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The notorious fermion sign problem, arising from fermion statistics, constitutes one of the main obstacles of deciphering quantum many-body systems by numerical approach. The progress in overcoming sign problem will definitely lead to a great leap in various areas of modern physics. Here, by deviating from the conventional cognition that nonequilibrium studies should be more complicated than equilibrium cases, we propose an innovative framework based on nonequilibrium critical dynamics to preempt sign problem and investigate quantum critical point in fermionic model through numerically exact quantum Monte Carlo (QMC) simulation. By virtue of universal scaling theory of imaginary-time relaxation dynamics, we demonstrate that accurate critical point and critical exponents can be obtained in the short-time stage, in which the sign problem is not severe such that the QMC is accessible. After confirming the effectiveness of the method in two typical interacting fermionic models featuring Dirac quantum critical point (QCP), we for the first time reveal the quantum phase diagram in the Hubbard model hosting $\rm SU(3)$-symmetric Dirac fermions, and find that the QCP between Dirac semi-metal and a $\lambda_8$-antiferromagnetic phase belongs to a new universality class different from the previously known Gross-Neveu transitions., Comment: 7+13 pages

Instruction tuning is a crucial technique for aligning language models with humans' actual goals in the real world. Extensive research has highlighted the quality of instruction data is essential for the success of this alignment. However, creating high-quality data manually is labor-intensive and time-consuming, which leads researchers to explore using LLMs to synthesize data. Recent studies have focused on using a stronger LLM to iteratively enhance existing instruction data, showing promising results. Nevertheless, previous work often lacks control over the evolution direction, resulting in high uncertainty in the data synthesis process and low-quality instructions. In this paper, we introduce a general and scalable framework, IDEA-MCTS (Instruction Data Enhancement using Monte Carlo Tree Search), a scalable framework for efficiently synthesizing instructions. With tree search and evaluation models, it can efficiently guide each instruction to evolve into a high-quality form, aiding in instruction fine-tuning. Experimental results show that IDEA-MCTS significantly enhances the seed instruction data, raising the average evaluation scores of quality, diversity, and complexity from 2.19 to 3.81. Furthermore, in open-domain benchmarks, experimental results show that IDEA-MCTS improves the accuracy of real-world instruction-following skills in LLMs by an average of 5\% in low-resource settings.

We present James Webb Space Telescope (JWST)-NIRCam observations of the massive star-forming molecular cloud Sagittarius C (Sgr C) in the Central Molecular Zone (CMZ). In conjunction with ancillary mid-IR and far-IR data, we characterize the two most massive protostars in Sgr C via spectral energy distribution (SED) fitting, estimating that they each have current masses of $m_* \sim 20\:M_\odot$ and surrounding envelope masses of $\sim 100\:M_\odot$. We report a census of lower-mass protostars in Sgr C via a search for infrared counterparts to mm continuum dust cores found with ALMA. We identify 88 molecular hydrogen outflow knot candidates originating from outflows from protostars in Sgr C, the first such unambiguous detections in the infrared in the CMZ. About a quarter of these are associated with flows from the two massive protostars in Sgr C; these extend for over 1 pc and are associated with outflows detected in ALMA SiO line data. An additional $\sim 40$ features likely trace shocks in outflows powered by lower-mass protostars throughout the cloud. We report the discovery of a new star-forming region hosting two prominent bow shocks and several other line-emitting features driven by at least two protostars. We infer that one of these is forming a high-mass star given an SED-derived mass of $m_* \sim 9\:M_\odot$ and associated massive ($\sim 90\:M_\odot$) mm core and water maser. Finally, we identify a population of miscellaneous Molecular Hydrogen Objects (MHOs) that do not appear to be associated with protostellar outflows., Comment: Appendix figures B1 and B2 will be made into online-only figure sets for the eventual ApJ publication

We study the ground-state phase diagram of a non-Hermitian cluster-XY spin chain in the language of free fermions. By calculating the second derivative of ground-state energy density and various types of order parameters, we establish the global ground-state phase diagram of the model, exhibiting rich quantum phases and corresponding phase transitions. Specially, the results reveal that the non-Hermitian cluster-XY model contains five different phases and two critical regions, i.e., ferromagnetic (FM), antiferromagnetic (AFM), symmetry-protected topological (SPT), paramagnetic (PM), Luttinger liquid-like phase, as well as critical region I and II. The order parameters and critical behaviors are investigated and the correctness of the theory is confirmed.

We introduce a novel method that utilizes the longitude-velocity (l-v) envelope to constrain the Milky Way (MW) bar potential. Previous work (Habing 2016) used the l-v diagram to explain the distribution of the observed high-velocity stars. We successfully reproduce their results, but find that their method is limited to only one single type of periodic orbits. In contrast, we propose that the l-v envelope provides much more comprehensive constraints. We compare the properties of test particles in the Portai et al. (2017) MW potential model (P17) with the observed SiO maser stars from the Bulge Asymmetries and Dynamical Evolution (BAaDE) survey. We find that the l-v envelope generated by the bar potential demonstrates reasonable agreement with the observational data, albeit with slight discrepancies near the Galactic center. The inconsistencies suggest that the P17 potential yields a lower central rotation curve, a slightly larger quadrupole strength, or a possibly underestimated pattern speed. We also adopt an updated version of the P17 potential with a modified central mass component (CMC) proposed by Hunter et al. (2024) (H24). The fitting of the l-v envelope suggests that the H24 potential does not completely address the existing challenges and may hint at a possible underestimation of the central bar mass. Our study demonstrates that the l-v envelope can be used as a valuable tool for constraining the Galactic potential and provides insights into the Milky Way bar potential., Comment: 20 pages, 17 figures, ApJ accepted

We propose a geometric series modulated non-Hermitian quasiperiodic lattice model, and explore its localization and topological properties. The results show that with the ever-increasing summation terms of the geometric series, multiple mobility edges and non-Hermitian point gaps with high winding number can be induced in the system. The point gap spectrum of the system has a Matryoshka doll-like structure in the complex plane, resulting in a high winding number. In addition, we analyze the limit case of summation of infinite terms. The results show that the mobility edges merge together as only one mobility edge when summation terms are pushed to the limit. Meanwhile, the corresponding point gaps are merged into a ring with winding number equal to one. Through Avila's global theory, we give an analytical expression for mobility edges in the limit of infinite summation, reconfirming that mobility edges and point gaps do merge and will result in a winding number that is indeed equal to one., Comment: main 6 pages, 7 figures

We construct a family of Hamiltonians whose phase diagram is guaranteed to have a single phase transition, yet the location of this phase transition is uncomputable. The Hamiltonians $H(\phi)$ describe qudits on a two-dimensional square lattice with translationally invariant, nearest-neighbour interactions tuned by a continuous parameter $\phi\in(0,1]$. For all $\phi\in(0,1]$, $H(\phi)$ is in one of two phases, one a gapless phase, the other a gapped phase. The phase transition occurs when $\phi$ equals the Chaitin's constant $\Omega$, a well-defined real number that encodes the Halting problem, and hence is uncomputable for Turing machines and undecidable for any consistent recursive axiomatization of mathematics. Our result implies that no general algorithm exists to determine the phase diagrams even under the promise that the phase diagram is exceedingly simple, and illustrates how uncomputable numbers may manifest in physical systems.

