arXiv subjects

Chao Liu

Publications and source records attributed to Chao Liu.

At least 109 records · Page 6Linked to original sources

arXiv2025

Introduction to the Chinese Space Station Survey Telescope (CSST)

The Chinese Space Station Survey Telescope (CSST) is an upcoming Stage-IV sky survey telescope, distinguished by its large field of view (FoV), high image quality, and multi-band observation capabilities. It can simultaneously conduct precise measurements of the Universe by performing multi-color photometric imaging and slitless spectroscopic surveys. The CSST is equipped with five scientific instruments, i.e. Multi-band Imaging and Slitless Spectroscopy Survey Camera (SC), Multi-Channel Imager (MCI), Integral Field Spectrograph (IFS), Cool Planet Imaging Coronagraph (CPI-C), and THz Spectrometer (TS). Using these instruments, CSST is expected to make significant contributions and discoveries across various astronomical fields, including cosmology, galaxies and active galactic nuclei (AGN), the Milky Way and nearby galaxies, stars, exoplanets, Solar System objects, astrometry, and transients and variable sources. This review aims to provide a comprehensive overview of the CSST instruments, observational capabilities, data products, and scientific potential.

astro-ph.IM↗

arXiv2025

Conceptual Design Report of Super Tau-Charm Facility: The Accelerator

Electron-positron colliders operating in the GeV region of center-of-mass energies or the Tau-Charm energy region, have been proven to enable competitive frontier research, due to its several unique features. With the progress of high energy physics in the last two decades, a new-generation Tau-Charm factory, Super Tau Charm Facility (STCF) has been actively promoting by the particle physics community in China. STCF holds great potential to address fundamental questions such as the essence of color confinement and the matter-antimatter asymmetry in the universe in the next decades. The main design goals of STCF are with a center-of-mass energy ranging from 2 to 7 GeV and a peak luminosity surpassing 5*10^34 cm^-2s^-1 that is optimized at a center-of-mass energy of 4 GeV, which is about 50 times that of the currently operating Tau-Charm factory - BEPCII. The STCF accelerator is composed of two main parts: a double-ring collider with the crab-waist collision scheme and an injector that provides top-up injections for both electron and positron beams. As a typical third-generation electron-positron circular collider, the STCF accelerator faces many challenges in both accelerator physics and technology. In this paper, the conceptual design of the STCF accelerator complex is presented, including the ongoing efforts and plans for technological R&D, as well as the required infrastructure. The STCF project aims to secure support from the Chinese central government for its construction during the 15th Five-Year Plan (2026-2030) in China.

physics.acc-ph↗

arXiv2025

Balancing Utility and Privacy: Dynamically Private SGD with Random Projection

Stochastic optimization is a pivotal enabler in modern machine learning, producing effective models for various tasks. However, several existing works have shown that model parameters and gradient information are susceptible to privacy leakage. Although Differentially Private SGD (DPSGD) addresses privacy concerns, its static noise mechanism impacts the error bounds for model performance. Additionally, with the exponential increase in model parameters, efficient learning of these models using stochastic optimizers has become more challenging. To address these concerns, we introduce the Dynamically Differentially Private Projected SGD (D2P2-SGD) optimizer. In D2P2-SGD, we combine two important ideas: (i) dynamic differential privacy (DDP) with automatic gradient clipping and (ii) random projection with SGD, allowing dynamic adjustment of the tradeoff between utility and privacy of the model. It exhibits provably sub-linear convergence rates across different objective functions, matching the best available rate. The theoretical analysis further suggests that DDP leads to better utility at the cost of privacy, while random projection enables more efficient model learning. Extensive experiments across diverse datasets show that D2P2-SGD remarkably enhances accuracy while maintaining privacy. Our code is available here.

cs.LG↗

arXiv2025

AttenTrack: Mobile User Attention Awareness Based on Context and External Distractions

