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S. Wang

Publications and source records attributed to S. Wang.

At least 19 recordsLinked to original sources
arXiv2026

High-Repetition-Rate Laser-Driven Fast Neutron Generation from Planar Liquid Heavy Water Jets

We demonstrate a high-repetition-rate, directional pitcher-catcher neutron source employing a continuously flowing, ambient-temperature liquid jet pitcher and a beryllium catcher target. Proton or deuteron beams are accelerated at 0.5 Hz from water (H$_{2}$O) or heavy water (D$_{2}$O) sheet jets using the $2ω$ ALEPH laser at Colorado State University. Deuteron-induced neutron generation shows an average flux enhancement in the target normal direction of 13x compared to proton-induced neutron generation, achieving peak fluxes of $7.9\times10^{5}$ neutrons/sr. The experimentally predicted ion-to-neutron conversion efficiency of 1.5$\times 10^{-5}$ for protons and 1.1$\times 10^{-3}$ for deuterons indicates a significant yield contribution from the deuteron breakup reaction. High shot-to-shot stability neutron spectra up to 8.7~MeV ($^9$Be(d,n)$^{10}$B) are observed for more than 200 consecutive shots.

physics.plasm-ph↗
arXiv2026

Open-H-RF: A Large-Scale Ultrasound Raw Channel Dataset Initiative

Medical ultrasound is a widely accessible, real-time imaging modality, yet progress in data-driven ultrasound research is constrained by the scarcity of large, open collections of raw channel data. Existing public datasets are predominantly based on reconstructed images, while the smaller number of open raw channel datasets is generally specialized to individual reconstruction or imaging tasks, limiting the development of general-purpose methods and foundation models that operate directly on ultrasound signals. While interpretive tasks can be performed on reconstructed images, many of the key technical challenges in ultrasound imaging, such as aberration correction and reverberation reduction, require the raw channel data itself. We introduce Open-H-RF, a community-driven open dataset initiative comprising approximately 40 TB of medical ultrasound raw channel data in 19,332 acquisitions, contributed by 38 institutions across academia and industry, spanning in-vivo, phantom, and simulated data. Each dataset is annotated with a number of supported tasks, ranging from generalized reconstruction, speed-of-sound estimation, and aberration correction to blood flow imaging, motion estimation, quantitative ultrasound, and image interpretation. Open-H-RF provides a unified, self-contained data format that captures raw channel data together with the acquisition, probe, metadata, and reconstruction information required for reproducible processing across scanners and acquisition schemes. The corpus is publicly hosted under a permissive CC BY 4.0 license and can be streamed programmatically and selectively at scale. By bringing heterogeneous ultrasound data into a common representation, backed by modern data infrastructure, Open-H-RF lowers the barrier to working with raw channel data and aims to open medical ultrasound research to new communities. See https://open-h.github.io/Open-H-RF.

eess.SP↗
arXiv2026

Joint Interference Detection and Identification via Adversarial Multi-task Learning

Precise interference detection and identification are crucial for enhancing the survivability of communication systems in non-cooperative wireless environments. While deep learning (DL) has advanced this field, existing single-task learning (STL) approaches neglect inherent task correlations. Furthermore, emerging multi-task learning (MTL) methods often lack a theoretical foundation for quantifying and modeling task relationships. To bridge this gap, we establish a theoretically grounded MTL framework for joint interference detection, modulation identification, and interference identification. First, we derive an upper bound for the weighted expected loss in MTL frameworks. This bound explicitly connects MTL performance to task similarity, quantified by the Wasserstein distance and learnable task relation coefficients. Guided by this theory, we present the adversarial multi-task interference detection and identification network (AMTIDIN), which integrates adversarial training to minimize distributional discrepancies across tasks and uses adaptive coefficients to model task correlations dynamically. Crucially, we conducted a quantitative analysis of task similarity to reveal intrinsic task relationships, specifically that modulation identification and interference identification share a substantial feature overlap distinct from interference detection. Experiments demonstrate that AMTIDIN outperforms its independently trained single-task counterparts and MTL baselines under the evaluated conditions of limited training data, short signal lengths, and low signal-to-noise ratios (SNRs)

cs.LG↗
arXiv2026

EBS and in-beam $γ$-ray investigation of FCVA-prepared Cr$_2$O$_3$ targets for low-energy $^{16}$O+$^{16}$O fusion experiments

