arXiv subjects

Hong Guo

Publications and source records attributed to Hong Guo.

At least 19 recordsLinked to original sources

arXiv2026

Scalar perturbations and strong cosmic censorship for an asymptotically de Sitter regular black hole

We investigate the quasinormal modes (QNMs) of scalar perturbations and strong cosmic censorship (SCC) in regular Ayón-Beato-García-Bronnikov-de Sitter (ABGB-dS) black hole spacetime. The main motivation of this work is to clarify whether the regularization of black hole core, which removes the central singularity, can also change the fate of SCC connected to the Cauchy horizon. We first study the dependence of the scalar QNM frequency (QNF) on the scalar mass and black hole parameters. For angular number $l=0$, a small scalar mass can give rise to a slowly decaying mode which is purely imaginary, while it will become complex for large enough scalar mass and we call it dS-like mode. We also find that the black hole charge and cosmological constant affect the QNM spectrum in qualitatively opposite ways. We then examine SCC under massless and massive scalar perturbations. For massless perturbations, the QNMs spectrum can be organized into photon sphere (PS), de Sitter (dS) and near-extremal (NE) families. Compared with the SCC in the Reissner-Nordström-de Sitter (RN-dS) case, SCC is generally more easily violated in the ABGB-dS spacetime, although this tendency is reversed for sufficiently large cosmological constant. For massive scalar perturbations, we find that the scalar mass does not restore SCC. Instead, it can enhance the violation by driving the system into the regime $β>1$. At last, we discuss what we may expect from the violation of SCC in a regular black hole spacetime.

gr-qc↗

arXiv2026

A cosmic filament catalog for COSMOS-Web Data Release 1 across 0.5 < z < 3.5

Cosmic filaments represent the environments in which most galaxies form and evolve. However, the spatial distribution of filaments and the link between galaxy properties and their positions relative to filaments remains unclear, particularly at high redshifts. In this work, using the deep-field catalog COSMOS-Web Data Release 1, we construct a filament catalog spanning 0.5 < z < 3.5 that can be directly applied to studies of galaxy evolution and the galaxy--large-scale-structure connection at the peak epoch of galaxy and black hole formation. We developed a new procedure based on the DisPerSE method that fully incorporates the probability distribution functions (PDFs) of galaxy photometric redshifts by generating multiple realizations for each tomographic 2D slice. We then stacked these realizations to construct ``filament probability maps'' (w_ fil maps), from which filaments were subsequently extracted. The filament extraction parameters were optimized using mock catalogs generated from TNG simulations by minimizing the discrepancies between 3D and projected 2D filaments. Applying this procedure to the COSMOS-Web data, we detected 12,523 filaments (comprising 136,210 segments) across 0.5 < z < 3.5 and released a filament catalog, a companion segment catalog, and filament probability maps for each slice. Validation against astrophysical properties shows a strong agreement between the extracted filaments and those in the simulations, supporting the robustness of the filament extraction. These data products provide a robust foundation for investigating galaxy--environment coevolution at cosmic noon and beyond.

astro-ph.CO↗

arXiv2026

Analysis of Hydrogen Contamination in Al/AlOx/Al Josephson Junctions

Hydrogen contamination in Josephson junctions may contribute to device-to-device variability in superconducting qubits, yet its incorporation, location, and bonding in tunnel barriers remain poorly understood. We combine molecular dynamics simulations of aluminum oxidation in dense O2 and H2O environments with atomistic quantum transport calculations. The simulations produce amorphous AlOx barriers with experimentally relevant hydrogen concentrations. Analysis of 400 statistically independent samples shows that the number of incorporated H atoms follows a beta-binomial distribution, reflecting correlations arising from self-limiting oxidation. Most H atoms reside near the AlOx surface, primarily in Al-OH and Al-OH-Al motifs. Quantum transport calculations for Al/Al2O3/Al junctions reveal that hydrogen enhances transmission near the Fermi level by creating an interface dipole that shifts the oxide bands relative to the electrode Fermi level. Combining hydrogen-number statistics with calculated transmission coefficients yields a probability distribution for the Josephson energy. At an average hydrogen content of 2.56 at.%, we predict E_J/h = 10.23 GHz with a standard deviation of 3.6 MHz. Hydrogen shifts the mean Josephson energy by approximately 11%, proportionally to its concentration, but contributes far less to device-to-device variability than observed in state-of-the-art fabricated junctions. These findings provide an atomistic understanding of hydrogen incorporation and its impact on Josephson energy.

