arXiv subjects

Manpreet Kaur

Publications and source records attributed to Manpreet Kaur.

At least 19 recordsLinked to original sources

arXiv2026

Towards compressed baryonic matter densities: D meson diffusion

We study the spatial diffusion coefficient and the momentum transport coefficients of D mesons through a dense nuclear medium in the relaxation time approximation of the kinetic theory. The in medium modifications of the D meson transport properties are computed in the chiral SU(3) hadronic model. Relaxation time is estimated using dilute and degenerate gas approximations for low and high baryonic densities, respectively. We have noticed that relaxation time and spatial diffusion of D meson decrease rapidly in the low density dilute gas domain and mildly in the high density degenerate gas domain. The detailed result of the present work on D meson diffusion is quite contemporary and important towards the compressed baryonic matter densities which can be assessed in future heavy ion collision experiments.

nucl-th↗

arXiv2026

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks

Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of frontier agents. We introduce OSWorld 2.0, a benchmark of 108 long-horizon computer-use workflows across everyday and professional tasks, designed to capture complex and challenging real-world phenomena. Each task represents a realistic end-to-end workflow that takes human users a median of about 1.6 hours to complete and requires an average of 318 tool calls with Claude Opus 4.7 using maximum thinking, compared with about 30 in OSWorld 1.0. OSWorld 2.0 targets challenge phenomena that are common in real workflows yet underrepresented in prior benchmarks, spanning interaction-design challenges such as streaming interaction and dynamic environments, as well as agent-pattern challenges such as cross-source reasoning, implicit-state inference, and visual-spatial precision. Tasks are grounded in authentic input artifacts and cross-referenced against realistic stateful user profile data, and include separate safety reports auditing safety-sensitive execution. Under our primary binary-completion metric at 500 steps, Claude Opus 4.8 with maximum thinking and batched tool calls scores best but still completes only 20.6% of tasks at a 54.8% partial score; GPT-5.5 is far more token-efficient yet plateaus near 13%. These results show that current agents are still far from professional-level computer use: rather than stumbling on basic GUI control or coding, they lose track of constraints, miss information that arrives mid-task, guess rather than ask the user, and skip verification, struggling most when a task hinges on hidden state they must recover.

cs.AI↗

arXiv2026

Magnetic moments of decuplet baryons in isospin asymmetric magnetized strange matter

We investigate the in-medium masses and magnetic moments of decuplet baryons $(\Delta,\Sigma^*,\Xi^*,\Omega^-)$ in isospin asymmetric magnetized strange matter at finite temperature within a unified chiral effective framework. Medium modifications of baryons are implemented using the chiral SU(3) quark mean-field (CQMF) model, where constituent quarks interact via scalar ($\sigma$, $\zeta$, $\delta$) and vector ($\omega$, $\rho$, $\phi$) meson fields considering the Dirac sea effects. The external magnetic field is incorporated through Landau quantization of charged particles together with anomalous magnetic moments (AMM) of baryons. The resulting in-medium mass of constituent quarks and decuplet baryons obtained from the CQMF model are subsequently employed as input to the chiral constituent quark model ($\chi$CQM) to evaluate magnetic moments of baryons. Contributions from valence quarks, sea quark spin polarizations, and orbital angular momentum of the quark sea are taken into account. Our results provide a systematic understanding of how dense, hot, and magnetized environments influence the magnetic properties of decuplet baryons.

hep-ph↗

arXiv2026

PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design

Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space and fragmented representations of structure, properties, and prior knowledge. This fragmentation leaves many AI models disconnected from physical and experimental reality, restricting their ability to support directly actionable design decisions. Here we introduce PolyFusionAgent, an interactive framework coupling a multimodal polymer foundation model (PolyFusion) with a tool-augmented, literature-grounded design agent (PolyAgent). PolyFusion aligns complementary polymer views including sequence, topology, 3D geometry, and fingerprints across millions of polymers to learn a shared latent space transferable across chemistries and data regimes, improving thermophysical property prediction and enabling property-conditioned generation of chemically valid, structurally novel polymers beyond the reference design space. PolyAgent closes the design loop by linking prediction and inverse design with evidence retrieval from the polymer literature, proposing, evaluating, and contextualizing hypotheses with explicit precedent in one workflow. Together, PolyFusionAgent enables interactive, evidence-linked polymer discovery combining large-scale representation learning, multimodal chemical knowledge, and verifiable scientific reasoning.

