Showing 1–50 of 665 results for author: Chan, J

Sublime Transfer Printing of Three-Dimensional Nanostructure Ensembles

Authors: Lei Chen, Hao Wang, Wang Zhang, Fu Fan, Peng Liu, Xiaoxue Bi, John You En Chan, Cheng-Feng Pan, Bochang Wu, Zhengchao Liu, Rou Yun Teo, Hongtao Wang, Huigao Duan, Joel K. W. Yang

Abstract: High-resolution three-dimensional (3D) nanostructures for visible-light photon manipulation provide unique and bespoke capabilities in optics and photonics. However subwavelength nanofabrication and reliable ensemble manipulation of the 3D prints onto arbitrary substrates remain challenging. Here, we introduce sublime transfer strategy tailored for transfer printing ensembles of delicate 3D printe… ▽ More High-resolution three-dimensional (3D) nanostructures for visible-light photon manipulation provide unique and bespoke capabilities in optics and photonics. However subwavelength nanofabrication and reliable ensemble manipulation of the 3D prints onto arbitrary substrates remain challenging. Here, we introduce sublime transfer strategy tailored for transfer printing ensembles of delicate 3D printed nanostructures. This strategy enables conformal, damage-free integration of arrays of 3D structures on diverse substrates. Naphthalene acts as a transient stamp to encapsulate the structures during transfer and placement. We rely on the low sublimation temperature of naphthalene to release the structures reliably with nearly zero stress, preventing mechanical damage and positional misalignment. This approach is broadly applicable to integrate diverse nanostructures and photonic devices onto various substrates, and enabling inorganic architectures through ensemble uniform post-processing, including 2.5D photonic crystals on flexible PDMS, diffractive optical elements on curved lenses, spiral phase plates on CMOS chips, multilayer achromatic metalens on optical fiber facet, as well as 3D glass photonic crystals and optical topological resonators on anti-stiction quartz. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Characterizing Rhetorical Misalignment in Decision-Making with Language Models

Authors: Zirui Cheng, Joey Chan, Simo Du, Chenhao Tan, Yue Guo, Hao Peng

Abstract: Human decision-making is often shaped by a range of well-documented cognitive biases. As large language models (LLMs) become increasingly integrated into high-stakes human-AI decision-making, it is important to understand whether their outputs can amplify potential biases, how this influences human decisions, and crucially, whether it can lead to harmful consequences. In this work, we develop a de… ▽ More Human decision-making is often shaped by a range of well-documented cognitive biases. As large language models (LLMs) become increasingly integrated into high-stakes human-AI decision-making, it is important to understand whether their outputs can amplify potential biases, how this influences human decisions, and crucially, whether it can lead to harmful consequences. In this work, we develop a decision-theoretic framework to study rhetorical misalignment, a failure mode where an LLM uses rhetorically inappropriate forms of presentation for a given decision context, thereby inducing suboptimal human decisions. We empirically investigate this phenomenon through a human-subject experiment in realistic clinical decision-making using a dataset curated from the United States Medical Licensing Examination. By measuring how LLM-generated information affects decisions, we observe that LLMs induce an average 2.81% rate of harmful decision flips across different models, where clinician participants change from a correct to an incorrect answer. Rationales reported by participants provide evidence that these revisions are closely related to the language used by LLMs that may induce different types of cognitive biases, including anchoring, authority bias, and loss aversion. To enable scalable evaluation, we instantiate our theoretical framework using decision-makers simulated by LLMs to computationally measure rhetorical misalignment. Our findings reveal a safety concern previously unrecognized in high-stakes domains: a model can be factually aligned yet still induce harm through its rhetorical presentation. △ Less

Submitted 23 July, 2026; originally announced August 2026.

Nodal discontinuous Galerkin methods for non-ideal equations of state: pressure equilibrium preservation and entropy correction

Authors: Jesse CHan, Hendrik Ranocha, Raymond Park, Joshua Lampert, Eric Ching, Ayaboe Edoh

Abstract: Structure-preserving discontinuous Galerkin (DG) methods typically improve the robustness of high order simulations of real fluids. In addition to conservation, key structures include the preservation of pressure equilibrium and satisfaction of at least one entropy inequality. In this work, we investigate conservative discretizations using exactly pressure equilibrium conserving (EPEC) and approxi… ▽ More Structure-preserving discontinuous Galerkin (DG) methods typically improve the robustness of high order simulations of real fluids. In addition to conservation, key structures include the preservation of pressure equilibrium and satisfaction of at least one entropy inequality. In this work, we investigate conservative discretizations using exactly pressure equilibrium conserving (EPEC) and approximately pressure equilibrium conserving (APEC) flux differencing DG formulations, as well as entropy stable formulations through the use of minimally dissipative corrections for non-ideal equations of state (EOS). We introduce an analysis of EPEC schemes and a new procedure for designing such fluxes based on a generalization of Tadmor's shuffle condition. We also analyze APEC DG schemes and show that the incorporation of dissipative interface penalization terms does not significantly increase pressure equilibrium errors, especially at higher orders of approximation. Finally, we observe that when combined with APEC flux differencing formulations, entropy correction improves robustness for under-resolved solutions and long-time simulations. △ Less

Submitted 14 August, 2026; originally announced August 2026.

LIGO A$^\sharp$: Detector Design and Science Prospects Beyond A+

Authors: L. Sun, K. Kuns, B. J. J. Slagmolen, P. Fritschel, P. Schmidt, B. T. Lantz, S. S. Y. Chua, Divyajyoti, S. W. Ballmer, M. A. Barton, A. V. Cumming, K. L. Dooley, J. C. Driggers, A. Effler, M. Evans, B. Farr, G. González, N. Lu, D. J. Ottaway, C. Palomba, O. J. Piccinni, G. Pratten, S. Raja, A. P. Subhash, P. J. Sutton , et al. (1131 additional authors not shown)

Abstract: We present the LIGO A$^\sharp$ detector concept, an upgrade for the LIGO observatories based on room-temperature interferometers beyond the fifth observing run (O5). Building on the A+ sensitivity, A$^\sharp$ targets broadband sensitivity improvements through heavier test masses, improved suspensions and seismic isolation, increased arm-cavity power, enhanced frequency-dependent squeezing, reduced… ▽ More We present the LIGO A$^\sharp$ detector concept, an upgrade for the LIGO observatories based on room-temperature interferometers beyond the fifth observing run (O5). Building on the A+ sensitivity, A$^\sharp$ targets broadband sensitivity improvements through heavier test masses, improved suspensions and seismic isolation, increased arm-cavity power, enhanced frequency-dependent squeezing, reduced coating thermal noise considering two scenarios, and improved control of mechanical motion and optical modes. We describe the principal design choices, projected noise performance, and corresponding astrophysical prospects. LIGO A$^\sharp$ substantially increases compact-binary detection rates, strengthens population inference, and improves both early-warning times and localization for binary neutron star mergers. The improved sensitivity enables more detailed studies of compact-binary coalescences, including higher-order multipoles, intermediate-mass black holes, remnant black hole ringdown, and the neutron star equation of state. It also broadens the discovery potential for new gravitational-wave sources such as continuous waves and bursts, should enable detection of the stochastic background from compact binary mergers if it remains undetected after O5, and strengthens the role of gravitational-wave detectors as probes of fundamental physics. We discuss key technical challenges and the role of A$^\sharp$ as both a major scientific upgrade for the 2030s and a technology pathfinder for next-generation gravitational-wave observatories, such as Cosmic Explorer. △ Less

Submitted 12 August, 2026; originally announced August 2026.

Comments: 78 pages, 22 figures

Report number: LIGO-P2600307

Constraints on ultralight bosons from merging binary and remnant black holes observed during the second and third parts of the fourth LIGO-Virgo-KAGRA observing run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1786 additional authors not shown)

Abstract: We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary co… ▽ More We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary coalescences that produced GW250114 and GW250207. We find no evidence for such signals from either target. Estimating our search sensitivity at a threshold corresponding to a 1% false alarm probability, we thus disfavor vector boson masses in the range of $[2.80, 3.95]\times 10^{-13}$ eV with greater than 90% confidence. In addition, we derive constraints on ultralight scalar and vector bosons from the inferred high spins of the constituent black holes in three binaries, using events GW240515, GW241113, and GW241225_08. The excluded mass ranges in this approach depend on the assumed black-hole ages. At $10^5$ years, corresponding to typical dynamically formed binaries, we exclude scalar and vector bosons in the ranges $[1.39, 6.94]\times 10^{-13}$ eV and $[0.32, 14.4]\times 10^{-13}$ eV at 90% confidence, respectively. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: 27 pages (12 pages author list, 15 pages main paper), 5 figures

Report number: LIGO-P2600218

BlockPython: A Process-Aware Agent-Supported Platform for the Transition from Block-Based to Python Programming

Authors: Jesse Yusuf Chan, Haoming Wang, Mingwei Xu, Xianlong Xu

Abstract: The transition from block-based to text-based programming requires learners to convert visible program structures into abstract textual expressions, which may create a cognitive gap between understanding computational concepts and expressing them in Python syntax. To support this transition, we designed and implemented BlockPython. The platform centers on bidirectional translation between blocks a… ▽ More The transition from block-based to text-based programming requires learners to convert visible program structures into abstract textual expressions, which may create a cognitive gap between understanding computational concepts and expressing them in Python syntax. To support this transition, we designed and implemented BlockPython. The platform centers on bidirectional translation between blocks and Python and guides learners through four stages: Task Decomposition, Block-Based Practice, Code Challenge, and Extended Interaction. Across these stages, learners progressively establish connections among program structure, runtime behavior, and textual code. During learning, the platform continuously collects process evidence, including block artifacts, code versions, run outcomes, use of support, and dialogue. Deterministic diagnosis, program visualization, and the learning assistant use this evidence to identify different difficulties in computational understanding and Python expression. The rule-based system is responsible for program execution, objective evaluation, and stage control, while the learning assistant uses verified evidence to provide explanations, prompts, and guiding questions. This report describes the design rationale, learning workflow, and process-aware support mechanisms of BlockPython and provides a system-design reference for supporting the transition from block-based to text-based programming and for analyzing learning processes. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: AIED 2026 Interactive Event Track

ePIC Early Science Report

Authors: D. Abbott, N. Abdelrahman, S. Abhijit, I. Abualrob, R. B. Achari, J. Adam, L. Adamczyk, K. Adkins, A. Affolder, K. Agarwal, J. Agarwala, N. Agrawal, C. A. Aidala, W. Akers, A. Al-bataineh, S. N. Alam, M. Alekseev, P. R. Altieri, J. -S. Alvarado Gallenao, S. B. L. Amar, R. Ammendola, I. Amos Cali, G. An, D. Anderson, E. Anderssen , et al. (774 additional authors not shown)

Abstract: This Early Science Report from the ePIC Collaboration outlines the compelling physics program achievable during the first years of operation of the Electron-Ion Collider (EIC), prior to the establishment of the full design luminosity and energy range. The analyses are based on realistic early-running beam configurations and detailed Geant4 ePIC detector simulations, hit digitization and data recon… ▽ More This Early Science Report from the ePIC Collaboration outlines the compelling physics program achievable during the first years of operation of the Electron-Ion Collider (EIC), prior to the establishment of the full design luminosity and energy range. The analyses are based on realistic early-running beam configurations and detailed Geant4 ePIC detector simulations, hit digitization and data reconstruction. The projected studies from the physics working groups of ePIC span inclusive, semi-inclusive, exclusive, diffractive and tagging, as well as jet and heavy flavor measurements in both electron-proton and electron-ion collisions. Even before the collider reaches its full design performance, these measurements will constrain parton distribution functions in nucleons and nuclei, access transverse-momentum-dependent and spin-dependent observables, probe gluon dynamics in nuclei, and initiate a program of imaging of quarks and gluons. Each measurement is directly connected to the core science pillars of the EIC, identified in the 2018 report by the National Academy of Sciences: understanding the origin of the nucleon mass, unraveling the spin structure of the nucleon, and exploring the emergent properties of dense gluonic matter. The results presented here provide examples that demonstrate that the early years of EIC running with ePIC will deliver novel world-leading insights into Quantum Chromodynamics. In addition, the early science program will establish measurement and analysis methodologies that will pave the way to the subsequent full EIC physics program. △ Less

Submitted 5 August, 2026; originally announced August 2026.