In the mobile internet era, managing limited attention amid information overload is crucial for enhancing collaboration and information delivery. However, current attention-aware systems often depend on wearables or personalized data, limiting their scalability and cross-context adaptability. Inspired by psychological theories, we attempt to treat mobile notifications as naturally occurring external distractions and infer users' attention states based on their response behaviors and contextual information. Our goal is to build an attention-aware model that does not rely on personalized historical data or complex subjective input, while ensuring strong cold-start capability and cross-context adaptability. To this end, We design a field study framework integrating subjective and objective data, closely aligned with real-world external distractions (i.e., mobile notifications). Through field studies, we construct a fine-grained and interpretable dataset centered on the relationship among current context - external distractions - subjective attention. Through our field studies, we conduct an in-depth analysis of the relationships among users' response behaviors, response motivations, contextual information, and attention states. Building on our findings, we propose AttenTrack, a lightweight, privacy-friendly attention awareness model with strong cold-start capability. The model relies solely on non-privacy-sensitive objective data available on mobile devices, and can be applied to a variety of attention management tasks. In addition, we will publicly release the constructed dataset to support future research and advance the field of mobile attention awareness.

cs.HC↗

arXiv2025

Toward High-Precision Astrometry with CSST Using Multi-Gaussian Fitting of PSF

The Chinese Space Station Survey Telescope (CSST) presents significant potential for high-precision astrometry. In this study, we show that the point spread function (PSF) modeled by the discrete PSF with Multi-Gaussian function can effectively enhance the astrometric accuracy. We determine that the PSF profile can be accurately modeled by three Gaussians, which takes advantage of reduced computational complexity in PSF convolution. In sparse star fields, the lowest centering accuracy we obtain after aberration correction can be below 1 mas. We find that the proper motion errors remain below 1.0 mas/yr for point sources with five observations and approximately 0.8 mas/yr for seven observations with a time baseline of around 3.5 years. We finally demonstrate that the precision of our position measurements for stars fainter than 21 mag in the simulated CSST crowded field is better than the results from both SExtractor and DOLPHOT.

astro-ph.IM↗

arXiv2025

Identification of OB associations using the LAMOST-Gaia OB star sample

OB associations, as an intermediate stage between Galactic clusters and field stars, play an important role in understanding the star formation process, early stellar evolution, and Galactic evolution. In this work, we construct a large sample of OB stars with 6D phase space parameters ($l, b, d, V_{\rm los}, pmra ,pmdec$) by combining the distances from Bailer-Jones et al. (2021), radial velocities derived from low-resolution spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), and proper motions from the \textit{Gaia} Data Release 3 (DR3). This sample includes 19,933 OB stars, most of which are located within 6\,kpc of the Sun. Using 6D phase space parameters and friends-of-friends clustering algorithm, we identify 67 OB associations and 112 OB association candidates, among them, 49 OB associations and 107 OB association candidates are newly identified. The Galactic rotation curve derived using 67 OB association members is relatively flat in the range of Galactocentric distances 7$<$$R$$<$13\,kpc. The angular rotation velocity at solar Galactocentric distance of $R_\odot$ =8.34\,kpc is $Ω_0$ = 29.05$\pm$0.55\,km\,s$^{-1}$\,kpc$^{-1}$. The spatial distribution of the 67 OB associations indicates that they are mainly located at low Galactic latitudes and near spiral arms of the Milky Way. Additionally, we estimate the velocity dispersions and sizes of these 67 OB associations. Our results show that the velocity dispersions decrease as Galactocentric distances increase, while their sizes increase as Galactocentric distances increase.

astro-ph.GA↗

arXiv2025

Blowups for a class of second order nonlinear hyperbolic equations: A reduced model of nonlinear Jeans instability

Understanding the formation of nonlinear structures in the universe and stellar systems is crucial. The nonlinear Jeans instability plays a key role in these formation processes. It has been a long-standing open problem in astrophysics for more than a century. In this article, we focus on a reduced model of the nonlinear Jeans instability in an expanding Newtonian universe, which is described by a class of second-order nonlinear hyperbolic equations. \begin{equation*} \Box \varrho(x^μ) +\frac{\mathcal{a} }{t} \partial_{t}\varrho(x^μ) - \frac{\mathcal{b}}{t^2} \varrho(x^μ) (1+ \varrho(x^μ) ) -\frac{\mathcal{c}-\mathcal{k} }{1+\varrho(x^μ)} (\partial_{t}\varrho(x^μ))^2= \mathcal{k} F(t). \end{equation*} We establish a family of nonlinear self-increasing blowup solutions (where the solution itself becomes infinite in a stable ODE-type blowup) for this equation. Furthermore, we provide estimates on the growth rate of $\varrho$, which may help explain why the nonlinear structures in the universe grow much faster in astrophysical observations than predicted by the classical Jeans instability.

