Showing 1–50 of 165 results for author: Mishra, A K

Comparing GNSS Derived Sea Ice Drift in the Arctic and Antarctic using Rotary Spectra and Principal Component Analysis

Authors: James H. Hepworth, Amit Kumar Mishra

Abstract: Sea ice drift underpins air-sea-ice coupling and model evaluation, but the Southern Ocean remains chronically undersampled relative to the Arctic. This work presents a cross-polar comparison of GNSS-tracked ice-drift time series using rotary spectral analysis, principal component analysis, inter-buoy coherence, complementary shape- and amplitude-sensitive spectral differences. Arctic data are aggr… ▽ More Sea ice drift underpins air-sea-ice coupling and model evaluation, but the Southern Ocean remains chronically undersampled relative to the Arctic. This work presents a cross-polar comparison of GNSS-tracked ice-drift time series using rotary spectral analysis, principal component analysis, inter-buoy coherence, complementary shape- and amplitude-sensitive spectral differences. Arctic data are aggregated into Beaufort Gyre and Transpolar Drift seasonal composites (2017--2024); Antarctic data comprise eight heterogeneous campaigns (2000--2022) with small buoy counts and short durations. After common quality control, the clearest cross-polar similarity is spectral organisation: both regions show strong low-frequency variance and a hemisphere-appropriate rotary enhancement near the Coriolis frequency, interpreted cautiously as a combined inertial--semidiurnal response. Coherence is highest at synoptic scales and declines toward higher frequencies. Southern Ocean campaigns occupy a higher-energy envelope, so similar band structure does not imply similar drift amplitude. Principal components capture much array-scale motion, but high cumulative variance does not substitute for dense sampling of smaller-scale processes. The results provide transferable frequency-resolved benchmarks (dominant variance below 0.5 cpd and in the near-inertial band, an expanded Arctic reference, and explicit separation of spectral shape from amplitude) to inform future observing-system design without assuming identical dynamical regimes. △ Less

Submitted 19 August, 2026; originally announced August 2026.

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks

Authors: Ashutosh Kumar Mishra, Emma Tolley, Nicolas Cerardi

Abstract: Generative machine learning models have recently emerged as powerful tools for producing cosmological simulations. However, many existing emulators do not explicitly enforce the underlying physical dynamics governing cosmological evolution, often leading to artifacts and poor adherence to the evolution equations. In this work, we present a physics-informed generative U-Net framework for fuzzy dark… ▽ More Generative machine learning models have recently emerged as powerful tools for producing cosmological simulations. However, many existing emulators do not explicitly enforce the underlying physical dynamics governing cosmological evolution, often leading to artifacts and poor adherence to the evolution equations. In this work, we present a physics-informed generative U-Net framework for fuzzy dark matter (FDM) that addresses two complementary tasks: (i) the evolution of cosmological fields from initial conditions to an arbitrary cosmological scale factor and (ii) the super-resolution of FDM simulations at a specified cosmological scale factor. Our model incorporates a physics-informed loss function that explicitly enforces consistency with the underlying Schrödinger-Poisson (SP) dynamics during training. For the evolution task, we find that the inclusion of this physics-based loss significantly improves the quality of the predicted simulations, even when only a small amount of training data is available. Using only 20% of the training data, the model accurately reproduces the target simulations in a 1 $h^{-1}$ Mpc box. Furthermore, the framework generalizes effectively across previously unseen realizations of the initial conditions. For the super-resolution task, we present, for the first time, a generative super-resolution model trained on FDM simulations obtained by solving the full SP equations, considering both single and multiple realizations of the initial conditions and analyzing the role of the physics-informed loss in each case. Our approach enables modern generative modeling of cosmological simulations while maintaining physical consistency and substantially reducing generative artifacts. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 21 pages, 7 figures (2 more in Appendix), submitted to ApJ; comments welcome

Sensitivity Analysis of Dynamic Line Rating for ACSR Conductors using IEEE-738

Authors: Shashank Singh, Ashish Kumar Mishra, Vinod M. P., Christian Romeis

Abstract: Dynamic Line Rating (DLR) is a novel technique that enhances the utilization of transmission line capacity. It is nevertheless unclear how much measurement uncertainty in important environmental parameters affects the DLR calculation. Using the IEEE-738 standard, this paper presents a systematic parametric sensitivity analysis of DLR for a 795 kcmil ACSR Drake conductor. The DLR computation encomp… ▽ More Dynamic Line Rating (DLR) is a novel technique that enhances the utilization of transmission line capacity. It is nevertheless unclear how much measurement uncertainty in important environmental parameters affects the DLR calculation. Using the IEEE-738 standard, this paper presents a systematic parametric sensitivity analysis of DLR for a 795 kcmil ACSR Drake conductor. The DLR computation encompasses 832 operating points which includes daytime/nighttime solar scenarios, clear/non-clear atmospheric clearness conditions, wind speeds ranging from 0 to 15.25 m/s, and ambient temperatures between 15 and 50 degrees Celsius. According to sensitivity analysis, wind sensitivity tends to decrease at higher ambient temperatures, whereas temperature sensitivity tends to increase with wind speed. Pearson correlation analysis indicates a strong negative linear association between DLR and ambient temperature, and a strong positive linear association with wind speed. A regression model incorporates both individual and interactive effects of wind and temperature, and explains over 93% of the observed DLR variability across all cases. Finally, the observations serve as a guide for operational planning and uncertainty assessment in DLR-based transmission systems. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Governance by Design: Architecting Agentic AI for Organizational Learning and Scalable Autonomy

Authors: Nelly Dux, Cristina Alaimo, Philippe Roussiere, Abhishek Kumar Mishra

Abstract: Agentic AI systems - systems that can pursue goals through multi-step planning and tool-mediated action with limited direct supervision - are moving from experimental prototypes to enterprise deployments. This transition introduces tensions in implementation, scaling, and governance: organizations seek scalable autonomy for knowledge and coordination work, yet must preserve accountability, safety,… ▽ More Agentic AI systems - systems that can pursue goals through multi-step planning and tool-mediated action with limited direct supervision - are moving from experimental prototypes to enterprise deployments. This transition introduces tensions in implementation, scaling, and governance: organizations seek scalable autonomy for knowledge and coordination work, yet must preserve accountability, safety, cost control, and responsibility as systems initiate actions, access enterprise data, and evolve through iterative updates. Building on an in-depth qualitative case of a large IT services company's 2025 development and staged rollout of an agentic system integrated with enterprise tools; we show that governance is implemented through concrete architectural and working arrangements that determine what the system is allowed to do, which tools and data it can use, how memory is handled, and how performance improvements are introduced over time. We then distill seven lessons that explain how to build effective governance into agentic AI during operationalization and scaling. △ Less

Submitted 17 April, 2026; originally announced May 2026.

