Search

Electronic correlation effects are manifested in quantum materials when either the onsite Coulomb repulsion is large or the electron kinetic energy is small. The former is the dominant effect in the cuprate superconductors or heavy fermion systems while the latter in twisted bilayer graphene or geometrically frustrated metals. However, the simultaneous cooperation of both effects in the same quantum material--the design principle to produce a correlated topological flat bands pinned at the Fermi level--remains rare. Here, using angle-resolved photoemission spectroscopy, we report the observation of a flat band at the Fermi level in a 3$d$ pyrochlore metal CuV$_2$S$_4$. From a combination of first-principles calculations and slave-spin calculations, we understand the origin of this band to be a destructive quantum-interference effect associated with the V pyrochlore sublattice and further renormalization to the Fermi level by electron interactions in the partially filled V $t_{2g}$ orbitals. As a result, we find transport behavior that indicates a deviation from Fermi-liquid behavior as well as a large Sommerfeld coefficient. Our work demonstrates the pathway into correlated topology by constructing and pinning correlated flat bands near the Fermi level out of a pure $d$-electron system by the combined cooperation of local Coulomb interactions and geometric frustration in a pyrochlore lattice system., Comment: 23 pages, 4 figures, to appear in Nature Physics

The intrinsic anomalous Hall effect (AHE) has been reported in numerous ferromagnetic (FM) Weyl semimetals. However, AHE in the antiferromagnetic (AFM) or paramagnetic (PM) state of Weyl semimetals has been rarely observed experimentally, and only in centrosymmetric materials. Different mechanisms have been proposed to establish the connection between the AHE and the type of magnetic order. In this paper, we report AHE in both the AFM and PM states of non-centrosymmetric compound SmAlSi. To account for the AHE in non-centrosymmetric Weyl semimetals without FM, we introduce a new mechanism based on magnetic field-induced Weyl nodes evolution. Angle-dependent quantum oscillations in SmAlSi provide evidence for the Weyl points and large AHE in both the PM and the AFM states. The proposed mechanism qualitatively explains the temperature dependence of the anomalous Hall conductivity (AHC), which displays unconventional power law behavior of the AHC in both AFM and PM states of SmAlSi.

Quantum key distribution provides secure keys with information-theoretic security ensured by the principle of quantum mechanics. The continuous-variable version of quantum key distribution using coherent states offers the advantages of its compatibility with telecom industry, e.g., using commercial laser and homodyne detector, is now going through a booming period. In this review article, we describe the principle of continuous-variable quantum key distribution system, focus on protocols based on coherent states, whose systems are gradually moving from proof-of-principle lab demonstrations to in-field implementations and technological prototypes. We start by reviewing the theoretical protocols and the current security status of these protocols. Then, we discuss the system structure, the key module, and the mainstream system implementations. The advanced progress for future applications are discussed, including the digital techniques, system on chip and point-to-multipoint system. Finally, we discuss the practical security of the system and conclude with promising perspectives in this research field., Comment: 55 pages, 44 figures

Recently, reinforcement learning has gained prominence in modern statistics, with policy evaluation being a key component. Unlike traditional machine learning literature on this topic, our work places emphasis on statistical inference for the parameter estimates computed using reinforcement learning algorithms. While most existing analyses assume random rewards to follow standard distributions, limiting their applicability, we embrace the concept of robust statistics in reinforcement learning by simultaneously addressing issues of outlier contamination and heavy-tailed rewards within a unified framework. In this paper, we develop an online robust policy evaluation procedure, and establish the limiting distribution of our estimator, based on its Bahadur representation. Furthermore, we develop a fully-online procedure to efficiently conduct statistical inference based on the asymptotic distribution. This paper bridges the gap between robust statistics and statistical inference in reinforcement learning, offering a more versatile and reliable approach to policy evaluation. Finally, we validate the efficacy of our algorithm through numerical experiments conducted in real-world reinforcement learning experiments., Comment: 63 pages, 32 figures

