arXiv subjects
Publications and source records attributed to Bing Yan.
We establish a version of the classical results concerning descriptions of isometries on $C^*$-algebras and noncommutative $L_p$-spaces due to Kadison (1951) and Yeadon (1981) in the setting of Haagerup--Schultz algebras. Precisely, we show that (not necessarily surjective) isometries on such algebras are necessarily implemented by partial isometries and trace-preserving Jordan $^*$-monomorphisms.
Let $LS(\mathcal{M})$ be the algebra of locally measurable operators affiliated with a von Neumann algebra $\mathcal{M}$, equipped with an $F$-norm defined via a dimension function and a probability measure. We prove that every bijective linear isometry between $LS(\mathcal{M})$ admits a canonical representation of the form $\Phi(x)=wJ(x)$, where $w$ is a unitary element and $J$ is a Jordan $^*$-isomorphism, which extends classical results such as the Banach--Stone theorem and Kadison's theorem. Under several structural assumptions on the underlying von Neumann algebras (including all type $\mathrm{II}_\infty$ and type $\mathrm{III}$ algebras, and all factors, and algebras with atomless centers), we prove the one-to-one correspondence between the $F$-norm and the pair $(\mu, D)$ of a probability measure and a dimension function, which fails for algebras with atomic centers.
Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists. As a result, scientists and AI agents need to locate relevant information, verify their provenance, and assemble cross-paper answers manually. We present AskChem, a claim-centered infrastructure for cross-paper chemistry search. AskChem changes the unit of retrieval from the paper to the provenance-carrying claim: each paper is converted into atomic, typed claims, each grounded by a source DOI and a verbatim quote or an explicit evidence locator. Over this shared claim store, AskChem exposes complementary structures for search and synthesis: a stabilized faceted taxonomy for hierarchical retrieval and browsing, an evidence graph linking claims through relations, and an exploratory living taxonomy that situates indexed papers under scientific principles. AskChem currently indexes 2.4M claims from 147K papers and provides a web interface, as well as REST, SDK, and MCP access for AI agents. On AskChem-Bench, grounding a GPT-5.5 reader in AskChem yields 100% resolvable DOIs, compared with 88.3% without retrieval, and the highest citation density among five tested systems. AskChem is live at https://askchem.org.
We report on the ground and numerous excited electronic states. In the ground state the C4n rings are closed-shell systems possessing polyynic structures and can be classified as double anti-aromatic molecules. In their energetically lowest lying triplet state the rings exhibit aromatic cumulenic structures. The overall change in the electronic structures is rather dramatic upon the found moderate geometric changes from polyynic to cumulenic structure. Among others, Hund's rule is violated in both C8 and C12 in their cumulenic structures. We mention that until now, graphene is the only carbon allotrope reported to violate Hund's rule. The reasons for the violation are analyzed. Much effort has been invested to understand the relaxation pathways of the low-lying states leading the C8 from polyynic to cumulenic geometry and vice versa. On its minimum energy path, the first singlet excited state changes from open-shell character in the polyynic structure to a closed-shell state in the cumulenic structure. The cumulenic state lowest in energy is an open-shell singlet which relaxes to the closed-shell polyynic ground state.
Low-latency live streaming (LLS) has emerged as a popular web application, with many platforms adopting real-time protocols such as WebRTC to minimize end-to-end latency. However, we observe a counter-intuitive phenomenon: even when the actual encoded bitrate does not fully utilize the available bandwidth, stalling events remain frequent. This insufficient bandwidth utilization arises from the intrinsic temporal variations of real-time video encoding, which cause conventional packet-level congestion control algorithms to misestimate available bandwidth. When a high-bitrate frame is suddenly produced, sending at the wrong rate can either trigger packet loss or increase queueing delay, resulting in playback stalls. To address these issues, we present Camel, a novel frame-level congestion control algorithm (CCA) tailored for LLS. Our insight is to use frame-level network feedback to capture the true network capacity, immune to the irregular sending pattern caused by encoding. Camel comprises three key modules: the Bandwidth and Delay Estimator and the Congestion Detector, which jointly determine the average sending rate, and the Bursting Length Controller, which governs the emission pattern to prevent packet loss. We evaluate Camel on both large-scale real-world deployments and controlled simulations. In the real-world platform with 250M users and 2B sessions across 150+ countries, Camel achieves up to a 70.8% increase in 1080P resolution ratio, a 14.4% increase in media bitrate, and up to a 14.1% reduction in stalling ratio. In simulations under undershooting, shallow buffers, and network jitter, Camel outperforms existing congestion control algorithms, with up to 19.8% higher bitrate, 93.0% lower stalling ratio, and 23.9% improvement in bandwidth estimation accuracy.