Report number: epic-AN-AC-2026-004

Estimating Social Effects with Randomized and Observational Network Data

Authors: TszKin Julian Chan, Juan Estrada, Kim Huynh, David Jacho-Chavez, Chungsang Tom Lam, Leonardo Sanchez-Aragon

Abstract: This paper introduces an innovative approach to identifying and estimating the parameters of interest in the widely recognized linear-in-means regression model under conditions where the initial randomization of peers determines the observed network. We assert that peers who are initially randomized do not produce social effects. However, after randomization, agents can endogenously develop signif… ▽ More This paper introduces an innovative approach to identifying and estimating the parameters of interest in the widely recognized linear-in-means regression model under conditions where the initial randomization of peers determines the observed network. We assert that peers who are initially randomized do not produce social effects. However, after randomization, agents can endogenously develop significant connections that potentially generate peer influences. We present a moment condition that compiles local heterogeneous identifying information for all agents within the population. Under the assumption of $ψ$-dependence in the endogenous network space, we propose a Generalized Method of Moments (GMM) estimator, which is proven to be consistent, asymptotically normally distributed, and straightforward to implement using commonly available statistical software due to its closed-form expression. Monte Carlo simulations demonstrate the GMM estimator's strong small-sample performance. An empirical analysis utilizing data from Hong Kong high school students reveals substantial positive spillover effects on math test scores among study partners in our sample, provided that their seatmates were exogenously assigned by their teachers. △ Less

Submitted 2 August, 2026; originally announced August 2026.

Comments: 42 pages (main manuscript), 34 pages (supplemental materials)

Journal ref: Journal of Econometric Methods, Volume 13, Number 2, Pages 205-224, October 2024

The beamformed trigger of RNO-G: its design and in-field performance

Authors: RNO-G Collaboration, :, S. Agarwal, J. A. Aguilar, N. Alden, S. Ali, P. Allison, M. Betts, D. Besson, A. Bishop, O. Botner, S. Bouma, S. Buitink, R. Camphyn, J. Chan, S. Chiche, B. A. Clark, K. Couberly, D. Dakroub, K. D. de Vries, C. Deaconu, P. Giri, C. Glaser, H. Gui, A. Hallgren , et al. (55 additional authors not shown)

Abstract: The Radio Neutrino Observatory in Greenland (RNO-G) is a neutrino detector under construction at Summit Station, with 8 out of a planned 35 stations currently deployed. We have designed and deployed a new phased array (PA) trigger based on delay-and-sum beamforming and power integration. This trigger improves detector performance by suppressing thermal noise and better targeting neutrino-induced A… ▽ More The Radio Neutrino Observatory in Greenland (RNO-G) is a neutrino detector under construction at Summit Station, with 8 out of a planned 35 stations currently deployed. We have designed and deployed a new phased array (PA) trigger based on delay-and-sum beamforming and power integration. This trigger improves detector performance by suppressing thermal noise and better targeting neutrino-induced Askaryan signals. The new PA trigger has been deployed since the 2025 season. The trigger performance has been characterized using test pulses and calibration pulsers both in the lab and in-situ, and we find across these tests a 25% average reduction in the signal-to-noise ratio (SNR) needed to trigger on signals. Simulations are shown to be representative of the detector, and simulated trigger efficiencies are within 10% of measured data. Following the in-situ trigger validation, we use data-driven trigger performance to inform simulations of the detector effective volumes. The PA trigger increases our effective volume significantly, by over a factor of 2 below 0.1 EeV and at least a factor of 1.3 at the highest energies of 100 EeV. △ Less

Submitted 27 July, 2026; originally announced July 2026.

Comments: 27 pages, 17 figures, to be submitted to JINST

GWTC-5.0: Tests of General Relativity

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1800 additional authors not shown)

Abstract: The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b).… ▽ More The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b). We restrict our analysis to the confident signals, henceforth called events, observed by at least two detectors that have estimated false alarm rates $\le 10^{-3} \ \rm{yr}^{-1}$. These include 72 events from O4b and five events from the first part of the fourth observing run that are now analyzed due to their increased significance from updated search results, bringing the total number of events for tests of GR in the cumulative GWTC to 168. After subtracting the best-fit waveforms, we find the residuals are consistent with detector noise for all events considered. We also find no strong evidence for additional polarizations beyond those predicted by GR. We perform tests of GW generation, improving the constraints on deviations from the GR post-Newtonian coefficients by factors of 1.2-2.6. Finally, we find overall consistency of the remnants with GR using both time- and frequency-domain methods. For GW240621_195059, postmerger data are consistent with the dominant quadrupolar ($\ell=|m|=2$) mode of a Kerr black hole and its first overtone, with spurious high-frequency content preventing a spectroscopic constraint of GR. In the frequency-domain ringdown analysis, the GR prediction lies in the tails of the combined results, possibly due to the limited catalog size. However, the combined results indicate improved consistency with GR over GWTC-4.0, owing to the contribution of GW250114 with a network matched-filter signal-to-noise ratio of 76.9. Overall, we find no evidence for physics beyond GR. △ Less

Submitted 21 July, 2026; originally announced July 2026.

Comments: 44 pages and 10 figures

Report number: LIGO-P2500781

Candidate Attended Dialogue State Tracking Using BERT

Authors: Junyuan Zheng, Onkar Salvi, John Chan

Abstract: Dialogue state tracking (DST) is one of the core components in task-oriented dialogue systems. At each turn in a conversation, DST estimates the user belief or dialogue state, which is used as input for downstream modules to predict system actions and generate responses. The increasingly popular dialogue system applications like Google Assistant, Siri and Alexa need to support a large number of se… ▽ More Dialogue state tracking (DST) is one of the core components in task-oriented dialogue systems. At each turn in a conversation, DST estimates the user belief or dialogue state, which is used as input for downstream modules to predict system actions and generate responses. The increasingly popular dialogue system applications like Google Assistant, Siri and Alexa need to support a large number of services and APIs, resulting in growing attention to the scalability of such systems. Especially for some domains with little or no training data, the capability of transferring existing knowledge of other domains is highly desired. In this paper, we present a novel scalable framework for multi-domain dialogue state tracking. The proposed system leverages the pretrained BERT model to achieve zero-shot generalization, making it easy to quickly adapt to new domains without additional training. The performance of our model is evaluated on recently released schema-based dialogue (SGD) dataset, showing significant improvement compared to previous baseline. △ Less

Submitted 17 July, 2026; originally announced July 2026.

Comments: 7 pages, 4 figures. Presented at the DSTC8 workshop, AAAI-20 (poster session)

ACM Class: I.2.7; I.2.6

The self-organized vacancy order in Pr$_9$Ge$_{16}$

Authors: Jayashani S. T. Wickramasinghe, Melissa G. Anderson, Kelci Graville, Gregory T. McCandless, Zachary J. Morgan, Brianna R. Billingsley, Tai Kong, Hyunsoo Kim, Aleksandr V. Chernatynskiy, Simon G. Mitchell, Liang Wu, Julia Y. Chan, Feng Ye, Halyna Hodovanets

Abstract: In this work, we report the discovery of a new crystal structure on the Ge-rich side of the Pr-Ge binary phase diagram. Using a high-temperature flux technique, we grew single crystals of $Pr_9Ge_{16}$, which adopt a previously unreported orthorhombic $Fdd$2 structure type featuring ordered Ge vacancies. We present the anisotropic magnetic properties and identify the crystallographic $b$ axis perp… ▽ More In this work, we report the discovery of a new crystal structure on the Ge-rich side of the Pr-Ge binary phase diagram. Using a high-temperature flux technique, we grew single crystals of $Pr_9Ge_{16}$, which adopt a previously unreported orthorhombic $Fdd$2 structure type featuring ordered Ge vacancies. We present the anisotropic magnetic properties and identify the crystallographic $b$ axis perpendicular to the crystal plane as the magnetic easy axis. Temperature-dependent resistivity measurements reveal metallic behavior with a distinct anomaly at $T_{\mathrm{C}}$ = 14.3 K. Hall resistivity data indicate that electron-like carriers dominate, with a carrier concentration on the order of $10^{27}~\mathrm{m}^{-3}$. The magnetic order is readily suppressed by a magnetic field of approximately 0.4 T applied along the easy $b$ axis. △ Less

Submitted 7 August, 2026; v1 submitted 14 July, 2026; originally announced July 2026.

Perturber-Driven Dynamics of Supermassive Black Hole Binaries in Galaxy Merger

Authors: Julian Chan, Alessia Gualandris, Walter Dehnen, Justin I. Read

Abstract: The orbital eccentricity of massive black hole binaries (MBHBs) at binary formation shapes the stochastic gravitational-wave background (GWB) detectable by pulsar timing arrays (PTAs). Previous $N$-body simulations show large run-to-run scatter in this quantity, dominated by Poisson noise, raising the question of whether physical substructure adds genuine astrophysical stochasticity. We test this… ▽ More The orbital eccentricity of massive black hole binaries (MBHBs) at binary formation shapes the stochastic gravitational-wave background (GWB) detectable by pulsar timing arrays (PTAs). Previous $N$-body simulations show large run-to-run scatter in this quantity, dominated by Poisson noise, raising the question of whether physical substructure adds genuine astrophysical stochasticity. We test this with high-resolution re-simulations of a major merger from IllustrisTNG100-1, evolved with the Griffin $N$-body code. A no-perturber control is compared with two matched suites in which $f_{\mathrm{target}}=0.1$ of the primary bulge mass is redistributed into equal-mass perturbers of $10^7,M_\odot$ ($μ_{\mathrm{p}}\approx3.2\times10^{-3}$) and $10^8,M_\odot$ ($μ_{\mathrm{p}}\approx3.2\times10^{-2}$), with four realisations per scenario. The control gives $σ_e\approx0.11$, consistent with the Poisson noise floor at this resolution. The $10^7,M_\odot$ case gives $σ_e\approx0.115$, indistinguishable from the control, whereas the $10^8,M_\odot$ case gives $σ_e\approx0.26$, a factor of $2.4$ above the floor, although statistically marginal given only four realisations. This excess scatter coincides with larger event-aligned residuals in orbital energy and angular momentum and stronger torque spikes, consistent with near-impulsive perturber--MBHB encounters. In binary--single scattering theory, the transition is set by the perturber--MBHB mass ratio $μ_{\mathrm{p}}$: the $10^7,M_\odot$ case remains diffusive, whereas the $10^8,M_\odot$ case approaches the near-impulsive regime. Because the expected perturber population in massive ellipticals lies mostly below this regime, perturber-driven eccentricity randomisation is unlikely to affect GWB-relevant MBHB mergers. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Comments: Accepted for publication in Monthly Notices of the Royal Astronomical Society (MNRAS) on 13 July 2026