cs.AI↗

arXiv2026

A study of $J/\psi$ mass shift and bound states: Impact of $D D$ and $DD^*$ meson loops

We investigate the modification of the $J/\psi$ meson mass in asymmetric nuclear matter at zero and finite temperatures employing an effective Lagrangian approach that considers the contributions of $DD$ and $DD^*$ meson loops. The medium dependence of $D$ meson masses is determined using the hadronic chiral SU(3) model, where scalar condensates are calculated and subsequently utilized in the QCD sum rules approach. Our findings indicate that an increase in baryonic density results in a negative mass shift of the $J/\psi$ meson. This suggests that the $J/\psi$ meson is attracted to nuclear mean fields indicating the possibility of the formation of meson-nucleus bound states. Moreover, we have also determined the binding energy and absorption decay width of the $J/\psi$ meson for both the ground and excited states of $\text{O}^{16}$, $\text{Ca}^{40}$, $\text{Zr}^{90}$, and $\text{Pb}^{208}$ nuclei. These results are expected to contribute to the understanding of experimental data from upcoming studies at Jefferson lab and the facility for antiproton and ion research, where low-momentum charmed mesons can be produced and examined within nuclei.

hep-ph↗

arXiv2025

WARC-Bench: Web Archive Based Benchmark for GUI Subtask Executions

Training web agents to navigate complex, real-world websites requires them to master $\textit{subtasks}$ - short-horizon interactions on multiple UI components (e.g., choosing the correct date in a date picker, or scrolling in a container to extract information). We introduce WARC-Bench (Web Archive Benchmark), a novel web navigation benchmark featuring 438 tasks designed to evaluate multimodal AI agents on subtasks. WARC-Bench enables sandboxed interactions with dynamic and realistic webpages using Web ARChive files. We show that WARC-Bench is challenging for leading computer-use models, with the highest observed success rate being 64.8%. To improve open source models on subtask, we explore two common training techniques: supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR). Experiments show that SFT models obtain a 48.8% success rate on the benchmark. Training with RLVR over SFT checkpoints, even in data-scarce settings, improves the score to 52.8% on WARC-Bench, outperforming many frontier models. Our analysis concludes that mastering these subtasks is essential for robust web planning and navigation, and is a capability not extensively evaluated by existing benchmarks.

cs.LG↗

arXiv2025

A novel method for measuring the Fermi velocity of elemental targets

The right kind of theoretical treatment of direct Coulomb ionization of inner-shell of target atoms including multiple ionization of their outer-shells by using accurate x-ray fluorescence yield data and electron capture by projectile ions from inner-shell electrons of target atoms enables us to fully understand the complex physics issues with the heavy-ion-induced inner-shell ionization phenomenon. Such great success has only been achieved recently [Phys. Rev. A 111 (2025) 042827]. Aftermath, further investigations exhibit such a picture only if the Fermi velocity of the elemental target is accurate, as it takes a significant role in correct evaluation of charge-state distribution of the projectile ions inside the target, which contributes an invaluable share in calculating the electron capture-induced ionization cross section correctly. In this work, we devise a powerful method that enables us to measure the correct and accurate Fermi velocity for almost every elemental metal in the periodic table. As per our present knowledge, this in turn not only improves our understanding of the said complex physics issues one step ahead but also helps move toward further miniaturization of integrated circuits and use the heavy-ion-induced X-ray emission in impurity analysis more reliable and accurate.