quant-ph↗

arXiv2026

Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models

Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (SLMs) are easier to deploy locally yet remain weaker in reasoning. This capability-deployment gap has motivated LLM-SLM collaboration, which aims to improve SLM reasoning using LLM capabilities while preserving the deployment advantages of SLMs. Existing approaches mainly follow two paradigms. Knowledge distillation uses LLM-generated answers and reasoning trajectories to train SLMs offline, but requires parameter updates and additional training. Alternatively, online collaboration routes difficult problems to an LLM or leverages LLM-generated guidance and corrections when an SLM encounters difficulties. Although effective, online collaboration requires repeated LLM access. Moreover, the guidance produced for a particular problem is discarded after inference and cannot benefit subsequent problems involving similar reasoning states. In the paper, we focus on a more constrained setting in which the LLM is accessed only offline, the SLM parameters remain fixed, and online inference is performed solely by the SLM. To this end, we propose Reusable Latent Correction (RLC), which converts one-off natural-language guidance from a black-box LLM into persistent corrective experiences in the hidden space of an SLM. RLC stores these experiences in an external bank and retrieves them according to the SLM's current reasoning state, enabling the SLM to reuse LLM-derived corrections during inference without any online LLM calls. Experiments across multiple reasoning benchmarks and SLM scales show that RLC consistently improves SLM reasoning without parameter updates or online LLM calls. Code is available at https://github.com/ZBH031/reusable-latent-correction.

cs.CL↗

arXiv2026

Multi-tracer mass bias in matched cosmic voids from SDSS DR7 and the ELUCID constrained simulation

Cosmic voids provide a unique environment for studying the relationship between galaxies, subhaloes, and dark matter in the underdense Universe. Using the SDSS galaxy catalogue and the ELUCID constrained simulation, we establish an observationally anchored framework for measuring multi-tracer mass bias within matched cosmic voids. A sample of 102 matched void pairs is constructed to directly compare galaxy, subhalo, and dark matter mass distributions within an observationally constrained realisation of the local Universe. We find that both the galaxy-to-dark matter and subhalo-to-dark matter mass ratios decrease toward void centres, indicating that luminous and halo tracers become increasingly depleted relative to the underlying matter distribution in the deepest underdensities. In contrast, the galaxy-to-subhalo mass ratio exhibits substantially larger statistical uncertainties within the inner void regions ($r/R_{\rm v}\lesssim0.5$). By comparing measurements obtained using independent and common coordinate frameworks, we show that coordinate offsets contribute to the observed scatter but cannot fully account for the large uncertainties. The remaining uncertainty primarily arises from the severe scarcity of massive subhaloes ($\log_{10}(M_{\rm sub}/h^{-1}M_\odot)\ge11.8$) within void interiors, which greatly reduces the number of statistically valid measurements near void centres. Our results provide an empirical characterization of multi-tracer mass bias in observationally constrained cosmic environments and demonstrate the importance of accounting for coordinate consistency and tracer scarcity when interpreting such measurements in extreme underdense regions.