Sub-Torque-Balance Upper Limits on Continuous Gravitational Waves from Scorpius X-1

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, the Precision Ephemerides for Gravitational-Wave Searches, Project, :, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend , et al. (1814 additional authors not shown)

Abstract: We present the results of a search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. By applying the resampling version of the cross-correlation pipeline to search for signal frequencies $f_0$ between $25$ and $200\un{Hz}$ (corresponding to neutron star spin frequencies of $12.5$ to… ▽ More We present the results of a search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. By applying the resampling version of the cross-correlation pipeline to search for signal frequencies $f_0$ between $25$ and $200\un{Hz}$ (corresponding to neutron star spin frequencies of $12.5$ to $100\un{Hz}$ for GW due to triaxiality, or $\sim15-20$ to $\sim120-150\un{Hz}$ for GW due to $r$-modes), we set upper limits below the standard torque balance level, independent of neutron star spin inclination, for $50\un{Hz}\lesssim f_0\lesssim200\un{Hz}$. While uncertainties in the modelling of torque and equation of state limit the strength of our inference, our results nonetheless argue against torque balance in this spin range for a neutron star described by a hadronic equation of state. The most sensitive upper limits on the gravitational wave amplitude $h_0$, at the upper end of the frequency band searched, approach $5\times10^{-26}$ marginalized over inclination angle and $2\times10^{-26}$ assuming the most favorable inclination. The marginalized upper limits correspond to a sensitivity depth of $70-75\un{Hz}^{-1/2}$, improving sensitivity considerably over previous searches. Expressed as constraints on the triaxial deformation of the neutron star, the limits correspond to an ellipticity of $3\times10^{-5}$ if the GW frequency $f_0$ is $75\un{Hz}$ and $3\times10^{-6}$ if $f_0=200\un{Hz}$, approaching deformations which could be supported by ordinary nuclear matter. Outliers from the search were ruled out as potential signals by a combination of hierarchical followup and analysis of additional data from later in the observing run. △ Less

Submitted 8 July, 2026; originally announced July 2026.

Comments: 30 pages, 7 figures

Report number: LIGO-P2500260-v10

Why does AI unlock new possibilities in STEM education? A Bibliometric Analysis of Trends and Future Agenda

Authors: Jesse Yusuf Chan, Mengyao Chen, Yang Hong, Ziyun Song, Haoming Wang, Xianlong Xu

Abstract: STEM education faces challenges in personalization and interdisciplinary integration. AI technology has brought new possibilities, but the mechanisms by which AI reshapes the STEM education ecosystem require systematic investigation. This study employs bibliometric methods to analyze 242 publications from 2015-2025, constructing knowledge maps to reveal the evolutionary trajectory. The findings sh… ▽ More STEM education faces challenges in personalization and interdisciplinary integration. AI technology has brought new possibilities, but the mechanisms by which AI reshapes the STEM education ecosystem require systematic investigation. This study employs bibliometric methods to analyze 242 publications from 2015-2025, constructing knowledge maps to reveal the evolutionary trajectory. The findings show that the field has transformed from intelligent tutoring systems to inquiry-based learning and computational thinking cultivation driven by LLMs. AI's key contribution lies in providing intelligent scaffolding that lowers the threshold for understanding knowledge. In this sense, AI is a core driving force promoting its shift from knowledge transmission to capability development. △ Less

Submitted 6 August, 2026; v1 submitted 10 June, 2026; originally announced July 2026.

Comments: Accepted by ISLS26 conference

Efficient classical simulation of two-dimensional long-range systems: Rydberg arrays and beyond

Authors: Jia-Lin Chan, Tao Xiang, Yantao Wu

Abstract: In variational Monte Carlo (VMC) calculations of $N$-site quantum systems with arbitrary all-to-all two-body interactions, evaluating the local energy generally costs $O(N^3)$. We introduce a new framework that reduces this cost to $O(N)$ for tensor network states, capable of scalable and accurate computation of real-time dynamics and ground states. As a result, we obtain accurate simulations of t… ▽ More In variational Monte Carlo (VMC) calculations of $N$-site quantum systems with arbitrary all-to-all two-body interactions, evaluating the local energy generally costs $O(N^3)$. We introduce a new framework that reduces this cost to $O(N)$ for tensor network states, capable of scalable and accurate computation of real-time dynamics and ground states. As a result, we obtain accurate simulations of the adiabatic real-time protocol of a $10\times10$ dipolar XY model realized in a Rydberg simulator [C. Chen et al., Nature 616, 691 (2023)], which was previously beyond the reach of classical simulation. Going beyond quantum experiments, we also directly perform ground state VMC to compare with the adiabatic state preparation. Our work demonstrates tensor network VMC as a powerful classical simulator for long-range quantum platforms such as Rydberg and ion-trap simulators, which are currently in urgent need of scalable classical benchmarking tools. As a separate technical contribution, we resolve the pathology of evolving from product states within of tensor network VMC. △ Less

Submitted 6 July, 2026; originally announced July 2026.

Gemma 4 Technical Report

Authors: Gemma Team, Sherif El Abd, Vaibhav Aggarwal, Robin Algayres, Alek Andreev, Olivier Bachem, Ian Ballantyne, Cormac Brick, Victor Cărbune, Michelle Casbon, Mayank Chaturvedi, Aditya Chawla, Victor Cotruta, Alice Coucke, Phil Culliton, Robert Dadashi, Lucas Dixon, Mohamed Elhawaty, Utku Evci, Clément Farabet, Johan Ferret, Filippo Galgani, Sertan Girgin, Jean-Bastien Grill, Maarten Grootendorst , et al. (298 additional authors not shown)

Abstract: We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parameters. Alongside improved vision and audio encoders for all model sizes, we propose a unified, encoder-free architecture… ▽ More We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parameters. Alongside improved vision and audio encoders for all model sizes, we propose a unified, encoder-free architecture for our 12B model, which ingests raw audio and image patches. Furthermore, we integrate a thinking mode, enabling Gemma models to generate reasoning traces prior to responding. We improve inference speed, memory, and compute efficiency, as well as long-context abilities through critical design choices. Gemma 4 establishes a leap in performance across STEM, multimodal, and long-context benchmarks, and rivals larger, frontier open models in human-rated tasks. △ Less

Submitted 24 July, 2026; v1 submitted 2 July, 2026; originally announced July 2026.

Comments: 17 pages, 2 figures, technical report, updated

High-Redshift Signatures from the Cosmic Dawn and the Epoch of Reionization

Authors: Rennan Barkana, Oliver Basquette, Ankita Bera, Jennifer Yik Ham Chan, Pravabati Chingangbam, Hector Afonso G. Cruz, Saswata Dasgupta, Kanan K. Datta, Anastasia Fialkov, Sambit K. Giri, Qin Han, Ilian T. Iliev, Bohua Li, Teppei Minoda, Shikhar Mittal, Julian B. Muñoz, Suvedha Suresh Naik, Janakee Raste, Aurel Schneider, Sudipta Sikder, Kinwah Wu, Yidong Xu, Bin Yue, Meng Zhang, Meng-Lin Zhao

Abstract: In this chapter, we provide a comprehensive overview of the astrophysical and cosmological processes that shape the 21-cm signal during Cosmic Dawn and the Epoch of Reionization. We investigate both standard and exotic signatures potentially observable with SKA-Low. Standard signatures are those expected within the $Λ$CDM framework, including contributions from the first stars, galaxies, and black… ▽ More In this chapter, we provide a comprehensive overview of the astrophysical and cosmological processes that shape the 21-cm signal during Cosmic Dawn and the Epoch of Reionization. We investigate both standard and exotic signatures potentially observable with SKA-Low. Standard signatures are those expected within the $Λ$CDM framework, including contributions from the first stars, galaxies, and black holes. Exotic signatures are more speculative indicating new physics, such as primordial black holes, modifications to the dark matter sector, non-standard primordial fluctuations, or strongly emitting radio galaxies. The effects of these different sources or scenarios are evaluated in the context of the expected sensitivity of SKA-Low, considering the AA* and AA4 configurations. The chapter aims to provide an overview of the theoretical landscape of 21-cm signatures and to highlight how the forthcoming SKA-Low observations will improve our understanding of astrophysical processes at early times and may open the door towards new physics beyond the $Λ$CDM framework. △ Less

Submitted 29 June, 2026; originally announced June 2026.

Comments: Published in Advancing Astrophysics with the SKA II (AASKAII), 2026 (arXiv:2606.20366). Report-no:AASKAII/Barkana01

Report number: AASKAII/Barkana01

RefGlass-GS: A UAV-Enabled Fusion Framework for Photorealistic, Semantic and Interactive Digitization of Reflective Glass Facades via Gaussian Splatting

Authors: Zhenyu Liang, Xiao Zhang, Boyu Wang, Zhaolun Liang, Ang Li, Jeff Chak Fu Chan, Mingzhu Wang, Jack C. P. Cheng

Abstract: Existing digitization of buildings with reflective glass facades suffers from geometric reconstruction distortion, unrealistic view-dependent texture rendering, and difficulties in object-based semantic enhancement. Therefore, we propose RefGlass-GS, a fusion framework that enables end-to-end UAV-based photorealistic, semantic, and interactive digitization of reflective glass facades. The contribu… ▽ More Existing digitization of buildings with reflective glass facades suffers from geometric reconstruction distortion, unrealistic view-dependent texture rendering, and difficulties in object-based semantic enhancement. Therefore, we propose RefGlass-GS, a fusion framework that enables end-to-end UAV-based photorealistic, semantic, and interactive digitization of reflective glass facades. The contributions include: (1) proposing an individual glass panel segmentation method based on maximum a posteriori estimation with structural regularities, robust to severe reflection and background interference; (2) formulating a UAV viewpoint planning optimization function that maximizes the coverage of view-dependent appearance for sufficient data capture; (3) developing an optimized Gaussian Splatting framework with a Reflection MLP, a novel deferred shading function, and two enhanced regularization terms for effective modeling of high-frequency near-field reflections; (4) introducing a standardized data organization paradigm for structuring GS-based representations into object-based models, facilitating interactive facility management on digital twin platforms. Experiments on real-world reflective glass facade scenes validate the effectiveness and superiority of the proposed method. Specifically, the glass panel segmentation achieves an improvement of 0.1927 in mIoU over SOTA methods, and only our method enables instance-level panel extraction. The UAV view planning improves novel view synthesis for reflective facades by 13.15 dB in PSNR compared to commercially used nap-of-the-object planning methods. The RefGlass-GS modeling outperforms SOTA Gaussian Splatting approaches for reflective scenes with an average improvement of 5.08 dB in PSNR. △ Less

Submitted 27 June, 2026; originally announced June 2026.