Extinction curves contain key information on interstellar dust composition and size distribution, with the 2175 {\AA} bump being the most prominent feature. We analyze 20 sightlines toward M31 using HST/STIS UV spectroscopy combined with multi-band photometry to characterize this feature. The extinction curves show substantial diversity, from MW-like shapes to flatter profiles with $R_V$ reaching up to $\sim5.8$. The strength of the 2175 {\AA} feature varies widely, including two sightlines where the bump is essentially absent. The bump central wavelength spans a broader range than previously reported, while its width remains consistent with earlier studies. A moderate positive correlation is found between bump strength ($c_3$) and width ($\gamma$). We derive an average UV extinction curve toward M31 with $R_V \approx 3.53$. These results provide new constraints on dust properties and their spatial variations in this galaxy.
Compared with traditional infrared thermal imaging, polarimetric imaging provides additional polarization information, which effectively enhances object contours and image contrast, with broad application in both military and civilian domains. However, the traditional long-wave infrared polarimetric camera suffers from severe thermal noise, low sensitivity and limited detection accuracy. To address the aforementioned problems, a novel cooled LWIR polarimetric camera based on an achromatic polarization multiplexed germanium-based metalens array optical chip is reported in this paper, enabling high-precision division of focal plane linearly polarimetric imaging. The proposed system demonstrates high-precision linearly polarimetric imaging, with the metalens array achieving an average transmittance of 84.7% across the 8.4~11.6{\mu}m band and a polarization extinction ratio exceeding 10. The metasurface-based camera attains an average polarization reconstruction error below 0.981%, markedly surpassing state-of-the-art commercial LWIR polarimetric systems. Additionally, the new camera presents excellent polarimetric imaging capability for complex scenes. To the best of our knowledge, this represents the world's first LWIR polarimetric camera utilizing the metasurface optical chip with performance superior to commercial cameras, promoting the practical development of metasurface-integrated devices.
We investigate the $e^+e^-\to \Sigma\bar{\Sigma}$ and $e^+e^-\to \Lambda\bar{\Sigma}^0$ reactions within the extended vector meson dominance model. In addition to the ground state mesons $\rho$ and $\omega$, we consider the contributions of the excited states $\rho(3D)$, $\omega(3D)$, $\phi(3D)$, and $\rho(6D)$. It is found that the current experimental data on the $\Sigma$ electromagnetic form factors in timelike region can be well reproduced. And the $\phi(3D)$ resonance is essential to the near threshold enhancement of the cross section for the $e^+e^-\to \Sigma\bar{\Sigma}$ reaction. Furthermore, in the $e^+e^-\to \Lambda\bar{\Sigma}^0$ reaction, the $\rho(3D)$ is important to get a good fit for the experimental results.
We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions. It is the first on-policy approach that allows significantly more gradient updates than the number of energy evaluations and model samples, allowing us to scale to much larger problem settings than previously explored by similar methods. Our framework is theoretically grounded in stochastic optimal control and shares the same theoretical guarantees as Adjoint Matching, being able to train without the need for corrective measures that push samples towards the target distribution. We show how to incorporate key symmetries, as well as periodic boundary conditions, for modeling molecules in both cartesian and torsional coordinates. We demonstrate the effectiveness of our approach through extensive experiments on classical energy functions, and further scale up to neural network-based energy models where we perform amortized conformer generation across many molecular systems. To encourage further research in developing highly scalable sampling methods, we plan to open source these challenging benchmarks, where successful methods can directly impact progress in computational chemistry.
