arXiv subjects

Xinyue Jiang

Publications and source records attributed to Xinyue Jiang.

10 recordsLinked to original sources

arXiv2026

Lingering Sweetness of Ethanol Clusters: Sensory Discovery and Objective Discrimination by Impedance-Based Electronic Tongue

Ethanol is conventionally perceived only as a pungent tastant, while the potential sweet properties of ethanol clusters have remained unrecognized. Here we show that ethanol tetramers exhibit a unique time dependent lingering sweetness, distinct from the immediate upupfront sweetness of conventional sweeteners. To objectively verify this phenomenon, we developed an impedance based bionic electronic tongue that monitors changes at a lipid polymer membrane interface. Sensory evaluation revealed increasing ethanol cluster content from 4.83% to 29.53% prolonged sweetness duration from 10s to 25s, whereas sweetness intensity remained low to moderate (1.0-1.7 on a 10 point scale). Using this electronic tongue, we achieved objective discrimination between upfront and lingering sweetness,full band phase angle scanning identified optimal frequencies of 0.933Hz (t=0.171s) for xylitol (fast binding and dissociation) and 0.03Hz (t=5.305s) for ethanol clusters (slow binding and dissociation). Phase angle responses correlated strongly with sensory sweetness duration. In natural aged Chinese Baijiu (1-20 years), low frequency phase angle signals positively correlated with sensory lingering sweetness scores, confirming that ethanol cluster accumulation during aging underpins the sweetness of Baijiu. This work expands the classic AH-B sweetness theory from single molecules to supramolecular clusters and provides an analytical platform for probing the temporal dimension of flavor perception.

physics.atom-ph↗

arXiv2026

Non-equilibrium pathway to mesoscale ordering in ethanol-water binary liquid

Ethanol-water mixtures are a classic example of thermodynamic non-ideality, yet the structural origin of their pronounced anomalies, such as volume contraction and a large negative excess entropy, has remained a long-standing puzzle. Here, we demonstrate these anomalies are not equilibrium properties but calorimetric fingerprint of an arrested phase transition. By imposing periodic thermal oscillations, we drive a 50% (v/v) ethanol-water system along a complete hierarchical self-assembly pathway that progressed from ethanol clusters to water-containing droplets, then to acicular flakes, and finally to micron-scale ordered ethanol aggregates. Fluorescence spectroscopy, two-dimensional correlation analysis and nuclear magnetic resonance revealed the underlying non-equilibrium molecular mechanism: a periodic perturbation of the water-dominated hydrogen-bond network initiates a ethanol-water coexistence intermediate, ultimately leading to the stable ordered assembly of an ethanol-rich phase. Our finding demonstrated that periodic physical perturbations capable drive spontaneous ordering across multiple length scales in a simple binary mixture, providing a kinetic perspective on the structural origin of solution non-ideality, and carry general implications for self-assembly strategies in soft matter.

cond-mat.soft↗

arXiv2026

From Vintage Mythology to Topological Physics: Unveiling a Universal Structural Attractor in Alcoholic Beverage Aging

Alcoholic beverage properties are increasingly understood through ethanol-water structural states rather than empirical labels such as alcohol content and vintage. Yet whether chronological vintage similarly reflects an intrinsic structural state remains unclear. Here, we apply persistent homology to map the topological evolution of self-assembled molecular aggregates in strong-aroma Baijiu aged 1-10 years. The resulting fingerprints reveal a three-stage maturation pathway: rapid scaffold consolidation (B0), population-level channel stabilization (B1), and non-monotonic cavity reorganization (B2). These coupled trajectories converge toward a mature topological state rather than passively tracking chronological age. We therefore propose a universal topological attractor, in which optimal aging is defined by a system's position in persistence space relative to a mature structural domain. This framework reframes beverage aging as navigation through structural state space, providing a physical basis for quality evaluation and accelerated maturation.

physics.atom-ph↗

arXiv2026

MultiPress: A Multi-Agent Framework for Interpretable Multimodal News Classification