Topological photonics enables unprecedented photon manipulation by realizing various topological states, such as corner states, edge states, and surface states. However, achieving a topological fiber state has remained elusive. Here, we demonstrate a topological fiber state in a Weyl gyromagnetic photonic crystal fiber. By applying an in-plane magnetic bias to a gyromagnetic photonic crystal fiber with broken parity-inversion symmetry, we create an asymmetrical Weyl bandgap that supports one-way fiber states associated with type-II Weyl points. Dispersion and topological invariant calculations reveal the transition from Weyl surface states to one-way Weyl fiber states. Electromagnetic field simulations confirm the existence of one-way Weyl fiber states and their robust transport in the presence of metallic obstacle along the transport path. Our findings offer an intriguing pathway for exploring novel topological states and guiding the design of topological fibers., Comment: 19 pages, 7 figures

Compared with single robots, Multi-Robot Systems (MRS) can perform missions more efficiently due to the presence of multiple members with diverse capabilities. However, deploying an MRS in wide real-world environments is still challenging due to uncertain and various obstacles (e.g., building clusters and trees). With a limited understanding of environmental uncertainty on performance, an MRS cannot flexibly adjust its behaviors (e.g., teaming, load sharing, trajectory planning) to ensure both environment adaptation and task accomplishments. In this work, a novel joint preference landscape learning and behavior adjusting framework (PLBA) is designed. PLBA efficiently integrates real-time human guidance to MRS coordination and utilizes Sparse Variational Gaussian Processes with Varying Output Noise to quickly assess human preferences by leveraging spatial correlations between environment characteristics. An optimization-based behavior-adjusting method then safely adapts MRS behaviors to environments. To validate PLBA's effectiveness in MRS behavior adaption, a flood disaster search and rescue task was designed. 20 human users provided 1764 feedback based on human preferences obtained from MRS behaviors related to "task quality", "task progress", "robot safety". The prediction accuracy and adaptation speed results show the effectiveness of PLBA in preference learning and MRS behavior adaption.

In the milli-Hertz frequency band, stochastic gravitational-wave background can be composed of both astronomical and cosmological sources, both can be anisotropic. Numerically depicting these anisotropies can be critical in revealing the underlying properties of their origins. For the first time, we perform a theoretical analysis of the constraining ability of TianQin on multiple moments of the stochastic background. First, we find that with a one-year operation, for a background with a signal-to-noise ratio of 16, TianQin can recover the multiple moments up to $l=4$. We also identified a unique feature of the stochastic background sky map, which is the mirror symmetry along the fixed orbital plane of TianQin. Thirdly, we explain the difference in anisotropy recovering ability between TianQin and LISA, by employing the criteria of the singularity of the covariance matrix (which is the condition number). Finally, we find that since the different data channel combinations correspond to different singularities, certain combinations might have an advantage in stochastic background map-making. We believe that the findings of this work can provide an important reference to future stochastic background analysis pipelines. It can also serve as a guideline for designing better gravitational-wave detectors aiming to decipher anisotropies in the stochastic background., Comment: 12 pages, 6 figures

The phase diagram and sound velocities of the Fe-Si binary alloy, crucial for understanding the Earth's core, are determined at inner core boundary pressure with \textit{ab-initio} accuracy through deep-learning-aided hybrid Monte Carlo simulations. A complex phase diagram emerges close to the melting temperature, where a re-entrance of the body-centered cubic (bcc) phase is observed. The bcc structure is stabilized by a pronounced short-range ordering of the Si atoms. The miscibility gap between the short-range ordered bcc structure and the long-range ordered cubic B2 structure shrinks with increasing temperature and the transition becomes continuous above 6000 K. We find that a bcc Fe-Si solid solution reproduces crucial geophysical data such as the low shear sound velocity and the seismic anisotropy of the inner core much better than other structures., Comment: 8 pages, 5 figures

The recent advances in large language models (LLMs) have significantly expanded their applications across various fields such as language generation, summarization, and complex question answering. However, their application to privacy compliance and technical privacy reviews remains under-explored, raising critical concerns about their ability to adhere to global privacy standards and protect sensitive user data. This paper seeks to address this gap by providing a comprehensive case study evaluating LLMs' performance in privacy-related tasks such as privacy information extraction (PIE), legal and regulatory key point detection (KPD), and question answering (QA) with respect to privacy policies and data protection regulations. We introduce a Privacy Technical Review (PTR) framework, highlighting its role in mitigating privacy risks during the software development life-cycle. Through an empirical assessment, we investigate the capacity of several prominent LLMs, including BERT, GPT-3.5, GPT-4, and custom models, in executing privacy compliance checks and technical privacy reviews. Our experiments benchmark the models across multiple dimensions, focusing on their precision, recall, and F1-scores in extracting privacy-sensitive information and detecting key regulatory compliance points. While LLMs show promise in automating privacy reviews and identifying regulatory discrepancies, significant gaps persist in their ability to fully comply with evolving legal standards. We provide actionable recommendations for enhancing LLMs' capabilities in privacy compliance, emphasizing the need for robust model improvements and better integration with legal and regulatory requirements. This study underscores the growing importance of developing privacy-aware LLMs that can both support businesses in compliance efforts and safeguard user privacy rights., Comment: 8 pages, 4 figures

Large Language Models (LLMs) have recently displayed their extraordinary capabilities in language understanding. However, how to comprehensively assess the sentiment capabilities of LLMs continues to be a challenge. This paper investigates the ability of LLMs to detect and react to sentiment in text modal. As the integration of LLMs into diverse applications is on the rise, it becomes highly critical to comprehend their sensitivity to emotional tone, as it can influence the user experience and the efficacy of sentiment-driven tasks. We conduct a series of experiments to evaluate the performance of several prominent LLMs in identifying and responding appropriately to sentiments like positive, negative, and neutral emotions. The models' outputs are analyzed across various sentiment benchmarks, and their responses are compared with human evaluations. Our discoveries indicate that although LLMs show a basic sensitivity to sentiment, there are substantial variations in their accuracy and consistency, emphasizing the requirement for further enhancements in their training processes to better capture subtle emotional cues. Take an example in our findings, in some cases, the models might wrongly classify a strongly positive sentiment as neutral, or fail to recognize sarcasm or irony in the text. Such misclassifications highlight the complexity of sentiment analysis and the areas where the models need to be refined. Another aspect is that different LLMs might perform differently on the same set of data, depending on their architecture and training datasets. This variance calls for a more in-depth study of the factors that contribute to the performance differences and how they can be optimized., Comment: 10 pages, 2 figures