Massive protostars launch accretion-powered, magnetically-collimated outflows, which play crucial roles in the dynamics and diagnostics of the star formation process. Here we calculate the shock heating and resulting free-free radio emission in numerical models of outflows of massive star formation within the framework of the Turbulent Core Accretion model. We post-process 3D magneto-hydrodynamic simulation snapshots of a protostellar disk wind interacts with an infalling core envelope, and calculate shock temperatures, ionization fractions, and radio free-free emission. We find heating up to ~10^7 K and near complete ionization in shocks at the interface between the outflow cavity and infalling envelope. However, line-of-sight averaged ionization fractions peak around ~10%, in agreement with values reported from observations of massive protostar G35.20-0.74N. By calculating radio continuum fluxes and spectra, we compare our models with observed samples of massive protostars. We find our fiducial models produce radio luminosities similar to those seen from low and intermediate-mass protostars that are thought to be powered by shock ionization. Comparing to more massive protostars, we find our model radio luminosities are ~10 to 100 times less luminous. We discuss how this apparent discrepancy either reflects aspects of our modeling related to the treatment of cooling of the post-shock gas or a dominant contribution in the observed systems from photoionization. Finally, our models exhibit 10-year radio flux variability of ~5%, especially in the inner 1000 au region, comparable to observed levels in some hyper-compact HII regions., Comment: Submitted to ApJ

To test theoretical models of massive star formation it is important to compare their predictions with observed systems. To this end, we conduct CO molecular line radiative transfer post-processing of 3D magneto-hydrodynamic (MHD) simulations of various stages in the evolutionary sequence of a massive protostellar core, including its infall envelope and disk wind outflow. Synthetic position-position-velocity (PPV) cubes of various transitions of CO, 13CO, and C18O emission are generated. We also carry out simulated Atacama Large Millimeter/submillimeter Array (ALMA) observations of this emission. We compare the mass, momentum and kinetic energy estimates obtained from molecular lines to the true values, finding that the mass and momentum estimates can have uncertainties of up to a factor of four. However, the kinetic energy estimated from molecular lines is more significantly underestimated. Additionally, we compare the mass outflow rate and momentum outflow rate obtained from the synthetic spectra with the true values. Finally, we compare the synthetic spectra with real examples of ALMA-observed protostars and determine the best fitting protostellar masses and outflow inclination angles. We then calculate the mass outflow rate and momentum outflow rate for these sources, finding that both rates agree with theoretical protostellar evolutionary tracks., Comment: ApJ Accepted

Early detection of dysplasia of the cervix is critical for cervical cancer treatment. However, automatic cervical dysplasia diagnosis via visual inspection, which is more appropriate in low-resource settings, remains a challenging problem. Though promising results have been obtained by recent deep learning models, their performance is significantly hindered by the limited scale of the available cervix datasets. Distinct from previous methods that learn from a single dataset, we propose to leverage cross-domain cervical images that were collected in different but related clinical studies to improve the model's performance on the targeted cervix dataset. To robustly learn the transferable information across datasets, we propose a novel prototype-based knowledge filtering method to estimate the transferability of cross-domain samples. We further optimize the shared feature space by aligning the cross-domain image representations simultaneously on domain level with early alignment and class level with supervised contrastive learning, which endows model training and knowledge transfer with stronger robustness. The empirical results on three real-world benchmark cervical image datasets show that our proposed method outperforms the state-of-the-art cervical dysplasia visual inspection by an absolute improvement of 4.7% in top-1 accuracy, 7.0% in precision, 1.4% in recall, 4.6% in F1 score, and 0.05 in ROC-AUC., Comment: accepted in ACM Multimedia 2023

Recent millimeter/sub-millimeter facilities have revealed the physical properties of filamentary molecular clouds in relation to high-mass star formation. A uniform survey of the nearest, face-on star-forming galaxy, the Large Magellanic Cloud (LMC), complements the Galactic knowledge. We present ALMA survey data with a spatial resolution of $\sim$0.1 pc in the 0.87 mm continuum and HCO$^{+}$(4-3) emission toward 30 protostellar objects with luminosities of 10$^4$-10$^{5.5}$ $L_{\odot}$ in the LMC. The spatial distributions of the HCO$^{+}$(4-3) line and thermal dust emission are well correlated, indicating that the line effectively traces dense, filamentary gas with an H$_2$ volume density of $\gtrsim$10$^5$ cm$^{-3}$ and a line mass of $\sim$10$^3$-10$^{4}$ $M_{\odot}$ pc$^{-1}$. Furthermore, we obtain an increase in the velocity linewidths of filamentary clouds, which follows a power-law dependence on their H$_2$ column densities with an exponent of $\sim$0.5. This trend is consistent with observations toward filamentary clouds in nearby star-forming regions withiin $ \lesssim$1 kpc from us and suggests enhanced internal turbulence within the filaments owing to surrounding gas accretion. Among the 30 sources, we find that 14 are associated with hub-filamentary structures, and these complex structures predominantly appear in protostellar luminosities exceeding $\sim$5 $\times$10$^4$ $L_{\odot}$. The hub-filament systems tend to appear in the latest stages of their natal cloud evolution, often linked to prominent H$\;${\sc ii} regions and numerous stellar clusters. Our preliminary statistics suggest that the massive filaments accompanied by hub-type complex features may be a necessary intermediate product in forming extremely luminous high-mass stellar systems capable of ultimately dispersing the parent cloud., Comment: 21 pages, 8 figures, 4 tables, accepted for publication in ApJ

