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The spin-$3/2$ chain is a versatile prototypical platform for the study of competition between different kinds of magnetic orders, with the objective of obtaining a deeper understanding of the corresponding quantum phase transitions. In this work, we investigate the spin-$3/2$ chain with nearest-neighbor $J_1$, next-nearest-neighbor $J_2$, and uniaxial single-ion anisotropy $D$ terms in the absence of a magnetic field. For positive values of $J_2/J_1$ and $D/J_1$, we find seven different phases in a rich phase diagram. Without frustration $J_2=0$, a gapless Luttinger liquid phase remains stable for all $D>0$. As $J_2$ increases, we observe three phases with distinct dimerized valence bond orders, which show an intricate competition with vector chiral order and incommensurate correlations. For large $J_2$, regions of phase coexistence between the dimerized and vector chiral orders emerge. We present large-scale numerical data for the determination of transition lines, order parameters, and the nature of the phase transitions., Comment: 8 pages, 10 figures

It is generally believed that electronic correlation, geometric frustration, and topology, \textit{individually}, can facilitate the emergence of various intriguing properties that have attracted a broad audience for both fundamental research and potential applications. Here, we report a systematic investigation on a quasi-kagome Kondo Weyl semimetal candidate Ce$_3$TiSb$_5$. A series of unconventional Hall effects are observed. In the paramagnetic phase, signature of dynamic $c$-$f$ hybridization is revealed by a reduction of anomalous Hall effect and is connected to frustration-promoted incoherent Kondo scattering. A large topological Hall effect exceeding 0.2 $\mu\Omega$ cm is found at low temperatures, which should be ascribed to the noncolinear magnetic structures of the frustrated quasi-kagome lattice. In addition, a peculiar loop-shaped Hall effect with switching chirality is also seen, which is inferred to be associated with magnetic domain walls that pin history-dependent spin chirality and / or Fermi-arc surface states projected from the in-gap Weyl nodes. These exotic results place Ce$_3$TiSb$_5$ in a regime of highly-frustrated antiferromagnetic dense Kondo lattice with a nontrivial topology on an ``extended" global phase diagram, and highlight the interplay among electronic correlation, geometric frustration and topology., Comment: 13+3 pages, 6+3 figures, 2+1 tables

Recently Diffusion-based Purification (DiffPure) has been recognized as an effective defense method against adversarial examples. However, we find DiffPure which directly employs the original pre-trained diffusion models for adversarial purification, to be suboptimal. This is due to an inherent trade-off between noise purification performance and data recovery quality. Additionally, the reliability of existing evaluations for DiffPure is questionable, as they rely on weak adaptive attacks. In this work, we propose a novel Adversarial Diffusion Bridge Model, termed ADBM. ADBM directly constructs a reverse bridge from the diffused adversarial data back to its original clean examples, enhancing the purification capabilities of the original diffusion models. Through theoretical analysis and experimental validation across various scenarios, ADBM has proven to be a superior and robust defense mechanism, offering significant promise for practical applications., Comment: 20 pages

In this article, we firstly studied wave function in static spherically symmetric spacetime and obtained effective potential of perturbed fields with spin. Then we applied $6^{\rm{th}}$ order WKB approximation to analyze quasinormal modes of Schwarzschild black hole in the Cold Dark Matter halo in perturbed fields with different spins and derived quasinormal frequencies. Further, to study the relation between quasinormal frequencies and optics, we compare the results of WKB method with eikonal limit formula. At last, we discussed greybody factor in different perturbed fields under this spacetime., Comment: 22 pages, 5 figures, 4 tables

Quantum error correction works effectively only if the error rate of gate operations is sufficiently low. However, some rare physical mechanisms can cause a temporary increase in the error rate that affects many qubits; examples include ionizing radiation in superconducting hardware and large deviations in the global control of atomic systems. We refer to such rare transient spikes in the gate error rate as error bursts. In this work, we investigate the resilience of the surface code to generic error bursts. We assume that, after appropriate mitigation strategies, the spike in the error rate lasts for only a single syndrome extraction cycle; we also assume that the enhanced error rate is uniform across the code block. Under these assumptions, and for a circuit-level depolarizing noise model, we perform Monte Carlo simulations to determine the regime in burst error rate and background error rate for which the memory time becomes arbitrarily long as the code block size grows. Our results indicate that suitable hardware mitigation methods combined with standard decoding methods may suffice to protect against transient error bursts in the surface code.