With the growing prevalence of multimodal news content, effective news topic classification demands models capable of jointly understanding and reasoning over heterogeneous data such as text and images. Existing methods often process modalities independently or employ simplistic fusion strategies, limiting their ability to capture complex cross-modal interactions and leverage external knowledge. To overcome these limitations, we propose MultiPress, a novel three-stage multi-agent framework for multimodal news classification. MultiPress integrates specialized agents for multimodal perception, retrieval-augmented reasoning, and gated fusion scoring, followed by a reward-driven iterative optimization mechanism. We validate MultiPress on a newly constructed large-scale multimodal news dataset, demonstrating significant improvements over strong baselines and highlighting the effectiveness of modular multi-agent collaboration and retrieval-augmented reasoning in enhancing classification accuracy and interpretability.

cs.CL↗

arXiv2026

Testing Screened Modified Gravity with Strongly Lensed Gravitational Waves

Screening mechanisms are essential components in many modified gravity theories, which satisfy local tests of General Relativity (GR) and address cosmic acceleration on cosmological scales. The strong gravitational lensing of gravitational waves (GWs) offers a unique observational probe into cosmology and fundamental physics. In this paper, we investigate the possibility of testing screened modified gravity theories with strongly lensed gravitational waves. Specially, we develop the refined theoretical and statistical framework, in order to measure the post-Newtonian parameter $γ_{\text{PN}}$ in the presence of screening effects. Specially, the mass-truncated power-law and Navarro-Frenk-White (NFW) models are introduced to quantify the modified lensing potential. Our analysis also addresses the mass-sheet degeneracy (MSD) problem, by incorporating the absolute magnification and time delay measurements accessible through strongly lensed GW systems. We find that individual lensed GW system detected by next-generation GW detectors can provide stringent constraints on the PPN parameter ($γ_{\text{PN}}$) across different screening scales ($Λ$). Therefore, future measurements of strongly lensed GWs have great promise to seek departures from GR on kpc-Mpc scales, due to more precise time delay from lensed GW signals.

astro-ph.GA↗

arXiv2026

Hierarchical cosmological constraints through strong lensing distance ratio

Strong gravitational lensing provides an independent and powerful probe of cosmic expansion by directly linking observables to cosmological distances. Upcoming surveys such as LSST will discover large number of galaxy-galaxy strong lensing systems, offering a new route to precise cosmological constraints. In this paper, we propose a Fisher-like sensitivity factor to map how the cosmological information of strong-lensing distances changes across the lens-source redshift plane. Applying such factor to the distance ratio $D_{ls}/D_s$, the time-delay distance $D_{Δt}$, and the double-source-plane ratio, we determine the ``sensitivity valleys'' where an observable becomes insensitive to a given parameter. The realistically simulated LSST lens population, which largely lies outside the distance-ratio valleys, covers the most sensitive region for $(w_0,w_a)$ parameter space. We then develop a new hierarchical framework, which could calibrate the redshift evolution of lens mass-density slopes and constrain cosmological parameters simultaneously. Focusing on the LSST mock data, we demonstrate that ignoring mass-profile evolution can bias $Ω_m$ by up to $\sim 10σ$, while modeling the lens evolution could perfectly recovers the fiducial cosmology and yield stringent cosmological constraints (e.g., $ΔΩ_m \simeq 0.01$ and $Δw \simeq 0.1$ for $\sim 10^4$ lenses).

astro-ph.CO↗

arXiv2025

New tests of cosmic distance duality relation with DESI 2024 BAO observations

In this paper, we test the cosmic distance duality relation (CDDR), as required by the Etherington reciprocity theorem, which connects the angular diameter distance and the luminosity distance via the relation $ D_{\rm L}(z) = D_{\rm A}(z)(1+z)^2 $. Our analysis is based on the latest baryon acoustic oscillation (BAO) measurements provided by the Dark Energy Survey (DES), the Baryon Oscillation Spectroscopic Survey (BOSS)/Extended BOSS (eBOSS), and the Dark Energy Spectroscopic Instrument (DESI) surveys. Specifically, an unbiased test of the CDDR is performed through a novel, model-independent method inspired by the two-point diagnostic approach, with DES-SN5YR and Pantheon type Ia supernova (SN Ia) sample reconstructed using the Artificial Neural Network (ANN) technique. This methodology effectively eliminates all nuisance parameters, including the sound horizon scale $ r_{\rm d} $ from BAO and the absolute magnitude $ M_{\rm B} $ from SN Ia. A set of $ N-1 $ independent CDDR ratios $ η_{ij} $ are constructed for statistical analysis. At the current observational level, no significant deviation from the CDDR is observed at low redshifts, whereas we find positive evidence ($>2σ$ C.L.) of deviation from the CDDR at two high redshifts ($z=2.33$ and $z=2.334$). Therefore, our results confirm that the BAO measurement provides a powerful tool to test such fundamental relation in modern cosmology.