The local oscillator in practical continuous-variable quantum key distribution system fluctuates at any time during the key distribution process, which may open security loopholes for the eavesdropper to hide her eavesdropping behaviors. Based on this, we investigate a more stealthy quantum attack where the eavesdroppers simulates random fluctuations of local oscillator intensity in a practical discrete-modulated continuous-variable quantum key distribution system. Theoretical simulations show that both communicating parties will misestimate channel parameters and overestimate the secret key rate due to the modified attack model, even though they have monitored the mean local oscillator intensity and shot-noise as commonly used. Specifically, the eavesdropper's manipulation of random fluctuations in LO intensity disturbs the parameter estimation in realistic discrete-modulated continuous-variable quantum key distribution system, where the experimental parameters are always used for constraints of the semidefinite program modeling. The modified attack introduced by random fluctuations of local oscillator can only be eliminated by monitoring the local oscillator intensity in real time which places a higher demand on the accuracy of monitoring technology. Moreover, similar quantum hacking will also occur in practical local local oscillator system by manipulating the random fluctuations in pilot intensity, which shows the strong adaptability and the important role of the proposed attack., Comment: 10 pages, 10 figures

Street-view imagery provides us with novel experiences to explore different places remotely. Carefully calibrated street-view images (e.g. Google Street View) can be used for different downstream tasks, e.g. navigation, map features extraction. As personal high-quality cameras have become much more affordable and portable, an enormous amount of crowdsourced street-view images are uploaded to the internet, but commonly with missing or noisy sensor information. To prepare this hidden treasure for "ready-to-use" status, determining missing location information and camera orientation angles are two equally important tasks. Recent methods have achieved high performance on geo-localization of street-view images by cross-view matching with a pool of geo-referenced satellite imagery. However, most of the existing works focus more on geo-localization than estimating the image orientation. In this work, we re-state the importance of finding fine-grained orientation for street-view images, formally define the problem and provide a set of evaluation metrics to assess the quality of the orientation estimation. We propose two methods to improve the granularity of the orientation estimation, achieving 82.4% and 72.3% accuracy for images with estimated angle errors below 2 degrees for CVUSA and CVACT datasets, corresponding to 34.9% and 28.2% absolute improvement compared to previous works. Integrating fine-grained orientation estimation in training also improves the performance on geo-localization, giving top 1 recall 95.5%/85.5% and 86.8%/80.4% for orientation known/unknown tests on the two datasets., Comment: This paper has been accepted by ACM Multimedia 2022. This version contains additional supplementary materials

Stochastic gradient descent with momentum (SGDM) has been widely used in many machine learning and statistical applications. Despite the observed empirical benefits of SGDM over traditional SGD, the theoretical understanding of the role of momentum for different learning rates in the optimization process remains widely open. We analyze the finite-sample convergence rate of SGDM under the strongly convex settings and show that, with a large batch size, the mini-batch SGDM converges faster than the mini-batch SGD to a neighborhood of the optimal value. Additionally, our findings, supported by theoretical analysis and numerical experiments, indicate that SGDM permits broader choices of learning rates. Furthermore, we analyze the Polyak-averaging version of the SGDM estimator, establish its asymptotic normality, and justify its asymptotic equivalence to the averaged SGD. The asymptotic distribution of the averaged SGDM enables uncertainty quantification of the algorithm output and statistical inference of the model parameters.