The stripe phase, an intertwined order observed in high-temperature superconductors, is regarded as playing a key role in elucidating the underlying mechanism of superconductivity, especially in cuprates. Following Jan Zaanen's early scenario, the full-filled charge stripe can be taken as the interactive elastic quantum strings of holes, stabilized by $\pi$-phase shifts between neighboring magnetic domains. However, this scenario is challenging to explain, particularly in terms of electron pairing, which necessitates hole pairs. In this work, we propose a new effective model for describing the stripe phase in the hole-doped $t$-$J_z$ model. With respect to the antiferromagnetic background, the model comprises three types of color-labeled point-defects coupling to {an effective} spin field. Comparing with numerical results from large-scale density matrix renormalization group (DMRG) simulations, we find semi-quantitative agreement in local hole density, magnetic moment, and the newly proposed spectrum features of the {effective} spin field. By systematically analyzing the hole-density distribution and the scaling of groundstate energy at different system sizes, we determine the effective core radius and the effective hopping amplitude of the quantum string. Furthermore, the local pinning field can be finely adjusted to drag the quantum string, offering a potential method for detecting it in optical lattices., Comment: 10 pages, 10 figures, comments are welcome, and more information at http://cqutp.org/users/xfzhang/

We obtained the metric of Schwarzschild-like black hole with LQG correction in anti-de Sitter (AdS) space-time under the assumption that cosmological constant is decoupled in loop quantum gravity (LQG), and investigated its thermodynamics, including equation of state, criticality, heat capacity and Gibbs free energy. $P$-$v$ graph is plotted and critical behavior has been calculated. It is found that due to LQG effect, quantum corrected Schwarzschild-AdS black hole has critical point and a critical ratio $7/18$. It is different from RN-AdS black hole $3/8$ (the same as Van der Waals system). But there are still some similarities compared to Van der Waals system, like same critical exponents and a similar $P$-$v$ graph. Moreover, it is concluded that energy-momentum tensor related to black hole's mass could break the usual first law. The modified first law will violate the conservation of Gibbs free energy during the first order phase transition. Joule-Thomson expansion is also studied. It is interesting that compared with Schwarzschild-AdS black hole, LQG effect leads to inversion points. The inversion curve divides $T$-$P$ coordinate system into two zones: heating region and cooling region, which is shown in inversion curves and isenthalpic curves detailedly. The results showed that there is a minimum inversion mass, which makes any black holes with a mass smaller than this value won't have inversion point., Comment: 35 pages, 8 figures, 1 table

Large language models (LLMs) have demonstrated remarkable capabilities across various domains, although their susceptibility to hallucination poses significant challenges for their deployment in critical areas such as healthcare. To address this issue, retrieving relevant facts from knowledge graphs (KGs) is considered a promising method. Existing KG-augmented approaches tend to be resource-intensive, requiring multiple rounds of retrieval and verification for each factoid, which impedes their application in real-world scenarios. In this study, we propose Self-Refinement-Enhanced Knowledge Graph Retrieval (Re-KGR) to augment the factuality of LLMs' responses with less retrieval efforts in the medical field. Our approach leverages the attribution of next-token predictive probability distributions across different tokens, and various model layers to primarily identify tokens with a high potential for hallucination, reducing verification rounds by refining knowledge triples associated with these tokens. Moreover, we rectify inaccurate content using retrieved knowledge in the post-processing stage, which improves the truthfulness of generated responses. Experimental results on a medical dataset demonstrate that our approach can enhance the factual capability of LLMs across various foundational models as evidenced by the highest scores on truthfulness.