astro-ph.CO↗

arXiv2026

The VariableTNG project: how baryonic mechanisms shape galaxy properties

We use 50 Sobol-sampled VariableTNG simulations, varying eight subgrid parameters at fixed cosmology and initial conditions, to determine which baryonic processes regulate galaxies and black holes at $z=6$ and $z=8$. We compare the simulations with recent high-redshift measurements of the stellar mass function, star-forming main sequence, stellar and gas-phase mass-metallicity relations, stellar mass-size relation, and black-hole host and accretion properties. The simulations reproduce several broad trends in these observables, although differences remain in gas-phase metallicity, galaxy size, and the most extreme black-hole populations. Given the substantial uncertainties in both the physical modelling and the observational inference of high-redshift galaxy properties, we regard these differences as diagnostic tensions rather than definitive model failures. Random-forest analyses reveal a clear hierarchy in parameter sensitivity. The abundance of low-mass galaxies is regulated primarily by stellar feedback, particularly the supernova temperature $T_{\mathrm{SN}}$ and thermal wind fraction $τ_{\mathrm{w}}$, whereas the sensitivity of the scatter in the star-forming main sequence is weaker and redshift dependent. The high-accretion tail of black-hole growth depends on black-hole seeding and feedback parameters, but also on $T_{\mathrm{SN}}$, suggesting that stellar feedback indirectly regulates rapid black-hole growth through its impact on the available gas supply. Although cosmic variance can obscure these intrinsic responses in independent small volumes, our controlled experiment identifies stellar feedback as a common physical link between early low-mass galaxy formation and rapid black-hole growth.

astro-ph.GA↗

arXiv2026

Extremal Scalarization of Charged Black Holes: Miransky Scaling across Reissner-Nordström Extremality

We study spontaneous scalarization near and at extremality in Einstein-Maxwell-scalar theory. As Reissner-Nordström (RN) extremality is approached from below, the nonextremal scalarization existence curves collapse toward a common critical threshold $α_c=1/4$ given by the Breitenlohner-Freedman bound for the near-horizon throat (AdS$_2\times S^2$) of its extremal black hole. For a polynomial coupling, we construct extremal black holes with nonconstant scalar hair, satisfying $M^2+Q_s^2=Q^2$, which places them in the overcharged region $Q/M>1$ beyond the RN bound. A common near-region phase mechanism predicts accumulation toward the RN extremality from both sides, yielding Miransky-type scaling. In the extremal sector, the logarithmic phase interval doubles, halving the exponent which denotes the geometric spacing of successive node scales.

gr-qc↗

arXiv2026

Scalarized Einstein-Euler-Heisenberg black holes at the approach to extremality

We investigate extremal black holes with scalar hair in the generic Einstein-Euler-Heisenberg (EEH)-scalar theory with two scalar couplings to the Maxwell term. One is an exponential coupling with coupling constant $α$ and the other is its polynomial coupling. We first construct scalarized black holes on the cold (C)-horizon of EEH black holes described by mass $M$ and magnetic charge $P$ both at the linear level, through the existence curves $α_n(q)$ with $q=P/M$, and as fully backreaction solutions. As extremality ($q=q_e$) is approached, all existence curves accumulate, following $α_n-α_c\sim 1/\ln^2(q_e-q)$, at the critical branch $α_c$ fixed by the Breitenlohner-Freedman bound for the near-horizon (AdS$_2\times S^2$) throat. We obtain scalarized extremal black hole (SEBH) with constant secondary hair and it is recovered exactly from the entropy function approach working on the near-horizon throat. Its entropy is an attractor invariant, being independent of the asymptotic modulus, so the scalar hair remains secondary. Exploiting this constant scalar, we seek further SEBHs with scalar hair keeping its charge $Q_s$ for the zero asymptotic scalar ($ϕ_\infty=0$). In the $(q,α)$ plane, we observe that these extremal solutions occupy $q\ge q_e$. Hence, the existence curves $α_n(q)$ existing for $q\le q_e$ and the extremal branches bound the scalarized domain from opposite sides and they meet only at $q=q_e$.

gr-qc↗

arXiv2026

Josephson energy of superconducting junctions: amorphous versus crystalline tunnel barriers

The Josephson energy $E_J$ is a key parameter governing the properties of transmon superconducting qubits. In Al/AlO$_x$/Al junctions, $E_J$ is set by electron tunneling through an ultrathin oxide barrier and therefore depends exponentially on the atomic structure of the barrier. We compute $E_J$ by first-principles device modeling based on the NEGF-DFT quantum-transport method, comparing a junction with a crystalline Al$_2$O$_3$ barrier against ten junctions with melt--quenched amorphous Al$_2$O$_3$ barriers of the same thickness. From the Fermi-level transmission and the Ambegaokar--Baratoff relation, we obtain a mean $E_J/h$ of $2.78$ GHz for the amorphous ensemble, with a standard deviation of $4.67$ GHz, compared with $0.73$ GHz for the crystalline reference; individual amorphous values span nearly two orders of magnitude. Scattering-state analysis shows that transport is quantum tunneling and that the variability originates from stoichiometric inhomogeneity of the amorphous oxide: Al-rich, low-barrier regions can connect into percolation-like tunneling pathways that strongly enhance the conductance. A realistic $200\times200$ nm$^2$ junction self-averages over more than $2\times10^4$ such microscopic regions. These results establish a quantitative atomistic route from oxide microstructure to the superconducting-circuit energy scale $E_J$.