Domain gap between synthetic and real data in visual regression (e.g. 6D pose estimation) is bridged in this paper via global feature alignment and local refinement on the coarse classification of discretized anchor classes in target space, which imposes a piece-wise target manifold regularization into domain-invariant representation learning. Specifically, our method incorporates an explicit self-supervised manifold regularization, revealing consistent cumulative target dependency across domains, to a self-training scheme (e.g. the popular Self-Paced Self-Training) to encourage more discriminative transferable representations of regression tasks. Moreover, learning unified implicit neural functions to estimate relative direction and distance of targets to their nearest class bins aims to refine target classification predictions, which can gain robust performance against inconsistent feature scaling sensitive to UDA regressors. Experiment results on three public benchmarks of the challenging 6D pose estimation task can verify the effectiveness of our method, consistently achieving superior performance to the state-of-the-art for UDA on 6D pose estimation., Comment: Accepted by IJCAI 2023

We report high-resolution ALMA observations toward a massive protostellar core C1-Sa ($\sim$30 M$_\odot$) in the Dragon Infrared Dark Cloud. At the resolution of 140 AU, the core fragments into two kernels (C1-Sa1 and C1-Sa2) with a projected separation of $\sim$1400 AU along the elongation of C1-Sa, consistent with a Jeans length scale of $\sim$1100 AU. Radiative transfer modeling using RADEX indicates that the protostellar kernel C1-Sa1 has a temperature of $\sim$75 K and a mass of 0.55 M$_\odot$. C1-Sa1 also likely drives two bipolar outflows, one being parallel to the plane-of-the-sky. C1-Sa2 is not detected in line emission and does not show any outflow activity but exhibits ortho-H$_2$D$^+$ and N$_2$D$^+$ emission in its vicinity, thus it is likely still starless. Assuming a 20 K temperature, C1-Sa2 has a mass of 1.6 M$_\odot$. At a higher resolution of 96 AU, C1-Sa1 begins to show an irregular shape at the periphery, but no clear sign of multiple objects or disks. We suspect that C1-Sa1 hosts a tight binary with inclined disks and outflows. Currently, one member of the binary is actively accreting while the accretion in the other is significantly reduced. C1-Sa2 shows hints of fragmentation into two sub-kernels with similar masses, which requires further confirmation with higher sensitivity., Comment: 7 figures, 2 tables, accepted by ApJ

We report the first detection of hot molecular cores in the Small Magellanic Cloud, a nearby dwarf galaxy with 0.2 solar metallicity. We observed two high-mass young stellar objects in the SMC with ALMA, and detected emission lines of CO, HCO+, H13CO+, SiO, H2CO, CH3OH, SO, and SO2. Compact hot-core regions are traced by SO2, whose spatial extent is about 0.1 pc, and the gas temperature is higher than 100 K based on the rotation diagram analysis. In contrast, CH3OH, a classical hot-core tracer, is dominated by extended (0.2-0.3 pc) components in both sources, and the gas temperature is estimated to be 39+-8 K for one source. Protostellar outflows are also detected from both sources as high-velocity components of CO. The metallicity-scaled abundances of SO2 in hot cores are comparable among the SMC, LMC, and Galactic sources, suggesting that the chemical reactions leading to SO2 formation would be regulated by elemental abundances. On the other hand, CH3OH shows a large abundance variation within SMC and LMC hot cores. The diversity in the initial condition of star formation (e.g., degree of shielding, local radiation field strength) may lead to the large abundance variation of organic molecules in hot cores. This work, in conjunction with previous hot-core studies in the LMC and outer/inner Galaxy, suggests that the formation of a hot core would be a common phenomenon during high-mass star formation across the metallicity range of 0.2-1 solar metallicity. High-excitation SO2 lines will be a useful hot-core tracer in the low-metallicity environments of the SMC and LMC., Comment: Accepted for publication in ApJL, 17 pages, 8 figures, 4 tables. arXiv admin note: text overlap with arXiv:2109.11123