Large Language Models (LLMs) have exhibited remarkable performance across various downstream tasks, but they may generate inaccurate or false information with a confident tone. One of the possible solutions is to empower the LLM confidence expression capability, in which the confidence expressed can be well-aligned with the true probability of the generated answer being correct. However, leveraging the intrinsic ability of LLMs or the signals from the output logits of answers proves challenging in accurately capturing the response uncertainty in LLMs. Therefore, drawing inspiration from cognitive diagnostics, we propose a method of Learning from Past experience (LePe) to enhance the capability for confidence expression. Specifically, we first identify three key problems: (1) How to capture the inherent confidence of the LLM? (2) How to teach the LLM to express confidence? (3) How to evaluate the confidence expression of the LLM? Then we devise three stages in LePe to deal with these problems. Besides, to accurately capture the confidence of an LLM when constructing the training data, we design a complete pipeline including question preparation and answer sampling. We also conduct experiments using the Llama family of LLMs to verify the effectiveness of our proposed method on four datasets.

Gravitational lensing effect is one of most significant observational probes to investigate compact dark matter/objects over a wide mass range. In this work, we first propose to derive the population information and the abundance of supermassive compact dark matter in the mass range $\sim10^5-10^7~M_{\odot}$ from 6 millilensed gamma-ray burst (GRB) candidates in 3000 Fermi GRB events using the hierarchical Bayesian inference method. We obtain that, for the mass range $\sim10^5-10^7~M_{\odot}$, the abundance of supermassive compact dark matter is $f_{\rm CO}=10^{-1.60}$ in the log-normal mass distribution scenario. This result is in obvious tension with some other observational constraints, e.g. ultra-faint dwarfs and dynamical friction. However, it also was argued that there is only one system in these 6 candidates has been identified as lensed GRB event with fairly high confidence. In this case, the tension would be significantly alleviated. Therefore, it would be an interesting clue for both the millilensed GRB identification and the formation mechanism of supermassive compact dark matter., Comment: 7 pages, 4 figures, accepted by PRD Letter

The continuously expanding sample of gravitational-wave observations is revealing the formation and evolutionary mechanism of merging compact binaries. Two primary channels, namely, isolated field binary evolution and dynamical capture, are widely accepted as potential producers of merging binary black holes (BBHs), which are distinguishable with the spin-orientation distributions of the BBHs. We investigate the two formation channels in GWTC-3, with a dedicated semi-parametric population model, i.e., a mixture of two sub-populations with different spin-orientation distributions (one is nearly-aligned and the other is nearly-isotropic). It turns out that the two sub-populations have different mass and mass-ratio distributions. The nearly-aligned sub-population, which is consistent with the isolated field formation channels, has a less preference for symmetric systems, and likely dominate the 10-solar-mass peak in the primary-mass function. While the isotropic sub-population shows a stronger preference for symmetric systems, and mainly contribute to the 35-solar-mass peak in the primary-mass function, consistent with the dynamical channels. Moreover, our results show that the purely isotropic-spin and the single well-aligned (i.e., the width of $\cos\theta$ distribution $\sigma_{\rm t}<0.5$) scenario are ruled out (by a Bayes factor of $\ln\mathcal{B}=5.2$ and $\ln\mathcal{B}=9.8$)., Comment: 26 pages, 16 figures

As world knowledge evolves and new task paradigms emerge, Continual Learning (CL) is crucial for keeping Large Language Models (LLMs) up-to-date and addressing their shortcomings. In practical applications, LLMs often require both continual instruction tuning (CIT) and continual pre-training (CPT) to adapt to new task paradigms and acquire necessary knowledge for task-solving. However, it remains challenging to collect CPT data that addresses the knowledge deficiencies in models while maintaining adequate volume, and improving the efficiency of utilizing this data also presents significant difficulties. Inspired by the 'summarizing mistakes' learning skill, we propose the Continue Evolving from Mistakes (CEM) method, aiming to provide a data-efficient approach for collecting CPT data and continually improving LLMs' performance through iterative evaluation and supplementation with mistake-relevant knowledge. To efficiently utilize these CPT data and mitigate forgetting, we design a novel CL training set construction paradigm that integrates parallel CIT and CPT data. Extensive experiments demonstrate the efficacy of the CEM method, achieving up to a 17% improvement in accuracy in the best case. Furthermore, additional experiments confirm the potential of combining CEM with catastrophic forgetting mitigation methods, enabling iterative and continual model evolution.