Comments: 17 pages, 1 figure, 3 tables

AirCatch: Effectively tracing advanced tag-based trackers

Authors: Abhishek Kumar Mishra, Swadeep, Guevara Noubir, Mathieu Cunche

Abstract: Tag-based tracking ecosystems help users locate lost items, but can be leveraged for unwanted tracking and stalking. Existing protocol-driven defenses and prior academic solutions largely assume stable identifiers or predictable beaconing. However, identifier-based defenses fundamentally break down against advanced rogue trackers that aggressively rotate identifiers. We present AirCatch, a passive… ▽ More Tag-based tracking ecosystems help users locate lost items, but can be leveraged for unwanted tracking and stalking. Existing protocol-driven defenses and prior academic solutions largely assume stable identifiers or predictable beaconing. However, identifier-based defenses fundamentally break down against advanced rogue trackers that aggressively rotate identifiers. We present AirCatch, a passive detection system that exploits a physical-layer constraint: while logical identifiers can change arbitrarily fast, the transmitter's analog imprint remains stable and reappears as a compact and persistently occupied region in Carrier Frequency Offset (CFO) feature space. AirCatch advances the state of the art along three axes: (i) a novel, modulation-aware CFO fingerprint that augments packet-level CFO with content-independent CFO components that amplify device distinctiveness; (ii) a new tracking detection algorithm based on high core density and persistence that is robust to contamination and evasion through per-identifier segmentation; and (iii) an ultra-low-cost receiver, an approximately 10 dollar BLE SDR named BlePhasyr, built from commodity components, that makes RF fingerprinting based detection practical in resource-constrained deployments. We evaluate AirCatch across Apple, Google, Tile, and Samsung tag families in multi-hour captures, systematically stress-test evasion using a scenario generator over a grid of transmission and rotation periods, and validate in diverse real-world mobility traces including home and office commutes, public transport, car travel, and airport journeys while sweeping background tag density. Across these stress tests, AirCatch achieves no false positives and early detection over a wide range of adversarial configurations and environments, degrading gracefully only in extreme low-rate regimes that also reduce attacker utility. △ Less

Submitted 7 February, 2026; originally announced February 2026.

Deep Search for Joint Sources of Gravitational Waves and High-Energy Neutrinos with IceCube During the Third Observing Run of LIGO and Virgo

Authors: The IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Argüelles, Y. Ashida, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, J. Baines-Holmes, A. Balagopal V., S. W. Barwick, S. Bash, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus , et al. (2193 additional authors not shown)

Abstract: The discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection of high-energy neutrinos and gravitational waves would provide insight into cosmic processes, from the dynamics of compact object mergers and stellar collapses to the mechanisms driving relativistic outflows. The joint… ▽ More The discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection of high-energy neutrinos and gravitational waves would provide insight into cosmic processes, from the dynamics of compact object mergers and stellar collapses to the mechanisms driving relativistic outflows. The joint detection of multiple cosmic messengers can also elevate the significance of the common observation even when some or all of the constituent messengers are sub-threshold, i.e. not significant enough to declare their detection individually. Using data from the LIGO, Virgo, and IceCube observatories, including sub-threshold events, we searched for common sources of gravitational waves and high-energy neutrinos during the third observing run of Advanced LIGO and Advanced Virgo detectors. Our search did not identify significant joint sources. We derive constraints on the rate densities of joint sources. Our results constrain the isotropic neutrino emission from gravitational-wave sources for very high values of the total energy emitted in neutrinos (> $10^{52} - 10^{54}$ erg). △ Less

Submitted 28 January, 2026; v1 submitted 12 January, 2026; originally announced January 2026.

Comments: Data release at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/34B5AP

Efficient Aspect Term Extraction using Spiking Neural Network

Authors: Abhishek Kumar Mishra, Arya Somasundaram, Anup Das, Nagarajan Kandasamy

Abstract: Aspect Term Extraction (ATE) identifies aspect terms in review sentences, a key subtask of sentiment analysis. While most existing approaches use energy-intensive deep neural networks (DNNs) for ATE as sequence labeling, this paper proposes a more energy-efficient alternative using Spiking Neural Networks (SNNs). Using sparse activations and event-driven inferences, SNNs capture temporal dependenc… ▽ More Aspect Term Extraction (ATE) identifies aspect terms in review sentences, a key subtask of sentiment analysis. While most existing approaches use energy-intensive deep neural networks (DNNs) for ATE as sequence labeling, this paper proposes a more energy-efficient alternative using Spiking Neural Networks (SNNs). Using sparse activations and event-driven inferences, SNNs capture temporal dependencies between words, making them suitable for ATE. The proposed architecture, SpikeATE, employs ternary spiking neurons and direct spike training fine-tuned with pseudo-gradients. Evaluated on four benchmark SemEval datasets, SpikeATE achieves performance comparable to state-of-the-art DNNs with significantly lower energy consumption. This highlights the use of SNNs as a practical and sustainable choice for ATE tasks. △ Less

Submitted 10 January, 2026; originally announced January 2026.

Task-Aware Morphology Optimization of Planar Manipulators via Reinforcement Learning

Authors: Arvind Kumar Mishra, Sohom Chakrabarty

Abstract: In this work, Yoshikawa's manipulability index is used to investigate reinforcement learning (RL) as a framework for morphology optimization in planar robotic manipulators. A 2R manipulator tracking a circular end-effector path is first examined because this case has a known analytical optimum: equal link lengths and the second joint orthogonal to the first. This serves as a validation step to tes… ▽ More In this work, Yoshikawa's manipulability index is used to investigate reinforcement learning (RL) as a framework for morphology optimization in planar robotic manipulators. A 2R manipulator tracking a circular end-effector path is first examined because this case has a known analytical optimum: equal link lengths and the second joint orthogonal to the first. This serves as a validation step to test whether RL can rediscover the optimum using reward feedback alone, without access to the manipulability expression or the Jacobian. Three RL algorithms (SAC, DDPG, and PPO) are compared with grid search and black-box optimizers, with morphology represented by a single action parameter phi that maps to the link lengths. All methods converge to the analytical solution, showing that numerical recovery of the optimum is possible without supplying analytical structure. Most morphology design tasks have no closed-form solutions, and grid or heuristic search becomes expensive as dimensionality increases. RL is therefore explored as a scalable alternative. The formulation used for the circular path is extended to elliptical and rectangular paths by expanding the action space to the full morphology vector (L1, L2, theta2). In these non-analytical settings, RL continues to converge reliably, whereas grid and black-box methods require far larger evaluation budgets. These results indicate that RL is effective for both recovering known optima and solving morphology optimization problems without analytical solutions. △ Less

Submitted 16 November, 2025; originally announced November 2025.