Space-borne detectors, including TianQin and Laser Interferometry Space Antenna (LISA), are tasked with the simultaneous observation of Galactic foreground, astrophysical and cosmological stochastic gravitational-wave backgrounds (SGWBs). For the first time, we employ a space-borne detector network to identify the multi-component SGWB. Specifically, we develop a tailored likelihood for cross-correlation detection with such networks. Combined with the likelihood, we use the simulated datasets of the TianQin + LISA network to conduct model selection and parameter estimation. Our results indicate that, after 4 years of operation, the network could detect a single SGWB from either astrophysical or cosmological origins, with an energy density $\Omega_{\rm ast/cos}$ (10 mHz) on the order of $10^{-12}$, despite the presence of a Galactic foreground. Furthermore, to distinguish the cosmological background from both a Galactic foreground and the expected astrophysical background, the energy density $\Omega_{\rm cos}$ should reach around $2\times 10^{-11}$., Comment: 17 pages, 9 figures

To coordinate resources among multi-level stakeholders and enhance the integration of electric vehicles (EVs) into multi-microgrids, this study proposes an optimal dispatch strategy within a multi-microgrid cooperative alliance using a nuanced two-stage pricing mechanism. Initially, the strategy assesses electric energy interactions between microgrids and distribution networks to establish a foundation for collaborative scheduling. The two-stage pricing mechanism initiates with a leader-follower game, wherein the microgrid operator acts as the leader and users as followers. Subsequently, it adjusts EV tariffs based on the game's equilibrium, taking into account factors such as battery degradation and travel needs to optimize EVs' electricity consumption. Furthermore, a bi-level optimization model refines power interactions and pricing strategies across the network, significantly enhancing demand response capabilities and economic outcomes. Simulation results demonstrate that this strategy not only increases renewable energy consumption but also reduces energy costs, thereby improving the overall efficiency and sustainability of the system., Comment: Accepted by IEEE Transactions on Sustainable Energy, Paper no. TSTE-00122-2024

Fast, collimated jets are ubiquitous features of young stellar objects (YSOs). They are generally thought to be powered by disk accretion, but the details are debated. Through 2D (axisymmetric) MHD simulations, we find that a fast ($>100$~km/s) collimated bipolar jet is continuously driven along the north and south poles of the circumstellar disk that is initially magnetized by a large-scale open poloidal field and contains a thermally ionized inner magnetically active zone surrounded by a dead zone. The fast jet is primarily driven magneto-centrifugally by the release of the gravitational binding energy of the so-called ``avalanche accretion streams" near the boundary of an evacuated poloidal field-dominated polar region and a thick disk atmosphere raised by a toroidal magnetic field. Specifically, the fast outflow is driven along the upper (open) branch of the highly pinched poloidal field lines threading the (strongly magnetically braked) accretion streams where the density is relatively low so that the lightly loaded material can be accelerated magneto-centrifugally along the open field line to a high speed. The highly pinched poloidal magnetic fields threading the avalanche accretion streams tend to reconnect, enabling mass to accrete to the center without dragging along the poloidal magnetic flux with it. The reconnection provides a potential heating source for producing chondrules and calcium- and aluminum-rich inclusions (CAIs).

Zero-shot coordination (ZSC) remains a major challenge in the cooperative AI field, which aims to learn an agent to cooperate with an unseen partner in training environments or even novel environments. In recent years, a popular ZSC solution paradigm has been deep reinforcement learning (DRL) combined with advanced self-play or population-based methods to enhance the neural policy's ability to handle unseen partners. Despite some success, these approaches usually rely on black-box neural networks as the policy function. However, neural networks typically lack interpretability and logic, making the learned policies difficult for partners (e.g., humans) to understand and limiting their generalization ability. These shortcomings hinder the application of reinforcement learning methods in diverse cooperative scenarios.We suggest to represent the agent's policy with an interpretable program. Unlike neural networks, programs contain stable logic, but they are non-differentiable and difficult to optimize.To automatically learn such programs, we introduce Knowledge-driven Programmatic reinforcement learning for zero-shot Coordination (KnowPC). We first define a foundational Domain-Specific Language (DSL), including program structures, conditional primitives, and action primitives. A significant challenge is the vast program search space, making it difficult to find high-performing programs efficiently. To address this, KnowPC integrates an extractor and an reasoner. The extractor discovers environmental transition knowledge from multi-agent interaction trajectories, while the reasoner deduces the preconditions of each action primitive based on the transition knowledge.

We adopt a set of second-order differential equations ($k-\omega$ model) to handle core convective overshooting in massive stars, simulate the evolution of WNL stars with different metallicities and initial masses, both rotating and non-rotating models, and compare the results with the classical overshooting model. The results indicate that under the same initial conditions, the $k-\omega$ model generally produces larger convective cores and wider overshooting regions, thereby increasing the mass ranges and extending the lifetimes of WNL stars, as well as the likelihood of forming WNL stars. The masses and lifetimes of WNL stars both increase with higher metallicities and initial masses. Under higher-metallicity conditions, the two overshooting schemes significantly differ in their impacts on lifetimes of the WNL stars, but insignificant in the mass ranges of the WNL stars. Rotation may drive the formation of WNL stars in low-mass, metal-poor counterparts, with this effect being more pronounced in the OV model. The surface nitrogen of metal-rich WNL stars formed during the MS phase is likely primarily from the CN-cycle, while it may come from both the CN- and NO-cycles for relatively metal-poor counterparts. Our model can effectively explain the distribution of WNL stars in the Milky Way, but appears to have inadequacies in explaining the WNL stars in the LMC., Comment: Accepted by the ApJ

Retrieving external knowledge and prompting large language models with relevant information is an effective paradigm to enhance the performance of question-answering tasks. Previous research typically handles paragraphs from external documents in isolation, resulting in a lack of context and ambiguous references, particularly in multi-document and complex tasks. To overcome these challenges, we propose a new retrieval framework IIER, that leverages Inter-chunk Interactions to Enhance Retrieval. This framework captures the internal connections between document chunks by considering three types of interactions: structural, keyword, and semantic. We then construct a unified Chunk-Interaction Graph to represent all external documents comprehensively. Additionally, we design a graph-based evidence chain retriever that utilizes previous paths and chunk interactions to guide the retrieval process. It identifies multiple seed nodes based on the target question and iteratively searches for relevant chunks to gather supporting evidence. This retrieval process refines the context and reasoning chain, aiding the large language model in reasoning and answer generation. Extensive experiments demonstrate that IIER outperforms strong baselines across four datasets, highlighting its effectiveness in improving retrieval and reasoning capabilities.