Quantum phase estimation is one of the fundamental primitives that underpins many quantum algorithms, including quantum amplitude estimation, the HHL algorithm for solving linear systems of equations, and quantum principal component analysis. Due to its significance as a subroutine, in this work, we study the coherent version of the phase estimation problem, where given an arbitrary input state and black-box access to unitaries $U$ and controlled-$U$, the goal is to estimate the phases of $U$ in superposition. Unlike most existing phase estimation algorithms, which employ intermediary measurements steps that inevitably destroy coherence, only a couple of algorithms, including the well-known standard quantum phase estimation algorithm, consider this coherent setting. In this work, we propose an improved version of this standard algorithm that utilizes tapering/window functions. Our algorithm, which we call tapered quantum phase estimation algorithm, achieves the optimal query complexity (total number of calls to $U$ and controlled-$U$) without requiring the use of a computationally expensive quantum sorting network for median computation, which the standard algorithm uses to boost the success probability arbitrarily close to one. We also show that the tapering functions that we use are optimal by formulating optimization problems with different optimization criteria. Beyond the asymptotic regime, we also provide non-asymptotic query complexity of our algorithm, as it is crucial for practical implementation. Finally, we also propose an efficient algorithm that prepares the quantum state corresponding to the optimal tapering function., Comment: 23 pages, 6 figures

As the brightest gamma-ray burst ever observed, GRB 221009A provided a precious opportunity to explore spectral line features. In this paper, we performed a comprehensive spectroscopy analysis of GRB 221009A jointly with GECAM-C and Fermi/GBM data to search for emission and absorption lines. For the first time we investigated the line feature throughout this GRB including the most bright part where many instruments suffered problems, and identified prominent emission lines in multiple time intervals. The central energy of the Gaussian emission line evolves from about 37 MeV to 6 MeV, with a nearly constant ratio (about 10\%) between the line width and central energy. Particularly, we find that both the central energy and the energy flux of the emission line evolve with time as a power law decay with power law index of -1 and -2 respectively. We suggest that the observed emission lines most likely originate from the blue-shifted electron positron pair annihilation 511 keV line. We find that a standard high latitude emission scenario cannot fully interpret the observation, thus we propose that the emission line comes from some dense clumps with electron positron pairs traveling together with the jet. In this scenario, we can use the emission line to directly, for the first time, measure the bulk Lorentz factor of the jet ($\Gamma$) and reveal its time evolution (i.e. $\Gamma \sim t^{-1}$) during the prompt emission. Interestingly, we find that the flux of the annihilation line in the co-moving frame keeps constant. These discoveries of the spectral line features shed new and important lights on the physics of GRB and relativistic jet., Comment: Accepted by SCIENCE CHINA Physics, Mechanics & Astronomy (SCPMA)

The optical properties of Euler-Heisenberg (EH) black hole (BH) surrounded by Cold Dark Matter (CDM) halo are investigated. By changing BH's parameters, we found that the radius of horizon r_{h} and radius of photon sphere r_{ph} will transparently increase as CDM halo parameters R and \rho increase. To show the influence of CDM halo on the BH's optical characteristics, we took two sets of R and \rho with prominent differences and plot the first four orders of images for thin accretion disk with different angle of inclination \theta of observer. The images with light intensity distributions using Novikov-Thorne (N-T) model are also derived, as well as the effective potential, photon orbits. Especially, analysis of intersection behaviors between photon trajectories with different impact parameters and circular time-like orbits in accretion disk will help better understand the image of thin accretion disk. Our results showed that CDM halo will make BH become more larger and dimmer distinctly., Comment: 42 pages,16 figures,4 tables