Bridging Theory and Observation in the SKA Era: A Cosmological Polarized Radiative Transfer Framework for Point-to-Point Polarized Sky Comparisons

Authors: Jennifer Y. H. Chan, Alvina Y. L. On, Paul C. W. Lai, Kinwah Wu

Abstract: Realizing the full scientific potential of the SKA requires not only revolutionary instrumentation but also accurate modeling of light propagation in an evolving, expanding Universe, in order to translate intensity and polarization data into physical insight about magnetic fields and cosmic plasma. When all-sky cosmological polarized radiative transfer (CPRT) calculations meets SKA observations, t… ▽ More Realizing the full scientific potential of the SKA requires not only revolutionary instrumentation but also accurate modeling of light propagation in an evolving, expanding Universe, in order to translate intensity and polarization data into physical insight about magnetic fields and cosmic plasma. When all-sky cosmological polarized radiative transfer (CPRT) calculations meets SKA observations, theory and data interlock to deliver a predictive, and testable picture of the evolving magneto-ionic Universe. This synergy transforms polarization observations -- assembled into empirical maps of diffuse emission and rotation-measure (RM) grids of discrete sources -- from descriptive data products into powerful astrophysical probes, advancing our understanding of cosmic magnetism across space and time. The CPRT formalism -- derived from fundamental conservation laws and incorporating relativistic, cosmological, and full radiative-transfer effects -- provides a robust platform and a common framework for observers, theorists, and simulation experts to pursue shared scientific goals. Observers gain synthetic templates to interpret RM grids and polarization maps; theorists can directly confront models of magnetogenesis and magnetic-field evolution with data; and simulation experts obtain a post-processing tool to transform cosmological magneto-hydrodynamic (MHD) outputs into observable skies. Furthermore, CPRT serves as a powerful testbed when traditional RM-based methods reach their limitations -- for example, in interpreting complex Faraday spectra, disentangling multiple intervening magnetized media, or achieving a coherent picture when diverse observational diagnostics -- such as dispersion measure, synchrotron emission and spectral index, and dust polarization -- are combined. △ Less

Submitted 23 June, 2026; originally announced June 2026.

Comments: Published in Advancing Astrophysics with the SKA II (AASKAII), 2026 (arXiv:2606.20366). Report-no:AASKAII/Chan01

Report number: AASKAII/Chan01

Small-scale Magnetic Fields in the Milky Way and Nearby Galaxies

Authors: Yik Ki Ma, Amit Seta, Aritra Basu, Sebastian Hutschenreuter, Marco Padovani, Georgia V. Panopoulou, Jeroen M. Stil, Craig S. Anderson, Lucia Armillotta, Jennifer Y. H. Chan, Marijke Haverkorn, Roland M. Crocker, Timea O. Kovacs, Sunil Malik, S. A. Mao, Kierra J. Weatherhead

Abstract: Magnetic fields in galaxies span decades in physical scale, from the coherent magnetic fields on galactic scales (> kpc) to the random magnetic fields from 100 pc to the resistive scale of the galactic plasma (i.e. ~1e6 cm). While many radio studies to date have placed more emphasis on the large-scale galactic magnetic fields than the small-scale counterparts, the emerging SKA will greatly facilit… ▽ More Magnetic fields in galaxies span decades in physical scale, from the coherent magnetic fields on galactic scales (> kpc) to the random magnetic fields from 100 pc to the resistive scale of the galactic plasma (i.e. ~1e6 cm). While many radio studies to date have placed more emphasis on the large-scale galactic magnetic fields than the small-scale counterparts, the emerging SKA will greatly facilitate accurate, detailed studies of the small-scale (< 100 pc) galactic magnetic fields. In this Chapter, we highlight the importance of understanding the small-scale galactic magnetic fields in furthering our understanding of star formation, galaxy evolution, and the fundamental physics of magnetohydrodynamics. Furthermore, we discuss some open questions in the research field and outline several possible large observation programmes with the SKA Array Assembly 4 (AA4). △ Less

Submitted 23 June, 2026; originally announced June 2026.

Comments: Published in Advancing Astrophysics with the SKA II (AASKAII), 2026 (arXiv:2606.20366). Report-no:AASKAII/Ma01

Report number: AASKAII/Ma01

Topological Hall Effect in Antiferromagnetic Co doped Fe$_3$GaTe$_2$

Authors: Shyam Raj Karullithodi, Yeonkyu Lee, Vadym Kulichenko, W. Kice Brown, Sang-Eon Lee, Chanyoung Lee, Jinyoung Yun, Gregory T. McCandless, Julia Y. Chan, Jeehoon Kim, Luis Balicas

Abstract: Fe$_3$GaTe$_2$ is van der Waals (vdW) ferromagnet with a Curie temperature $T_C$ ranging from 350 K to 380 K, followed upon cooling by a ferrimagnetic transition near room temperature. Substituting Fe with Co was previously reported to induce antiferromagnetism (AFM) at a Co fraction dependent Neel temperature $T_N$. In this work, we confirm the overall phase diagram of the Fe$_{3-x}$Co$_x$GaTe… ▽ More Fe$_3$GaTe$_2$ is van der Waals (vdW) ferromagnet with a Curie temperature $T_C$ ranging from 350 K to 380 K, followed upon cooling by a ferrimagnetic transition near room temperature. Substituting Fe with Co was previously reported to induce antiferromagnetism (AFM) at a Co fraction dependent Neel temperature $T_N$. In this work, we confirm the overall phase diagram of the Fe$_{3-x}$Co$_x$GaTe$_2$ series as a function of $x$ and temperature via magnetization and electrical transport measurements. For $x \simeq 0.6$ the Hall effect is observed to mimic the magnetization as the AF ground state is suppressed by the external magnetic field via a metamagnetic transition, thus displaying an anomalous Hall response. At low temperatures, we also observe a pronounced topological Hall signal peaking at $μ_0H$ = 4 T, or within the metamagnetic transition region of fields. This observation points to the presence of magnetic field-induced chiral spin textures, such as skyrmions upon approaching magnetization saturation. Magnetic force microscopy (MFM) reveals the emergence of nearly circular magnetic domains, with diameters on the order of 100 to 200 nm, within the antiferromagnetic phase. A detailed analysis of the MFM images indicates that the topological Hall effect is closely linked to the field-induced stabilization of magnetic domain structures, likely exhibiting chiral textures. This observation suggests the possible formation of skyrmions already in the AFM phase, i.e., AFM skyrmions, that evolve into ferromagnetic (FM) ones upon increasing the magnetic field. Consequently, Co-doped Fe$_3$GaTe$_2$ might provide a platform to investigate the transformation of skyrmions, initially coupled antiferromagnetically into ferromagnetic skyrmions, and to explore its impact on the topological and skyrmion Hall effects. △ Less

Submitted 19 June, 2026; originally announced June 2026.

Comments: 5 figures; supporting information included

Journal ref: ACS Nano 2026

Probabilistic representation and classical solutions of wave equations with complex polynomial nonlinearities

Authors: Joshua J. Y. Chan, Nicolas Privault

Abstract: We review the probabilistic representation of solutions of wave equations with polynomial nonlinearities in spatial dimensions d=1,2,3 using stochastic branching processes. Under regularity assumptions on the initial data, we derive conditions ensuring the integrability of the corresponding Monte Carlo estimator, and the existence and smoothness of mild and classical solutions. We also present num… ▽ More We review the probabilistic representation of solutions of wave equations with polynomial nonlinearities in spatial dimensions d=1,2,3 using stochastic branching processes. Under regularity assumptions on the initial data, we derive conditions ensuring the integrability of the corresponding Monte Carlo estimator, and the existence and smoothness of mild and classical solutions. We also present numerical results and comparisons with grid-based algorithms for the solution of nonlinear wave equations. △ Less

Submitted 17 June, 2026; originally announced June 2026.

MSC Class: 35L05; 35L70; 60J80; 65C05

Steering Autoregressive Vision-Language-Action Policies via Action Token Intervention

Authors: Jason Chan, Jonathan C. Kao

Abstract: We present Token Steering (TS), a method for dynamically steering trajectories generated by an autoregressive vision-language-action (VLA) model through direct intervention in the action-token space. TS injects low-dimensional user inputs into the model's native action-token representation, allowing users to influence trajectory generation without modifying the underlying vision-language model (VL… ▽ More We present Token Steering (TS), a method for dynamically steering trajectories generated by an autoregressive vision-language-action (VLA) model through direct intervention in the action-token space. TS injects low-dimensional user inputs into the model's native action-token representation, allowing users to influence trajectory generation without modifying the underlying vision-language model (VLM) architecture. Because TS operates entirely at inference time, it requires no additional training or finetuning. User inputs guide rather than override the pretrained policy, allowing users to influence robot actions while preserving the dexterity, smoothness, and task priors learned by the VLA. We evaluate TS on two household manipulation tasks -- drawer closing after object placement and state-aware object swapping -- and improve success rates from 10.0% to 72.5% and from 16.7% to 93.8%, respectively. By enabling lightweight, intuitive steering over robot foundation models, our interface has the potential to improve human-robot interaction in consumer environments and broaden accessibility for individuals with limited physical control. Project website: https://jasontchan.github.io/token-steering/ . △ Less

Submitted 12 June, 2026; originally announced June 2026.

Comments: 9 pages, 5 figures

Unlocking Latent Dimensions: Exploring Representations of Large-Scale X-ray Scattering Data using Variational Autoencoders

Authors: Monika Choudhary, Xiaoya Chong, Runbo Jiang, Wiebke Koepp, Petrus H. Zwart, Damon English, Gregory M. Su, Eric Schaible, Chenhui Zhu, Mostafa Nassr, Noah P. Wamble, Kelvin Kam-Yun Li, Jonathan M. Chan, Jose Carlos Diaz, Cameron McKay, Lynn Katz, Benny Freeman, Guillaume Freychet, Yevgen Matviychuk, Eliot Gann, Daniel B. Allan, Benedikt Sochor, Frank Schluenzen, Stephan V. Roth, Ethan J. Crumlin , et al. (3 additional authors not shown)

Abstract: Scientific user facilities generate X-ray scattering data faster than traditional workflows can process them. We address this challenge across two settings, offline dataset exploration and live on-the-fly analysis. We train a domain-specific attention-based Convolutional Variational Autoencoder (C-VAE) on 1.5 million X-ray scattering images to learn low-dimensional representations capturing struct… ▽ More Scientific user facilities generate X-ray scattering data faster than traditional workflows can process them. We address this challenge across two settings, offline dataset exploration and live on-the-fly analysis. We train a domain-specific attention-based Convolutional Variational Autoencoder (C-VAE) on 1.5 million X-ray scattering images to learn low-dimensional representations capturing structural variation across diverse experimental conditions. The learned latent space reveals well-organized clusters and smooth trajectories reflecting experimental progression. It further supports controlled synthetic scattering image generation across diverse structural states. When deployed without retraining, the model organizes time-resolved film formation experiments at two synchrotron facilities into interpretable latent structures. Benchmarking against DINOv3 (ViT-7B), a general-purpose vision foundation model, demonstrates that domain-specific training yields more interpretable latent organization for scattering data. Both workflows are integrated within Latent Space Explorer, a component of the MLExchange platform, supporting interactive structural exploration across archived datasets and live experiments. △ Less

Submitted 14 July, 2026; v1 submitted 12 June, 2026; originally announced June 2026.