Comments: 10 pages, 11 figures, It is submitted as a journal option paper associated with the IFAC World Congress 2026

3D-HQAM Constellation Design and Performance Evaluation under AWGN

Authors: Sukhsagar, Nagendra Kumar, Ambuj Kumar Mishra, Vimal Bhatia, Ondrej Krejcar

Abstract: This paper proposes a simple and effective method for constructing higher-order three-dimensional (3D) signal constellations, aiming to enhance the reliability of digital communication systems. The approach systematically extends the conventional two-dimensional hexagonal quadrature amplitude modulation (2D-HQAM) constellation into a 3D-HQAM signal space, forming structured lattice configurations.… ▽ More This paper proposes a simple and effective method for constructing higher-order three-dimensional (3D) signal constellations, aiming to enhance the reliability of digital communication systems. The approach systematically extends the conventional two-dimensional hexagonal quadrature amplitude modulation (2D-HQAM) constellation into a 3D-HQAM signal space, forming structured lattice configurations. To address the increased decision complexity resulting from a larger number of constellation points, a dimension reduction (DR) technique is introduced, allowing the derivation of closed-form symbol error probability (SEP) expressions under additive white Gaussian noise (AWGN) conditions. Theoretical SEPs closely match simulation results, validating the accuracy of the proposed method. The minimum Euclidean distance (MED) of the 3D constellations shows a minimum increase of 12.14% over 2D constellation for 8-HQAM, reaching up to 160.81% for 1024-HQAM constellations. This significant improvement in MED leads to enhanced error performance. Therefore, the proposed 3D constellations are promising candidates for high-quality and reliable next-generation digital communication systems. △ Less

Submitted 14 November, 2025; originally announced November 2025.

Comments: 5 pages, 22 figures, 2 tables, 1 algorithm

Pressure-Driven Phase Evolution and Optoelectronic Properties of Lead-free Halide Perovskite Rb$_2$TeBr$_6$

Authors: Suvashree Mukherjee, Asish Kumar Mishra, K. A. Irshad, Boby Joseph, Goutam Dev Mukherjee

Abstract: The structural, vibrational, and optical properties of Rb$_2$TeBr$_6$ have been investigated under high pressure using synchrotron X-ray diffraction, Raman spectroscopy, photoluminescence (PL), and optical absorption measurements. At ambient conditions, Rb$_2$TeBr$_6$ crystallizes in the cubic Fm-3m structure, which remains stable below 8.0 GPa. Within this pressure range, subtle inter-octahedral… ▽ More The structural, vibrational, and optical properties of Rb$_2$TeBr$_6$ have been investigated under high pressure using synchrotron X-ray diffraction, Raman spectroscopy, photoluminescence (PL), and optical absorption measurements. At ambient conditions, Rb$_2$TeBr$_6$ crystallizes in the cubic Fm-3m structure, which remains stable below 8.0 GPa. Within this pressure range, subtle inter-octahedral rotations develop, producing a gradual localized deviation from the ideal cubic framework. This local reorientation facilitates radiative recombination, leading to a pronounced enhancement of PL intensity with pressure up to 2.4 GPa. Beyond this pressure point, enhancement of nonradiative relaxation channels result in gradual PL quenching. Additionally, the PL intensity increases upon the application of an external weak magnetic field. A structural transition to the orthorhombic Pnnm phase occurs at around 8.0 GPa, followed by a monoclinic P$2_1/m$ phase above 10.7 GPa, and eventual amorphization beyond 25.5 GPa. Optical absorption spectra reveal continuous band-gap narrowing upon compression. These findings demonstrate the strong coupling among lattice dynamics, electronic structure, and optical response in Rb$_2$TeBr$_6$, underscoring its potential as a pressure-tunable optoelectronic material △ Less

Submitted 17 April, 2026; v1 submitted 4 November, 2025; originally announced November 2025.

Variational Autoencoder for Calibration: A New Approach

Authors: Travis Barrett, Amit Kumar Mishra, Joyce Mwangama

Abstract: In this paper we present a new implementation of a Variational Autoencoder (VAE) for the calibration of sensors. We propose that the VAE can be used to calibrate sensor data by training the latent space as a calibration output. We discuss this new approach and show a proof-of-concept using an existing multi-sensor gas dataset. We show the performance of the proposed calibration VAE and found that… ▽ More In this paper we present a new implementation of a Variational Autoencoder (VAE) for the calibration of sensors. We propose that the VAE can be used to calibrate sensor data by training the latent space as a calibration output. We discuss this new approach and show a proof-of-concept using an existing multi-sensor gas dataset. We show the performance of the proposed calibration VAE and found that it was capable of performing as calibration model while performing as an autoencoder simultaneously. Additionally, these models have shown that they are capable of creating statistically similar outputs from both the calibration output as well as the reconstruction output to their respective truth data. We then discuss the methods of future testing and planned expansion of this work. △ Less

Submitted 1 November, 2025; originally announced November 2025.

Comments: 6 pages, 5 figures

Journal ref: 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Chemnitz, Germany, 2025

A summary of instruments proposed for observing pulsating variables from the Mt. Abu Observatory

Authors: Anwesh Kumar Mishra, Deekshya Roy Sarkar, Prachi Prajapati, Alka Singh, Prashanth K. Kasarla, Shashikiran Ganesh

Abstract: Pulsating variables play a significant role in shaping modern astronomy. Presently it is an exciting era in observational study of variable stars owing to surveys like OGLE and TESS. The vast number of sources being discovered by these surveys is also creating opportunities for 1-2m class telescopes to provide follow-up observations to characterize these. We present some initial observations of ty… ▽ More Pulsating variables play a significant role in shaping modern astronomy. Presently it is an exciting era in observational study of variable stars owing to surveys like OGLE and TESS. The vast number of sources being discovered by these surveys is also creating opportunities for 1-2m class telescopes to provide follow-up observations to characterize these. We present some initial observations of type-II cepheids from the Mt. Abu observatory and highlight the need for dedicated observing runs of pulsating variables. We also present optical designs for several suggested instruments for the Mt. Abu observatory that will contribute towards this goal. We present designs that are fairly simple and yet take due benefit of the unique telescopes and facilities present at the observatory. △ Less

Submitted 30 October, 2025; originally announced October 2025.