physics.atom-ph↗

arXiv2025

Kaon structure modifications in strange hadronic matter

We present the valence quark distributions of the kaons in an isospin asymmetric dense strange medium consisting of nucleons and hyperons. The comparative analysis of in-medium parton distribution functions, electromagnetic form factors, and charge densities with respect to the free space distributions is studied in the light-cone quark model. The medium effects are incorporated in these distribution functions by using the effective quark masses, computed from the chiral SU(3) quark mean field model for finite values of baryonic density, isospin asymmetry, and strangeness fraction parameters. We observe a suppression of the kaon electromagnetic form factors and a redistribution of charge density in high-density strange matter.

hep-ph↗

arXiv2025

$\phi$ meson properties in dense resonance matter at finite temperature

The effective mass and decay width of the $\phi$ meson in the isospin asymmetric hot and dense resonance matter are studied using the effective Lagrangian framework considering the $\phi K \bar K $ interactions at one-loop level. In addition to spin$-1/2$ octet baryons, we consider the effect of resonances $\Delta^{++,+,0,-}, \Sigma^{*\pm,0},\Xi^{*0,-}, \Omega^{-}$, on the properties of $\phi$ meson. The in-medium effects on the $\phi$ meson properties are simulated through the effective masses of kaons and antikaons computed using the chiral SU(3) hadronic mean field model in the presence of resonance baryons. The loop integral appearing in the computation of $\phi$ meson self energies is regularized using the dipole form factor with a cutoff parameter. The presence of resonance baryons within the medium at finite temperature is observed to significantly modify the effective mass and decay width of $\phi$ mesons. Examining the $\phi$ meson masses and decay width within a dense medium is anticipated to be essential for understanding experimental results from heavy-ion collision experiments.

hep-ph↗

arXiv2025

Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI

Despite continuous advancements in cancer treatment, brain metastatic disease remains a significant complication of primary cancer and is associated with an unfavorable prognosis. One approach for improving diagnosis, management, and outcomes is to implement algorithms based on artificial intelligence for the automated segmentation of both pre- and post-treatment MRI brain images. Such algorithms rely on volumetric criteria for lesion identification and treatment response assessment, which are still not available in clinical practice. Therefore, it is critical to establish tools for rapid volumetric segmentations methods that can be translated to clinical practice and that are trained on high quality annotated data. The BraTS-METS 2025 Lighthouse Challenge aims to address this critical need by establishing inter-rater and intra-rater variability in dataset annotation by generating high quality annotated datasets from four individual instances of segmentation by neuroradiologists while being recorded on video (two instances doing "from scratch" and two instances after AI pre-segmentation). This high-quality annotated dataset will be used for testing phase in 2025 Lighthouse challenge and will be publicly released at the completion of the challenge. The 2025 Lighthouse challenge will also release the 2023 and 2024 segmented datasets that were annotated using an established pipeline of pre-segmentation, student annotation, two neuroradiologists checking, and one neuroradiologist finalizing the process. It builds upon its previous edition by including post-treatment cases in the dataset. Using these high-quality annotated datasets, the 2025 Lighthouse challenge plans to test benchmark algorithms for automated segmentation of pre-and post-treatment brain metastases (BM), trained on diverse and multi-institutional datasets of MRI images obtained from patients with brain metastases.

q-bio.OT↗

arXiv2025

Towards full understanding the physics of heavy ion induced inner shell ionization

The complex physics of inner shell ionization of target atoms by heavy ion impact has remained only partially solved for decades. Recently, agreement between theory and experiment has been achieved by considering inner shell ionization of target atoms due to projectile electron capture in addition to direct Coulomb ionization including multiple ionization effects. A thorough investigation exhibits such a picture only if the atomic parameters of the target atoms are correct. In fact, the theoretical approach is found to be right, but the problem arises with the faulty atomic parameters. Furthermore, we show that fluorescence yields play a major role among the atomic parameters. We explore such a powerful method that enables us to measure the correct and accurate fluorescence yields for almost every element in the periodic table. As per our present knowledge, this in turn not only solves the said complex issue fully but also makes the PIXE analysis more reliable and accurate using both light and heavy ions.