Despite large language models (LLMs) have demonstrated impressive performance in various tasks, they are still suffering from the factual inconsistency problem called hallucinations. For instance, LLMs occasionally generate content that diverges from source article, and prefer to extract information that appears at the beginning and end of the context, especially in long document summarization. Inspired by these findings, we propose to improve the faithfulness of LLMs in summarization by impelling them to process the entire article more fairly and faithfully. We present a novel summary generation strategy, namely SliSum, which exploits the ideas of sliding windows and self-consistency. Specifically, SliSum divides the source article into overlapping windows, and utilizes LLM to generate local summaries for the content in the windows. Finally, SliSum aggregates all local summaries using clustering and majority voting algorithm to produce more faithful summary of entire article. Extensive experiments demonstrate that SliSum significantly improves the faithfulness of diverse LLMs including LLaMA-2, Claude-2 and GPT-3.5 in both short and long text summarization, while maintaining their fluency and informativeness and without additional fine-tuning and resources. We further conduct qualitative and quantitative studies to investigate why SliSum works and impacts of hyperparameters in SliSum on performance., Comment: Long paper accepted at LREC-COLING 2024 (oral)

We present the results of the ALMA Large Program Early Planet Formation in Embedded disks observations of the Class 0 protostar GSS30 IRS3. Our observations included 1.3 mm continuum with a resolution of 0.''05 (7.8 au) and several molecular species including $^{12}$CO, $^{13}$CO, C$^{18}$O, H$_{2}$CO and c-C$_{3}$H$_{2}$. The dust continuum analysis unveiled a disk-shaped structure with a major axis size of $\sim$200 au. We observed an asymmetry in the minor axis of the continuum emission suggesting that the emission is optically thick and the disk is flared. On the other hand, we identified two prominent bumps along the major axis located at distances of 26 and 50 au from the central protostar. The origin of the bumps remains uncertain and might be due to an embedded substructure within the disk or the result of the temperature distribution instead of surface density due to optically thick continuum emission. The $^{12}$CO emission reveals a molecular outflow consisting of three distinct components: a collimated one, an intermediate velocity component exhibiting an hourglass shape, and a wider angle low-velocity component. We associate these components with the coexistence of a jet and a disk-wind. The C$^{18}$O emission traces both a Keplerian rotating circumstellar disk and the infall of the rotating envelope. We measured a stellar dynamical mass of 0.35$\pm$0.09 M$_{\odot}$., Comment: 25 pages, 19 figures. Accepted for publication in A&A

The HH 111 protostellar disk has recently been found to host a pair of spiral arms. Here we report the dust polarization results in the disk as well as the inner envelope around it, obtained with the Atacama Large Millimeter/submillimeter Array in continuum at lambda ~ 870 micron and ~ 0. 05" resolution. In the inner envelope, polarization is detected with a polarization degree of ~ 6% and an orientation almost everywhere parallel to the minor axis of the disk, and thus likely to be due to the dust grains magnetically aligned mainly by toroidal fields. In the disk, the polarization orientation is roughly azimuthal on the far side and becomes parallel to the minor axis on the near side, with a polarization gap in between on the far side near the central protostar. The disk polarization degree is ~ 2%. The polarized intensity is higher on the near side than the far side, showing a near-far side asymmetry. More importantly, the polarized intensity and thus polarization degree are lower in the spiral arms, but higher in between the arms, showing an anticorrelation of the polarized intensity with the spiral arms. Our modeling results indicate that this anticorrelation is useful for constraining the polarization mechanism and is consistent with the dust self-scattering by the grains that have grown to a size of ~ 150 micron. The interarms are sandwiched and illuminated by two brighter spiral arms and thus have higher polarized intensity. Our dust self-scattering model can also reproduce the observed polarization orientation parallel to the minor axis on the near side and the observed azimuthal polarization orientation at the two disk edges in the major axis., Comment: 23 pages, 5 figures

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the binary Class 0 protostellar system BHR 71 IRS1 and IRS2 as part of the Early Planet Formation in Embedded Disks (eDisk) ALMA Large Program. We describe the $^{12}$CO ($J$=2--1), $^{13}$CO ($J$=2--1), C$^{18}$O ($J$=2--1), H$_2$CO ($J=3_{2,1}$--$2_{2,0}$), and SiO ($J$=5--4) molecular lines along with the 1.3 mm continuum at high spatial resolution ($\sim$0.08" or $\sim$5 au). Dust continuum emission is detected toward BHR 71 IRS1 and IRS2, with a central compact component and extended continuum emission. The compact components are smooth and show no sign of substructures such as spirals, rings or gaps. However, there is a brightness asymmetry along the minor axis of the presumed disk in IRS1, possibly indicative of an inclined geometrically and optically thick disk-like component. Using a position-velocity diagram analysis of the C$^{18}$O line, clear Keplerian motions were not detected toward either source. If Keplerian rotationally-supported disks are present, they are likely deeply embedded in their envelope. However, we can set upper limits of the central protostellar mass of 0.46 M$_\odot$ and 0.26 M$_\odot$ for BHR 71 IRS1 and BHR 71 IRS2, respectively. Outflows traced by $^{12}$CO and SiO are detected in both sources. The outflows can be divided into two components, a wide-angle outflow and a jet. In IRS1, the jet exhibits a double helical structure, reflecting the removal of angular momentum from the system. In IRS2, the jet is very collimated and shows a chain of knots, suggesting episodic accretion events., Comment: 38 pages, 29 figures, accepted in ApJ

The data circulation is a complex scenario involving a large number of participants and different types of requirements, which not only has to comply with the laws and regulations, but also faces multiple challenges in technical and business areas. In order to systematically and comprehensively address these issues, it is essential to have a comprehensive and profound understanding of 'data circulation'. The traditional analysis method tends to proceed based on the traditional circulation model of commodities, that is, tangible objects, which has some defects and shortcomings, and tends to be a formalized approach, which is faced numerous challenges in practice. This paper analyzes the circulation of data with a philosophical approach, obtains the new explication of data and executing entity, and provides a new definition of the concepts of data utilization and data key stakeholders (objects). At the same time, it puts forward the idea of ``data alienation'', and constructs a new interpretive framework of ``data circulation''. Based on the framework of this interpretation, it is clearly proposed that ``data alienation'' is the core of ``data circulation'', benefit distribution is the driving force, and legal compliance is the foundation, and further discussed the three modes of ``data circulation''. It further discusses the three modes of ``data circulation''. It is pointed out that ``data circulation'' is different from traditional ``commodity circulation''. To achieve ``data circulation'',a comprehensive information infrastructure needs to be established. from a theoretical point of view, it lays a solid foundation for the development of ``data circulation''.