quant-ph↗

arXiv2026

Accelerating Atom Simulations with Variable-Block Sparse Matrix Library

Modern atomistic simulations increasingly employ localized orbitals to represent quantum operators, yielding sparse block matrices whose block shapes vary with chemical species and basis choice. Conventional scalar sparse formats store the entries of each block individually, obscuring this local structure and limiting the use of efficient block algorithms. We present VBCSR, a distributed sparse matrix library that preserves variable-size atomic blocks and accelerates the core linear algebra of large-scale atomistic simulations. A unified interface automatically maps scalar, uniform-basis, and multispecies operators to compressed sparse row (CSR), block sparse row (BSR), or variable-block compressed sparse row (VBCSR). Our advanced acceleration method groups blocks of equal shape and dispatches them to optimized dense kernels. In the reported benchmarks, VBCSR outperforms the tested Python-accessible reference implementations for several block-sparse benchmarks. We further demonstrate VBCSR in an InP nanoparticle application containing more than $10^6$ atoms.

cond-mat.mtrl-sci↗

arXiv2026

The Shape of Information: Global Information Geometric Limits in Multi-task Quantum Systems

Future quantum networks are expected to perform multiple tasks simultaneously within a single system, such as integrated sensing and communication (ISAC) architectures. Despite various metrics, we find that the evaluation of multiple tasks can be unified by their information capacity, and the total task capacity is not determined simply by addition, but is fundamentally constrained by an information geometry which we call the global quantum Fisher information matrix (g-QFIM). With this insight, we derive a non-asymptotic, measurement-independent upper bound on the Holevo information for multi-task systems, which takes a Shannon-capacity-like form. It not only quantifies the capacity limit, but also the allocability. Our results reveal a structural phase transition in multi-task performance under resource variation, where additional physical resources no longer increase independent task capacity but instead concentrate more information into a new mono-task mode. Numerical simulations based on photonic phase encoding and realistic noise channels confirm these predictions. This work establishes a unified information-geometric principle for quantum multi-task systems, with implications for the design of future quantum networks and ISAC architectures.

quant-ph↗

arXiv2026

Accelerating Stochastic Gravitational Wave Backgrounds Parameter Estimation in Pulsar Timing Arrays with Flow Matching

\Acp{PTA} are essential tools for detecting the \ac{SGWB}, but their analysis faces significant computational challenges. Traditional methods like \ac{MCMC} struggle with high-dimensional parameter spaces where noise parameters often dominate, % while existing deep learning approaches fail to model the \ac{HD} correlation or are validated only on synthetic datasets. while existing deep learning approaches have so far been validated on synthetic datasets or require training on the full pulsar set, incurring substantial computational and memory costs. We propose a flow-matching-based \ac{CNF} for efficient \ac{PTA} parameter estimation. Using ten pulsars selected according to published NANOGrav 12.5-year dropout factors and applied to the NANOGrav 15-year residuals, our method produces \ac{SGWB} posteriors consistent with a reference \ac{MCMC} analysis, with Jensen-Shannon divergences below $10^{-2}$ nat. After amortized training, posterior generation is reduced from approximately 50 hours for the reference \ac{MCMC} pipeline to approximately 4 minutes for \ac{CNF} sampling. The present study demonstrates that flow-matching-based \acp{CNF} can serve as an efficient posterior-sampling accelerator for reduced \ac{PTA} datasets. Rather than providing new astrophysical constraints, the method is intended to complement conventional \ac{MCMC} analyses and to provide a scalable route toward faster inference in future \ac{PTA} applications.