We study the astrochemical diagnostics of the isolated massive protostar G28.20-0.05. We analyze data from ALMA 1.3~mm observations with resolution of 0.2 arcsec ($\sim$1,000 au). We detect emission from a wealth of species, including oxygen-bearing (e.g., $\rm{H_2CO}$, $\rm{CH_3OH}$, $\rm{CH_3OCH_3}$), sulfur-bearing (SO$_2$, H$_2$S) and nitrogen-bearing (e.g., HNCO, NH$_2$CHO, C$_2$H$_3$CN, C$_2$H$_5$CN) molecules. We discuss their spatial distributions, physical conditions, correlation between different species and possible chemical origins. In the central region near the protostar, we identify three hot molecular cores (HMCs). HMC1 is part of a mm continuum ring-like structure, is closest in projection to the protostar, has the highest temperature of $\sim300\:$K, and shows the most line-rich spectra. HMC2 is on the other side of the ring, has a temperature of $\sim250\:$K, and is of intermediate chemical complexity. HMC3 is further away, $\sim3,000\:$au in projection, cooler ($\sim70\:$K) and is the least line-rich. The three HMCs have similar mass surface densities ($\sim10\:{\rm{g\:cm}}^{-2}$), number densities ($n_{\rm H}\sim10^9\:{\rm{cm}}^{-3}$) and masses of a few $M_\odot$. The total gas mass in the cores and in the region out to $3,000\:$au is $\sim 25\:M_\odot$, which is comparable to that of the central protostar. Based on spatial distributions of peak line intensities as a function of excitation energy, we infer that the HMCs are externally heated by the protostar. We estimate column densities and abundances of the detected species and discuss the implications for hot core astrochemistry., Comment: Accepted for publication in ApJ

We present Atacama Large Millimeter/submillimeter Array observations of the $\sim$10 kAU environment surrounding 21 protostars in the Orion A molecular cloud tracing outflows. Our sample is composed of Class 0 to flat-spectrum protostars, spanning the full $\sim$1 Myr lifetime. We derive the angular distribution of outflow momentum and energy profiles and obtain the first two-dimensional instantaneous mass, momentum, and energy ejection rate maps using our new approach: the Pixel Flux-tracing Technique (PFT). Our results indicate that by the end of the protostellar phase, outflows will remove $\sim$2 to 4 M$_\odot$ from the surrounding $\sim$1 M$_\odot$ low-mass core. These high values indicate that outflows remove a significant amount of gas from their parent cores and continuous core accretion from larger scales is needed to replenish core material for star formation. This poses serious challenges to the concept of ``cores as well-defined mass reservoirs", and hence to the simplified core-to-star conversion prescriptions. Furthermore, we show that cavity opening angles, and momentum and energy distributions all increase with the protostar evolutionary stage. This is clear evidence that even garden-variety protostellar outflows: (a) effectively inject energy and momentum into their environments on $10$ kAU scales, and (b) significantly disrupt their natal cores, ejecting a large fraction of the mass that would have otherwise fed the nascent star. Our results support the conclusion that protostellar outflows have a direct impact on how stars get their mass, and that the natal sites of individual low-mass star formation are far more dynamic than commonly accepted theoretical paradigms., Comment: 76 pages, 43 figures. Accepted by ApJ 2023.2.6

Star formation is ubiquitously associated with the ejection of accretion-powered outflows that carve bipolar cavities through the infalling envelope. This feedback is expected to be important for regulating the efficiency of star formation from a natal pre-stellar core. These low-extinction outflow cavities greatly affect the appearance of a protostar by allowing the escape of shorter wavelength photons. Doppler-shifted CO line emission from outflows is also often the most prominent manifestation of deeply embedded early-stage star formation. Here, we present 3D magneto-hydrodynamic simulations of a disk wind outflow from a protostar forming from an initially $60\:M_\odot$ core embedded in a high pressure environment typical of massive star-forming regions. We simulate the growth of the protostar from $m_*=1\:M_\odot$ to $26\:M_\odot$ over a period of $\sim$100,000 years. The outflow quickly excavates a cavity with half opening angle of $\sim10^\circ$ through the core. This angle remains relatively constant until the star reaches $4\:M_\odot$. It then grows steadily in time, reaching a value of $\sim 50^\circ$ by the end of the simulation. We estimate a lower limit to the star formation efficiency (SFE) of 0.43. However, accounting for continued accretion from a massive disk and residual infall envelope, we estimate that the final SFE may be as high as $\sim0.7$. We examine observable properties of the outflow, especially the evolution of the cavity opening angle, total mass and momentum flux, and velocity distributions of the outflowing gas, and compare with the massive protostars G35.20-0.74N and G339.88-1.26 observed by ALMA, yielding constraints on their intrinsic properties., Comment: Accepted for publication in ApJ