Generative Language Models (LMs) such as ChatGPT have exhibited remarkable performance across various downstream tasks. Nevertheless, one of their most prominent drawbacks is generating inaccurate or false information with a confident tone. Previous studies have devised sophisticated pipelines and prompts to induce large LMs to exhibit the capability for self-correction. However, large LMs are explicitly prompted to verify and modify its answers separately rather than completing all steps spontaneously like humans. Moreover, these complex prompts are extremely challenging for small LMs to follow. In this paper, we introduce the \underline{I}ntrinsic \underline{S}elf-\underline{C}orrection (ISC) in generative language models, aiming to correct the initial output of LMs in a self-triggered manner, even for those small LMs with 6 billion parameters. Specifically, we devise a pipeline for constructing self-correction data and propose Partial Answer Masking (PAM), aiming to endow the model with the capability for intrinsic self-correction through fine-tuning. We conduct experiments using LMs with parameters sizes ranging from 6 billion to 13 billion in two tasks, including commonsense reasoning and factual knowledge reasoning. Our experiments demonstrate that the outputs generated using ISC outperform those generated without self-correction. We believe that the output quality of even small LMs can be further improved by empowering them with the ability to intrinsic self-correct.

A generation method of new metric in the case of static spherically symmetric space-time is derived. Using this approach, we construct a metric which describes Euler-Heisenberg black hole surrounded by perfect fluid dark matter and investigate its optical and thermodynamic properties. We found that radius of shadow will increase with the increase of dark matter effect, and more strong dark matter will diminish the light intensity of accretion disk generally. Moreover, in thermodynamics, when quantum electrodynamic parameter is positive, there will be a critical value of dark matter parameter, which determine the number of black hole's critical points., Comment: 34 pages, 11 figures

The early afterglow of a Gamma-ray burst (GRB) can provide critical information on the jet and progenitor of the GRB. The extreme brightness of GRB 221009A allows us to probe its early afterglow in unprecedented detail. In this letter, we report comprehensive observation results of the early afterglow of GRB 221009A (from $T_0$+660 s to $T_0$+1860 s, where $T_0$ is the \textit{Insight}-HXMT/HE trigger time) in X/$\gamma$-ray energy band (from 20 keV to 20 MeV) by \textit{Insight}-HXMT/HE, GECAM-C and \textit{Fermi}/GBM. We find that the spectrum of the early afterglow in 20 keV-20 MeV could be well described by a cutoff power-law with an extra power-law which dominates the low and high energy bands respectively. The cutoff power-law $E_{\rm peak}$ is $\sim$ 30 keV and the power-law photon index is $\sim$ 1.8 throughout the early afterglow phase. By fitting the light curves in different energy bands, we find that a significant achromatic break (from keV to TeV) is required at $T_0$ + 1246$^{+27}_{-26}$ s (i.e. 1021 s since the afterglow starting time $T_{\rm AG}$=$T_0$+225 s), providing compelling evidence of a jet break. Interestingly, both the pre-break and post-break decay slopes vary with energy, and these two slopes become closer in the lower energy band, making the break less identifiable. Intriguingly, the spectrum of the early afterglow experienced a slight hardening before the break and a softening after the break. These results provide new insights into the understanding of this remarkable GRB., Comment: Accepted for publication in ApJ Letters on 19-Jan-2024, 11 pages, 7 figures and 2 tables

It is known that deep neural networks are vulnerable to adversarial attacks. Although Automatic Speaker Verification (ASV) built on top of deep neural networks exhibits robust performance in controlled scenarios, many studies confirm that ASV is vulnerable to adversarial attacks. The lack of a standard dataset is a bottleneck for further research, especially reproducible research. In this study, we developed an open-source adversarial attack dataset for speaker verification research. As an initial step, we focused on the over-the-air attack. An over-the-air adversarial attack involves a perturbation generation algorithm, a loudspeaker, a microphone, and an acoustic environment. The variations in the recording configurations make it very challenging to reproduce previous research. The AdvSV dataset is constructed using the Voxceleb1 Verification test set as its foundation. This dataset employs representative ASV models subjected to adversarial attacks and records adversarial samples to simulate over-the-air attack settings. The scope of the dataset can be easily extended to include more types of adversarial attacks. The dataset will be released to the public under the CC BY-SA 4.0. In addition, we also provide a detection baseline for reproducible research., Comment: Accepted by ICASSP2024