Verifiable User Simulation for Search and Recommendation Systems

Authors: Chenglong Ma, Xinye Wanyan, Danula Hettiachchi, Ziqi Xu, Yongli Ren, Jeffrey Chan

Abstract: Large-language-model (LLM) based user simulation is increasingly adopted for evaluating search engines, recommender systems, and retrieval-augmented generation pipelines, yet most simulators remain opaque: it is difficult to determine why a simulated user made a particular choice or whether that choice is consistent with the intended user profile. Compounding this, recent research shows that LLMs… ▽ More Large-language-model (LLM) based user simulation is increasingly adopted for evaluating search engines, recommender systems, and retrieval-augmented generation pipelines, yet most simulators remain opaque: it is difficult to determine why a simulated user made a particular choice or whether that choice is consistent with the intended user profile. Compounding this, recent research shows that LLMs can produce biased or discriminatory responses depending on user background characteristics such as language, education level, and cultural context, raising concerns about the equitable treatment of minority and disadvantaged groups. This half-day, in-person tutorial introduces a proposed design-and-audit framework that treats a user simulator as a verifiable engineering artefact composed of seven auditable components - structured Persona, task-aware Contract, matched human-vs-agent Execution, auditable Trace, persona-aligned Verification, structured Feedback, and a Refinement loop that updates personas and contracts. Through two hands-on mini-labs on recommendation-list evaluation and search-query formulation, participants will inspect simulator behaviour end-to-end, distinguish diagnostic discrepancy analysis from statistical validation, and apply checks for fidelity, credibility, and demographic bias. The tutorial targets information retrieval and recommender systems researchers and practitioners interested in user behaviour simulation and responsible AI. △ Less

Submitted 12 June, 2026; originally announced June 2026.

Comments: Presented as a half-day tutorial at SIGIR 2026, 4 pages

ACM Class: H.3.3; H.3.4; I.2.11

Journal ref: In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2026)

Flow Control: Steering Vision-Language-Action Models with Simple Real-Time Inputs

Authors: Jonathan C. Kao, Jason Chan, Andy Wang

Abstract: We introduce flow control of vision-language-action (VLA) models, a simple and effective way to steer VLA actions in real-time through generic inputs, such as a keyboard. This method can be used out-of-the-box and does not require retraining or fine-tuning VLAs. It enables relatively crude user inputs to steer a VLA to align with user intent. The VLA transforms these inputs into action samples dra… ▽ More We introduce flow control of vision-language-action (VLA) models, a simple and effective way to steer VLA actions in real-time through generic inputs, such as a keyboard. This method can be used out-of-the-box and does not require retraining or fine-tuning VLAs. It enables relatively crude user inputs to steer a VLA to align with user intent. The VLA transforms these inputs into action samples drawn from the VLA expert action distribution learned during training, so that the generated actions are high quality (conformity to the action expert distribution) and high fidelity (reflecting the user's intent). We demonstrate that flow control has many desirable properties: (1) flow control accurately and responsively steers robot actions with user inputs, (2) it is robust to suboptimal user inputs, (3) it enables users to steer VLAs to achieve significantly higher success rates and faster task completion, and (4) fine-tuning a VLA on flow control trajectories improves the autonomous policy. Together, these results provide a simple and intuitive way for users to help steer VLA actions, increasing task performance. △ Less

Submitted 8 June, 2026; originally announced June 2026.

Comments: 10 pages, 5 figures

MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry

Authors: Joey Chan, Wonbin Kweon, Ashley Shin, Niharika Bhattacharjee, Pengcheng Jiang, Yue Guo, Jiawei Han

Abstract: Large language models (LLMs) have shown promise for molecular property prediction, but their ability to reason over chemical structures remains limited, as molecular representations such as SMILES differ substantially from the natural language on which LLMs are primarily trained. To bridge this semantic and chemical knowledge gap, we propose MolE-RAG, a training-free, molecule-centric retrieval-au… ▽ More Large language models (LLMs) have shown promise for molecular property prediction, but their ability to reason over chemical structures remains limited, as molecular representations such as SMILES differ substantially from the natural language on which LLMs are primarily trained. To bridge this semantic and chemical knowledge gap, we propose MolE-RAG, a training-free, molecule-centric retrieval-augmented generation framework for LLM-based molecular property prediction. MolE-RAG augments each prediction with three complementary sources of inference-time context: retrieved chemistry literature, molecule-specific information including compound synonyms, identifiers, functional group annotations, and physicochemical descriptors, and structurally similar molecules retrieved from the training set. We evaluate MolE-RAG across nine molecular property prediction tasks using proprietary, chemistry-specialized, and open-source LLMs. Across general-purpose LLMs, MolE-RAG improves ROC-AUC by up to 28 percentage points on classification tasks and reduces regression RMSE by up to 67% relative to a SMILES-only baseline. We further find that the utility of each context source varies across models and tasks, with different models benefiting most from textual retrieval, molecular context, or structural retrieval. These results suggest that molecule-centric retrieval can improve LLM-based molecular property prediction without model fine-tuning while providing a flexible framework for integrating heterogeneous chemical knowledge at inference time. △ Less

Submitted 14 June, 2026; v1 submitted 4 June, 2026; originally announced June 2026.

GWTC-5.0: Constraints on the Cosmic Expansion Rate and Modified Gravitational-wave Propagation

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1788 additional authors not shown)

Abstract: We employ 236 gravitational-wave (GW) sources in the fifth LIGO--Virgo--KAGRA Collaboration (LVK) Gravitational-Wave Transient Catalog (GWTC-5.0) to estimate the Hubble constant $H_0$. We compare the luminosity distance measured from GWs to the redshift inferred i) using features in the mass spectrum, and ii) using statistical host galaxy association. Probing the relationship between source lumino… ▽ More We employ 236 gravitational-wave (GW) sources in the fifth LIGO--Virgo--KAGRA Collaboration (LVK) Gravitational-Wave Transient Catalog (GWTC-5.0) to estimate the Hubble constant $H_0$. We compare the luminosity distance measured from GWs to the redshift inferred i) using features in the mass spectrum, and ii) using statistical host galaxy association. Probing the relationship between source luminosity distances and redshifts obtained in this way yields constraints on cosmological parameters. We estimate $H_0 = {71.7}_{-7.5}^{+9.4}\,{\text{km}\,\text{s}^{-1}\,\text{Mpc}^{-1}}$ (median with $68\%$ symmetric credible interval). This combines information from the source-frame mass distribution with the $H_0$ measurement from GW170817 and its electromagnetic counterpart as well as galaxy catalog information from Dark Energy Survey Year 6 (DES-Y6). We improve over the GWTC-4.0 measurement by using more GW sources, some with significantly smaller sky localization volumes, which leads to a reduction by $22.0\%$ of the $H_0$ uncertainty and a reconstructed mass distribution with lower uncertainties. We also constrain deviations from general relativity (GR) which affect GW propagation, specifically that modify the luminosity distance inferred from the GW signal. We find no departures from GR in parameterized tests of GW propagation. △ Less

Submitted 4 August, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: main paper: 20 pages and 7 figures; total with appendices: 51 pages and 13 figures. This article draws heavily from the corresponding GWTC-4 article, arXiv:2509.04348

Report number: LIGO-P2600018

GWTC-5.0: Population Properties of Merging Compact Binaries

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1791 additional authors not shown)

Abstract: We present the population properties of merging compact binaries inferred using 267 mergers from the cumulative Gravitational-Wave Transient Catalog 5.0. As this data set contains no new sources with a neutron star, we primarily focus on the properties of the binary black hole mergers. We infer the merger rate of binary black holes with component masses between $2.5\,\mathrm{M}_\odot $ and… ▽ More We present the population properties of merging compact binaries inferred using 267 mergers from the cumulative Gravitational-Wave Transient Catalog 5.0. As this data set contains no new sources with a neutron star, we primarily focus on the properties of the binary black hole mergers. We infer the merger rate of binary black holes with component masses between $2.5\,\mathrm{M}_\odot $ and $200\,\mathrm{M}_\odot $ to be $27.5\text{--} 49.4 \, \mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$ (all intervals at $90\%$ credible levels) at redshift $z = 0.2$. We find evidence for a subpopulation of binary black hole mergers that host a rapidly spinning black hole (dimensionless spins $χ\sim 0.7$), consistent with signatures of hierarchical mergers. We find that these occur at two mass scales, the first at primary masses $\sim 10$--$20\,\mathrm{M}_\odot $ and the second above $\sim 45\,\mathrm{M}_\odot $, and we estimate their total rate at $z=0.2$ to be $0.2\text{--} 3.11 \, {\rm Gpc}^{-3} {\rm yr}^{-1}$. We infer that, above $40\,\mathrm{M}_\odot $, the mass distribution of the less massive (secondary) black hole declines more steeply than that of the more massive (primary) one. This is consistent with a flatter mass-ratio distribution and indicates the prevalence of unequal-mass binaries with large primary masses. We find evidence for two features in the black hole mass spectrum: a peak around $10\,\mathrm{M}_\odot $ and a change of slope at around $35\,\mathrm{M}_\odot $. Black holes of $\sim 35\,\mathrm{M}_\odot $ pair preferentially with companions of similar mass. Additionally, we find that the effective inspiral spin distribution of binary black holes is asymmetric about zero, based on which we infer that at least $9 \%$ of mergers occur in channels with some preference for spin-orbit alignment. We find evidence that... △ Less

Submitted 1 July, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: Abstract truncated in Arxiv metadata. The paper appendices draw heavily from the corresponding GWTC-4 article, arXiv:2508.18083

Report number: LIGO-P2600045

GWTC-5.0: Observations from the Second Part of the Fourth LIGO-Virgo-KAGRA Observing Run and Updates to the Gravitational-Wave Transient Catalog

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1805 additional authors not shown)

Abstract: Version 5.0 of the Gravitational-Wave Transient Catalog (GWTC-5.0) adds new candidates detected by the LIGO Virgo KAGRA network of observatories through the second part of the fourth observing run (O4b: 2024 April 10 15:00:00 to 2025 January 28 17:00:00 UTC) and four days of the preceding engineering run (2024 April 6 to 2024 April 10). We find 161 compact binary coalescence candidates that are id… ▽ More Version 5.0 of the Gravitational-Wave Transient Catalog (GWTC-5.0) adds new candidates detected by the LIGO Virgo KAGRA network of observatories through the second part of the fourth observing run (O4b: 2024 April 10 15:00:00 to 2025 January 28 17:00:00 UTC) and four days of the preceding engineering run (2024 April 6 to 2024 April 10). We find 161 compact binary coalescence candidates that are identified by at least one of our search algorithms with a probability of astrophysical origin $p_\mathrm{astro} \geq 0.5$ and that are not vetoed during event validation. We also provide detailed source property measurements for 104 candidates that have a false-alarm rate < 1yr$^{-1}$. Based on the inferred component masses, all these candidates are consistent with signals from binary black holes. Median inferred component masses in the new candidates range from 5.14$M_\odot$ (GW241109_115924) to 70$M_\odot$ (GW241116_151753). Improvements in detector sensitivity allow us to observe compact binary coalescences with increasing clarity: 5 binary-black-hole signals have network signal-to-noise ratio exceeding 30, with a maximum to date of 76.9 for GW250114_082203. Such loud signals enable more precise studies of properties of their astrophysical sources and tests of general relativity. We also present updated results up to the first part of the fourth observing run, identifying 229 candidates. This brings the total number of transients in the cumulative GWTC having $p_\mathrm{astro} \geq 0.5$ to 390, further expanding the size of the catalog and our view of the gravitational-wave universe. △ Less