Journal ref: J. Astrophys. Astr. (2024) 45:34

The Model's Language Matters: A Comparative Privacy Analysis of LLMs

Authors: Abhishek K. Mishra, Antoine Boutet, Lucas Magnana

Abstract: Large Language Models (LLMs) are increasingly deployed across multilingual applications that handle sensitive data, yet their scale and linguistic variability introduce major privacy risks. Mostly evaluated for English, this paper investigates how language structure affects privacy leakage in LLMs trained on English, Spanish, French, and Italian medical corpora. We quantify six linguistic indicato… ▽ More Large Language Models (LLMs) are increasingly deployed across multilingual applications that handle sensitive data, yet their scale and linguistic variability introduce major privacy risks. Mostly evaluated for English, this paper investigates how language structure affects privacy leakage in LLMs trained on English, Spanish, French, and Italian medical corpora. We quantify six linguistic indicators and evaluate three attack vectors: extraction, counterfactual memorization, and membership inference. Results show that privacy vulnerability scales with linguistic redundancy and tokenization granularity: Italian exhibits the strongest leakage, while English shows higher membership separability. In contrast, French and Spanish display greater resilience due to higher morphological complexity. Overall, our findings provide the first quantitative evidence that language matters in privacy leakage, underscoring the need for language-aware privacy-preserving mechanisms in LLM deployments. △ Less

Submitted 9 October, 2025; originally announced October 2025.

InSpecLearn4SDL: Interpretable Spectral Features Predict Conductivity in Self-Driving Doped Conjugated Polymer Labs

Authors: Ankush Kumar Mishra, Jacob P. Mauthe, Nicholas Luke, Aram Amassian, Baskar Ganapathysubramanian

Abstract: To accelerate materials discovery using self-driving labs (SDLs), we present a machine learning pipeline that predicts the electrical conductivity of doped conjugated polymers using rapid, non-destructive optical spectroscopy. Our approach automates spectral featurization by combining a genetic algorithm with adaptive area-under-the-curve (AUC) computations, creating a quantitative structure-prope… ▽ More To accelerate materials discovery using self-driving labs (SDLs), we present a machine learning pipeline that predicts the electrical conductivity of doped conjugated polymers using rapid, non-destructive optical spectroscopy. Our approach automates spectral featurization by combining a genetic algorithm with adaptive area-under-the-curve (AUC) computations, creating a quantitative structure-property relationship (QSPR) that links optical response and processing parameters to conductivity. By incorporating SHAP-guided selection and domain-knowledge-based feature expansion, the model matches expert-curated performance while theoretically reducing experimental effort by $\sim 33\%$ by minimizing the need for costly direct conductivity measurements. Notably, the model recovers known physical descriptors in pBTTT and identifies informative tail-state regions correlated with polymer bleaching upon successful doping. This generic, interpretable, small-data-friendly methodology can be extended to other spectroscopic modalities, such as Raman or FTIR, providing a framework for autonomous decision-making in SDLs. △ Less

Submitted 24 January, 2026; v1 submitted 6 September, 2025; originally announced September 2025.

Comments: 37 Pages, 20 Figures

Enhanced Cosmic-Ray Cooling in AGN from Dark Matter Deep Inelastic Scattering

Authors: Linjie Li, Chih-Ting Lu, Arvind Kumar Mishra, Liangliang Su, Lei Wu

Abstract: The diffusion of high-energy cosmic rays (CRs) through the dark matter (DM) spikes of active galactic nuclei entails significant energy loss via interactions with DM. While previous studies of sub-GeV DM have focused on elastic scattering, this process becomes insufficient at higher proton energies and DM masses. In this work, we investigate the CR-DM deep inelastic scattering (DIS) as mediated by… ▽ More The diffusion of high-energy cosmic rays (CRs) through the dark matter (DM) spikes of active galactic nuclei entails significant energy loss via interactions with DM. While previous studies of sub-GeV DM have focused on elastic scattering, this process becomes insufficient at higher proton energies and DM masses. In this work, we investigate the CR-DM deep inelastic scattering (DIS) as mediated by a vector portal. We calculate the DIS contribution to the CR energy loss rate and derive stringent exclusion limits on the CR-DM scattering cross-section for DM masses between $10^{-6}$ GeV and $1$ GeV. For higher CR energies and mediator masses, the resulting CR cooling timescales are reduced by orders of magnitude after involving the DIS contribution, producing stringent constraints that surpass most of current experimental limits. △ Less

Submitted 3 October, 2025; v1 submitted 15 September, 2025; originally announced September 2025.

Comments: 9 pages, 4 figures

Where Should I Study? Biased Language Models Decide! Evaluating Fairness in LMs for Academic Recommendations

Authors: Krithi Shailya, Akhilesh Kumar Mishra, Gokul S Krishnan, Balaraman Ravindran

Abstract: Large Language Models (LLMs) are increasingly used as daily recommendation systems for tasks like education planning, yet their recommendations risk perpetuating societal biases. This paper empirically examines geographic, demographic, and economic biases in university and program suggestions from three open-source LLMs: LLaMA-3.1-8B, Gemma-7B, and Mistral-7B. Using 360 simulated user profiles var… ▽ More Large Language Models (LLMs) are increasingly used as daily recommendation systems for tasks like education planning, yet their recommendations risk perpetuating societal biases. This paper empirically examines geographic, demographic, and economic biases in university and program suggestions from three open-source LLMs: LLaMA-3.1-8B, Gemma-7B, and Mistral-7B. Using 360 simulated user profiles varying by gender, nationality, and economic status, we analyze over 25,000 recommendations. Results show strong biases: institutions in the Global North are disproportionately favored, recommendations often reinforce gender stereotypes, and institutional repetition is prevalent. While LLaMA-3.1 achieves the highest diversity, recommending 481 unique universities across 58 countries, systemic disparities persist. To quantify these issues, we propose a novel, multi-dimensional evaluation framework that goes beyond accuracy by measuring demographic and geographic representation. Our findings highlight the urgent need for bias consideration in educational LMs to ensure equitable global access to higher education. △ Less

Submitted 12 November, 2025; v1 submitted 1 September, 2025; originally announced September 2025.

Comments: Accepted at IJCNLP-AACL 2025 Findings

GWTC-4.0: Population Properties of Merging Compact Binaries

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, S. Ahmadzadeh, L. Aiello, A. Ain, P. Ajith, T. Akutsu, S. Albanesi, R. A. Alfaidi , et al. (1783 additional authors not shown)

Abstract: We detail the population properties of merging compact objects using 158 mergers from the cumulative Gravitational-Wave Transient Catalog 4.0, which includes three types of binary mergers: binary neutron star, neutron star--black hole binary, and binary black hole mergers. We resolve multiple over- and under-densities in the black hole mass distribution: features persist at primary masses of… ▽ More We detail the population properties of merging compact objects using 158 mergers from the cumulative Gravitational-Wave Transient Catalog 4.0, which includes three types of binary mergers: binary neutron star, neutron star--black hole binary, and binary black hole mergers. We resolve multiple over- and under-densities in the black hole mass distribution: features persist at primary masses of $10\,M_\odot$ and $35\,M_\odot$ with a possible third feature at $\sim 20\,M_\odot$. These are departures from an otherwise power-law-like continuum that steepens above $35\,M_\odot$. Binary black holes with primary masses near $10\,M_\odot$ are more likely to have less massive secondaries, with a mass ratio distribution peaking at $q = 0.74^{+0.13}_{-0.13}$, potentially a signature of stable mass transfer during binary evolution. Black hole spins are inferred to be non-extremal, with 90\% of black holes having $χ< 0.57$, and preferentially aligned with binary orbits, implying many merging binaries form in isolation. However, we find a significant fraction, 0.24-0.42, of binaries have negative effective inspiral spins, suggesting many could be formed dynamically in gas-free environments. We find evidence for correlation between effective inspiral spin and mass ratio, though it is unclear if this is driven by variation in the mode of the distribution or the width. (Abridged) △ Less

Submitted 17 September, 2025; v1 submitted 25 August, 2025; originally announced August 2025.