The Cr$_2$O$_3$ solid target for low-energy $^{16}$O+$^{16}$O fusion experiments was fabricated using filtered cathodic vacuum arc (FCVA) deposition. Its composition, oxygen areal density and impurity content were characterized by elastic backscattering spectrometry (EBS), and the impurity-induced background contributions were investigated by in-beam $γ$-ray spectroscopy. EBS results indicate that the Cr$_2$O$_3$ film exhibits good stoichiometry and uniformity, with $^{16}$O areal densities ranging from $(3.24-3.25)\times10^{17}$ atoms/cm$^2$. The EBS analysis reveals a carbon atomic fraction of approximately 1.25-1.29\% in the Cr$_2$O$_3$ layer, while a large amount of carbon impurities are also identified on the surface of Cr substrate. In-beam $γ$-ray spectra reveal prominent transitions associated with $^{27}$Al and $^{24}$Mg at 844, 1015, and 1369 keV, mainly originating from $^{12}$C+$^{16}$O fusion reactions induced by carbon impurities under $^{16}$O irradiation. Meanwhile, characteristic $γ$-rays emissions from evaporation channels of the $^{16}$O+$^{16}$O reaction, including $^{31}$S, $^{31}$P, and $^{28}$Si, were also observed and can be used to extract the $^{16}$O+$^{16}$O fusion cross sections. This work provides an experimental basis for the development of high-purity oxide targets and the optimization of target configurations for future low-background $^{16}$O+$^{16}$O fusion cross section measurements.

physics.ins-det↗
arXiv2026

The DarkLight Experiment at TRIUMF

This paper reports on the commissioning of the DarkLight experiment at the ARIEL superconducting electron linear accelerator located at TRIUMF in Vancouver, Canada. DarkLight was designed to utilize the ARIEL electron beam to search for a new boson, $A^\prime$, which preferentially couples to leptons, with a mass in the range 13-17 MeV/$c^2$. Such a boson could be produced via the $e^-~X\rightarrow e^-~X~A^\prime$ process, and the resulting $A^\prime\rightarrow e^+~e^-$ decay used to reconstruct the invariant mass of the $A^\prime$. The $e^+e^-$ pair is detected using a pair of magnetic spectrometers. Each spectrometer is instrumented with two triple GEM detectors and a scintillating strip hodoscope to trigger the event readout. Electron beam energies between 10 and 30 MeV were used to commission the experiment with a 1$~μ$m thick carbon target. With both spectrometer polarities set to select electrons, elastic and Møller scattering were used to examine detector performance and compare with predicted distributions from Monte Carlo simulations. Planned upgrades to the e-linac will allow searches to be made with beam energies up to 50 MeV using a 1$~μ$m thick tantalum target.

physics.ins-det↗
arXiv2026

Apodex 1.1: Scaling Agentic Intelligence for Complex Work

General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information sources, and executable code, together with state maintenance, failure recovery, and verifiable delivery. We call this \emph{working capability}: sustained, verifiable progress toward a real-world objective. Apodex 1.1 develops this capability along two complementary dimensions. \emph{Environment Scaling} expands the diversity and verifiability of executable file, search, and code environments, while \emph{Agentic Coordination Scaling} trains agents to decompose long-horizon tasks, delegate parallel work, integrate asynchronous results, and replan. A shared execution harness and AgentOS maintain task state and provenance across tools and agents, and training turns environment trajectories and coordination traces into reliable behavior. Across complex professional work, finance, scientific research, mathematics, coding, and search, Apodex 1.1 reaches the leading performance band despite using a substantially smaller model than many frontier systems. The 35B-parameter Apodex 1.1 Mini further retains strong working capability in a locally deployable form. These results ground agentic intelligence in useful, verifiable work completed over time and advance our goal of building a \emph{Heavy-Duty Solver} for ambitious, long-running tasks.

cs.AI↗
arXiv2026

Probing the Size of Neutron and Proton Single-Particle Orbitals from Nucleon Knockout Reactions