math.AP↗

arXiv2025

SimViews: An Interactive Multi-Agent System Simulating Visitor-to-Visitor Conversational Patterns to Present Diverse Perspectives of Artifacts in Virtual Museums

Offering diverse perspectives on a museum artifact can deepen visitors' understanding and help avoid the cognitive limitations of a single narrative, ultimately enhancing their overall experience. Physical museums promote diversity through visitor interactions. However, it remains a challenge to present multiple voices appropriately while attracting and sustaining a visitor's attention in the virtual museum. Inspired by recent studies that show the effectiveness of LLM-powered multi-agents in presenting different opinions about an event, we propose SimViews, an interactive multi-agent system that simulates visitor-to-visitor conversational patterns to promote the presentation of diverse perspectives. The system employs LLM-powered multi-agents that simulate virtual visitors with different professional identities, providing diverse interpretations of artifacts. Additionally, we constructed 4 conversational patterns between users and agents to simulate visitor interactions. We conducted a within-subject study with 20 participants, comparing SimViews to a traditional single-agent condition. Our results show that SimViews effectively facilitates the presentation of diverse perspectives through conversations, enhancing participants' understanding of viewpoints and engagement within the virtual museum.

cs.HC↗

arXiv2025

The binary fraction of Blue Horizontal-Branch (BHB) Stars

Blue horizontal-branch (BHB) stars are old, low-mass, metal-poor stars that serve as important tracers of the Galactic halo structure, kinematics, and evolution.Understanding their binary properties provides key insights into their formation channels and the role of binary interactions in the evolution of horizontal branch stars. We intend to investigate the intrinsic binary fraction $f_{\rm b}^{\rm in}$ of BHB stars and its dependencies on metallicity, kinematics, and effective temperature. We collect \GG{299} BHB stars from LAMOST with multiple radial velocity (RV) measurements and classify the sample into halo-like and disk-like BHBs based on their kinematics and metallicity, as well as into bluer and redder BHBs based on their \G{effective temperature}. We then investigate the observed binary fraction for each group based on the radial velocity variations and apply a set of Monte Carlo simulations, assuming distributions of $f(P) \propto P^π$ and $f(q) \propto q^κ$, to correct the observed binary fraction for observational biases and derive the intrinsic binary fraction. After correcting for observational biases, the intrinsic binary fraction increases to 31% for n > 2 and 32% for n > 3. A clear contrast is observed between halo-like and disk-like BHB stars, with halo-like BHBs exhibiting a lower intrinsic binary fraction (28% for n > 2 and 29% for n> 3) compared to disk-like BHBs (46% and 51%, respectively), indicating different formation pathways. Additionally, we find that bluer BHB stars exhibit a significantly higher binary fraction (42% for n > 2 and 45% for n> 3) than redder BHB stars (24% and 23%, respectively), which suggests a possible link between binarity and the effective temperature, although more samples are required to confirm this.

astro-ph.SR↗

arXiv2025

Controlling diverse robots by inferring Jacobian fields with deep networks

Mirroring the complex structures and diverse functions of natural organisms is a long-standing challenge in robotics. Modern fabrication techniques have greatly expanded the feasible hardware, but using these systems requires control software to translate the desired motions into actuator commands. Conventional robots can easily be modeled as rigid links connected by joints, but it remains an open challenge to model and control biologically inspired robots that are often soft or made of several materials, lack sensing capabilities, and may change their material properties with use. Here, we introduce a method that uses deep neural networks to map a video stream of a robot to its visuomotor Jacobian field (the sensitivity of all 3D points to the robot's actuators). Our method enables the control of robots from only a single camera, makes no assumptions about the robots' materials, actuation, or sensing, and is trained without expert intervention by observing the execution of random commands. We demonstrate our method on a diverse set of robot manipulators that vary in actuation, materials, fabrication, and cost. Our approach achieves accurate closed-loop control and recovers the causal dynamic structure of each robot. Because it enables robot control using a generic camera as the only sensor, we anticipate that our work will broaden the design space of robotic systems and serve as a starting point for lowering the barrier to robotic automation.