physics.atom-ph↗

arXiv2025

Precise charge state distribution of projectile ions through solid targets

The charge state distribution (CSD) of the projectile ions through solid targets in the intermediate energy range (1 MeV/u $<$ E $<$ 4 MeV/u) has a major impact on the collision of the ion atom and accelerator physics. We explore the mean charge states taken from the empirical formula [Schiwietz $et~al.$, Nucl. Inst. Meths. {\bf 225}, 4(2004)] are only good for projectile ions with $Z_1 \le 16$. To solve this issue, we develop a model in which instead of a single formula, if we employ four formulae, the comparative picture between experimental and empirical data becomes impressive. Furthermore, the CSDs with the mean charge state so obtained and the Gaussian distribution function having distribution width given by [Novikov and Teplove, Phys. Lett. {\bf378}, 1286(2014)] compare well with the experimentally measured CSDs for the entire range of projectile ions. We believe that precise CSDs will be highly useful in both ion-atom collision and accelerator physics.

physics.atom-ph↗

arXiv2025

Bremsstrahlung induced atomic processes

The observed spectra in the collisions of neon (Ne) projectiles of 1.8 and 2.1 MeV with an aluminum target (Al) have been successfully segregated from strong bremsstrahlung backgrounds and then analyzed by comparing the transition energies and rates with the theoretical predictions of the flexible atomic structure code and the general purpose relativistic atomic structure package. The spectra contain K{\alpha}, Kh{\alpha} , and K{\alpha}{\alpha} lines. The K{\alpha}{\alpha} emissions are due to two-electron one-photon transitions. Interestingly, the K{\alpha}{\alpha} lines in projectile ions are only seen with 1.8 MeV energy. In contrast, the K{\alpha}{\alpha} lines in the target ions are also well observed with 2.1 MeV energy. Surprisingly, the Al K x-ray line intensities are strongly suppressed, and the K{\alpha}{\alpha} line intensities are unexpectedly enhanced. The underlying physical process is found to be the photoionization caused by intense bremsstrahlung radiation. This photoionization process converts most of the singly ionized K shell states (\approx 82\% at 2.1 MeV) to doubly ionized K shell states. This phenomenon is silently present on many occasions. We take some of such events to validate this remarkable finding. This bremsstrahlung radiation induced secondary ionization process stands as an eye opening incidence to the plasma physics, astronomy and astrophysics communities; may revolutionize these fields of research.

physics.atom-ph↗

arXiv2024

Ensemble Classification-Based Spectrum Sensing Using Support Vector Machine for CRN

As the demand for internet of things (IoT) and device-to-device (D2D) applications in next generation communication systems increases, we are confronted with a challenge of spectrum scarcity. One promising solution to this problem is cognitive radio network (CRN), where the key element is the spectrum - a valuable and sharable natural resource that should not be wasted. To design efficient and sustainable networks for the future, it is crucial to ensure that spectrum sensing is not only accurate and rapid, but also energy-efficient. Spectrum sensing is a critical aspect of CRNs, and this study is mainly focused on it. In this research, we employ the supervised machine learning algorithm, support vector machine (SVM), to detect primary users (PU). We investigate different variants of SVM, including linear, polynomial, and Gaussian radial basic function (RBF), and employ an ensemble classification-based approach to improve the classifier's performance and productivity. The simulation results demonstrate that the ensemble classifier achieves the highest performance.

cs.IT↗

arXiv2024

Cross Domain Adaptation using Adversarial networks with Cyclic loss

Deep Learning methods are highly local and sensitive to the domain of data they are trained with. Even a slight deviation from the domain distribution affects prediction accuracy of deep networks significantly. In this work, we have investigated a set of techniques aimed at increasing accuracy of generator networks which perform translation from one domain to the other in an adversarial setting. In particular, we experimented with activations, the encoder-decoder network architectures, and introduced a Loss called cyclic loss to constrain the Generator network so that it learns effective source-target translation. This machine learning problem is motivated by myriad applications that can be derived from domain adaptation networks like generating labeled data from synthetic inputs in an unsupervised fashion, and using these translation network in conjunction with the original domain network to generalize deep learning networks across domains.