Comments: As part of the Astrophysical Journal Letters Focus Issue on the Gravitational Wave Transient Catalog

Report number: LIGO-P2400004

GWTC-4.0: Methods for Identifying and Characterizing Gravitational-wave Transients

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, S. Ahmadzadeh, L. Aiello, A. Ain, P. Ajith, S. Akcay, T. Akutsu, S. Albanesi, R. A. Alfaidi , et al. (1787 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 fourth release, GWTC-4.0, focusing on the analysis of the first part of the fourth observing run of Advanced LIGO, Advanced Virgo and KAGRA. △ Less

Submitted 29 June, 2026; v1 submitted 25 August, 2025; originally announced August 2025.

Comments: As part of the Astrophysical Journal Letters Focus Issue on the Gravitational Wave Transient Catalog. Published version

Report number: LIGO-P2400300

Journal ref: The Astrophysical Journal Letters, 2026, Volume 1004, Number 2

GWTC-4.0: An Introduction to Version 4.0 of the Gravitational-Wave Transient Catalog

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, S. Ahmadzadeh, L. Aiello, A. Ain, P. Ajith, S. Akcay, T. Akutsu, S. Albanesi, R. A. Alfaidi , et al. (1786 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 data release of this dataset and version 4.0 extends the catalog to include observations made during the first part of the fourth LIGO-Virgo-KAGRA observing run up until 2024 January 31. This paper marks an introduction to a collection of articles related to this version of the catalog, GWTC-4.0. 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 26 June, 2026; v1 submitted 25 August, 2025; originally announced August 2025.

Comments: As part of the Astrophysical Journal Letters Focus Issue on the Gravitational Wave Transient Catalog. Update following peer review

Report number: LIGO-P2400293

Journal ref: The Astrophysical Journal Letters, 2025, Volume 995, Number 1

Optimization of airgap in a monocentric lens assembly and metasurface based anti-reflecting coating in the long-wave IR regime

Authors: Manish Kala, Pawan Singh, Sanjay Kumar Mishra, Unnikrishnan Gopinathan, Ajay Kumar, Akhilesh Kumar Mishra

Abstract: Owing to minimal aberration, larger field-of-view, and high resolution, monocentric lenses are preferred over other imagers in hemispherical image surface scenarios, particularly in the long-wave infrared (LWIR) region. Herein, we study a monocentric lens assembly consisting of a ball lens and two hemispherical shell lenses of given radii of curvature and lens materials to enhance the transmission… ▽ More Owing to minimal aberration, larger field-of-view, and high resolution, monocentric lenses are preferred over other imagers in hemispherical image surface scenarios, particularly in the long-wave infrared (LWIR) region. Herein, we study a monocentric lens assembly consisting of a ball lens and two hemispherical shell lenses of given radii of curvature and lens materials to enhance the transmission of LWIR ranging from 8μm to 12μm wavelength. We optimize the air gaps between the lenses of the assembly for a wider range of incidence angles, assuming antireflecting coating (ARC) on all surfaces of the lenses. Additionally, the effect of temperature variation on the transmittance is also studied to attain an optimum air gap between the lenses. With the variation in incidence angle and temperature, modulations in focal length and spot size are reported for different wavelengths. Further, we propose a metasurface design to replace conventional multilayer ARCs to enhance the transmittance through the lens assembly over the given wavelength range for a wide field-of-view. △ Less

Submitted 24 December, 2025; v1 submitted 18 August, 2025; originally announced August 2025.

Comments: 20 pages, 33 figures (including the figures of the supplementary)

Journal ref: Optics Communications, 2025

On-axis afocal telescopes as framework for Cubesat based astronomical imagers and slit-less spectrographs

Authors: Anwesh Kumar Mishra, Gourav Banerjee, Rekhesh Mohan, Maheswar Gopinathan

Abstract: Cubesats present unique opportunities for observational astronomy in the modern era. They are useful in observing difficult-to-access wavelength regions and long-term monitoring of interesting astronomical sources. However, conventional telescope designs are not necessarily the best fit for restricted envelope of a Cubesat. Additionally, fine-pointing stability on these platforms is difficult due… ▽ More Cubesats present unique opportunities for observational astronomy in the modern era. They are useful in observing difficult-to-access wavelength regions and long-term monitoring of interesting astronomical sources. However, conventional telescope designs are not necessarily the best fit for restricted envelope of a Cubesat. Additionally, fine-pointing stability on these platforms is difficult due to the low mass of the spacecraft and special allocations within the optical design are needed to achieve stable pointing. We propose afocal telescope designs as the framework to realise imagers and low-resolution spectrographs on Cubesat platforms. These designs help reduce the number of components in the optical chain and aim to improve throughput and sensitivity compared to conventional designs. Additionally, they also provide a fine steering mechanism within a collimated beam section. Fine beam steering within the collimated beam section avoids issues of image degradation due to out-of-plane rotation of the image plane or offset in the rotation axis of the mirror. This permits the use of simple and mostly off-the-shelf tip-tilt mirrors for beam steering. The designs discussed here also allow for a standard telescope design to be used in many instrument types; thus reducing the complexity as well as the development time and cost. The optical design, performance and SNR estimations of these designs along with some interesting science cases are discussed. A number of practical aspects in implementation such as guiding, tolerancing, choice of detectors, vibration analysis and laboratory test setups are also presented. △ Less

Submitted 11 July, 2025; originally announced July 2025.