cs.RO↗

arXiv2025

An Improved ChaCha Algorithm Based on Quantum Random Number

Due to the merits of high efficiency and strong security against timing and side-channel attacks, ChaCha has been widely applied in real-time communication and data streaming scenarios. However, with the rapid development of AI-assisted cryptanalysis and quantum computing technologies, there are serious challenges to the secure implementation of ChaCha cipher. To further strengthen the security of ChaCha cipher, we propose an improved variant based on quantum random numbers, i.e., Quantum Random Number Enhanced ChaCha (QRE-ChaCha). Specifically, the design XORs the initial constants with quantum random numbers and periodically injects quantum random numbers into selected state words during odd rounds to enhance diffusion. Compared with the original ChaCha, the present variant shows stronger resistance to differential attacks and generates a keystream with statistical randomness, thereby offering increased robustness against both classical and quantum attacks. To evaluate the security and performance of the present ChaCha, our analysis proceeds in three main parts. Firstly, we analyze its theoretical security in terms of quantum randomness and attack testing, and conduct differential cryptanalysis with an automated search method based on the Boolean satisfiability problem (SAT). Secondly, we subject the keystream generated by the cipher to randomness tests using the NIST statistical test suite and the GM/T 0005-2021 randomness testing standard. Finally, we assess its encryption and decryption performance by measuring its encryption speed on files of various sizes. According to the results, the present ChaCha is significantly improved to resist differential attacks while maintaining the high efficiency of the original ChaCha cipher, and its keystream successfully passes statistical randomness tests using the NIST and GM/T 0005-2021 standards, meeting cryptographic application requirements.

cs.CR↗

arXiv2025

Closed-Form and Boundary Expressions for Task-Success Probability in Status-Driven Systems

Timely and efficient dissemination of server status is critical in compute-first networking systems, where user tasks arrive dynamically and computing resources are limited and stochastic. In such systems, the access point plays a key role in forwarding tasks to a server based on its latest received server status. However, modeling the task-success probability suffering the factors of stochastic arrivals, limited server capacity, and bidirectional link delays. Therefore, we introduce a unified analytical framework that abstracts the AP forwarding rule as a single probability and models all network and waiting delays via their Laplace transforms. This approach yields a closed form expression for the end to end task success probability, together with upper and lower bounds that capture Erlang loss blocking, information staleness, and random uplink/downlink delays. We validate our results through simulations across a wide range of parameters, showing that theoretical predictions and bounds consistently enclose observed success rates. Our framework requires only two interchangeable inputs (the forwarding probability and the delay transforms), making it readily adaptable to alternative forwarding policies and delay distributions. Experiments demonstrate that our bounds are able to achieve accuracy within 0.01 (upper bound) and 0.016 (lower bound) of the empirical task success probability.

cs.NI↗

arXiv2025

Similarity Memory Prior is All You Need for Medical Image Segmentation

In recent years, it has been found that "grandmother cells" in the primary visual cortex (V1) of macaques can directly recognize visual input with complex shapes. This inspires us to examine the value of these cells in promoting the research of medical image segmentation. In this paper, we design a Similarity Memory Prior Network (Sim-MPNet) for medical image segmentation. Specifically, we propose a Dynamic Memory Weights-Loss Attention (DMW-LA), which matches and remembers the category features of specific lesions or organs in medical images through the similarity memory prior in the prototype memory bank, thus helping the network to learn subtle texture changes between categories. DMW-LA also dynamically updates the similarity memory prior in reverse through Weight-Loss Dynamic (W-LD) update strategy, effectively assisting the network directly extract category features. In addition, we propose the Double-Similarity Global Internal Enhancement Module (DS-GIM) to deeply explore the internal differences in the feature distribution of input data through cosine similarity and euclidean distance. Extensive experiments on four public datasets show that Sim-MPNet has better segmentation performance than other state-of-the-art methods. Our code is available on https://github.com/vpsg-research/Sim-MPNet.