The polarization spectrum, or wavelength dependence of the polarization fraction, of interstellar dust emission provides important insights into the grain alignment mechanism of interstellar dust grains. We investigate the far-infrared polarization spectrum of a realistic simulated high-mass star forming cloud under various models of grain alignment and emission. We find that neither a homogeneous grain alignment model nor a grain alignment model that includes collisional dealignment is able to produce the falling spectrum seen in observations. On the other hand, we find that a grain alignment model with grain alignment efficiency dependent on local temperature is capable of producing a falling spectrum that is in qualitative agreement with observations of OMC-1. For the model most in agreement with OMC-1, we find no correlation between temperature and the slope of the polarization spectrum. However, we do find a positive correlation between column density and the slope of the polarization spectrum. We suggest this latter correlation to be the result of wavelength-dependent polarization by absorption., Comment: 14 pages, 6 figures, 2 tables; Accepted to ApJ

Recent (sub)millimeter polarization observations of protoplanetary disks reveal toroidally aligned, effectively prolate dust grains large enough (at least ~100 $\mu$m) to efficiently scatter millimeter light. The alignment mechanism for these grains remains unclear. We explore the possibility that gas drag aligns grains through gas-dust relative motion when the grain's center of mass is offset from its geometric center, analogous to a badminton birdie's alignment in flight. A simple grain model of two non-identical spheres illustrates how a grain undergoes damped oscillations from flow-induced restoring torques which align its geometric center in the flow direction relative to its center of mass. Assuming specular reflection and subsonic flow, we derive an analytical equation of motion for spheroids where the center of mass can be shifted away from the spheroid's geometric center. We show that a prolate or an oblate grain can be aligned with the long axis parallel to the gas flow when the center of mass is shifted along that axis. Both scenarios can explain the required effectively prolate grains inferred from observations. Application to a simple disk model shows that the alignment timescales are shorter than or comparable to the orbital time. The grain alignment direction in a disk depends on the disk (sub-)structure and grain Stokes number (St) with azimuthal alignment for large St grains in sub-Keplerian smooth gas disks and for small St grains near the gas pressure extrema, such as rings and gaps., Comment: 21 pages, 12 figures, submitted to MNRAS

Rings and gaps are routinely observed in the dust continuum emission of protoplanetary discs (PPDs). How they form and evolve remains debated. Previous studies have demonstrated the possibility of spontaneous gas rings and gaps formation in wind-launching disks. Here, we show that such gas substructures are unstable to the Rossby Wave Instability (RWI) through numerical simulations. Specifically, shorter wavelength azimuthal modes develop earlier, and longer wavelength ones dominate later, forming elongated (arc-like) anti-cyclonic vortices in the rings and (strongly magnetized) cyclonic vortices in the gaps that persist until the end of the simulation. Highly elongated vortices with aspect ratios of 10 or more are found to decay with time in our non-ideal MHD simulation, in contrast with the hydro case. This difference could be caused by magnetically induced motions, particularly strong meridional circulations with large values of the azimuthal component of the vorticity, which may be incompatible with the columnar structure preferred by vortices. The cyclonic and anti-cyclonic RWI vortices saturate at moderate levels, modifying but not destroying the rings and gaps in the radial gas distribution of the disk. In particular, they do not shut off the poloidal magnetic flux accumulation in low-density regions and the characteristic meridional flow patterns that are crucial to the ring and gap formation in wind-launching disks. Nevertheless, the RWI and their associated vortices open up the possibility of producing non-axisymmetric dust features observed in a small fraction of protoplanetary disks through non-ideal MHD, although detailed dust treatment is needed to explore this possibility., Comment: Accepted by MNRAS. 18 pages, 16 figures

We construct Einstein-Maxwell-Scalar (EMS) theories that admit regular electric black holes. Such a Maxwell-scalar theory is equivalent to some nonlinear electrodynamics (NLED) at the level of equations of motion, but it has the advantage of circumventing the no-go theorem of regular electric black holes under a given Lagrangian of NLED. We study the thermodynamics and show that the mass of the regular black hole can be determined solely by the Maxwell field, without having to know the metric profile function. Our formalism allows to study the applications of the electrically-charged regular black holes in areas that were previously available only to the non-regular ones., Comment: Latex, 28 pages, 3 graphs grouped in one figure

In the NISQ era, achieving large-scale quantum computing demands compact circuits to mitigate decoherence and gate error accumulation. Quantum operations with diverse degrees of freedom hold promise for circuit compression, but conventional approaches encounter challenges in simultaneously adjusting multiple parameters. Here, we propose a transition composite gate (TCG) scheme grounded on state-selective transition path engineering, enabling more expressive conditional operations. We experimentally validate a controlled unitary (CU) gate as an example, with independent and continuous parameters. By adjusting the parameters of $\rm X^{12}$ gate, we obtain the CU family with a fidelity range of 95.2% to 99.0% leveraging quantum process tomography (QPT). To demonstrate the capability of circuit compression, we use TCG scheme to prepare 3-qubit Greenberger-Horne-Zeilinger (GHZ) and W states, with the fidelity of 96.77% and 95.72%. TCG can achieve the reduction in circuit depth of about 40% and 44% compared with the use of CZ gates only. Moreover, we show that short-path TCG (SPTCG) can further reduce the state-preparation circuit time cost. The TCG scheme exhibits advantages in certain quantum circuits and shows significant potential for large-scale quantum algorithms., Comment: 21 pages, 12 figures