The size of neutron and proton single-particle orbitals of $^{52}$Ca, $^{53}$Ca, $^{54}$Ca, and $^{55}$Sc were investigated via nucleon knockout reactions at $\sim$ 230 MeV/nucleon. The determination method is based on the measured fragment momentum distributions in $(p,pn)$ and $(p,2p)$ reactions, which are shown to be sensitive to the spatial extension of the wave function of the knocked-out nucleon, interpreted within the distorted wave impulse approximation (DWIA) framework. A systematic sensitivity study is carried out for the $(p,pn)$ recoil-momentum distribution method and is presented in this work. The experimental momentum distributions are compared to state-of-the-art mean field and $ab$ $initio$ in-medium similarity renormalization group and self-consistent Green's function calculations in combination with DWIA reaction theory calculations. Based on this work, the 1$p$ neutron orbitals are consistently found $0.48-0.78$ fm larger than the $0f_{7/2}$ neutron orbitals in $^{52-54}$Ca, while the size evolution of the valence proton orbitals remains inconclusive due to the large associated statistical uncertainties.

nucl-ex↗
arXiv2026

Compound Interference Recognition for LR-FHSS Satellite IoT Uplinks via Multi-Domain Instance Fusion

Long range-frequency hopping spread spectrum (LR-FHSS) is a promising uplink physical layer for massive low Earth orbit satellite Internet of Things, where low power terminals report short packets from wide area regions with limited terrestrial infrastructure. However, satellite IoT links are exposed to external interference, and the coexistence of multiple interference components can severely degrade receiver reliability and complicate interference mitigation. Existing recognition methods either focus on single interference scenarios or treat each compound interference combination as an independent class, leading to limited generalization or poor scalability. To address this problem, this paper formulates LR-FHSS uplink compound interference recognition as a multi-instance multi-label learning problem and proposes a multi-domain instance fusion method. The proposed method fuses local instances from the time-frequency and frequency domains and aggregates their predictions for bag-level multi-label recognition. A dataset construction pipeline is developed based on the US915 LR-FHSS configuration and incorporates shadowed-Rician fading and time-varying Doppler to emulate practical satellite communication conditions. Considering the difficulty of obtaining labeled compound interference samples in practice, single-to-compound generalization and few-shot compound interference adaptation are investigated as two practical receiver deployment scenarios. Experimental results show that the proposed method improves the overall exact accuracy over the strongest baseline by 14.71 percentage points in single-to-compound generalization and by 14.81 percentage points in few-shot compound interference adaptation for $r=1$.

cs.IT↗
arXiv2026

Development for the Belle II vertex detector upgrade with depleted monolithic active pixel sensors

The vertex detector upgrade project for the Belle II experiment, based on CMOS depleted monolithic active pixel sensor technology, is planned to be carried out in conjunction with the major modification of the interaction region of the SuperKEKB collider during Long Shutdown 2 from 2032 to 2034. The MAPS sensor, named OBELIX currently under development, is derived from the successor to TJ-Monopix2, with modifications implemented to ensure compatibility with the Belle II trigger system. The new vertex detector consists of two layers of four self-supported consecutive OBELIX sensors, and three layers of discrete OBELIX sensors mounted on mechanical support structures with readout flex circuits attached to the sensors. The detector is arranged cylindrically around the beam pipe at radii ranging from 14 mm to 140 mm. The minimization of the material budget is required in order to enhance physics performance. We present an overview of the project and its latest developments, with particular emphasis on the development of low-material-budget flex circuits employing aluminum conductors.

physics.ins-det↗
arXiv2026

Statistical Characteristics of Tunneling States in Strong-Field Atomic Ionization

The state of the tunneling electron under the potential barrier is important in strong laser-atom interaction but is difficult to identify. Recent experiments showed that the tunneling electron may be located in a bound state with high symmetry [Phys. Rev. Lett. 134, 213201 (2025)]. However, the quantitative characteristic of the tunneling state in a tunneling event remains unclear. Here, we study tunneling ionization of atoms in strong circular laser fields. The calculated photoelectron momentum distribution (PMD) through numerical solution of time-dependent Schrödinger equation (TDSE) presents an isotropic ring-shaped distribution and the most probable momentum (MPM) along the ring can be easily identified. The kinetic energy related to MPM is remarkably smaller than that predicted by the strong-field approximation (SFA) that ignores Coulomb potential. Surprisingly, for different target atoms and laser parameters, the kinetic energy difference of MPM between TDSE and SFA is always close to half of the corresponding Coulomb potential at the tunnel exit. This phenomenon can be well described by a proposed model, which indicates that the tunneling electron is in an exit-position-dependent quasibound state agreeing with the virial theorem. These results quantitatively reveal the characteristics of tunneling states from a statistical perspective.