astro-ph.CO↗

arXiv2024

Newest measurements of Hubble constant from DESI 2024 BAO observations

In this Letter, we use the latest results from the Dark Energy Spectroscopic Instrument (DESI) survey to measure the Hubble constant. Baryon acoustic oscillation (BAO) observations released by the DESI survey, allow us to determine $H_0$ from the first principles. Our method is purely data-driven and relies on unanchored luminosity distances reconstructed from SN Ia data and $H(z)$ reconstruction from cosmic chronometers. Thus it circumvents calibrations related to the value of the sound horizon size at the baryon drag epoch or intrinsic luminosity of SN Ia. We find $H_0=68.4^{+1.0}_{-0.8}~{\rm km~s^{-1}~Mpc^{-1}}$ at 68% C.L., which provides the Hubble constant at an accuracy of 1.3% with minimal assumptions. Our assessments of this fundamental cosmological quantity using the BAO data spanning the redshift range $z=0.51-2.33$ agree very well with Planck's results and TRGB results within $1\sigma$. This result is still in a $4.3\sigma$ tension with the results of the Supernova H0 for the Equation of State (SH0ES).

astro-ph.CO↗

arXiv2024

Weaver: Foundation Models for Creative Writing

This work introduces Weaver, our first family of large language models (LLMs) dedicated to content creation. Weaver is pre-trained on a carefully selected corpus that focuses on improving the writing capabilities of large language models. We then fine-tune Weaver for creative and professional writing purposes and align it to the preference of professional writers using a suit of novel methods for instruction data synthesis and LLM alignment, making it able to produce more human-like texts and follow more diverse instructions for content creation. The Weaver family consists of models of Weaver Mini (1.8B), Weaver Base (6B), Weaver Pro (14B), and Weaver Ultra (34B) sizes, suitable for different applications and can be dynamically dispatched by a routing agent according to query complexity to balance response quality and computation cost. Evaluation on a carefully curated benchmark for assessing the writing capabilities of LLMs shows Weaver models of all sizes outperform generalist LLMs several times larger than them. Notably, our most-capable Weaver Ultra model surpasses GPT-4, a state-of-the-art generalist LLM, on various writing scenarios, demonstrating the advantage of training specialized LLMs for writing purposes. Moreover, Weaver natively supports retrieval-augmented generation (RAG) and function calling (tool usage). We present various use cases of these abilities for improving AI-assisted writing systems, including integration of external knowledge bases, tools, or APIs, and providing personalized writing assistance. Furthermore, we discuss and summarize a guideline and best practices for pre-training and fine-tuning domain-specific LLMs.

cs.CL↗

arXiv2024

Exploring $f(T)$ Gravity via strongly lensed fast radio bursts

This study aims to investigate the strong gravitational lensing effects in $f(T)$ gravity. We present the theoretical analytic expressions for the lensing effects in $f(T)$ gravity, including deflection angle, magnification, and time delay. On this basis, we also take the plasma lensing effect into consideration. We compare the lensing effects between the General Relativity in a vacuum environment and the $f(T)$ gravity in a plasma environment. From a strongly lensed fast radio burst, the results indicate that in a plasma environment, General Relativity and $f(T)$ gravity can generate indistinguishable image positions, but the magnification and time delay on these positions are significantly different, which can be distinguished by current facilities in principle. Therefore, the discrepancies between observational results and theoretical expectations can serve as clues for a modified gravity theory and provide constraints on $f(T)$ gravity.

gr-qc↗