In this paper, we present a unique multi-functional super-resolution instrument, the SuperNANO system, which integrates real-time super-resolution imaging with direct laser nanofabrication capabilities. Central to the func-tionality of the SuperNANO system is its capacity for simultaneous nanoimaging and nanopatterning, enabling the creation of anti-counterfeiting markings and precision cutting with exceptional accuracy. The SuperNANO system, featuring a unibody superlens objective, achieves a resolution ranging from 50 to 320 nm. We showcase the instrument's versatility through its application in generating high-security anti-counterfeiting features on an aluminum film. These 'invisible' security features, which are nanoscale in dimension, can be crafted with arbi-trary shapes at designated locations. Moreover, the system's precision is further evidenced by its ability to cut silver nanowires to a minimum width of 50 nm. The integrated imaging and fabricating functions of the Su-perNANO make it a pivotal tool for a variety of applications, including nano trapping, sensing, cutting, weld-ing, drilling, signal enhancement, detection, and nano laser treatment.
The total cross sections of the process $e^+ e^-\to \Lambda_c^+ \bar{\Lambda}_c^-$ close to the threshold are calculated within the vector meson dominance model. It is found that the theoretical results can describe the current experimental measurements. In particular, the results for the angular distribution parameters about the differential cross section are consistent with the experiments from BESIII Collaboration. In addition, the relative phase $\Delta \Phi$ of the electromagnetic form factors was given, and the spin polarization of $\Lambda_c^+$ is predicted at center-mass energy $4.7 \ \rm GeV$. It is hopeful to provide a new perspective on the characteristics of the charmed baryon $\Lambda_c^+$.
Active learning is considered a viable solution to alleviate the contradiction between the high dependency of deep learning-based segmentation methods on annotated data and the expensive pixel-level annotation cost of medical images. However, most existing methods suffer from unreliable uncertainty assessment and the struggle to balance diversity and informativeness, leading to poor performance in segmentation tasks. In response, we propose an efficient Predictive Accuracy-based Active Learning (PAAL) method for medical image segmentation, first introducing predictive accuracy to define uncertainty. Specifically, PAAL mainly consists of an Accuracy Predictor (AP) and a Weighted Polling Strategy (WPS). The former is an attached learnable module that can accurately predict the segmentation accuracy of unlabeled samples relative to the target model with the predicted posterior probability. The latter provides an efficient hybrid querying scheme by combining predicted accuracy and feature representation, aiming to ensure the uncertainty and diversity of the acquired samples. Extensive experiment results on multiple datasets demonstrate the superiority of PAAL. PAAL achieves comparable accuracy to fully annotated data while reducing annotation costs by approximately 50% to 80%, showcasing significant potential in clinical applications. The code is available at https://github.com/shijun18/PAAL-MedSeg.
Within the extended vector meson dominance model, we investigate the $e^+ e^- \to \Lambda^+_c \bar{\Lambda}^-_c$ reaction and the electromagnetic form factors of the charmed baryon $\Lambda_c^+$. The model parameters are determined by fitting them to the cross sections of the process $e^+e^-\rightarrow \Lambda_c^+ \bar{\Lambda}_c^-$ and the magnetic form factor $|G_M|$ of $\Lambda^+_c$. By considering four charmoniumlike states, called $\psi(4500)$, $\psi(4660)$, $\psi(4790)$, and $\psi(4900)$, we can well describe the current data on the $e^+ e^- \to \Lambda^+_c \bar{\Lambda}^-_c$ reaction from the reaction threshold up to $4.96 \ \mathrm{GeV}$. In addition to the total cross sections and $|G_M|$, the ratio $|G_E/G_M|$ and effective form factor $|G_{\mathrm{eff}}|$ for $\Lambda^+_c$ are also calculated, and found that these calculations are consistent with the experimental data. Within the fitted model parameters, we have also estimated the charge radius of the charmed $\Lambda_c^+$ baryon.
