ are the resistance of manganin at ambient pressure and finite pressure, respectively. Our results indicate that upon cooling $\alpha$ first decreases, then goes through a broad minimum at $\sim$120 K and increases again towards lower temperatures. In addition, we find that $\alpha$ is almost pressure-independent for $T\gtrsim$60 K up to $p\sim$2 GPa, but shows a pronounced $p$ dependence for $T\lesssim$60K. Using this manganin manometer, we demonstrate that $p$ overall decreases with decreasing temperature in the piston-cylinder cell for the full pressure range and that the size of the pressure difference between room temperature and low temperatures ($T=1.8$ K), $\Delta p$, decreases with increasing pressure. We also compare the pressure values inferred from the magnanin manometer with the low-temperature pressure, determined from the superconducting transition temperature of elemental lead (Pb). As a result of these data and analysis we propose a practical algorithm to infer the evolution of pressure with temperature in a piston-cylinder cell.

Two charge density wave transition can be detected in LaAu$_x$Sb$_2$ at ~ 110 and ~ 90 K by careful electrical transport measurements. Whereas control of the Au site occupancy in LaAu$_x$Sb$_2$ (for 0.9 < x < 1.0) can suppress each of these transitions by ~ 80 K, the application of hydrostatic pressure can completely suppress the lower transition by ~ 10 kbar and the upper transition by ~ 17 kbar. Clear anomalies in the resistance as well as the magnetoresistance are observed to coincide with the pressures at which the charge density wave transitions are driven to zero.

Iron-based superconductors are well-known for their intriguing phase diagrams, which manifest a complex interplay of electronic, magnetic and structural degrees of freedom. Among the phase transitions observed are superconducting, magnetic, and several types of structural transitions, including a tetragonal-to-orthorhombic and a collapsed-tetragonal transition. In particular, the widely-observed tetragonal-to-orthorhombic transition is believed to be a result of an electronic order that is coupled to the crystalline lattice and is, thus, referred to as nematic transition. Nematicity is therefore a prominent feature of these materials, which signals the importance of the coupling of electronic and lattice properties. Correspondingly, these systems are particularly susceptible to tuning via pressure (hydrostatic, uniaxial, or some combination). We review efforts to probe the phase diagrams of pressure-tuned iron-based superconductors, with a strong focus on our own recent insights into the phase diagrams of several members of this material class under hydrostatic pressure. These studies on FeSe, Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$, Ca(Fe$_{1-x}$Co$_x$)$_2$As$_2$ and CaK(Fe$_{1-x}$Ni$_x$)$_4$As$_4$ were, to a significant extent, made possible by advances of what measurements can be adapted to the use under differing pressure environments. We point out the potential impact of these tools for the study of the wider class of strongly correlated electron systems., Comment: 31 pages, 17 figures, submitted to Annalen der Physik

The sulfur substituted FeSe system, FeSe$_{1-x}$S$_{x}$, provides a versatile platform for studying the relationship between nematicity, antiferromagnetism, and superconductivity. Here, by nuclear magnetic resonance (NMR) and resistivity measurements up to 4.73 GPa on FeSe$_{0.91}$S$_{0.09}$, we established the pressure($p$)-temperature($T$) phase diagram in which the nematic state is suppressed with pressure showing a nematic quantum phase transition (QPT) around $p$ = 0.5 GPa, two SC regions, separated by the QPT, appear and antiferromagnetic (AFM) phase emerges above $\sim$3.3 GPa. From the NMR results up to 2.1 GPa, AFM fluctuations are revealed to be characterized by the stripe-type wavevector which remains the same for the two SC regions. Furthermore, the electronic state is found to change in character from non-Fermi liquid to Fermi liquid around the nematic QPT and persists up to $\sim$ 2.1 GPa. In addition, although the AFM fluctuations correlate with $T_{\rm c}$ in both SC states, demonstrating the importance of the AFM fluctuations for the appearance of SC in the system, we found that, when nematic order is absent, $T_{\rm c}$ is strongly correlated with the AFM fluctuations, whereas $T_{\rm c}$ weakly depends on the AFM fluctuations when nematic order is present. Our findings on FeSe$_{0.91}$S$_{0.09}$ were shown to be applied to the whole FeSe$_{1-x}$S$_{x}$ system and also provide a new insight into the relationship between AFM fluctuations and SC in Fe-based superconductors., Comment: 10 pages, 10 figures including 4 pages and 6 figures of Supplementary Material, accepted for publication in Phys. Rev. B rapid communication