As a new member of the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) after GECAM-A and GECAM-B, GECAM-C (originally called HEBS), which was launched on board the SATech-01 satellite on July 27, 2022, aims to monitor and localize X-ray and gamma-ray transients from $\sim$ 6 keV to 6 MeV. GECAM-C utilizes a similar design to GECAM but operates in a more complex orbital environment. In this work, we utilize the secondary particles simultaneously produced by the cosmic-ray events on orbit and recorded by multiple detectors, to calibrate the relative timing accuracy between all detectors of GECAM-C. We find the result is 0.1 $\mu \rm s$, which is the highest time resolution among all GRB detectors ever flown and very helpful in timing analyses such as minimum variable timescale and spectral lags, as well as in time delay localization. Besides, we calibrate the absolute time accuracy using the one-year Crab pulsar data observed by GECAM-C and Fermi/GBM, as well as GECAM-C and GECAM-B. The results are $2.02\pm 2.26\ \mu \rm s$ and $5.82\pm 3.59\ \mu \rm s$, respectively. Finally, we investigate the spectral lag between the different energy bands of Crab pulsar observed by GECAM and GBM, which is $\sim -0.2\ {\rm \mu s\ keV^{-1}}$., Comment: submitted

Controllable video generation has gained significant attention in recent years. However, two main limitations persist: Firstly, most existing works focus on either text, image, or trajectory-based control, leading to an inability to achieve fine-grained control in videos. Secondly, trajectory control research is still in its early stages, with most experiments being conducted on simple datasets like Human3.6M. This constraint limits the models' capability to process open-domain images and effectively handle complex curved trajectories. In this paper, we propose DragNUWA, an open-domain diffusion-based video generation model. To tackle the issue of insufficient control granularity in existing works, we simultaneously introduce text, image, and trajectory information to provide fine-grained control over video content from semantic, spatial, and temporal perspectives. To resolve the problem of limited open-domain trajectory control in current research, We propose trajectory modeling with three aspects: a Trajectory Sampler (TS) to enable open-domain control of arbitrary trajectories, a Multiscale Fusion (MF) to control trajectories in different granularities, and an Adaptive Training (AT) strategy to generate consistent videos following trajectories. Our experiments validate the effectiveness of DragNUWA, demonstrating its superior performance in fine-grained control in video generation. The homepage link is \url{https://www.microsoft.com/en-us/research/project/dragnuwa/}

Helium white dwarfs (HeWDs) are thought to form from low-mass red giant stars experiencing binary interaction. Because the helium core mass of a red giant star is closely related to the stellar radius, there exists well-known relation between the orbital period ($P_{\rm orb}$) and the mass ($M_{\rm WD}$) of the HeWDs, which is almost independent of the type of the companion star. Traditional derivation of the $M_{\rm WD}$-$P_{\rm orb}$ relation generally neglected the effect of wind mass loss from the red giants, while observations show that wind mass loss from red giants in binary systems is systematically higher than that from isolated stars. In this work, we calculate binary evolution with tidally enhanced stellar wind (TEW) and find that it causes significantly scatter of the traditional $M_{\rm WD}$-$P_{\rm orb}$ relation. The TEW can prevent the red giants from overflowing their Roche lobes and slow down the growth of the helium core, leaving a lower-mass HeWD for given orbital period. This scenario may account for some of the HeWD binaries that deviate from the traditional $M_{\rm WD}$-$P_{\rm orb}$ relation. However, we point out that observations of more HeWD binaries in wide orbits are needed to test the TEW model and to constrain the enhanced wind factor., Comment: 11 pages, 8 figures, 3 tables, accepted for publication in MNRAS, comments are welcome!