physics.atom-ph↗
arXiv2026

Application of exhaustive simulation flow for advanced performance prediction of monolithic active pixel sensors

Monolithic active pixel sensor (MAPS) developments have pushed the detection performance in various directions, especially relative to timing where nanosecond-level precision is now considered. This evolution calls for a simultaneous upgrade of the simulation tools. We have developed a simulation flow that covers steps from the signal creation in the sensitive volume to the output of the pixel digital logic that performs the time-of-arrival and time-over-threshold (ToA/ToT) measurements. This approach adds several new features to the traditional use the of the TCAD - Allpix Squared duo, among which : the integration of the pixel wells from the layout in order to precisely describe the pixel key characteristics such as leakage and punch-through currents and the coupling of Monte Carlo simulations (Allpix Squared) with high precision electrical simulations (SPICE). The first (Allpix Squared) for the precise description of the current induced at the collection electrode and the second (SPICE) to guarantee high precision simulation of the front-end electronics using realistic signal events. Irradiation is also modeled, both from the charge propagation side (charge trapping) and from the front-end response side (high input signal discharge). We have applied this methodology to the MAPS developed in the context of the Belle II vertex detector upgrade. In this contribution, we detail the key features of the exhaustive simulation flow, present the outcome of the comparison with the TJ-Monopix2 measurements and discuss the interest of the methodology for the development of modern MAPS.

physics.ins-det↗
arXiv2026

Accurate Quantization for Gait Representation Learning

Existing deep learning methods have made significant progress in gait representation learning. Quantization can facilitate the application of gait models as a model-agnostic general compression technique. Typically, appearance-based models binarize inputs into silhouette sequences. However, mainstream quantization methods prioritize minimizing task loss over quantization error, which is detrimental to gait representation learning with binarized inputs. To address this, we propose a differentiable soft quantizer, which better simulates the gradient of the round function during backpropagation. This enables the network to learn from subtle input perturbations. However, our theoretical analysis and empirical studies reveal that directly applying the soft quantizer can hinder network convergence. We addressed this issue by adopting a two-stage training strategy, introducing a soft quantizer during the fine-tuning phase. However, in the first stage of training, we observed a significant change in the output distribution of different samples in the feature space compared to the full-precision network. It is this change that led to a loss in performance. Based on this, we propose an Inter-class Distance-guided Calibration (IDC) strategy to preserve the relative distance between the embeddings of samples with different labels. Extensive experiments validate the effectiveness of our approach, demonstrating state-of-the-art accuracy across various settings and datasets.

cs.CV↗
arXiv2026

MiroThinker-1.7 & H1: Towards Heavy-Duty Research Agents via Verification

We present MiroThinker-1.7, a new research agent designed for complex long-horizon reasoning tasks. Building on this foundation, we further introduce MiroThinker-H1, which extends the agent with heavy-duty reasoning capabilities for more reliable multi-step problem solving. In particular, MiroThinker-1.7 improves the reliability of each interaction step through an agentic mid-training stage that emphasizes structured planning, contextual reasoning, and tool interaction. This enables more effective multi-step interaction and sustained reasoning across complex tasks. MiroThinker-H1 further incorporates verification directly into the reasoning process at both local and global levels. Intermediate reasoning decisions can be evaluated and refined during inference, while the overall reasoning trajectory is audited to ensure that final answers are supported by coherent chains of evidence. Across benchmarks covering open-web research, scientific reasoning, and financial analysis, MiroThinker-H1 achieves state-of-the-art performance on deep research tasks while maintaining strong results on specialized domains. We also release MiroThinker-1.7 and MiroThinker-1.7-mini as open-source models, providing competitive research-agent capabilities with significantly improved efficiency.

cs.CL↗
arXiv2026

Equilibria in non-Euclidean geometries

In this paper, extending the work of Gal'perin (Comm. Math. Phys. 154: 63-84, 1993), we investigate generalizations of the concepts of centroids and static equilibrium points of a convex body in spherical, hyperbolic and normed spaces. In addition, we examine the minimum number of equilibrium points a $2$- or $3$-dimensional convex body can have in these spaces. In particular, we show that every plane convex body in any of these spaces has at least four equilibrium points, and that there are mono-monostatic convex bodies in $3$-dimensional spherical, hyperbolic, and certain normed spaces. Our results are generalizations of results of Domokos, Papadopoulos and Ruina (J. Elasticity 36: 59-66, 1994), and Várkonyi and Domokos (J. Nonlinear Sci. 16: 255-281, 2006) for convex bodies in Euclidean space.