Submitted 23 June, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: main paper: 30 pages, 8 figures; total with appendices: 43 pages, 9 figures. This article draws heavily from the corresponding GWTC-4 article, arXiv:2508.18082

Report number: LIGO-P2600152

GWTC-5.0: Methods for Identifying and Characterizing Gravitational-wave Transients

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1800 additional authors not shown)

Abstract: The Gravitational-Wave Transient Catalog (GWTC) is a collection of candidate gravitational-wave transient signals identified and characterized by the LIGO-Virgo-KAGRA Collaboration. Producing the contents of the GWTC from detector data requires complex analysis methods. These comprise techniques to model the signal; identify the transients in the data; evaluate the quality of the data and mitigate… ▽ More The Gravitational-Wave Transient Catalog (GWTC) is a collection of candidate gravitational-wave transient signals identified and characterized by the LIGO-Virgo-KAGRA Collaboration. Producing the contents of the GWTC from detector data requires complex analysis methods. These comprise techniques to model the signal; identify the transients in the data; evaluate the quality of the data and mitigate possible instrumental issues; infer the parameters of each transient; compare the data with the waveform models for compact binary coalescences, and handle the large amount of results associated with all these different analyses. In this paper, we describe the methods employed to produce the catalog's fifth release, GWTC-5.0, focusing on the analysis of the second part of the fourth observing run of LIGO, Virgo and KAGRA. △ Less

Submitted 23 June, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: This article supersedes the corresponding GWTC-4 article, arXiv:2508.18081

Report number: LIGO-P2600166

GWTC-5.0: An Introduction to Version 5.0 of the Gravitational-Wave Transient Catalog

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1800 additional authors not shown)

Abstract: The Gravitational-Wave Transient Catalog (GWTC) is a collection of short-duration (transient) gravitational-wave signals identified by the LIGO-Virgo-KAGRA Collaboration in gravitational-wave data produced by the eponymous detectors. The catalog provides information about the identified candidates, such as the arrival time and amplitude of the signal and properties of the signal's source as inferr… ▽ More The Gravitational-Wave Transient Catalog (GWTC) is a collection of short-duration (transient) gravitational-wave signals identified by the LIGO-Virgo-KAGRA Collaboration in gravitational-wave data produced by the eponymous detectors. The catalog provides information about the identified candidates, such as the arrival time and amplitude of the signal and properties of the signal's source as inferred from the observational data. GWTC is the release of this dataset and version 5.0 extends the catalog to include observations made during the second part of the fourth LIGO-Virgo-KAGRA observing run up until 2025 January 28. This paper marks an introduction to a collection of articles related to this version of the catalog, GWTC-5.0. This update significantly increases the number of detected merging binary systems of black holes and neutron stars to over 300, enabling many follow-up studies toward understanding the gravitational-wave universe. The collection of articles accompanying the catalog provides documentation of the methods used to analyze the data, summaries of the catalog of events, observational measurements drawn from the population, and detailed discussions of selected candidates. △ Less

Submitted 23 June, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: This article supersedes the corresponding GWTC-4 article, arXiv:2508.18080

Report number: LIGO-P2500701

Open Data from LIGO, Virgo, and KAGRA through the Second Part of the Fourth Observing Run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1787 additional authors not shown)

Abstract: LIGO, Virgo, KAGRA, and GEO 600 form a network of gravitational-wave observatories. Data and analysis results from this network are made publicly available through the Gravitational Wave Open Science Center (GWOSC). This paper describes open data from this network, including the addition of data from the second part of the fourth observing run (O4b) and selected periods from the preceding engineer… ▽ More LIGO, Virgo, KAGRA, and GEO 600 form a network of gravitational-wave observatories. Data and analysis results from this network are made publicly available through the Gravitational Wave Open Science Center (GWOSC). This paper describes open data from this network, including the addition of data from the second part of the fourth observing run (O4b) and selected periods from the preceding engineering run (ER16), which were collected from times spanning April 6th, 2024 to January 28th, 2025. The public data set includes calibrated strain time series for each instrument, data from additional channels used for noise subtraction and detector characterization, and new analysis data products in the online GWOSC release associated with version 5.0 of the Gravitational-Wave Transient Catalog. △ Less

Submitted 17 June, 2026; v1 submitted 26 May, 2026; originally announced May 2026.

Comments: This version has an updated author list, updated references and some text has been modified to improve clarity. This article draws heavily from the corresponding O4a article, arXiv:2508.18079

Report number: LIGO-P2600085

WeeCare: Towards Handheld Bladder Fullness Sensing with a Conformable Pad

Authors: Zhikai Qin, Siqi Zhang, Shuyi Zeng, Xiyuxing Zhang, Junyi Zhu, Justin Chan

Abstract: Patients with bladder dysfunction often lose the sensation of bladder fullness and cannot void naturally, forcing reliance on fixed-schedule catheterization that is uncomfortable and risks complications. We present WeeCare, a handheld conformable pad with fabric electrodes for on-demand bladder fullness sensing using electrical impedance tomography (EIT). The central challenge is that repeated rem… ▽ More Patients with bladder dysfunction often lose the sensation of bladder fullness and cannot void naturally, forcing reliance on fixed-schedule catheterization that is uncomfortable and risks complications. We present WeeCare, a handheld conformable pad with fabric electrodes for on-demand bladder fullness sensing using electrical impedance tomography (EIT). The central challenge is that repeated removal and reattachment can introduce variation in electrode position and contact quality. We assess WeeCare along three axes: in-silico simulations characterizing electrode layout and noise robustness, in-vitro phantom experiments across urine salinities and filling levels, and an in-vivo study tracking voiding dynamics and fullness sensing across 8 participants, with filling dynamics characterized in a single participant. Our results provide an early assessment of WeeCare's feasibility under controlled conditions. △ Less

Submitted 25 July, 2026; v1 submitted 25 May, 2026; originally announced May 2026.

Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems

Authors: Imesh Ekanayake, Elham Naghizade, Jeffrey Chan

Abstract: The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sectors with significant societal impact. Current methods rarely address privacy, fairness, and accuracy together, which can potentially compromise ethical standards and privacy regulations. However, balancing these three objectives is quite challenging si… ▽ More The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sectors with significant societal impact. Current methods rarely address privacy, fairness, and accuracy together, which can potentially compromise ethical standards and privacy regulations. However, balancing these three objectives is quite challenging since each of objective often imposes conflicting requirements on the design and training of models, making it difficult to optimize one without compromising the others. This paper introduces a novel multitask adversarial model that treats fairness and privacy as integral objectives rather than afterthoughts, and learns a latent representation that hides sensitive attributes while preserving essential task-related information. Our approach dynamically balances fairness with accuracy and privacy through an optimized cost function with minimal performance loss even under strict conditions. Extensive testing on diverse datasets shows the ability of our model to achieve high standards of fairness and privacy without significant sacrifice to accuracy. Benchmarking against state-of-the-art privacy and fairness standards shows that our method enhances the robustness of privacy, fairness, and accuracy optimization, proving its adaptability across various datasets. △ Less

Submitted 23 May, 2026; originally announced May 2026.

Comments: 13 Pages, 6 figures, IEEE TKDE

Markov Renewal Theory for Transfer Operators and Point Processes on the Line

Authors: Yoon Jun Chan, Markus Heydenreich, Sabine Jansen

Abstract: We prove exponential decay of pair correlations for 1D stationary point processes when spacings satisfy a Markov condition, geometric ergodicity, and a condition on exponential moments. The conditions are phrased for stationary sequences of spacings (intervals between consecutive points) whose law comes from the Palm distribution of the point process. The key technical ingredient is a Markov renew… ▽ More We prove exponential decay of pair correlations for 1D stationary point processes when spacings satisfy a Markov condition, geometric ergodicity, and a condition on exponential moments. The conditions are phrased for stationary sequences of spacings (intervals between consecutive points) whose law comes from the Palm distribution of the point process. The key technical ingredient is a Markov renewal theorem with exponential convergence rate. The proofs combine classical regeneration techniques with the notion of geometric ergodicity for Markov chains with general state space. We apply the result to two models from statistical mechanics: (1) Gibbs point processes with a hard-core, finite-range pair potentials and (2) a harmonic chain of atoms, related to an autoregressive Gaussian process. △ Less

Submitted 28 July, 2026; v1 submitted 20 May, 2026; originally announced May 2026.

Comments: 37 pages, 2 figures. Extended the theorem for the harmonic chain case to include identification of the limit measure with the translation-invariant point process

MSC Class: 60G55; 60K05; 82B21

VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals

Authors: Joey Chan, Zhen Chen, Ershun Pan

Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly detection is essential for ensuring safe battery operation. However, as battery systems and operating scenarios become increasingly complex, battery fault diagnosis and maintenance require stronger cross-domain adaptability and human-AI collaborati… ▽ More With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly detection is essential for ensuring safe battery operation. However, as battery systems and operating scenarios become increasingly complex, battery fault diagnosis and maintenance require stronger cross-domain adaptability and human-AI collaboration. Traditional fault detection and diagnosis methods are usually designed for specific scenarios and predefined workflows, making them less effective in complex real-world applications. To address the scarcity of open-source battery fault report corpora and the lack of unified maintenance knowledge representation, this study proposes a descriptive text modeling approach for battery signal reports. Monitoring signals, statistical features, anomaly records, and state assessment results are transformed into structured and readable natural language descriptions, forming a language corpus for battery health diagnosis and maintenance. Based on this corpus, we propose VBFDD-Agent, a vehicle battery fault detection and diagnosis agent for automotive-grade battery systems. VBFDD-Agent integrates descriptive battery-state texts, historical case retrieval, local maintenance manuals, and large language model reasoning to generate structured diagnostic results and maintenance recommendations. Experiments show that the proposed framework can accurately perform anomaly monitoring based on descriptive textual representations and provide flexible, efficient, and actionable maintenance suggestions. Expert evaluation further confirms the practical value of the generated recommendations. Overall, VBFDD-Agent extends traditional battery diagnosis from label prediction to interpretable and maintenance-oriented decision support. △ Less

Submitted 20 May, 2026; originally announced May 2026.

Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA

Authors: Sterling Huang, Abigayle Brown, Jiyoo Noh, Jiakang Xu, Wantong Huo, Kaung Myat Kyaw, Jonathan Chan

Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations focus mainly on autoregressive architectures. This study examines whether LLMLingua-2 transfers effectively to diffusion large language models (DLLMs), specifically LLaDA-8B-Instruct. We evaluate GSM8K, DUC2004, and ShareGPT using 250 prompts per dataset at an approximate 50\% compression r… ▽ More Prompt compression reduces inference cost and context length in large language models, but prior evaluations focus mainly on autoregressive architectures. This study examines whether LLMLingua-2 transfers effectively to diffusion large language models (DLLMs), specifically LLaDA-8B-Instruct. We evaluate GSM8K, DUC2004, and ShareGPT using 250 prompts per dataset at an approximate 50\% compression ratio, covering mathematical reasoning, prompt reconstruction, and summarization. Outputs from original, compressed, and reconstructed prompts are compared using exact-match accuracy, BLEU, ROUGE, and BERTScore. Results show that high semantic preservation does not necessarily ensure stable downstream behavior in diffusion models. Summarization remains relatively robust, while mathematical reasoning degrades substantially despite high semantic similarity. Reconstruction further shows that semantically similar prompts may omit reasoning-critical information needed for stable denoising. Overall, compression failures are mainly driven by information omission rather than semantic drift, suggesting that autoregressive prompt compression methods may not transfer uniformly to DLLMs. These findings motivate diffusion-aware compression strategies. △ Less

Submitted 11 July, 2026; v1 submitted 18 May, 2026; originally announced May 2026.

Comments: Accepted to appear in The 14th International Conference on Advances in Information Technology (IAIT2026)

Double Metric Learning for Building Directed Graphs with Chain Connections for the ATLAS ITk Detector

Authors: Jay Chan

Abstract: Graph construction is an essential step in the Graph Neural Network (GNN) based tracking pipelines. The goal of the graph construction is to construct a graph that contains only the defined true edge connections between nodes (detector hits). A promising approach for the graph construction is through the Metric Learning approach, where a node representation in an embedding space is learned, and no… ▽ More Graph construction is an essential step in the Graph Neural Network (GNN) based tracking pipelines. The goal of the graph construction is to construct a graph that contains only the defined true edge connections between nodes (detector hits). A promising approach for the graph construction is through the Metric Learning approach, where a node representation in an embedding space is learned, and nodes are connected according to their distance in the embedding space. The loss function for the metric learning in this case is a contrastive loss encouraging the true pairs of nodes to be close to each other, and pulling away the false pairs of nodes. This approach presents a conflict of the learning objective for the hopping connections when a true edge is defined as a chain connection in a particle track. To address the conflict for this case, we propose a ``Double Metric Learning'' approach, where two node representations are learned. A directed graph can then be constructed based on the distance between the two representations from two nodes respectively. We test this idea with the ATLAS ITk detector at the HL-LHC using the ATLAS ITk simulation and show better graph construction performance particularly for particles with high transverse momentum compared to the Simple Metric Learning approach. We also show that Double Metric Learning is able to accurately predict edge direction. △ Less

Submitted 13 May, 2026; originally announced May 2026.

Comments: 7 pages, 5 figures

Journal ref: Proceedings of the CTD 2025, PROC-CTD2025-071

Task-Aware Automated User Profile Generation for Recommendation Simulation Using Large Language Models

Authors: Xinye Wanyan, Chenglong Ma, Danula Hettiachchi, Ziqi Xu, Jeffrey Chan

Abstract: Large Language Model (LLM)-based agent simulation has emerged as a promising approach to meet the increasing demand for real-time and rigorous evaluation in modern recommender systems. A typical LLM-driven simulation framework comprises three essential components: the profile module, memory module, and action module. However, existing studies have primarily concentrated on enhancing the memory and… ▽ More Large Language Model (LLM)-based agent simulation has emerged as a promising approach to meet the increasing demand for real-time and rigorous evaluation in modern recommender systems. A typical LLM-driven simulation framework comprises three essential components: the profile module, memory module, and action module. However, existing studies have primarily concentrated on enhancing the memory and action modules, with limited attention to profile generation, which plays a pivotal role in ensuring realistic agent behaviours and aligning simulated interactions with real user dynamics. Moreover, the scarcity of datasets specifically designed for recommendation simulations has led to heavy reliance on manually crafted profiles, significantly limiting the scalability and generalisability of simulation frameworks across different datasets. To address these challenges, this work proposes an Automated Profile Generation Framework for Recommendation Simulation, APG4RecSim, that constructs realistic, coherent, and robust user profiles with minimal supervision. Extensive experiments on three benchmark datasets demonstrate that APG4RecSim achieves the best overall performance on discrimination, ranking, and rating tasks, improving ranking quality by up to 7% in nDCG@10 and reducing rating distribution divergence by 8% in JSD compared to existing profile-generation baselines. Beyond overall performance gains, our results show that profiles generated by APG4RecSim are resilient to popularity- and position-induced biases and maintain stable performance across datasets and different LLMs. △ Less

Submitted 13 May, 2026; originally announced May 2026.

Comments: Accepted by SIGIR 2026

Unveiling Hidden Lyman Alpha Emitters in the DESI DR1 Data

Authors: Jui-Kuan Chan, Ting-Wen Lan, J. Xavier Prochaska, Shun Saito, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, A. Cuceu, A. de la Macorra, Biprateep Dey, P. Doel, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, Satya Gontcho A Gontcho, G. Gutierrez, C. Hahn, J. Jimenez, R. Joyce, S. Juneau, D. Kirkby, A. Kremin, M. Landriau, M. Manera , et al. (17 additional authors not shown)

Abstract: We present an automatic method based on machine-learning convolutional neural network (CNN) architecture to detect Lyman alpha emitters (LAE) hidden in the Data Release 1 spectroscopic dataset of the Dark Energy Spectroscopic Instrument (DESI). Those LAEs mostly have incorrect redshift estimations because the current DESI pipeline is not designed to detect and measure the redshifts of galaxies at… ▽ More We present an automatic method based on machine-learning convolutional neural network (CNN) architecture to detect Lyman alpha emitters (LAE) hidden in the Data Release 1 spectroscopic dataset of the Dark Energy Spectroscopic Instrument (DESI). Those LAEs mostly have incorrect redshift estimations because the current DESI pipeline is not designed to detect and measure the redshifts of galaxies at $z>2$. To uncover those sources, we first visually inspect thousands of DESI spectra and construct a sample, consisting of both LAEs and non-LAEs, for training and testing the CNN-based model to (1) detect LAEs in DESI spectra and (2) determine their Ly$α$ redshifts. The final model yields $95.2\%$ purity and $95.9\%$ completeness for detecting LAEs. We apply this model to approximately $2\times10^{6}$ spectra of sources targeted as emission-line galaxies and detect 19,685 LAEs from $z\sim2$ to $3.5$ within 12 minutes with a single GPU, illustrating the high efficiency of this model for identifying LAEs. The detected LAEs are mostly at the bright end of the luminosity function with Ly$α$ luminosity $L_{\rm Lyα} \gtrsim 10^{43}$ erg/s. The high signal-to-noise composite spectrum of the detected LAEs further shows various spectral features, including P-Cygni profiles of metal lines and MgII emission lines, possible indicators of Lyman continuum escape fraction, revealing the rich astrophysical information in this LAE sample. Finally, this sample can be used to train and validate the pipelines for redshift determination of LAEs for the preparation of the DESI-II survey. △ Less

Submitted 12 May, 2026; originally announced May 2026.

Comments: 27 pages, 21 figures, submitted to ApJ

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

Authors: Rezarta Islamaj, Robert Leaman, Joey Chan, Nicholas Wan, Qiao Jin, Natalie Xie, John Wilbur, Shubo Tian, Lana Yeganova, Po-Ting Lai, Chih-Hsuan Wei, Yifan Yang, Yao Ge, Qingqing Zhu, Zhizheng Wang, Zhiyong Lu

Abstract: Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain discriminative as model capabilities improve. Existing biomedical question answering (QA) benchmarks are limited in this respect. Multiple-choice formats can allow models to succeed through answer elimination rather than inference, while widely circul… ▽ More Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain discriminative as model capabilities improve. Existing biomedical question answering (QA) benchmarks are limited in this respect. Multiple-choice formats can allow models to succeed through answer elimination rather than inference, while widely circulated exam-style datasets are increasingly vulnerable to performance saturation and training data contamination. Multi-hop reasoning, defined as the ability to integrate information across multiple sources to derive an answer, is central to clinically meaningful tasks such as diagnostic support, literature-based discovery, and hypothesis generation, yet remains underrepresented in current biomedical QA benchmarks. MedHopQA is a disease-centered multi-hop reasoning benchmark consisting of 1,000 expert-curated question-answer pairs introduced as a shared task at BioCreative IX. Each question requires synthesis of information across two distinct Wikipedia articles, and answers are provided in an open-ended free-text format. Gold annotations are augmented with ontology-grounded synonym sets from MONDO, NCBI Gene, and NCBI Taxonomy to support both lexical and concept-level evaluation. MedHopQA was constructed through a structured process combining human annotation, triage, iterative verification, and LLM-as-a-judge validation. To reduce leaderboard gaming and contamination risk, the 1,000 scored questions are embedded within a publicly downloadable set of 10,000 questions, with answers withheld, on a CodaBench leaderboard. MedHopQA provides both a benchmark and a reusable framework for constructing future biomedical QA datasets that prioritize compositional reasoning, saturation resistance, and contamination resistance as core design constraints. △ Less

Submitted 12 May, 2026; originally announced May 2026.

Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering

Authors: Rezarta Islamaj, Joey Chan, Robert Leaman, Jongmyung Jung, Hyeongsoon Hwang, Quoc-An Nguyen, Hoang-Quynh Le, Harikrishnan Gurushankar Saisudha, Ganesh Chandrasekar, Rustam R. Taktashov, Nadezhda Yu. Bizyukova, Sofia I. R. Conceição, Paulo R. C. Lopes, Reem Abdel Salam, Mary Adewunmi, Zhiyong Lu

Abstract: Multi-hop question answering (QA) remains a significant challenge in the biomedical domain, requiring systems to integrate information across multiple sources to answer complex questions. To address this problem, the BioCreative IX MedHopQA shared task was designed to benchmark in multi-hop reasoning for large language models (LLMs). We developed a novel dataset of 1,000 challenging QA pairs spann… ▽ More Multi-hop question answering (QA) remains a significant challenge in the biomedical domain, requiring systems to integrate information across multiple sources to answer complex questions. To address this problem, the BioCreative IX MedHopQA shared task was designed to benchmark in multi-hop reasoning for large language models (LLMs). We developed a novel dataset of 1,000 challenging QA pairs spanning diseases, genes, and chemicals, with particular emphasis on rare diseases. Each question was constructed to require two-hop reasoning through the integration of information from two distinct Wikipedia pages. The challenge attracted 48 submissions from 13 teams. Systems were evaluated using both surface string comparison and conceptual accuracy (MedCPT score). The results showed a substantial performance gap between baseline LLMs and enhanced systems. The top-ranked submission achieved an 89.30% F1 score on the MedCPT metric and an 87.30% exact match (EM) score, compared with 67.40% and 60.20%, respectively, for the zero-shot baseline. A central finding of the challenge was that retrieval-augmented generation (RAG) and related retrieval-based strategies were critical for strong performance. In addition, concept-level evaluation improved answer assessment when correct responses differed in surface form. The MedHopQA dataset is publicly available to support continued progress in this important area. Challenge materials: https://www.ncbi.nlm.nih.gov/research/bionlp/medhopqa and benchmark https://www.codabench.org/competitions/7609/ △ Less

Submitted 12 May, 2026; originally announced May 2026.