We investigate the nonmonotonic behavior observed in the time-like nucleon electromagnetic form factors. Using a phenomenological extending vector meson dominance model, where the ground states $\rho$ and $\omega$ and their excited states $\rho(2D)$, $\omega(3D)$, and $\omega(5S)$ are taken into account, we have successfully reproduced the cross sections of $e^+ e^- \to p \bar{p}$ and $e^+ e^- \to n \bar{n}$ reactions. Furthermore, we have derived the nucleon electromagnetic form factors in the time-like region, and it is found that the so-called periodic behaviour of the nucleon effective form factors is not confirmed. However, there are indeed nonmonotonic structures in the line shape of nucleon effective form factors, which can be naturally reproduced by considering the contributions from the low-lying excited vector states.
Large Language Models (LLMs) excel in diverse areas, yet struggle with complex scientific reasoning, especially in the field of chemistry. Different from the simple chemistry tasks (e.g., molecule classification) addressed in previous studies, complex chemistry problems require not only vast knowledge and precise calculation, but also compositional reasoning about rich dynamic interactions of different concepts (e.g., temperature changes). Our study shows that even advanced LLMs, like GPT-4, can fail easily in different ways. Interestingly, the errors often stem not from a lack of domain knowledge within the LLMs, but rather from the absence of an effective reasoning structure that guides the LLMs to elicit the right knowledge, incorporate the knowledge in step-by-step reasoning, and iteratively refine results for further improved quality. On this basis, we introduce StructChem, a simple yet effective prompting strategy that offers the desired guidance and substantially boosts the LLMs' chemical reasoning capability. Testing across four chemistry areas -- quantum chemistry, mechanics, physical chemistry, and kinetics -- StructChem substantially enhances GPT-4's performance, with up to 30\% peak improvement. Our analysis also underscores the unique difficulties of precise grounded reasoning in science with LLMs, highlighting a need for more research in this area. Code is available at \url{https://github.com/ozyyshr/StructChem}.
Electricity prices determined by economic dispatch that do not consider fixed costs may lead to significant uplift payments. However, when fixed costs are included, prices become non-monotonic with respect to demand, which can adversely impact market transparency. To overcome this issue, convex hull (CH) pricing has been introduced for unit commitment with fixed costs. Several CH pricing methods have been presented, and a feasible cost has been used as a quality measure for the CH price. However, obtaining a feasible cost requires a computationally intensive optimization procedure, and the associated duality gap may not provide an accurate quality measure. This paper presents a new approach for quantifying the quality of the CH price by establishing an upper bound on the optimal dual value. The proposed approach uses Surrogate Lagrangian Relaxation (SLR) to efficiently obtain near-optimal CH prices, while the upper bound decreases rapidly due to the convergence of SLR. Testing results on the IEEE 118-bus system demonstrate that the novel quality measure is more accurate than the measure provided by a feasible cost, indicating the high quality of the upper bound and the efficiency of SLR.
We propose a phenomenological extended vector meson dominance model for the baryon electromagnetic structure, and it is found that the current experimental data on the $\Sigma$ and $\Xi$ electromagnetic form factors in the time-like region can be well described. Meanwhile, we can also reproduce the ratios of the total cross sections of reactions $e^+e^- \to \Sigma^+\bar{\Sigma}^-$, $\Sigma^0\bar{\Sigma}^0$, and $\Sigma^-\bar{\Sigma}^+$, which are $9.7 \pm 1.3 : 3.3 \pm 0.7 :1$ at center-of-mass energies from $2.3864$ to $3.02$ GeV. We also analytically continue the expression of the form factors to space-like region and estimate the charge radii of the $\Sigma$ and $\Xi$ hyperons. The result for the $\Sigma^-$ is in agreement with the experimental date.
Photonic hook (PH) is a new type of artificial self-bending beam focused by a dielectric particle-lens with a curved waist smaller than the wavelength, which has the potential to revolutionize mesoscale photonics in many applications, e.g., optical trapping, signal switching, imaging, etc. In this paper, we discover a new mechanism that the highly curved PHs can be realised by the light interaction with the fully or partially metal-coated microchannels. The generated W-shaped and J-shaped PHs have bending angles exceeding 80-degree. Compared to other PH setups, the proposed design has a larger range to flexibly control the bending angle through the coating process and can be easily integrated with the established microfluidic systems.