Theoretical studies predicted possible superconductivity in electron-doped chromium pnictides isostructural to their iron counterparts. Here, we report the synthesis and characterization of a new ZrCuSiAs-type Cr-based compound ThCrAsN, as well as its oxygen-doped variants. All samples of ThCrAsN$_{1-x}$O$_x$ show metallic conduction, but no superconductivity is observed above 30 mK even though the oxygen substitution reaches 75\%. The magnetic structure of ThCrAsN is determined to be G-type antiferromagnetic by magnetization measurements and first-principles calculations jointly. The calculations also indicate that the in-plane Cr--Cr direct interaction of ThCrAsN is robust against the heavy electron doping. The calculated density of states of the orbital occupations of Cr for ThCrAs(N,O) is strongly spin-polarized. Our results suggest the similarities between chromium pnictides and iron-based superconductors shouldn't be overestimated.

The study of quasi-periodic oscillations (QPOs) and power density spectra (PDS) continuum properties can help shed light on the still illusive emission physics of magnetars and as a window into the interiors of neutron stars using asteroseismology. In this work, we employ a Bayesian method to search for the QPOs in the hundreds of X-ray bursts from SGR J1935+2154 observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to January 2022. Although no definitive QPO signal (significance $>3\sigma$) is detected in individual bursts or the averaged periodogram of the bursts grouped by duration, we identify several bursts exhibiting possible QPO at $\sim$ 40 Hz, which is consistent with that reported in the X-ray burst associated with FRB 200428. We investigate the PDS continuum properties and find that the distribution of the PDS slope in the simple power-law model peaks $\sim$ 2.5, which is consistent with other magnetars but higher than 5/3 commonly seen in gamma-ray bursts. Besides, the distribution of the break frequency in the broken power-law model peaks at $\sim$ 60 Hz. Finally, we report that the power-law index of PDS has an anti-correlation and power-law dependence on the burst duration as well as the minimum variation timescale., Comment: comments welcome

Observations of elliptical galaxies suggest that black holes (BHs) might serve as dark energy candidates, coupled to the expansion of the Universe. According to this hypothesis, the mass of a BH could increase as the Universe expands. BH low-mass X-ray binaries (LMXBs) in the Galactic disk were born several gigayears ago, making the coupling effect potentially significant. In this work, we calculate the evolution of BH binaries with a binary population synthesis method to examine the possible influence of cosmologically-coupled growth of BHs, if it really exists. The measured masses of the compact objects in LMXBs show a gap around $\sim 2.5-5~{\rm M_\odot}$, separating the most massive neutron stars from the least massive BHs. Our calculated results indicate that, considering the mass growth seem to (partially) account for the mass gap and the formation of compact BH LMXBs, alleviating the challenges in modeling the formation and evolution of BH LMXBs with traditional theory. However, critical observational evidence like the detection of intermediate-mass black hole binaries is required to test this hypothesis., Comment: 10 pages, 4 figures, 3 tables, accepted for publication in ApJ, comments are welcome

It is widely accepted that quite a number of double compact objects (DCOs) in the Milky Way can be identified by future space-based gravitational wave (GW) detectors, while systematic investigations on the detection of the GW sources in nearby galaxies are still lacking. In this paper, we present calculations of potential populations of GW sources for all types of DCOs in the Local Group galaxy M31. For M31, we use an age-dependent model for the evolution of the metallicity and the star-formation rate. By varying assumptions of common-envelope ejection efficiencies and supernova-explosion mechanisms during binary evolution, we make predictions on the properties of DCOs that can be detected by the Laser Interferometer Space Antenna (LISA). Our calculations indicate that a few (a dozen) DCOs are likely to be observed by LISA during its 4 (10) yr mission. We expect that the sources with black-hole components are more likely to be firstly identified during a 4-yr mission since these binaries have relatively large chirp masses, while the systems with white-dwarf components dominate the overall population of detectable GW sources during a 10-yr mission. LISA can only detect very tight fast-merging systems in M31, corresponding to the peak of orbital period distribution from $\sim 2$ min for double white dwarfs to $\sim 20$~min for double black holes., Comment: 15 pages, 7 figures, 1 table, accepted by ApJ