Comments: Accepted to Journal of Astrophysics and Astronomy on June 25th, 2025

Pressure induced ferromagnetic to antiferromagnetic phase transition in transition metal chalcogenide Cr$_{3}$Te$_4$

Authors: Asish Kumar Mishra, Souvick Chakraborty, Bidisha Mukherjee, Mrinmay Sahu, Suvashree Mukherjee, Shubham Purwar, Harekrishna Bhunia, S. Thirupathaiah, Peter Liermann, Satyabrata Raj, Goutam Dev Mukherjee

Abstract: We have carried out a detailed high-pressure investigation on the strongly correlated transition metal chalcogenide $Cr_{3}Te_4$ using Raman spectroscopy and XRD, which is ferromagnetic and metallic at ambient conditions. We find that the monoclinic structure remains stable up to 30 GPa, the highest pressure studied. The Cr-Te bond length and octahedral volume decrease drastically up to 7.6 GPa pr… ▽ More We have carried out a detailed high-pressure investigation on the strongly correlated transition metal chalcogenide $Cr_{3}Te_4$ using Raman spectroscopy and XRD, which is ferromagnetic and metallic at ambient conditions. We find that the monoclinic structure remains stable up to 30 GPa, the highest pressure studied. The Cr-Te bond length and octahedral volume decrease drastically up to 7.6 GPa pressure. The $A_{1g}$ Raman mode shows a red shift up to 7.6 GPa, and the $E_g$ Raman mode shows a sudden drop around the same pressure. Further low-temperature Raman spectroscopic investigation shows that the Raman modes soften at the ferromagnetic to antiferromagnetic phase transition. This suggests a change in the magnetic ordering at high pressure. Our Density Functional Theory (DFT) calculations reveal the change in magnetic ground state from ferromagnetic state to antiferromagnetic state above 7.6 GPa pressure, corroborating our experimental result. △ Less

Submitted 10 July, 2025; originally announced July 2025.

Can Orbital Decay of Accreting Binary Pulsars Probe Dark Matter?

Authors: Arvind Kumar Mishra

Abstract: The merger of binary pulsars in dark matter (DM)-rich environments can result in DM particle accretion, leading to an increase in the individual pulsar masses. In this work, we investigate the effects of DM accretion on the change in orbital period rate of binary pulsars. Our analysis reveals that while DM accretion increases the system's mass, it may also modify the orbital evolution by enhancing… ▽ More The merger of binary pulsars in dark matter (DM)-rich environments can result in DM particle accretion, leading to an increase in the individual pulsar masses. In this work, we investigate the effects of DM accretion on the change in orbital period rate of binary pulsars. Our analysis reveals that while DM accretion increases the system's mass, it may also modify the orbital evolution by enhancing the orbital decay rate. By comparing our results with existing binary pulsar data near Earth's location, we report that the current DM accretion rate is insufficient to place meaningful constraints on DM particle properties. However, we demonstrate that future observations of pulsar mergers in the high DM-density environment of the galactic center could offer a unique opportunity to probe DM microphysics through this mechanism. △ Less

Submitted 8 July, 2025; originally announced July 2025.

Comments: 9 pages, 2 figures, 2 tables, Suggestions and comments are welcome

StateFi: Effectively Identifying Wi-Fi Devices through State Transitions

Authors: Abhishek K. Mishra, Mathieu Cunche

Abstract: Randomized MAC addresses aim to prevent passive device tracking, yet Wi-Fi management frames still leak structured behavioral patterns. Prior work has relied primarily on syntactic probe-request features such as Information Elements (IEs), sequence numbers (SEQ), or RSSI correlations, which degrade in dense environments and fail under aggressive randomization. We introduce StateFi, a fingerprintin… ▽ More Randomized MAC addresses aim to prevent passive device tracking, yet Wi-Fi management frames still leak structured behavioral patterns. Prior work has relied primarily on syntactic probe-request features such as Information Elements (IEs), sequence numbers (SEQ), or RSSI correlations, which degrade in dense environments and fail under aggressive randomization. We introduce StateFi, a fingerprinting framework that models device behavior as finite-state machines (FSMs), capturing both structural transition patterns and temporal execution logic. These FSMs are embedded into compact feature vectors that support efficient similarity computation and supervised classification. Across five heterogeneous campus environments, StateFi achieves 94-97% accuracy for in-network fingerprinting using full management-frame FSMs. With probe-only FSMs, it re-identifies devices under MAC randomization with up to 97% accuracy across large public datasets comprising more than a million frames. When looking at the discrimination accuracy of the model, StateFi reaches 98%, outperforming the strongest prior signature by up to 17 percentage points. These results demonstrate that FSM-level behavioral dynamics form a powerful and largely unmitigated side channel, stable enough to defeat randomization and expressive enough for robust, scalable device identification. △ Less

Submitted 14 January, 2026; v1 submitted 3 July, 2025; originally announced July 2025.

Filters for NIR astronomical photometry: comparison of commercial IRWG filters and designs using OpenFilters

Authors: Anwesh Kumar Mishra, U. S. Kamath

Abstract: The photometric accuracy in the near-infrared (NIR) wavelength range (0.9 -2.6 microns) is strongly affected by the variability of atmospheric transmission. The Infrared Working Group (IRWG) has recommended filters that help alleviate this issue and provide a common standard of NIR filtersets across different observatories. However, accurate implementation of these filters are yet to be available… ▽ More The photometric accuracy in the near-infrared (NIR) wavelength range (0.9 -2.6 microns) is strongly affected by the variability of atmospheric transmission. The Infrared Working Group (IRWG) has recommended filters that help alleviate this issue and provide a common standard of NIR filtersets across different observatories. However, accurate implementation of these filters are yet to be available to astronomers. In the meantime, InGaAs based detectors have emerged as a viable option for small and medium telescopes. The present work explores the combination of IRWG filtersets with InGaAs detectors. A few commercially available filtersets that approximate the IRWG profile are compared. Design of more accurate IRWG filtersets suitable for the InGaAs sensitivity range is undertaken using an open-source filter design software - OpeFilters. Along with the photometric filters iZ, iJ and iH, design of a few useful narrow band filters is also presented. These filters present opportunities for small and medium telescopes for dedicated long-term observation of interesting infrared sources. △ Less

Submitted 27 June, 2025; originally announced June 2025.

Journal ref: J. Astrophys. Astr. (2022) 43:13

Black Hole Spectroscopy with Conditional Variational Autoencoder

Authors: Akash K Mishra

Abstract: Gravitational waves provide a unique opportunity to test general relativity in the strong-field regime, enabling the extraction of key physical parameters from observational data. Traditional likelihood-based inference methods, while robust, become computationally expensive in high-dimensional parameter spaces, such as when incorporating multiple ringdown modes or beyond Kerr deviations. In this p… ▽ More Gravitational waves provide a unique opportunity to test general relativity in the strong-field regime, enabling the extraction of key physical parameters from observational data. Traditional likelihood-based inference methods, while robust, become computationally expensive in high-dimensional parameter spaces, such as when incorporating multiple ringdown modes or beyond Kerr deviations. In this paper, we explore the implementation of a conditional variational autoencoder-based machine-learning framework for accelerated ringdown parameter estimation. As a first application, we use the neural network to infer the remnant properties of a final black hole under the Kerr hypothesis. We demonstrate the performance of this algorithm with simulated ringdown waveforms consistent with advanced LIGO sensitivity and compare with Bayesian analysis results. We further extend the framework beyond the Kerr paradigm by incorporating deviations predicted in braneworld gravity. △ Less

Submitted 21 June, 2025; originally announced June 2025.