astro-ph.IM↗

arXiv2026

FASHI DR2: A Catalog of 132 Low-Redshift HI 21 cm Absorption Systems

We present an untargeted survey of 21 cm HI absorption systems based on the second data release of the FAST All Sky HI survey (FASHI DR2), covering approximately 19,500 deg$^{2}$ at $z\lesssim0.09$. A total of 132 HI absorbers are identified, including approximately 60 new discoveries, forming one of the largest homogeneous samples of low-redshift HI absorbers assembled to date. The sample extends to continuum flux densities as low as 2.6 mJy, substantially below the limits of previous flux-limited surveys. The absorber population is dominated by narrow systems ($W_{50}<100$ km s$^{-1}$), while broad absorbers ($W_{50}>200$ km s$^{-1}$) account for 13.6% of the sample. Most absorbers are optically thin, with a median optical depth of $τ_{\rm HI}\approx0.14$. The velocity-offset distribution is broadly symmetric about the systemic velocities of the host galaxies. The associated absorbers are preferentially found in massive, actively star-forming galaxies. We find tentative evidence for a weak anti-correlation between HI column density and stellar mass, although the relation exhibits substantial scatter. These results provide the first statistical characterization of the low-redshift HI absorber population based on the FASHI DR2 sample and establish a valuable benchmark for future HI absorption surveys with next-generation radio facilities.

astro-ph.GA↗

arXiv2026

Observational Evidence for the Kinematic Memory of Cosmic Filaments from Satellite Orbital Orientations

We present an observational study of the kinematic coherence between satellite orbital planes and the cosmic web. Using the SDSS DR12 galaxy sample combined with the Bisous filament catalogue, we investigate whether the orbital motion of satellites preserves the memory of filamentary accretion. For each satellite system, we define a projected orbital-normal vector using galaxy sky positions and line-of-sight velocity offsets. By measuring the angle $θ$ between this vector and the local projected filament direction, we detect a distinctive preferred orientation: satellite orbital planes tend to contain or lie parallel to the filament axis. This signal deviates from the isotropic expectation at a high significance level of $12.8σ$. The strength of this kinematic connection depend strongly on environment and host properties. The preference for orbital planes to track the filament direction is most pronounced for groups in close distance to the filament spine and for more massive hosts. Conversely, at intermediate distances from the filament and at large group-centric radii, the signal reverses, indicating a tendency for orbital planes to be oriented perpendicular to the filament. Our findings provide direct observational evidence for the two-phase model of filamentary accretion, where a transition from initial perpendicular collapse toward the filament spine to subsequent parallel streamwise infall into dark matter haloes governs the orientation of satellite orbital angular momentum and galaxy spin. The observed transition may further trace the characteristic radial scale of filaments, offering a dynamical perspective on the internal structure and assembly of the cosmic filament.

astro-ph.GA↗

arXiv2026

The VariableTNG project: mass-dependent regulation of galaxy morphology by baryonic feedback

Galaxy morphology is shaped by both assembly history and baryonic processes, but their relative roles remain uncertain. We use the VariableTNG (VTNG) simulation suite to investigate how variations in baryonic feedback regulate galaxy morphology while keeping the initial conditions fixed. VTNG consists of cosmological magnetohydrodynamic simulations performed with the moving-mesh code {\sc AREPO}, varying eight parameters governing stellar and AGN feedback. At $z=1$, we characterize morphology using $κ_{\rm co}$, $v/σ$, and the axis ratio $c/a$. We find substantial morphological diversity across feedback models, with the dominant mechanism strongly dependent on stellar mass. For $M_\ast \lesssim 10^{11}\,{\rm M_\odot}$, morphology is primarily controlled by the supernova temperature $T_{\rm SN}$: larger $T_{\rm SN}$ delays early star formation, promotes a denser and more rotationally supported gas reservoir, and favours subsequent disc growth through in-situ star formation. At higher masses, morphology becomes increasingly sensitive to AGN feedback, particularly the quasar-mode coupling efficiency $ε_{\rm f,high}$. Higher $ε_{\rm f,high}$ suppresses early black hole growth, thereby weakening subsequent radio-mode feedback associated with gas depletion and loss of rotational support. The resulting morphology--mass relation is non-monotonic, with maximum rotational support at intermediate stellar masses. Our results demonstrate that baryonic feedback regulates galaxy morphology through distinct mass-dependent pathways, with stellar feedback dominating at lower masses and AGN self-regulation becoming increasingly important at the massive end.