Non-Hermitian dynamics in quantum systems have unveiled novel phenomena, yet the implementation of valid non-Hermitian quantum measurement remains a challenge, because a universal quantum projective mechanism on the complete but skewed non-Hermitian eigenstates is not explicit in experiment. This limitation hinders the direct acquisition of non-Hermitian observable statistics (e.g., non-Hermitian population dynamics), also constrains investigations of non-Hermitian quantum measurement properties such as uncertainty relation. Here, we address these challenges by presenting a non-Hermitian projective protocol and investigating the non-Hermitian uncertainty relation. We derive the uncertainty relation for pseudo-Hermitian (PH) observables that is generalized beyond the Hermitian ones. We then investigate the projective properties of general quantum states onto complete non-Hermitian eigenvectors, and present a quantum simulating method to apply the valid non-Hermitian projective measurement on a direct-sum dilated space. Subsequently, we experimentally construct a quantum simulator in the quantum optical circuit and realize the 3-dimensional non-Hermitian quantum measurement on the single-photon qutrit. Employing this platform, we explore the uncertainty relation experimentally with different PH metrics. Our non-Hermitian quantum measurement method is state-independent and outputs directly the non-Hermitian quantum projective statistics, paving the way for studies of extensive non-Hermitian observable in quantum domain., Comment: 6 pages, 4 figures

Sign language is a visual language used by the deaf and dumb community to communicate. However, for most recognition methods based on monocular cameras, the recognition accuracy is low and the robustness is poor. Even if the effect is good on some data, it may perform poorly in other data with different interference due to the inability to extract effective features. To solve these problems, we propose a sign language recognition network that integrates skeleton features of hands and facial expression. Among this, we propose a hand skeleton feature extraction based on coordinate transformation to describe the shape of the hand more accurately. Moreover, by incorporating facial expression information, the accuracy and robustness of sign language recognition are finally improved, which was verified on A Dataset for Argentinian Sign Language and SEU's Chinese Sign Language Recognition Database (SEUCSLRD)., Comment: 2023 38th Youth Academic Annual Conference of Chinese Association of Automation (YAC)

The Lyapunov exponent, serving as an indicator of the localized state, is commonly utilized to identify localization transitions in disordered systems. In non-Hermitian quasicrystals, the non-Hermitian effect induced by non-reciprocal hopping can lead to the manifestation of two distinct Lyapunov exponents on opposite sides of the localization center. Building on this observation, we here introduce a comprehensive approach for examining the localization characteristics and mobility edges of non-reciprocal quasicrystals, referred to as asymmetric transfer matrix analysis. We demonstrate the application of this method to three specific scenarios: the non-reciprocal Aubry-Andr\'e model, the non-reciprocal off-diagonal Aubry-Andr\'e model, and the non-reciprocal mosaic quasicrystals. This work may contribute valuable insights to the investigation of non-Hermitian quasicrystal and disordered systems., Comment: 12 pages, 4 figures

Global seismic tomography, taking advantage of seismic waves from natural earthquakes, provides essential insights into the earth's internal dynamics. Advanced Full-waveform Inversion (FWI) techniques, whose aim is to meticulously interpret every detail in seismograms, confront formidable computational demands in forward modeling and adjoint simulations on a global scale. Recent advancements in Machine Learning (ML) offer a transformative potential for accelerating the computational efficiency of FWI and extending its applicability to larger scales. This work presents the first 3D global synthetic dataset tailored for seismic wavefield modeling and full-waveform tomography, referred to as the GlobalTomo dataset. This dataset is uniquely comprehensive, incorporating explicit wave physics and robust geophysical parameterization at realistic global scales, generated through state-of-the-art forward simulations optimized for 3D global wavefield calculations. Through extensive analysis and the establishment of ML baselines, we illustrate that ML approaches are particularly suitable for global FWI, overcoming its limitations with rapid forward modeling and flexible inversion strategies. This work represents a cross-disciplinary effort to enhance our understanding of the earth's interior through physics-ML modeling., Comment: 36 pages

This paper presents two new, simple yet effective approaches to measure the vibration of a swaying millimeter-wave radar (mmRadar) utilizing geometrical information. Specifically, for the planar vibrations, we firstly establish an equation based on the area difference between the swaying mmRadar and the reference objects at different moments, which enables the quantification of planar displacement. Secondly, volume differences are also utilized with the same idea, achieving the self-vibration measurement of a swaying mmRadar for spatial vibrations. Experimental results confirm the effectiveness of our methods, demonstrating its capability to estimate both the amplitude and a crude direction of the mmRadar's self-vibration., Comment: 5 pages, 4 figures,submitted to the IEEE for publication

This comment discusses the feasibility of hot ion mode ${{T}_{i}}/{{T}_{e}}=4$ for proton-boron fusion which is critical for the roadmap proposed in Liu, M et al [Phys. Plasmas 31, 062507 (2024)]. The hot ion mode ${{T}_{i}}/{{T}_{e}}=4$ has been calculated to be far from accessible (${{T}_{i}}/{{T}_{e}}<1.5$ for ${{T}_{i}}=150\text{keV}$) under the most optimal conditions if fusion provides the heating (Xie, H [Introduction to Fusion Ignition Principles: Zeroth Order Factors of Fusion Energy Research (in Chinese), USTC Press, Hefei, 2023]), i.e., that all fusion power serves to heat the ions and that electrons acquire energy only through interactions with ions. We also discuss if hot ion mode of ${{T}_{i}}/{{T}_{e}}=4$ could be achieved by an ideal heating method which is much more efficient than fusion itself (near 20 times fusion power for ${{T}_{i}}=150\text{keV}$) and only heats the ions, whether it makes sense economically., Comment: 3 figures

As a fundamental structural feature, the symmetry of materials determines the exotic quantum properties in transition metal dichalcogenides (TMDs) with charge density wave (CDW). Breaking the inversion symmetry, the Janus structure, an artificially constructed lattice, provides an opportunity to tune the CDW states and the related properties. However, limited by the difficulties in atomic-level fabrication and material stability, the experimental visualization of the CDW states in 2D TMDs with Janus structure is still rare. Here, using surface selenization of VTe2, we fabricated monolayer Janus VTeSe. With scanning tunneling microscopy, an unusual root13-root13 CDW state with threefold rotational symmetry breaking was observed and characterized. Combined with theoretical calculations, we find this CDW state can be attributed to the charge modulation in the Janus VTeSe, beyond the conventional electron-phonon coupling. Our findings provide a promising platform for studying the CDW states and artificially tuning the electronic properties toward the applications.