cs.CV↗

arXiv2025

Millions of Main-Sequence Binary Stars from Gaia BP/RP Spectra

We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a forward modeling approach that maps stellar mass and photometric metallicity to XP spectra using a neural network. Our methodology identifies binary systems through statistical comparison of single- and binary-star model fits, enabling detection of binaries with mass ratios between 0.4 and 1.0 and flux ratios larger than 0.1. From an initial sample of 35 million stars within 1 kpc, we identify 14 million binary candidates and define a high-confidence "golden sample" of 1 million binary systems. This large, homogeneous sample enables detailed statistical analysis of binary properties across diverse Galactic environments, providing new insights into binary star formation and evolution. In addition, the $χ^2$ comparison allows us to distinguish stars with luminous companions from single stars or binaries with dark companions, such as white dwarfs, neutron stars and black hole candidates, improving our understanding of compact object populations.

astro-ph.SR↗

arXiv2025

Super Co-alignment of Human and AI for Sustainable Symbiotic Society

As Artificial Intelligence (AI) advances toward Artificial General Intelligence (AGI) and eventually Artificial Superintelligence (ASI), it may potentially surpass human control, deviate from human values, and even lead to irreversible catastrophic consequences in extreme cases. This looming risk underscores the critical importance of the "superalignment" problem - ensuring that AI systems which are much smarter than humans, remain aligned with human (compatible) intentions and values. While current scalable oversight and weak-to-strong generalization methods demonstrate certain applicability, they exhibit fundamental flaws in addressing the superalignment paradigm - notably, the unidirectional imposition of human values cannot accommodate superintelligence's autonomy or ensure AGI/ASI's stable learning. We contend that the values for sustainable symbiotic society should be co-shaped by humans and living AI together, achieving "Super Co-alignment." Guided by this vision, we propose a concrete framework that integrates external oversight and intrinsic proactive alignment. External oversight superalignment should be grounded in human-centered ultimate decision, supplemented by interpretable automated evaluation and correction, to achieve continuous alignment with humanity's evolving values. Intrinsic proactive superalignment is rooted in a profound understanding of the Self, others, and society, integrating self-awareness, self-reflection, and empathy to spontaneously infer human intentions, distinguishing good from evil and proactively prioritizing human well-being. The integration of externally-driven oversight with intrinsically-driven proactive alignment will co-shape symbiotic values and rules through iterative human-ASI co-alignment, paving the way for achieving safe and beneficial AGI and ASI for good, for human, and for a symbiotic ecology.

cs.AI↗

arXiv2025

$La_3Pd_2NaO_9$: A High-Valent Insulating Palladate

A high-valent palladate, $La_3Pd_2NaO_9$, has been synthesized for the first time. Single crystals with dimensions of 20 $μ$m on edge were successfully grown using the flux method at 420 $^o$C and 70 bar oxygen pressure. Energy dispersive spectroscopy (EDS) and inductively coupled plasma mass spectroscopy (ICP) measurements show that the atomic ratio of La: (Pd+Na) is 3: 3 and Pd: Na is 2: 1. X-ray photoelectron spectroscopy (XPS) measurements show that the oxidation state of Pd is dominated by +4. Synchrotron X-ray single-crystal diffraction measurements revealed that this material crystallizes in the monoclinic $P2_1/c$ space group with charge ordering of Na and Pd. Real-space imaging via scanning transmission electron microscopy (STEM) confirmed the crystal structure and revealed excellent sample homogeneity. Electrical resistivity measurements show an insulating behavior. Magnetic measurements show an unexpected paramagnetic behavior, which probably originate from a small fraction of high-spin Pd$^{2+}$ evidenced by XPS. The successful growth of $La_3Pd_2NaO_9$ single crystals with a high-valent oxidation state of Pd offers an approach for exploring interesting palladates, including potential bilayer Ruddlesden-Popper palladates analogous to the high temperature superconducting $La_3Ni_2O_7$.