cs.LG↗

arXiv2024

Multi-View 3D Reconstruction using Knowledge Distillation

Large Foundation Models like Dust3r can produce high quality outputs such as pointmaps, camera intrinsics, and depth estimation, given stereo-image pairs as input. However, the application of these outputs on tasks like Visual Localization requires a large amount of inference time and compute resources. To address these limitations, in this paper, we propose the use of a knowledge distillation pipeline, where we aim to build a student-teacher model with Dust3r as the teacher and explore multiple architectures of student models that are trained using the 3D reconstructed points output by Dust3r. Our goal is to build student models that can learn scene-specific representations and output 3D points with replicable performance such as Dust3r. The data set we used to train our models is 12Scenes. We test two main architectures of models: a CNN-based architecture and a Vision Transformer based architecture. For each architecture, we also compare the use of pre-trained models against models built from scratch. We qualitatively compare the reconstructed 3D points output by the student model against Dust3r's and discuss the various features learned by the student model. We also perform ablation studies on the models through hyperparameter tuning. Overall, we observe that the Vision Transformer presents the best performance visually and quantitatively.

cs.CV↗

arXiv2024

Effect of Asymmetric Nuclear Medium on the Valence Quark Structure of the Kaons

The role of asymmetric nuclear medium on the properties of kaon is investigated at zero and finite temperature employing a hybrid approach integrating the light cone quark model (LCQM) and the chiral SU(3) quark mean field (CQMF) model. The in-medium quark masses are calculated within the CQMF model and are used as inputs to study the medium modifications in the kaon properties. In particular, we have analysed the impact of baryonic density, isospin asymmetry and temperature on the weak decay constant, distribution amplitudes (DAs) and parton quark distributions (PDFs) of valence quark structure of kaons. The effects of isospin asymmetry on the kaon doublet $K =\left(\begin{array}{c} K^{+} \\ K^{0} \end{array} \right)$ and antikaon doublet $\bar{K}$= ($K^-, \bar{K}^0$) are also studied. In order to compare with future experiments, we have also evolved the in-medium DAs and PDFs of kaons to $Q^2=16$ GeV$^2$. As compared to the temperature and isospin asymmetry, change in baryonic density of the nuclear medium makes more significant changes to the DAs and PDFs of kaons.

hep-ph↗

arXiv2024

Kaons and antikaons in isospin asymmetric dense resonance matter at finite temperature

We study the in-medium properties of kaons and antikaons in isospin asymmetric hot and dense resonance matter within the chiral SU(3) hadronic mean field model. Along with nucleons and hyperons, the interactions of $K$ and $\bar K$ mesons with all decuplet baryons ($\Delta^{++,+,0,-}, \Sigma^{*\pm,0},\Xi^{*0,-}, \Omega^{-}$) are explicitly considered in the dispersion relations. The properties of mesons in the chiral SU(3) model are modified at finite density and temperature of asymmetric resonance matter through the exchange of scalar fields $\sigma, \zeta$ and $\delta$ and the vector fields $\omega, \rho$ and $\phi$. The presence of resonance baryons in the medium at finite temperature is observed to modify significantly the effective masses of $K$ and $\bar{K}$ mesons. We also calculated the optical potentials of kaons and antikaons as a function of momentum in resonance matter. The present study of in-medium masses and optical potentials of kaons and antikaons will be important for understanding the experimental observables from the heavy-ion collision experiments where hot and dense matter may be produced. Our results indicate that when resonance baryons are present within the medium at finite baryonic density, the mass reduction of kaons and antikaons becomes more pronounced as the temperature of the medium increases from zero to 100 and 150 MeV. The study of the optical potentials of kaons and antikaons reveals a stronger correlation with strangeness fraction compared to isospin asymmetry.

hep-ph↗