We explore the generation of topological defects in the course of a dynamical phase transition in a ring with a weak link, i.e., a SSS Josephson junction, from the AdS/CFT correspondence. By setting different parameters of the junction (width, steepness, depth) and the final temperature of the quench, the configurations of the charge density and condensate of the order parameters of the dual field theory are presented. Meanwhile, we observe that in the final equilibrium state, variations in parameters of the junctions only affect the configurations of the charge density and condensate of the order parameters, without altering their values outside the junction. However, variations in the final temperature will directly affect the values of the charge density and condensate of the order parameters outside of the junction. Moreover, in the final equilibrium state, we propose an analytic relation between the gauge-invariant velocity in the two superconducting states in the SSS Josephson junction, which agrees well with the numerical results., Comment: 16 pages, 8 figures

The fast algorithms in Fourier optics have invigorated multifunctional device design and advanced imaging technologies. However, the necessity for fast computations has led to limitations in the widely used conventional Fourier methods, manifesting as fixed size image plane at a certain diffraction distance. These limitations pose challenges in intricate scaling transformations, 3D reconstructions and full-color displays. Currently, there is a lack of effective solutions, often resorting to pre-processing that compromise fidelity. In this paper, leveraging a higher-dimensional phase space method, we present a universal framework allowing for customized diffraction calculation methods. Within this framework, we establish a variable-scale diffraction computation model which allows the adjustment of the size of the image plane and can be operated by fast algorithms. We validate the model's robust variable-scale capabilities and its aberration automatic correction capability for full-color holography, achieving high fidelity. The large-magnification tomography experiment demonstrates that this model provides a superior solution for holographic 3D reconstruction. In addition, this model is applied to achieve full-color metasurface holography with near-zero crosstalk, showcasing its versatile applicability at nanoscale. Our model presents significant prospects for applications in the optics community, such as beam shaping, computer-generated holograms (CGHs), augmented reality (AR), metasurface optical elements (MOEs) and advanced holographic head-up display (HUD) systems., Comment: 26 pages, 13 figures

The recently delimited altermagnetic phase is characterized by zero net magnetization but momentum-dependent collinear spin-splitting. To explore the intriguing physical effects and potential applications of altermagnets, it is essential to analyze their Fermi surface properties, encompassing both configurations and spin textures. Here, we conduct a Fermiology study on metallic altermagnets and demonstrate that the collinear spin-split features of their Fermi surfaces can be clearly revealed through quantum oscillation measurements. By introducing a transverse Zeeman field to remove the spin-degenerate lines in the momentum space, the Fermi surface undergoes a Lifshitz transition, giving rise to spin-flipped cyclotron motion between orbits with opposite spins. Accordingly, the Lifshitz-Onsager quantization yields two sets of Landau levels, leading to frequency splitting of the Shubnikov-de Haas oscillations in conductivity. In the presence of spin-orbit coupling, the Zeeman field causes two separate cyclotron orbits to merge at the Lifshitz transition point before splitting again. This results in the two original frequencies discontinuously changing into a single frequency equal to their sum. Our work unveils a unique and universal signature of altermagnetic Fermi surfaces that can be probed through quantum oscillation measurements., Comment: 6 pages, 4 figures

In the 1960s, it was proposed that in small indirect band-gap materials, excitons can spontaneously form because the density of carriers is too low to screen the attractive Coulomb interaction between electrons and holes. The result is a novel strongly interacting insulating phase known as an excitonic insulator. Here we employ scanning tunnelling microscopy (STM) and spectroscopy (STS) to show that the enhanced Coulomb interaction in quantum-confined elemental Sb nanoflakes drives the system to the excitonic insulator state. The unique feature of the excitonic insulator, a charge density wave (CDW) without periodic lattice distortion, is directly observed. Furthermore, STS shows a gap induced by the CDW near the Fermi surface. Our observations suggest that the Sb(110) nanoflake is an excitonic insulator.

In this paper, we present a converse to a version of Skoda's $L^2$ division theorem by investigating the solvability of $\bar{\partial}$ equations of a specific type., Comment: 19 pages

In this paper, we obtain several classification results of $2$-dimensional complete Lagrangian translators and lagrangian self-expanders with constant squared norm $|\vec{H}|^{2}$ of the mean curvature vector in $\mathbb{C}^{2}$ by using a new Omori-Yau type maximum principle which was proved by Chen and Qiu \cite{CQ}. The same idea is also used to give a similar result of Lagrangian $\xi$-translators in $\mathbb{C}^{2}$.

Global redundancy resolution (GRR) roadmaps is a novel concept in robotics that facilitates the mapping from task space paths to configuration space paths in a legible, predictable, and repeatable way. Such roadmaps could find widespread utility in applications such as safe teleoperation, consistent path planning, and motion primitives generation. However, previous methods to compute GRR roadmaps often necessitate a lengthy computation time and produce non-smooth paths, limiting their practical efficacy. To address this challenge, we introduce a novel method Expansion-GRR that leverages efficient configuration space projections and enables rapid generation of smooth roadmaps that satisfy the task constraints. Additionally, we propose a simple multi-seed strategy that further enhances the final quality. We conducted experiments in simulation with a 5-link planar manipulator and a Kinova arm. We were able to generate the Expansion-GRR roadmaps up to 2 orders of magnitude faster while achieving higher smoothness. We also demonstrate the utility of the GRR roadmaps in teleoperation tasks where our method outperformed prior methods and reactive IK solvers in terms of success rate and solution quality., Comment: Accepted by International Conference on Intelligent Robots and Systems (IROS), 2024

Cross-domain sequential recommendation (CDSR) aims to uncover and transfer users' sequential preferences across multiple recommendation domains. While significant endeavors have been made, they primarily concentrated on developing advanced transfer modules and aligning user representations using self-supervised learning techniques. However, the problem of aligning item representations has received limited attention, and misaligned item representations can potentially lead to sub-optimal sequential modeling and user representation alignment. To this end, we propose a model-agnostic framework called \textbf{C}ross-domain item representation \textbf{A}lignment for \textbf{C}ross-\textbf{D}omain \textbf{S}equential \textbf{R}ecommendation (\textbf{CA-CDSR}), which achieves sequence-aware generation and adaptively partial alignment for item representations. Specifically, we first develop a sequence-aware feature augmentation strategy, which captures both collaborative and sequential item correlations, thus facilitating holistic item representation generation. Next, we conduct an empirical study to investigate the partial representation alignment problem from a spectrum perspective. It motivates us to devise an adaptive spectrum filter, achieving partial alignment adaptively. Furthermore, the aligned item representations can be fed into different sequential encoders to obtain user representations. The entire framework is optimized in a multi-task learning paradigm with an annealing strategy. Extensive experiments have demonstrated that CA-CDSR can surpass state-of-the-art baselines by a significant margin and can effectively align items in representation spaces to enhance performance.