math.MG↗
arXiv2025

Variants of a theorem of Macbeath in finite dimensional normed spaces

A classical theorem of Macbeath states that for any integers $d \geq 2$, $n \geq d+1$, $d$-dimensional Euclidean balls are hardest to approximate, in terms of volume difference, by inscribed convex polytopes with $n$ vertices. In this paper we investigate normed variants of this problem: we intend to find the extremal values of the Busemann volume, Holmes-Thompson volume, Gromov's mass and Gromov's mass$^*$ of a largest volume convex polytope with $n$ vertices, inscribed in the unit ball of a $d$-dimensional normed space.

math.MG↗
arXiv2025

Simulation of the thermoelectric effect in a multi-metallic superconducting cavity

Superconducting radio frequency accelerating cavities made with different material layers, such as copper, Nb or Nb3Sn, are susceptible to thermoelectric effects due to differences in Seebeck coefficients between the metals. A temperature gradient across the surfaces can drive thermoelectric currents, which may impact the cavity performance. A layered Cu/Nb/Nb3Sn single cell cavity was tested with cryocoolers in 2022. Three heaters were mounted on the cavity surface at different locations and three single axis cryogenic fluxgate magnetometers were attached close to the cavity equator. A linear increase in the magnetic field was measured while increasing the heaters power. The cavity setup was analysed with COMSOL and the results showed a trend similar to that observed in the experiment. This contribution details the approach chosen for the simulation and some of the challenges encountered.

physics.acc-ph↗
arXiv2025

A Decentralized Framework for Radio-interferometric Image Reconstruction

The advent of large aperture arrays, such as the ones currently under construction for the SKA project, allows for observing the Universe in the radio-spectrum at unprecedented resolution and sensitivity. To process the enormous amounts of data produced by these telescopes, scalable software pipelines are required. This paper helps address this by proposing a framework that allows for decentralized radio-interferometric image reconstruction, parallelizing by spatial frequency. This is achieved by creating pseudo-full-resolution problems for each node by using the local visibilities together with previous major cycle reconstructed images from the other nodes. We apply the proposed framework to both multiscale CLEAN and sparsity regularized convex reconstruction and compare them to their serial counterparts across four different data sets of varying properties in the context of two visibility partitions. We found that the parallelization framework allows for significantly improved reconstruction times for images of similar quality. This was especially the case for our larger datasets where we were able to achieve close to the optimal $2\times$ speedup.

astro-ph.IM↗
arXiv2025

Einstein Probe Discovery of EP J182730.0-095633: A New Black Hole X-ray Binary Candidate in Faint Outburst?

Black hole X-ray binaries (candidates) currently identified in our galaxy are mainly transient sources, with the majority discovered through the detection of their X-ray outbursts. Among these, only four were found during faint outbursts exhibiting peak X-ray luminosities $L_{\rm X}\lesssim10^{36}~{\rm erg~s^{-1}}$, likely due to the previous lack of sensitive, wide-field monitoring instruments in the X-ray band. In this Letter, we present the discovery of an intriguing X-ray transient, EP J182730.0-095633, via the Einstein Probe (EP) and subsequent multi-wavelength follow-up studies. This transient, located on the Galactic plane, experienced a faint and brief X-ray outburst lasting about 20 days. Its X-ray spectrum is non-thermal and consistent with a power-law model with a nearly constant photon index of $Γ\sim2$ throughout the outburst. A long-lasting millihertz quasi-periodic oscillation (QPO) signal was detected in its X-ray light curve, centered around a frequency of $\sim0.04$ Hz. A transient near-infrared source was identified as its counterpart, although no optical emission was detectable, likely due to significant extinction. A radio counterpart was also observed, displaying an inverted radio spectrum with $α\sim0.45$. The X-ray spectral and temporal characteristics, along with the multi-wavelength properties, indicate that the source is a faint low-mass X-ray binary, with the compact object likely being a black hole. This work demonstrates the potential of the EP in discovering new X-ray binaries by capturing faint-level X-ray outbursts.

astro-ph.HE↗