Single crystals of monoclinic La$_{5}$Co$_{2}$Ge$_{3}$ were grown using a self-flux method and were characterized by room-temperature powder X-ray diffraction, anisotropic temperature and field dependent magnetization, temperature dependent resistivity, specific heat, and muon spin rotation. La$_{5}$Co$_{2}$Ge$_{3}$ has a Curie temperature ($T_\mathrm{C}$) of 3.8~K and clear signatures of ferromagnetism in magnetization and $\mu SR$ data, as well as a clear loss of spin disorder scattering in resistivity data and a sharp specific heat anomaly. The magnetism associated with La$_{5}$Co$_{2}$Ge$_{3}$ is itinerant, has a change in the entropy at $T_\mathrm {C}$ of $\simeq$0.05 R ln2 per mol-Co, and has a low-field saturated moment of $\sim 0.1 \mu_\mathrm B$/Co, making it a rare, itinerant, small moment, low $T_\mathrm C$ compound.

We report temperature dependent measurements of ambient pressure specific heat, magnetic susceptibility, anisotropic resistivity and thermal expansion as well as in-plane resistivity under pressure up to 20.8 kbar on single crystals of EuAg$_4$As$_2$. Based on thermal expansion and in-plane electrical transport measurements at ambient pressure this compound has two, first order, structural transitions in 80 - 120 K temperature range. Ambient pressure specific heat, magnetization and thermal expansion measurements show a cascade of up to seven transitions between 8 and 16 K associated with the ordering of the Eu$^{2+}$ moments. In-plane electrical transport is able to detect more prominent of these transitions: at 15.5, 9.9, and 8.7 K as well as a weak feature at 11.8 K at ambient pressure. Pressure dependent electrical transport data show that the magnetic transitions shift to higher temperatures under pressure, as does the upper structural transition, whereas the lower structural transition is suppressed and ultimately vanishes. A jump in resistivity, associated with the upper structural transition, decreases under pressure with an extrapolated disappearance (or a change of sign) by 30-35 kbar. In the 10 - 15 kbar range a kink in the pressure dependence of the upper structural transition temperature as well as the high and low temperature in-plane resistivities suggest that a change in the electronic structure may occur in this pressure range. The results are compared with the literature data for SrAg$_4$As$_2$.

We report the synthesis of CeBi single crystals out of Bi self flux and a systematic study of the magnetic and transport properties with varying temperature and applied magnetic fields. From these $R(T,H)$ and $M(T,H)$ data we could assemble the field-temperature ($H-T$) phase diagram for CeBi and visualize the three dimensional $M-T-H$ surface. In the phase diagram, we identify regions with well defined magnetization values, and identify a new phase region. The magnetoresistance (MR) in the low temperature regime shows, above $6~$T a power-law, non-saturated behavior with large MR ($\sim 3\times10^5 \%$ at $2~$K and $13.95~$T), along with Shubnikov-de Haas oscillations. With increasing temperatures, MR decreases, and then becomes negative for $T\gtrsim 10~$K. This crossover in MR seems to be unrelated to any specific magnetic or metamagnetic transitions, but rather is associated with changing from a low-temperature normal metal regime with little or no scattering from the Ce$^{3+}$ moments and an anomalously large MR, to an increased scattering from local Ce moments and a negative MR as temperature increases.

Uniaxial stress, as well as hydrostatic pressure are often used to tune material properties in condensed matter physics. Here, we present a setup which allows for the study of the combined effects of quasi-uniaxial stress and hydrostatic pressure. Following earlier designs for measurements under finite stress at ambient pressure (e.g., Chu et al., Science 337, 710 (2012)), the present setup utilizes a piezoelectric actuator to change stress in situ inside the piston-cylinder pressure cell. We show that the actuator can be operated over the full temperature (from 30K up to 260 K) and pressure range (up to ~2GPa), resulting in a clear and measurable quasi-uniaxial strain. To demonstrate functionality, measurements of the elastoresistance (i.e., the change of resistance of a sample as a response to quasi-uniaxial strain) under finite hydrostatic pressure on the iron-based compound BaFe$_2$As$_2$ are presented as a proof-of-principle example, and discussed in the framework of electronic nematicity. Overall, this work introduces the combination of in situ tunable quasi-uniaxial stress and large (up to ~2GPa) hydrostatic pressure as a powerful combination in the study of novel electronic phases. In addition, it also points towards further technical advancements which can be made in the future., Comment: 8 figures, 27 pages