Reverse engineers would acquire valuable insights from descriptive function names, which are absent in publicly released binaries. Recent advances in binary function name prediction using data-driven machine learning show promise. However, existing approaches encounter difficulties in capturing function semantics in diverse optimized binaries and fail to reserve the meaning of labels in function names. We propose Epitome, a framework that enhances function name prediction using votes-based name tokenization and multi-task learning, specifically tailored for different compilation optimization binaries. Epitome learns comprehensive function semantics by pre-trained assembly language model and graph neural network, incorporating function semantics similarity prediction task, to maximize the similarity of function semantics in the context of different compilation optimization levels. In addition, we present two data preprocessing methods to improve the comprehensibility of function names. We evaluate the performance of Epitome using 2,597,346 functions extracted from binaries compiled with 5 optimizations (O0-Os) for 4 architectures (x64, x86, ARM, and MIPS). Epitome outperforms the state-of-the-art function name prediction tool by up to 44.34%, 64.16%, and 54.44% in precision, recall, and F1 score, while also exhibiting superior generalizability., Comment: 24 pages, 10 figures, ACM ESEC/FSE 2024

The magnetic field of a molecular cloud core may play a role in the formation of circumstellar disks in the core. We present magnetic field morphologies in protostellar cores of 16 targets in the Atacama Large Millimeter/submillimeter Array large program "Early Planet Formation in Embedded Disks (eDisk)", which resolved their disks with 7 au resolutions. The 0.1-pc scale magnetic field morphologies were inferred from the James Clerk Maxwell Telescope (JCMT) POL-2 observations. The mean orientations and angular dispersions of the magnetic fields in the dense cores are measured and compared with the radii of the 1.3 mm continuum disks and the dynamically determined protostellar masses from the eDisk program. We observe a significant correlation between the disk radii and the stellar masses. We do not find any statistically significant dependence of the disk radii on the projected misalignment angles between the rotational axes of the disks and the magnetic fields in the dense cores, nor on the angular dispersions of the magnetic fields within these cores. However, when considering the projection effect, we cannot rule out a positive correlation between disk radii and misalignment angles in three-dimensional space. Our results suggest that the morphologies of magnetic fields in dense cores do not play a dominant role in the disk formation process. Instead, the sizes of protostellar disks may be more strongly affected by the amount of mass that has been accreted onto star+disk systems, and possibly other parameters, for example, magnetic field strength, core rotation, and magnetic diffusivity., Comment: 14 pages, 4 figures, accepted by ApJ

It is known that particles with exotic properties can emerge in systems made of simple constituents such as qubits, due to long-range quantum entanglement. In this paper, we provide quantitative characterizations of entanglement necessary for emergent anyons and fermions by using the geometric entanglement measure (GEM) which quantifies the maximal overlap between a given state and any short-range entangled states. For systems with emergent anyons, based on the braiding statistics, we show that the GEM scales linearly in the system size regardless of microscopic details. The phenomenon of emergent anyons can also be understood within the framework of quantum error correction (QEC). Specifically, we show that the GEM of any 2D stabilizer codes must be at least quadratic in the code distance. Our proof is based on a generic prescription for constructing string operators, establishing a rigorous and direct connection between emergent anyons and QEC. For systems with emergent fermions, despite that the ground state subspaces could be exponentially huge and their coding properties could be rather poor, we show that the GEM also scales linearly in the system size. Our results also establish an intriguing link between quantum anomaly and entanglement: a quantum state respecting anomalous $1$-form symmetries, be it pure or mixed, must be long-range entangled and have large GEM, offering a non-trivial class of intrinsically mixed state phases.

It is commonly believed that logical states of quantum error-correcting codes have to be highly entangled such that codes capable of correcting more errors require more entanglement to encode a qubit. Here we show that this belief may or may not be true depending on a particular code. To this end, we characterize a tradeoff between the code distance $d$ quantifying the number of correctable errors, and geometric entanglement of logical states quantifying their maximal overlap with product states or more general "topologically trivial" states. The maximum overlap is shown to be exponentially small in $d$ for three families of codes: (1) low-density parity check (LDPC) codes with commuting check operators, (2) stabilizer codes, and (3) codes with a constant encoding rate. Equivalently, the geometric entanglement of any logical state of these codes grows at least linearly with $d$. On the opposite side, we also show that this distance-entanglement tradeoff does not hold in general. For any constant $d$ and $k$ (number of logical qubits), we show there exists a family of codes such that the geometric entanglement of some logical states approaches zero in the limit of large code length.

We investigate the non-Abelian Thouless pumping in a disorder tunable Lieb chain with degenerate flat bands. The results reveal that quasiperiodic disorder will cause a topological phase transition from the trivial (without non-Abelian Thouless pumping) to the non-trivial (with non-Abelian Thouless pumping) phase. The mechanism behind is that the monopole originally outside the topological region can be driven into the topological region due to the introduction of quasiperiodic disorder. Moreover, since the corresponding monopole will turn into a nodal line to spread beyond the boundaries of the topological region, the system with large disorder strength will result in the disappearance of non-Abelian Thouless pumping. Furthermore, we numerically simulate the Thouless pumping of non-Abelian systems, and the evolution results of center of mass' displacement are consistent with the Chern number. Finally, we discuss the localization properties of the system and find that, similar to [PRL 130, 206401(2023)], the inverse Anderson transition does not occur in the system with the increase of quasiperiodic strength, while the system still maintains the coexistence of localized and extended states., Comment: 9 pages,5 figures

(abridged) Protostellar outflows exhibit large variations in their structure depending on the observed gas emission. This study analyzes the atomic jet and molecular outflow in the Class I protostar, TMC1A to characterize morphology and identify previously undetected spatial features with JWST's NIRSpec IFU. In addition to identifying a large number of Fe II and H2 lines, we have detected the bipolar Fe jet by revealing, for the first time, the presence of a red-shifted atomic jet. Similarly, the red-shifted component of the H2 slower wide-angle outflow is observed. Both Fe II and H2 red-shifted emission exhibit significantly lower flux densities compared to their blue-shifted counterparts. Additionally, we report the detection of a collimated high-velocity (100 km s-1), blue-shifted H2 outflow, suggesting the presence of a molecular jet in addition to the well-known wider angle low-velocity structure. The Fe II and H2 jets show multiple intensity peaks along the jet axis, which may be associated with ongoing or recent outburst events. In addition to the variation in their intensities, the H2 wide-angle outflow exhibits a "ring"-like structure. The blue-shifted H2 outflow also shows a left-right brightness asymmetry likely due to interactions with the surrounding ambient medium and molecular outflows. Using the Fe II line ratios, the extinction along the atomic jet is estimated to be between Av = 10-30 on the blue-shifted side, with a trend of decreasing extinction with distance from the protostar. A similar Av is found for the red-shifted side, supporting the argument for an intrinsic red-blue outflow lobe asymmetry rather than environmental effects such as extinction. This intrinsic difference revealed by the unprecedented sensitivity of JWST, suggests that younger outflows already exhibit the red-blue side asymmetry more commonly observed towards jets associated with Class II disks., Comment: 16 pages, 11 figures