cond-mat.str-el↗

arXiv2025

The emergence of nonlinear Jeans-type instabilities for quasilinear wave equations

This article contributes a key ingredient to the longstanding open problem of understanding the fully nonlinear version of Jeans instability, as highlighted by A. Rendall [Living Rev. Relativ. 8, 6 (2005)]. We establish a family of self-increasing blowup solutions for the following class of quasilinear wave equations (a model of the Peebles' and Noh-Hwang's equations) that have not previously been studied: \[ \partial^2_t \varrho- \biggl(\frac{ \mathsf{m}^2 (\partial_{t}\varrho )^2}{(1+\varrho )^2} + 4(\mathsf{k}-\mathsf{m}^2)(1+\varrho )\biggr) Δ\varrho = F(t,\varrho,\partial_μ \varrho) \] where $F$ is given by \[ F(t,\varrho,\partial_μ \varrho):= \underbrace{\frac{2}{3 } \varrho (1+\varrho) }_{ \text{(i) self-increasing}} \underbrace{-\frac{1}{3} \partial_{t}\varrho }_{ \text{(ii) damping}} + \underbrace{\frac{4}{3} \frac{(\partial_{t}\varrho )^2}{1+\varrho } }_{\text{(iii) Riccati}} + \underbrace{ \biggl(\mathsf{m}^2 \frac{ (\partial_{t}\varrho )^2}{(1+\varrho )^2} + 4(\mathsf{k}-\mathsf{m}^2) (1+\varrho ) \biggr) q^i \partial_{i}\varrho }_{\text{(iv) convection}} - \mathtt{K}^{ij} \partial_{i}\varrho\partial_{j}\varrho. \] The result implies the solutions can attain arbitrarily large values over time, leading to self-increasing singularities at some future endpoints of null geodesics provided the inhomogeneous perturbations of data are sufficiently small. Moreover, the solution exhibits almost blowup behavior in the long-wavelength domain. This phenomenon is referred to as the nonlinear Jeans-type instability because this wave equation is closely related to the nonlinear version of the Jeans instability problem in the Euler-Poisson and Einstein-Euler systems, which characterizes the formation of nonlinear structures in the universe. The growth rate of $\varrho$ is significantly faster than that of the solutions to the classical linearized Jeans instability.

math.AP↗

arXiv2025

The structural and kinematical properties of NGC 5634, a globular cluster associated with the Sagittarius dwarf galaxy?

We investigate the origin of NGC 5634 through a comprehensive analysis of its morphology, kinematics and dynamics. Utilizing data from the DESI Legacy Survey, we refined its fundamental parameters (age t = 12.8 +/- 0.3 Gyr, metallicity [Fe/H] = -1.8 +/- 0.1 dex, distance modulus dm = 17.0 +/- 0.1 mag) and constructed matched-filter template based on the combination of these parameters to search for extra-tidal structures. However, no significant features were detected above a 3 sigma signal-to-noise threshold, which limits our ability to further investigate the association between NGC 5634 and the Sagittarius (Sgr) stream based on morphological evidence. Incorporating GAIA data, we further examine the orbital path of NGC 5634. We found that its orbit only briefly intersects with the Sgr stream and diverges significantly over long-term integrations. This behavior contrasts with that of confirmed Sgr-associated clusters, whose orbits remain closely aligned with the stream throughout their orbital evolution. Additionally, NGC 5634 exhibits a relatively shorter semi-major axis and smaller apocenter and pericenter distances compared to Sgr clusters. These orbital characteristics are more consistent with clusters associated with the Gaia-Sausage-Enceladus (GSE) or the Helmi streams. From a dynamical perspective, in the Lz-E space, NGC 5634 is also distinctly different from Sgr clusters and aligns more closely with the GSE and Helmi regions. Taken together, these findings do not support a strong connection between NGC 5634 and the Sgr dSph, but instead suggest a potential association with another progenitor system, such as GSE or Helmi stream. Nevertheless, further evidence is needed to definitively establish its origin.

astro-ph.GA↗