GW240925 and GW250207: Astrophysical Calibration of Gravitational-wave Detectors

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith , et al. (1817 additional authors not shown)

Abstract: GW240925 and GW250207 are two loud gravitational-wave signals from binary black hole coalescences observed with network signal-to-noise ratios $\sim 32$ and $\sim 69$, respectively, by the LIGO Hanford--LIGO Livingston--Virgo network. Gravitational-wave signals from coalescing binaries have characteristic phase and amplitude evolution predicted by general relativity. These signal waveforms, togeth… ▽ More GW240925 and GW250207 are two loud gravitational-wave signals from binary black hole coalescences observed with network signal-to-noise ratios $\sim 32$ and $\sim 69$, respectively, by the LIGO Hanford--LIGO Livingston--Virgo network. Gravitational-wave signals from coalescing binaries have characteristic phase and amplitude evolution predicted by general relativity. These signal waveforms, together with measured instrumental calibration uncertainties, are used to infer source parameters. However, for sufficiently loud detections it is possible to constrain the calibration of the detectors directly using the signals themselves. We present the first informative astrophysical measurements of gravitational-wave detector calibration. For GW240925, we verify the inference of Hanford calibration from the astrophysical signal through cross-checks with known calibration errors obtained from in-situ measurements. At the time of GW250207, the Hanford detector was not fully stabilized, leading to elevated calibration uncertainties; thus, astrophysical calibration is essential to obtain accurate data and to enable source localization. These well-localized, high signal-to-noise observations have the potential to offer precise measurements of source properties, stringent tests of general relativity, and informative dark siren measurements, provided that calibration uncertainties are properly incorporated. As detector sensitivity improves, astrophysical calibration will become an increasingly valuable complement to in-situ calibration measurements. Obtaining accurate calibration will be essential for precision gravitational-wave science. △ Less

Submitted 17 August, 2026; v1 submitted 12 May, 2026; originally announced May 2026.

Comments: 38 pages (11 pages author list, 7 pages main paper, 8 pages references, 12 pages supplemental material), 15 figures (4 in main text, 11 in supplemental material); data products available from https://doi.org/10.5281/zenodo.18600070

Report number: LIGO-P2500565

Journal ref: Phys. Rev. Lett. 137, 071401 (2026)

Searches for Binary Mergers with Sub-solar Mass Components in Data from the First Part of LIGO--Virgo--KAGRA's Fourth Observing Run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith , et al. (1810 additional authors not shown)

Abstract: We report on a gravitational wave search for compact binary coalescences involving at least one component with mass between $0.2\,M_\odot$ to $1\,M_\odot$, and ratio of component masses between 0.1 and 1. The analysis uses data collected by the LIGO detectors between May 24 2023 15:00 UTC and January 16 2024 16:00 UTC. No statistically significant sub-solar mass candidates were identified by the p… ▽ More We report on a gravitational wave search for compact binary coalescences involving at least one component with mass between $0.2\,M_\odot$ to $1\,M_\odot$, and ratio of component masses between 0.1 and 1. The analysis uses data collected by the LIGO detectors between May 24 2023 15:00 UTC and January 16 2024 16:00 UTC. No statistically significant sub-solar mass candidates were identified by the participating search algorithms. We report the detection sensitivity of the current searches to the target sub-solar mass black hole population. With the absence of detections, we place upper limits on the merger rate of sub-solar mass black holes, ranging from 110 ${\rm Gpc^{-3}\,yr^{-1}}$ to 10000 ${\rm Gpc^{-3}\,yr^{-1}}$ at 90\% confidence. We constrain two illustrative dark matter scenarios that can form sub-solar mass compact objects with these searches: primordial black holes, and dark black holes forming in a dissipative dark matter model. For late-forming primordial black hole binaries, our search excludes the fraction of dark matter in primordial black holes to be $\leq 1$ only for masses above $0.9\,M_\odot$. In the early-formation scenario, we limit this fraction to be $\leq 7\%$ at $1\,M_\odot$, and $\leq 40\%a$ at $0.35\,M_\odot$. For the dissipative model, the excluded region in the parameter space of dark matter fraction in dark black holes and their minimum possible mass extends down to (0.9 to 1.2) $\times 10^{-5}$ at $1\,M_\odot$ with no constraints below $0.02\,M_\odot$. For the first time, we report the detection sensitivity of our searches to binaries with sub-solar mass neutron stars, and place the 90\% confidence merger rate limit at (570 to 710) ${\rm Gpc^{-3}\,yr^{-1}}$ for a population with component masses distributed uniformly down to $0.5\,M_\odot$. △ Less

Submitted 23 July, 2026; v1 submitted 6 May, 2026; originally announced May 2026.

Report number: LIGO-P2400387

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations

Authors: Zhao Wei, Kenneth Hor Cheng Koh, Sheng Yuan Chin, James Chun Yip Chan, Chin Chun Ooi, Yew-Soon Ong

Abstract: Solving inverse problems in dynamical systems governed by high-dimensional coupled ordinary differential equations (ODEs) is a ubiquitous challenge in scientific machine learning. In many real-world applications, researchers seek to uncover unknown parameters or model unknown dynamics even as the underlying physics is only partially characterized, and observations are sparse and limited to specifi… ▽ More Solving inverse problems in dynamical systems governed by high-dimensional coupled ordinary differential equations (ODEs) is a ubiquitous challenge in scientific machine learning. In many real-world applications, researchers seek to uncover unknown parameters or model unknown dynamics even as the underlying physics is only partially characterized, and observations are sparse and limited to specific measurable channels. While physics-informed neural networks (PINNs) are ideal for inverse inference under partial observability, existing PINNs typically rely on task-specific joint optimization, which suffers from optimization difficulties and poor generalization. In this paper, we propose a meta-inverse physics-informed neural network (MI-PINN) that reformulates inverse modeling as a two-stage meta-learning problem. MI-PINN first learns a physics-aware representation across multiple tasks, and then performs inverse modeling by optimizing task-specific unknowns while keeping the learned representation fixed. This two-stage formulation significantly reduces the parameter search dimension, thereby improving sample efficiency and enabling accurate inference. To handle multi-scale dynamics common in these high-dimensional ODE systems, we further introduce an adaptive clustering-based multi-branch learning scheme. We demonstrate the effectiveness of MI-PINN on whole-body physiologically based pharmacokinetic (PBPK) models with up to 33 coupled ODEs, using paracetamol and theophylline under intravenous and oral dosing scenarios. Experimental results show that MI-PINN enables accurate recovery of masked kinetic parameters and reconstruction of missing mechanistic terms despite limited clinical observations. △ Less

Submitted 5 May, 2026; originally announced May 2026.

Agentopic: A Generative AI Agent Workflow for Explainable Topic Modeling

Authors: Brice Valentin Kok-Shun, Johnny Chan, Gabrielle Peko, David Sundaram

Abstract: Agentopic is a novel agent-based workflow for explainable topic modeling that leverages the reasoning capabilities of Large Language Models (LLMs). Existing topic modeling approaches such as Latent Dirichlet Allocation (LDA) and BERTopic often lack transparency on how topics are assigned or grouped. Agentopic addresses this by using multiple agents that collaboratively perform topic identification… ▽ More Agentopic is a novel agent-based workflow for explainable topic modeling that leverages the reasoning capabilities of Large Language Models (LLMs). Existing topic modeling approaches such as Latent Dirichlet Allocation (LDA) and BERTopic often lack transparency on how topics are assigned or grouped. Agentopic addresses this by using multiple agents that collaboratively perform topic identification, validation, hierarchical grouping, and natural language explanation. This design enables users to trace the reasoning behind topic assignments, enhancing interpretability without sacrificing accuracy. When seeded with topics from the British Broadcasting Corporation (BBC) dataset, Agentopic achieves an F1-score of 0.95, matching GPT-4.1, improving on LDA (0.93), and close to BERTopic (0.98). We used Agentopic to augment the BBC dataset with generated explanations to improve the dataset's richness and context. The unseeded Agentopic generated 2045 semantically coherent topics organized across six hierarchical levels, vastly enriching the original five-category structure. By embedding explainability throughout the workflow, Agentopic offers an interpretable alternative to black-box models, making it particularly valuable for crucial applications like finance and healthcare. △ Less

Submitted 1 April, 2026; originally announced May 2026.

Comments: 16 pages, 2 figures

ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?

Authors: Joey Chan, Yikun Han, Jingyuan Chen, Samuel Fang, Lauren D. Gryboski, Alexandra Lee, Sheel Tanna, Qingqing Zhu, Zhiyong Lu, Lucy Lu Wang, Yue Guo

Abstract: Plain Language Summaries (PLS) aim to make research accessible to lay readers, but they are typically written in a one-size-fits-all style that ignores differences in readers' information needs and comprehension. In health contexts, this limitation is particularly important because misunderstanding scientific information can affect real-world decisions. Large language models (LLMs) offer new oppor… ▽ More Plain Language Summaries (PLS) aim to make research accessible to lay readers, but they are typically written in a one-size-fits-all style that ignores differences in readers' information needs and comprehension. In health contexts, this limitation is particularly important because misunderstanding scientific information can affect real-world decisions. Large language models (LLMs) offer new opportunities for personalizing PLS, but it remains unclear whether personalization helps, which strategies are most effective, and how to balance personalization with safety. We introduce ReLay, a dataset of 300 participant--PLS pairs from 50 lay participants in both static (expert-written) and interactive (LLM-personalized) settings. ReLay includes user characteristics, health information needs, information-seeking behavior, comprehension outcomes, interaction logs, and quality ratings. We use ReLay to evaluate five LLMs across two personalization methods. Personalization improves comprehension and perceived quality, but it also raises the risk of reinforcing user biases and introducing hallucinations, revealing a trade-off between personalization and safety. These findings highlight the need for personalization methods that are both effective and trustworthy for diverse lay audiences. △ Less

Submitted 1 May, 2026; originally announced May 2026.

Digital Simulation of Non-Hermitian Knotted Bands on Quantum Hardware

Authors: Truman Yu Ng, Yuzhu Wang, Wei Jie Chan, Ruizhe Shen, Tianqi Chen, Ching Hua Lee

Abstract: Knots and links represent a fundamental motif of non-local connectivity that permeates the physical sciences from string theory to protein folds. While spectral braiding has been explored in two-band non-Hermitian models across various platforms, its direct simulation and characterization on programmable quantum hardware, particularly beyond two strands, remains a formidable challenge due to the l… ▽ More Knots and links represent a fundamental motif of non-local connectivity that permeates the physical sciences from string theory to protein folds. While spectral braiding has been explored in two-band non-Hermitian models across various platforms, its direct simulation and characterization on programmable quantum hardware, particularly beyond two strands, remains a formidable challenge due to the limitations of variational optimization in these systems. Here, we introduce a family of non-Hermitian multi-band twister models and implement a non-variational protocol to characterize their complex braided band structures on a programmable superconducting quantum processor. By mapping the winding of eigenstates to the spectral topology, we devise an efficient measurement strategy that extracts braid information, including braid words and knot invariants like the Alexander and Jones polynomials, without requiring full spectral tomography or repeated optimization. We experimentally demonstrate the reconstruction of complicated knots and links such as the Hopf chain and Solomon's knot. Our approach provides a general framework for investigating exotic non-Hermitian topology on near-term quantum devices, opening a route to simulate more sophisticated topological structures in knot theory. △ Less

Submitted 29 April, 2026; originally announced April 2026.

Comments: 48 pages, 11 figures, 3 tables