Comments: 10 pages, 5 figures, 1 table

Theoretical Analysis for the CommSense Measurement System

Authors: Sandip Jana, Amit Kumar Mishra, Mohammed Zafar Ali Khan

Abstract: Future 6G networks envisions to blur the line between communication and sensing, leveraging ubiquitous OFDM waveforms for both high throughput data and environmental awareness. In this work, we do a thorough analysis of Communication based Sensing (CommSense) framework that embeds lightweight, PCA based detectors into standard OFDM receivers; enabling real-time, device free detection of passive sc… ▽ More Future 6G networks envisions to blur the line between communication and sensing, leveraging ubiquitous OFDM waveforms for both high throughput data and environmental awareness. In this work, we do a thorough analysis of Communication based Sensing (CommSense) framework that embeds lightweight, PCA based detectors into standard OFDM receivers; enabling real-time, device free detection of passive scatterers (e.g. drones, vehicles etc.) without any extra transmitters. Starting from a realistic three link Rician channel model (direct Tx to Rx, cascaded Tx to Scatterer and Scatterer to Rx), we compare four detectors: the full dimensional Likelihood Ratio Test (Full LRT), PCA based LRT, PCA-SVM with linear and RBF kernels. By projecting N-dimensional CSI onto a P (very less than N) principal component subspace, inference time gets reduced by an order of magnitude compared to the full LRT, while achieving optimal error rates i.e. empirical errors align tightly with the Bhattacharyya error bound and Area Under ROC Curve (AUC) approx. equal to 1 for P approx. equal to 10. From the simulated result we have shown LRT based techniques are susceptible to the parameter estimation error, where as SVM is resilient to that. Our results demonstrate that PCA driven detection when paired with lightweight SVMs can deliver fast, accurate, and robust scatterer sensing, paving the way for integrated sensing and communication (ISAC) in 6G and beyond. △ Less

Submitted 24 July, 2025; v1 submitted 9 June, 2025; originally announced June 2025.

How Tough Is Location Anonymization? Re-identifying 100K Real-User Trajectories in Japan

Authors: Abhishek Kumar Mishra, Mathieu Cunche, Heber H. Arcolezi

Abstract: Mobility traces are among the most revealing forms of personal data, yet trajectory releases are often protected only by ad hoc transformations. We stress-test such practices on recently-released YJMob100K, an anonymized dataset of 100,000 user trajectories in Japan. First, we show that the applied protection leaves enough spatial and temporal structure to recover both the real-world geographic fr… ▽ More Mobility traces are among the most revealing forms of personal data, yet trajectory releases are often protected only by ad hoc transformations. We stress-test such practices on recently-released YJMob100K, an anonymized dataset of 100,000 user trajectories in Japan. First, we show that the applied protection leaves enough spatial and temporal structure to recover both the real-world geographic frame and the actual calendar timeline by exploiting density signatures, urban correlations, and temporal activity profiles. On top of this reconstruction, we quantify privacy risks through trajectory-level metrics that capture spatio-temporal k-anonymity, -point unicity, home-work and multi-anchor uniqueness, and exposure to secluded and sensitive locations. These metrics reveal extensive re-identification surfaces: a small number of observations, anchors, or sensitive venues often suffices to uniquely pinpoint users or their social neighborhoods. Finally, we evaluate representative sanitization strategies: geo-indistinguishability, local differential privacy, and aggressive spatial de-structuring; and observe a consistent pattern: strong privacy parameters destroy downstream utility, while utility-preserving settings leave structural leakage largely intact. Overall, our findings show that current sanitization techniques are insufficient for large-scale mobility data, and they highlight the urgent need for trajectory-aware privacy mechanisms and stronger publication standards. △ Less

Submitted 10 May, 2026; v1 submitted 5 June, 2025; originally announced June 2025.

Statistics of Non-Rayleigh Speckles Generated from Nonlinear Media

Authors: Deependra Singh Gaur, Akanksha Gautam, Rakesh Kumar Singh, Akhilesh Kumar Mishra

Abstract: We analytically derive an expression for a speckle field's intensity probability density function (PDF) in a nonlinear medium. The analytically driven results are in good agreement with the numerical outcomes. In a focusing nonlinear medium, the local intensity of the speckle is enhanced as manifested through the longer tail of the PDF. In contrast, the local intensity of speckle is reduced in the… ▽ More We analytically derive an expression for a speckle field's intensity probability density function (PDF) in a nonlinear medium. The analytically driven results are in good agreement with the numerical outcomes. In a focusing nonlinear medium, the local intensity of the speckle is enhanced as manifested through the longer tail of the PDF. In contrast, the local intensity of speckle is reduced in the presence of a defocusing nonlinearity, and the tail of the probability density function also reduces. This change in local intensity of the speckles arises due to the cubic Kerr nonlinearity, which eventually modifies the second-order statistics. Hence, the intensity correlation is altered as per the nature of the associated nonlinearity while the field correlation remains invariant of both types of the nonlinear conditions. △ Less

Submitted 14 June, 2025; v1 submitted 5 June, 2025; originally announced June 2025.

Comments: 7 pages, 4 figures

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks

Authors: Ashutosh Kumar Mishra, Emma Tolley

Abstract: Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving differential equations by integrating physical laws into the learning process. This work leverages PINNs to simulate gravitational collapse, a critical phenomenon in astrophysics and cosmology. We introduce the Schrödinger-Poisson informed neural network (SPINN) which solve nonlinear Schrödinger-Poisson (SP) equat… ▽ More Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving differential equations by integrating physical laws into the learning process. This work leverages PINNs to simulate gravitational collapse, a critical phenomenon in astrophysics and cosmology. We introduce the Schrödinger-Poisson informed neural network (SPINN) which solve nonlinear Schrödinger-Poisson (SP) equations to simulate the gravitational collapse of Fuzzy Dark Matter (FDM) in both 1D and 3D settings. Results demonstrate accurate predictions of key metrics such as mass conservation, density profiles, and structure suppression, validating against known analytical or numerical benchmarks. This work highlights the potential of PINNs for efficient, possibly scalable modeling of FDM and other astrophysical systems, overcoming the challenges faced by traditional numerical solvers due to the non-linearity of the involved equations and the necessity to resolve multi-scale phenomena especially resolving the fine wave features of FDM on cosmological scales. △ Less

Submitted 3 June, 2025; originally announced June 2025.