The merits of fast convergence and potentially better performance of the weight normalization family have drawn increasing attention in recent years. These methods use standardization or normalization that changes the weight $\boldsymbol{W}$ to $\boldsymbol{W}'$, which makes $\boldsymbol{W}'$ independent to the magnitude of $\boldsymbol{W}$. Surprisingly, $\boldsymbol{W}$ must be decayed during gradient descent, otherwise we will observe a severe under-fitting problem, which is very counter-intuitive since weight decay is widely known to prevent deep networks from over-fitting. In this paper, we \emph{theoretically} prove that the weight decay term $\frac{1}{2}\lambda||{\boldsymbol{W}}||^2$ merely modulates the effective learning rate for improving objective optimization, and has no influence on generalization when the weight normalization family is compositely employed. Furthermore, we also expose several critical problems when introducing weight decay term to weight normalization family, including the missing of global minimum and training instability. To address these problems, we propose an $\epsilon-$shifted $L_2$ regularizer, which shifts the $L_2$ objective by a positive constant $\epsilon$. Such a simple operation can theoretically guarantee the existence of global minimum, while preventing the network weights from being too small and thus avoiding gradient float overflow. It significantly improves the training stability and can achieve slightly better performance in our practice. The effectiveness of $\epsilon-$shifted $L_2$ regularizer is comprehensively validated on the ImageNet, CIFAR-100, and COCO datasets. Our codes and pretrained models will be released in https://github.com/implus/PytorchInsight., Comment: 12 pages, 9 figures

The tetragonal-to-orthorhombic phase transition at $T_s$, which precedes the antiferromagnetic phase transition at $T_N$ in many iron-based superconductors, is considered as one of the manifestations of electronic \textit{nematic} order. By constructing temperature-pressure phase diagrams of pure and Co-doped BaFe$_2$As$_2$, we study the relation of $T_s$ and $T_N$ under pressure $p$. Our data disclose two qualitatively different regimes in which $\Delta T\,=\,T_s-T_N$ either increases or decreases with $p$. We provide experimental evidence that the transition between the two regimes may be associated with sudden changes of the Fermi surface topology. Therefore, our results not only support the electronic origin of the structural order, but also emphasize the importance of details of the Fermi surface for the evolution of nematic order under pressure., Comment: 6 pages, 4 figures (+ Appendix)

We present a study of electrical transport properties of $R$Bi$_2$ ($R$ = La, Ce) under hydrostatic pressure up to $\sim$ 2.5 GPa. These measurements are complemented by thermodynamic measurements of the specific heat on CeBi$_2$ at different pressures up to 2.55 GPa. For CeBi$_2$, we find a moderate increase of the antiferromagnetic transition, $T_\text N$, from 3.3 K to 4.4 K by pressures up to 2.55 GPa. Notably, resistance measurements for both CeBi$_2$ and LaBi$_2$ show signatures of superconductivity for pressures above $\sim$ 1.7 GPa. However, the absence of superconducting feature in specific heat measurements for CeBi$_2$ indicates that superconductivity in CeBi$_2$ (and most likely LaBi$_2$ as well) is not bulk and likely originates from traces of Bi flux, either on the surface of the plate-like samples, or trapped inside the sample as laminar inclusions.