With the fast development of big data, it has been easier than before to learn the optimal decision rule by updating the decision rule recursively and making online decisions. We study the online statistical inference of model parameters in a contextual bandit framework of sequential decision-making. We propose a general framework for online and adaptive data collection environment that can update decision rules via weighted stochastic gradient descent. We allow different weighting schemes of the stochastic gradient and establish the asymptotic normality of the parameter estimator. Our proposed estimator significantly improves the asymptotic efficiency over the previous averaged SGD approach via inverse probability weights. We also conduct an optimality analysis on the weights in a linear regression setting. We provide a Bahadur representation of the proposed estimator and show that the remainder term in the Bahadur representation entails a slower convergence rate compared to classical SGD due to the adaptive data collection.

We experimentally demonstrated a sub-Mbps key rate Gaussian-modulated coherent-state continuous-variable quantum key distribution (CV-QKD) over 100 km transmission distance. To efficiently control the excess noise, the quantum signal and the pilot tone are co-transmitted in fiber channel based on wide-band frequency and polarization multiplexing methods. Furthermore, a high-accuracy data-assisted time domain equalization algorithm is carefully designed to compensate the phase noise and polarization variation in low signal-to-noise ratio. The asymptotic secure key rate (SKR) of the demonstrated CV-QKD is experimentally evaluated to be 10.36 Mbps, 2.59 Mbps, and 0.69 Mbps over transmission distance of 50 km, 75 km, and 100 km, respectively. The experimental demonstrated CV-QKD system significantly improves transmission distance and SKR compared to the state-of-art GMCS CV-QKD experimental results, and shows the potential for long-distance and high-speed secure quantum key distribution., Comment: 4 pages, 7 figures

Contextual bandit has been widely used for sequential decision-making based on the current contextual information and historical feedback data. In modern applications, such context format can be rich and can often be formulated as a matrix. Moreover, while existing bandit algorithms mainly focused on reward-maximization, less attention has been paid to the statistical inference. To fill in these gaps, in this work we consider a matrix contextual bandit framework where the true model parameter is a low-rank matrix, and propose a fully online procedure to simultaneously make sequential decision-making and conduct statistical inference. The low-rank structure of the model parameter and the adaptivity nature of the data collection process makes this difficult: standard low-rank estimators are not fully online and are biased, while existing inference approaches in bandit algorithms fail to account for the low-rankness and are also biased. To address these, we introduce a new online doubly-debiasing inference procedure to simultaneously handle both sources of bias. In theory, we establish the asymptotic normality of the proposed online doubly-debiased estimator and prove the validity of the constructed confidence interval. Our inference results are built upon a newly developed low-rank stochastic gradient descent estimator and its non-asymptotic convergence result, which is also of independent interest., Comment: 81 pages

Molecular lines tracing the orbital motion of gas in a well-defined disk are valuable tools for inferring both the properties of the disk and the star it surrounds. Lines that arise only from a disk, and not also from the surrounding molecular cloud core that birthed the star or from the outflow it drives, are rare. Several such emission lines have recently been discovered in one example case, those from NaCl and KCl salt molecules. We studied a sample of 23 candidate high-mass young stellar objects (HMYSOs) in 17 high-mass star-forming regions to determine how frequently emission from these species is detected. We present five new detections of water, NaCl, KCl, PN, and SiS from the innermost regions around the objects, bringing the total number of known briny disk candidates to nine. Their kinematic structure is generally disk-like, though we are unable to determine whether they arise from a disk or outflow in the sources with new detections. We demonstrate that these species are spatially coincident in a few resolved cases and show that they are generally detected together, suggesting a common origin or excitation mechanism. We also show that several disks around HMYSOs clearly do not exhibit emission in these species. Salty disks are therefore neither particularly rare in high-mass disks, nor are they ubiquitous., Comment: accepted to ApJ