astro-ph.GA↗

arXiv2026

The VariableTNG project: Unveiling the physical drivers of galaxy quenching

Understanding the physical processes that regulate galaxy quenching is a key challenge in galaxy formation and evolution. The VariableTNG (VTNG) project provides a laboratory to investigate these processes, as it systematically varies eight parameters of galaxy formation while keeping the initial conditions fixed, allowing the effects of individual feedback prescriptions to be isolated. We use interpretable machine-learning techniques as a tool to identify the parameters that most strongly regulate the quenched galaxy fraction. Our goal is to quantify the relative importance of the galaxy formation and feedback parameters that regulate the quenched galaxy fraction at z=0, determine how their influence changes across stellar mass and environment. We compute the quenched galaxy fraction for 26 VTNG boxes as a function of stellar mass, black hole mass, and gas mass, considering both the total galaxy population and separate samples of central and satellite galaxies. We train Random Forest regressors to predict the variation of the quenched fraction relative to the TNG100-1 model and use SHAP values to quantify both the magnitude and direction of the influence of each parameter. Our analysis reveals that only a small subset of the VTNG parameters dominates the variance of the quenched fraction. The stellar feedback wind parameter is the primary driver at low stellar masses, while its importance gradually shifts toward AGN-related parameters at higher masses. The supernova temperature also plays an important role at both extremes of the stellar-mass range. This transition persists when the galaxy population is divided into central and satellite systems. Comparisons with observational measurements further suggest that variations in these feedback parameters may contribute to the discrepancies between the fiducial TNG100-1 model and the observed passive galaxy population.

astro-ph.GA↗

arXiv2026

Quantum-Device Simulation of Optical Decoherence of Hole-Spin Qubits in Self-Assembled Quantum Dots

Spin-photon interfaces are essential for communications between distant spin qubits in quantum technologies, but the interband optical excitation can also damp electrically driven hole-spin Rabi oscillations in semiconductor self-assembled quantum dots (SAQDs). We report a device-level modeling workflow that integrates realistic SAQD geometry and multiband electronic-structure analysis with models of electrically driven spin control, interband optical transitions, and open-system dynamics. This workflow enables device-level estimation of Rabi-oscillation damping arising from repeated interband absorption-emission cycles. As an example, for a gated GaAs SAQD subjected to a uniform magnetic field $B_0$ along the growth direction of the SAQD, we predict the Rabi frequency of the hole spin qubit and its damping under external illumination. At $B_0=2$ T, the calculations yield a hole-spin Rabi frequency of 37.3 MHz. When the electrically driven SAQD is illuminated by a broadband LED centered at a wavelength of 790 nm, increasing the optical power from 0.3 to 1.5 mW shortens the Rabi-oscillation decay time from 90.3 to 17.5 ns. Increasing the SAQD height reduces the electron-hole overlap and thus the emission rate, but the resulting redshift moves the interband transitions into stronger spectral overlap with the LED spectrum, thereby increasing the rate of repeated absorption-emission cycles and enhancing photon-induced Rabi-oscillation damping. The results show that geometry, spin-control conditions, and illumination spectrum should be co-optimized in semiconductor spin-photon devices.

cond-mat.mes-hall↗

arXiv2026

Shapley-Value-Based Feature Attribution for Data Masking

Despite its many benefits, widespread access to individuals' personal data also causes severe privacy concerns for consumers, companies, and policymakers. This study proposes a novel framework that adapts the Shapley-value-based feature attribution approach to the problem domain of data privacy by capturing the two crucial dimensions of data privacy---disclosure risk and data utility. Our proposed framework takes a holistic view of data masking through a fair feature attribution approach based on Shapley values. Different from the existing literature that mostly focuses on the risk-utility tradeoff at the dataset level, the proposed framework addresses the tradeoff at the feature level. Furthermore, the proposed framework is agnostic to data masking methods, statistical and machine learning methods, and data utility and disclosure risk evaluation metrics. Experimental results show that our proposed method can effectively reduce disclosure risk while preserving data utility.

cs.LG↗