The pressure dependencies of the magnetic and superconducting transitions, as well as that of the superconducting upper critical field are reported for single crystalline EuRbFe$_4$As$_4$. Resistance measurements were performed under hydrostatic pressures up to 6.21 GPa and in magnetic fields up to 9 T. Zero-field-cool magnetization measurements were performed under hydrostatic pressures up to 1.24 GPa under 20 mT applied field. Superconducting transition temperature, $T_\text c$, up to 6.21 GPa and magnetic transition temperature, $T_\text M$, up to 1.24 GPa were obtained and a pressure-temperature phase diagram was constructed. Our results show that $T_\text c$ is monotonically suppressed upon increasing pressure. $T_\text M$ is linearly increased up to 1.24 GPa. For the studied pressure range, no signs of the crossing of $T_\text M$ and $T_\text c$ lines are observed. The normalized slope of the superconducting upper critical field is gradually suppressed with increasing pressure, which may be due to the continuous change of Fermi-velocity $v_F$ with pressure., Comment: 5 pages, 7 figures

We report on the resistance behavior of bare-chip Cernox thermometers under pressures up to 2 GPa, generated in a piston-cylinder pressure cell. Our results clearly show that Cernox thermometers, frequently used in low-temperature experiments due to their high sensitivity, remain highly sensitive even under applied pressure. We show that these thermometers are therefore ideally suited for measurements of heat capacity under pressure utilizing an ac oscillation technique up to at least 150 K. Our Cernox-based system is very accurate in determining changes of the specific heat as a function of pressure as demonstrated by measurements of the heat capacity on three different test cases: (i) the superconducting transition in elemental Pb (T_{c} = 7.2 K), (ii) the antiferromagnetic transition in the rare-earth compound GdNiGe3 (T_{N} = 26 K) and (iii) the structural/magnetic transition in the iron-pnictide BaFe2As2 (T_{s,N} = 130 K). The chosen examples demonstrate the versatility of our technique for measuring the specific heat under pressure of various condensed matter systems with very different transition temperatures as well as amounts of removed entropy., Comment: 25 pages, 8 figures

We present an experimental study of the superconducting properties of NiBi3 as a function of pressure by means of resistivity and magnetization measurements and combine our results with DFT calculations of the band structure under pressure. We find a moderate suppression of the critical temperature Tc from ~ 4.1K to ~ 3K by pressures up to 2GPa. By taking into account the change of the band structure as a function of pressure, we argue that the decrease in Tc is consistent with conventional, electron-phonon-mediated BCS-type superconductivity.

Measurements of temperature-dependent resistance and magnetization under hydrostatic pressures up to 2.13 GPa are reported for single-crystalline, superconducting BaBi$_3$. A temperature - pressure phase diagram is determined and the results suggest three different superconducting phases ${\alpha}$, $\beta$, and $\gamma$ in the studied pressure range. We further show that occurrence of the three superconducting phases is intuitively linked to phase transitions at higher temperature which are likely first order in nature. $T_p$, which separates phase ${\alpha}$ from $\beta$ and $\gamma$, is associated with an abrupt resistance change as pressure is increased from 0.27 GPa to 0.33 GPa. Above 0.33 GPa, an "S-shape" anomaly in the temperature-dependent resistance curve, $T_\text S$, is observed and associated with the transition between the $\beta$ and $\gamma$ phases. Further increasing of pressure above 1.05 GPa suppresses this transition and BaBi$_3$ stays in $\gamma$ phase over the whole investigated temperature range. These high-temperature anomalies are likely related to structural degrees of freedom. With the ${\alpha}$ phase being the ambient-pressure tetragonal structure ($P4/mmm$), our first-principle calculations suggest the $\beta$ phase to be cubic structure ($Pm-3m$) and the $\gamma$ phase to be a distorted tetragonal structure where the Bi atoms are moved out of the face-centered position. Finally, an analysis of the evolution of the superconducting upper critical field with pressure further confirms these transitions in the superconducting state and suggests a possible change of band structure or a Lifshitz transition near 1.54 GPa in $\gamma$ phase. Given the large atomic numbers of both Ba and Bi, our results establish BaBi$_3$ as a good candidate for the study of the interplay of structure with superconductivity in the presence of strong spin-orbit coupling., Comment: 11 pages, 10 figures