Kramers nodal lines (KNLs) have recently been proposed theoretically as a special type of Weyl line degeneracy connecting time-reversal invariant momenta. KNLs are robust to spin orbit coupling and are inherent to all non-centrosymmetric achiral crystal structures, leading to unusual spin, magneto-electric, and optical properties. However, their existence in in real quantum materials has not been experimentally established. Here we gather the experimental evidence pointing at the presence of KNLs in SmAlSi, a non-centrosymmetric metal that develops incommensurate spin density wave order at low temperature. Using angle-resolved photoemission spectroscopy, density functional theory calculations, and magneto-transport methods, we provide evidence suggesting the presence of KNLs, together with observing Weyl fermions under the broken inversion symmetry in the paramagnetic phase of SmAlSi. We discuss the nesting possibilities regarding the emergent magnetic orders in SmAlSi. Our results provide a solid basis of experimental observations for exploring correlated topology in SmAlSi., Comment: 40 pages, 5 figures, 1 table

We study the problem of multi-task non-smooth optimization that arises ubiquitously in statistical learning, decision-making and risk management. We develop a data fusion approach that adaptively leverages commonalities among a large number of objectives to improve sample efficiency while tackling their unknown heterogeneities. We provide sharp statistical guarantees for our approach. Numerical experiments on both synthetic and real data demonstrate significant advantages of our approach over benchmarks., Comment: 25 pages

The development of modern technology has enabled data collection of unprecedented size, which poses new challenges to many statistical estimation and inference problems. This paper studies the maximum score estimator of a semi-parametric binary choice model under a distributed computing environment without pre-specifying the noise distribution. An intuitive divide-and-conquer estimator is computationally expensive and restricted by a non-regular constraint on the number of machines, due to the highly non-smooth nature of the objective function. We propose (1) a one-shot divide-and-conquer estimator after smoothing the objective to relax the constraint, and (2) a multi-round estimator to completely remove the constraint via iterative smoothing. We specify an adaptive choice of kernel smoother with a sequentially shrinking bandwidth to achieve the superlinear improvement of the optimization error over the multiple iterations. The improved statistical accuracy per iteration is derived, and a quadratic convergence up to the optimal statistical error rate is established. We further provide two generalizations to handle the heterogeneity of datasets and high-dimensional problems where the parameter of interest is sparse.

In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact first-order oracle of each individual objective function and exchange information with its time-varying neighbors. We revisit the distributed subgradient method in this circumstance and show its suboptimality under square summable but not summable step sizes. We also present several conditions on the inexactness of the local oracles to ensure an exact convergence of the iterative sequences towards the global optimal solution. A numerical example is given to verify the efficiency of our algorithm., Comment: 13 pages, 3 figures

This paper addresses the leader-following consensus problem for discrete-time positive multi-agent systems over time-varying graphs. We assume that the followers may have mutually different positive dynamics which can also be different from the leader. Compared with most existing positive consensus works for homogeneous multi-agent systems, the formulated problem is more general and challenging due to the interplay between the positivity requirement and high-order heterogeneous dynamics. To solve the problem, we present an extended version of existing observer-based design for positive multi-agent systems. By virtue of the common quadratic Lyapunov function technique, we show the followers will maintain their state variables in the positive orthant and finally achieve an output consensus specified by the leader. A numerical example is used to verify the efficacy of our algorithms.

Magnetic topological semimetals (TSMs) allow for an effective control of the topological electronic states by tuning the spin configuration, and therefore are promising materials for next-generation electronic and spintronic applications. Of magnetic TSMs, Weyl nodal-line (NL) semimetals likely have the most tunability, and yet they are the least experimentally studied so far due to the scarcity of material candidates. Here, using a combination of angle-resolved photoemission spectroscopy and quantum oscillation measurements, together with density functional theory calculations, we identify the square-net compound EuGa4 as a new magnetic Weyl nodal ring (NR) semimetal, in which the line nodes form closed rings in the vicinity of the Fermi level. Remarkably, the Weyl NR states show distinct Landau quantization with clear spin splitting upon application of a magnetic field. At 2 K in a field of 14 T, the transverse magnetoresistance of EuGa4 exceeds 200,000%, which is more than two orders of magnitude larger than that of other known magnetic TSMs. High field magnetoresistance measurements indicate no saturation up to 40 T. Our theoretical model indicates that the nonsaturating MR naturally arises as a consequence of the Weyl NR state. Our work thus point to the realization of Weyl NR states in square-net magnetic materials, and opens new avenues for the design of magnetic TSMs with very large magnetoresistance.