The minimum variation timescale (MVT) of soft gamma-ray repeaters can be an important probe to estimate the emission region in pulsar-like models, as well as the Lorentz factor and radius of the possible relativistic jet in gamma-ray burst (GRB)-like models, thus revealing their progenitors and physical mechanisms. In this work, we systematically study the MVTs of hundreds of X-ray bursts (XRBs) from SGR J1935+2154 observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to Jan 2022 through the Bayesian Block algorithm. We find that the MVTs peak at $\sim$ 2 ms, corresponding to a light travel time size of about 600 km, which supports the magnetospheric origin in pulsar-like models. The shock radius and the Lorentz factor of the jet are also constrained in GRB-like models. Interestingly, the MVT of the XRB associated with FRB 200428 is $\sim$ 70 ms, which is longer than that of most bursts and implies its special radiation mechanism. Besides, the median of MVTs is 7 ms, shorter than the median MVTs of 40 ms and 480 ms for short GRBs or long GRBs, respectively. However, the MVT is independent of duration, similar to GRBs. Finally, we investigate the energy dependence of MVT and suggest that there is a marginal evidence for a power-law relationship like GRBs but the rate of variation is at least about an order of magnitude smaller. These features may provide an approach to identify bursts with a magnetar origin., Comment: accepted for publication in ApJS

In this paper, we study in detail the nonlinear propagation of magnetic soliton in a ferromagnetic film. The sample is magnetized to saturation by an external field perpendicular to film plane. A new generalized (2+1)-dimensional short-wave asymptotic model is derived. The bilinear-like forms of this equation are constructed, and exact magnetic line soliton solutions are exhibited. It is observed that a series of stable lumps can be generated by an unstable magnetic soliton under Gaussian disturbance. Such magnetic lumps are highly stable and can maintain their shapes and velocities during evolution or collision. The interaction between lump and magnetic soliton, as well as interaction between two lumps, are numerically investigated. We further discuss the nonlinear motion of lumps in ferrites with Gilbert-damping and inhomogeneous exchange effects. The results show that the Gilbert-damping effects make the amplitude and velocity of the magnetic lump decay exponentially during propagation. And the shock waves are generated from a lump when quenching the strength of inhomogeneous exchange., Comment: 7 pages, 7figures

As a general framework, Matrix Exponential Dimensionality Reduction (MEDR) deals with the small-sample-size problem that appears in linear Dimensionality Reduction (DR) algorithms. High complexity is the bottleneck in this type of DR algorithm because one has to solve a large-scale matrix exponential eigenproblem. To address it, here we design a general quantum algorithm framework for MEDR based on the block-encoding technique. This framework is configurable, that is, by selecting suitable methods to design the block-encodings of the data matrices, a series of new efficient quantum algorithms can be derived from this framework. Specifically, by constructing the block-encodings of the data matrix exponentials, we solve the eigenproblem and then obtain the digital-encoded quantum state corresponding to the compressed low-dimensional dataset, which can be directly utilized as input state for other quantum machine learning tasks to overcome the curse of dimensionality. As applications, we apply this framework to four linear DR algorithms and design their quantum algorithms, which all achieve a polynomial speedup in the dimension of the sample over their classical counterparts., Comment: 14 pages, 6 figures

We have performed a spectral-timing analysis on the black hole X-ray binary MAXI J1535--571 during its 2017 outburst, with the aim of exploring the evolution of the inner accretion flow geometry. X-ray reverberation lags are observed in the hard-intermediate state (HIMS) and soft-intermediate state (SIMS) of the outburst. During the HIMS, the characteristic frequency of the reverberation lags $\nu_0$ (the frequency at which the soft lag turns to zero in the lag-frequency spectra) increases when the spectrum softens. This reflects a reduction of the spatial distance between the corona and accretion disc, when assuming the measured time lags are associated with the light travel time. We also find a strong correlation between $\nu_0$ and type-C Quasi Periodic Oscillation (QPO) centroid frequency $\nu_{QPO}$, which can be well explained by the Lense-Thirring (L-T) precession model under a truncated disk geometry. Despite the degeneracy in the spectral modellings, our results suggest that the accretion disc is largely truncated in the low hard state (LHS), and moves inward as the spectrum softens. Combine the spectral modelling results with the $\nu_0$ - $\nu_{QPO}$ evolution, we are inclined to believe that this source probably have a truncated disk geometry in the hard state.