We present the electrical resistivity data under application of pressures up to $\sim$ 26 GPa and down to 50 mK temperatures on YbFe$_2$Zn$_{20}$. We find a pressure induced magnetic phase transition with an onset at $p_c$=18.2$\pm$0.8 GPa. At ambient pressure, YbFe$_2$Zn$_{20}$ manifests a heavy fermion, nonmagnetic ground state and the Fermi liquid behavior at low temperatures. As pressure is increased, the power law exponent in resistivity, $n$, deviates significantly from Fermi liquid behavior and tends to saturate with $n$ = 1 near $p_c$. A pronounced resistivity maximum, $T_\text{max}$, which scales with Kondo temperature is observed. $T_\text{max}$ decreases with increasing pressure and flattened out near $p_c$ indicating the suppression of Kondo exchange interaction. For $p>p_c$, $T_\text{max}$ shows a sudden upward shift, most likely becoming associated with crystal electric field scattering. Application of magnetic field for $p>p_c$ broadens the transition and shifts it toward the higher temperature, which is a typical behavior of the ferromagnetic transition. The magnetic transition appears to abruptly develop above $p_c$, suggesting probable first-order (with changing pressure) nature of the transition; once stabilized, the ordering temperature does not depend on pressure up to $\sim$ 26 GPa. Taken as a whole, these data suggest that YbFe$_2$Zn$_{20}$ has a quantum phase transition at $p_c$ = 18.2 GPa associated with the avoided quantum criticality in metallic ferromagnets.

Single crystals of AlFe$_{2}$B$_{2}$ have been grown using the self flux growth method and then measured the structural properties, temperature and field dependent magnetization, and temperature dependent electrical resistivity at ambient as well as high pressure. The Curie temperature of AlFe$_{2}$B$_{2}$ is determined to be $274$~K. The measured saturation magnetization and the effective moment for paramagnetic Fe-ion indicate the itinerant nature of the magnetism with a Rhode-Wohlfarth ratio $ \frac{M_{C}}{M_{sat}}\approx 1.14$. Temperature dependent resistivity measurements under hydrostatic pressure shows that transition temperature \textit{T$_C$} is suppressed down to 255 K for $p = 2.24$~GPa pressure with a suppression rate of $\sim -8.9$~K/GPa. The anisotropy fields and magnetocrystalline anisotropy constants are in reasonable agreement with density functional theory calculations., Comment: 12 pages, 12 figures

The pressure dependence of the magnetic and superconducting transitions, as well as that of the superconducting upper critical field is reported for CaK(Fe$_{1-x}$Ni$_{x}$)$_4$As$_4$, the first example of an Fe-based superconductor with spin-vortex-crystal-type magnetic ordering. Resistance measurements were performed on single crystals with two substitution levels ($x=0.033, 0.050$) under hydrostatic pressures up to 5.12 GPa and in magnetic fields up to 9 T. Our results show that, for both compositions, magnetic transition temperatures, $T_\textrm{N}$, are suppressed upon applying pressure, the superconducting transition temperatures $T_\textrm{c}$ are suppressed by pressure as well, except for $x=0.050$ in the pressure region where $T_\textrm{N}$ and $T_\textrm{c}$ cross. Furthermore, the pressure associated with the crossing of the $T_\textrm{N}$ and $T_\textrm{c}$ lines also coincides with a minimum in the normalized slope of the superconducting upper critical field, consistent with a likely Fermi-surface reconstruction associated with the loss of magnetic ordering. Finally, at $p \sim$ 4 GPa, both Ni-substituted CaK(Fe$_{1-x}$Ni$_{x}$)$_4$As$_4$ samples likely go through a half-collapsed-tetragonal (hcT) phase transition, similar to the parent compound CaKFe$_4$As$_4$.

The pressure dependence of the structural, magnetic and superconducting transitions and of the superconducting upper critical field were studied in sulfur-substituted Fe(Se$_{1-x}$S$_{x}$). Resistance measurements were performed on single crystals with three substitution levels ($x$=0.043, 0.096, 0.12) under hydrostatic pressures up to 1.8 GPa and in magnetic fields up to 9 T, and compared to data on pure FeSe. Our results illustrate the effects of chemical and physical pressure on Fe(Se$_{1-x}$S$_{x}$). On increasing sulfur content, magnetic order in the low-pressure range is strongly suppressed to a small dome-like region in the phase diagrams. However, $T_s$ is much less suppressed by sulfur substitution and $T_c$ of Fe(Se$_{1-x}$S$_{x}$) exhibits similar non-monotonic pressure dependence with a local maximum and a local minimum present in the low pressure range for all $x$. The local maximum in $T_c$ coincides with the emergence of the magnetic order above $T_c$. At this pressure the slope of the upper critical field decreases abruptly. The minimum of $T_c$ correlates with a broad maximum of the upper critical field slope normalized by $T_c$.