In recent years, mobile robots are becoming ambitious and deployed in large-scale scenarios. Serving as a high-level understanding of environments, a sparse skeleton graph is beneficial for more efficient global planning. Currently, existing solutions for skeleton graph generation suffer from several major limitations, including poor adaptiveness to different map representations, dependency on robot inspection trajectories and high computational overhead. In this paper, we propose an efficient and flexible algorithm generating a trajectory-independent 3D sparse topological skeleton graph capturing the spatial structure of the free space. In our method, an efficient ray sampling and validating mechanism are adopted to find distinctive free space regions, which contributes to skeleton graph vertices, with traversability between adjacent vertices as edges. A cycle formation scheme is also utilized to maintain skeleton graph compactness. Benchmark comparison with state-of-the-art works demonstrates that our approach generates sparse graphs in a substantially shorter time, giving high-quality global planning paths. Experiments conducted in real-world maps further validate the capability of our method in real-world scenarios. Our method will be made open source to benefit the community.

We present a detailed study of the massive star-forming region G35.2-0.74N with ALMA 1.3 mm multi-configuration observations. At 0.2" (440 au) resolution, the continuum emission reveals several dense cores along a filamentary structure, consistent with previous ALMA 0.85 mm observations. At 0.03" (66 au) resolution, we detect 22 compact sources, most of which are associated with the filament. Four of the sources are associated with compact centimeter continuum emission, and two of these are associated with H30{\alpha} recombination line emission. The H30{\alpha} line kinematics show ordered motion of the ionized gas, consistent with disk rotation and/or outflow expansion. We construct models of photoionized regions to simultaneously fit the multi-wavelength free-free fluxes and the H30{\alpha} total fluxes. The derived properties suggest the presence of at least three massive young stars with nascent hypercompact Hii regions. Two of these ionized regions are surrounded by a large rotating structure that feeds two individual disks, revealed by dense gas tracers, such as SO2, H2CO, and CH3OH. In particular, the SO2 emission highlights two spiral structures in one of the disks and probes the faster-rotating inner disks. The 12CO emission from the general region reveals a complex outflow structure, with at least four outflows identified. The remaining 18 compact sources are expected to be associated with lower-mass protostars forming in the vicinity of the massive stars. We find potential evidence for disk disruption due to dynamical interactions in the inner region of this protocluster. The spatial distribution of the sources suggests a smooth overall radial density gradient without subclustering, but with tentative evidence of primordial mass segregation., Comment: 46 pages, 21 figures, 5 tables. Accepted to ApJ

We have investigated the protostellar disk around a Class 0/I protostar, L1527 IRS, using multi-wavelength observations of the dust continuum emission at $\lambda=0.87$, 2.1, 3.3, and 6.8 mm obtained by the Atacama Large Millimeter/submillimeter Array (ALMA) and the Jansky Very Large Array (VLA). Our observations achieved a spatial resolution of $3-13$ au and revealed an edge-on disk structure with a size of $\sim80-100$ au. The emission at 0.87 and 2.1 mm is found to be optically thick within a projected disk radius of $ r_{\rm proj}\lesssim50$ au. The emission at 3.3 and 6.8 mm shows that the power-law index of the dust opacity ($\beta$) is $\beta\sim1.7$ around $ r_{\rm proj}\sim 50$ au, suggesting that grain growth has not yet begun. The dust temperature ($T_{\rm dust}$) shows a steep decrease with $T_{\rm dust}\propto r_{\rm proj}^{-2}$ outside of the VLA clumps previously identified at $r_{\rm proj}\sim20$ au. Furthermore, the disk is gravitationally unstable at $r_{\rm proj}\sim20$ au, as indicated by a Toomre {\it Q} parameter value of $Q\lesssim1.0$. These results suggest that the VLA clumps are formed via gravitational instability, which creates a shadow on the outside of the substructure, resulting in the sudden drop in temperature. The derived dust masses for the VLA clumps are $\gtrsim0.1$ $M_{\rm J}$. Thus, we suggest that Class 0/I disks can be massive enough to be gravitationally unstable, which might be the origin of gas-giant planets in a 20 au radius. Furthermore, the protostellar disks can be cold due to shadowing., Comment: 23 pages, 18 figures, 1 table. Accepted for publication in ApJ