Comments: Submitted to ApJ

Automated grading and staging of ovarian cancer using deep learning on the transmission optical microscopy bright-field images of thin biopsy tissue samples

Authors: Ashmit K Mishra, Mousa Alrubayan, Prabhakar Pradhan

Abstract: Ovarian cancer remains a challenging malignancy to diagnose and manage, with prognosis heavily dependent on the stage at detection. Accurate grading and staging, primarily based on histopathological examination of biopsy tissue samples, are crucial for treatment planning and predicting outcomes. However, this manual process is time-consuming and subject to inter-observer variability among patholog… ▽ More Ovarian cancer remains a challenging malignancy to diagnose and manage, with prognosis heavily dependent on the stage at detection. Accurate grading and staging, primarily based on histopathological examination of biopsy tissue samples, are crucial for treatment planning and predicting outcomes. However, this manual process is time-consuming and subject to inter-observer variability among pathologists. The increasing volume of digital histopathology slides necessitates the development of robust, automated methods to assist in this critical diagnostic step for ovarian cancer. (Methods) This study presents a deep learning framework for the automated prediction of ovarian cancer stage (classified into five categories: 0, I, II, III, IV) using routine histopathological images. We employed a transfer learning approach, fine-tuning a ResNet-101 convolutional neural network pre-trained on ImageNet. The training process incorporated comprehensive data augmentation, weighted random sampling, and class weighting to address dataset characteristics. Hyperparameter optimization for learning rate, dropout rate, and weight decay was performed using a genetic algorithm to enhance model performance and generalization. (Results) Evaluated on an independent test set of ovarian thin tissue brightfield images, the developed model achieved a high overall classification accuracy of 97.62%. △ Less

Submitted 15 May, 2025; originally announced May 2025.

Comments: 5 figures, 15 pages

Dynamic Beam-Stabilized, Additive-Printed Flexible Antenna Arrays with On-Chip Rapid Insight Generation

Authors: Sreeni Poolakkal, Abdullah Islam, Arpit Rao, Shrestha Bansal, Ted Dabrowski, Kalsi Kwan, Zhongxuan Wang, Amit Kumar Mishra, Julio Navarro, Shenqiang Ren, John Williams, Sudip Shekhar, Subhanshu Gupta

Abstract: Conformal phased arrays promise shape-changing properties, multiple degrees of freedom to the scan angle, and novel applications in wearables, aerospace, defense, vehicles, and ships. However, they have suffered from two critical limitations. (1) Although most applications require on-the-move communication and sensing, prior conformal arrays have suffered from dynamic deformation-induced beam poin… ▽ More Conformal phased arrays promise shape-changing properties, multiple degrees of freedom to the scan angle, and novel applications in wearables, aerospace, defense, vehicles, and ships. However, they have suffered from two critical limitations. (1) Although most applications require on-the-move communication and sensing, prior conformal arrays have suffered from dynamic deformation-induced beam pointing errors. We introduce a Dynamic Beam-Stabilized (DBS) processor capable of beam adaptation through on-chip real-time control of fundamental gain, phase, and delay for each element. (2) Prior conformal arrays have leveraged additive printing to enhance flexibility, but conventional printable inks based on silver are expensive, and those based on copper suffer from spontaneous metal oxidation that alters trace impedance and degrades beamforming performance. We instead leverage a low-cost Copper Molecular Decomposition (CuMOD) ink with < 0.1% variation per degree C with temperature and strain and correct any residual deformity in real-time using the DBS processor. Demonstrating unified material and physical deformation correction, our CMOS DBS processor is low power, low-area, and easily scalable due to a tile architecture, thereby ideal for on-device implementations. △ Less

Submitted 19 May, 2025; v1 submitted 14 May, 2025; originally announced May 2025.

Comments: This work was intended as a replacement of arXiv:2406.07797 and any subsequent updates will appear there

Probing Gauged $U(1)$ Sub-GeV Dark Matter via Cosmic Ray Cooling in Active Galactic Nuclei

Authors: Arvind Kumar Mishra, Ning Liu, Chih-Ting Lu

Abstract: Cosmic rays (CRs) traversing the dark matter (DM) spike surrounding active galactic nuclei (AGNs) can be cooled through interactions with DM particles. In this study, we investigated constraints on sub-GeV DM particles charged under various $U(1)$ gauge symmetries by exploiting the cooling effect of CRs in AGNs. We find that for low DM and mediator masses, the CR cooling rate is higher compared to… ▽ More Cosmic rays (CRs) traversing the dark matter (DM) spike surrounding active galactic nuclei (AGNs) can be cooled through interactions with DM particles. In this study, we investigated constraints on sub-GeV DM particles charged under various $U(1)$ gauge symmetries by exploiting the cooling effect of CRs in AGNs. We find that for low DM and mediator masses, the CR cooling rate is higher compared to the standard model cooling process. Furthermore, by utilizing constraints from the CR cooling effect in NGC 1068 and TXS 0506+056, we explore the bounds on the DM-electron and DM-proton elastic scattering cross-sections. Our results indicate that in the sub-GeV DM mass range, these constraints are more stringent than those from certain boosted DM mechanisms and current direct detection limits. △ Less

Submitted 4 April, 2025; originally announced April 2025.

Comments: 10 pages, 6 figures, 1 Table, Suggestions and comments are welcome

Pressure-Induced Volume Collapse and Metallization in Inverse Spinel Co$_2$TiO$_4$

Authors: Mrinmay Sahu, Souvick Chakraborty, Bidisha Mukherjee, Bishnupada Ghosh, Asish Kumar Mishra, Satyabrata Raj, Goutam Dev Mukherjee

Abstract: The structural, vibrational, electronic, and magnetic properties of inverse spinel $Co_2TiO_4$ (CTO-Sp) under high-pressure (HP) conditions are systematically investigated using X-ray diffraction, Raman spectroscopy, in situ optical microscopy, and first-principles density functional theory (DFT) calculations. At ambient conditions, CTO-Sp exhibits a cubic phase with a space group $Fd\bar{3}m$, an… ▽ More The structural, vibrational, electronic, and magnetic properties of inverse spinel $Co_2TiO_4$ (CTO-Sp) under high-pressure (HP) conditions are systematically investigated using X-ray diffraction, Raman spectroscopy, in situ optical microscopy, and first-principles density functional theory (DFT) calculations. At ambient conditions, CTO-Sp exhibits a cubic phase with a space group $Fd\bar{3}m$, and it undergoes two notable structural phase transitions at HP. The first transition, occurring at approximately 7.3 GPa, leads to the tetragonal-$I4_1/amd$ phase with minimal alteration in unit cell volume. {The second transition takes place near 17.3 GPa, where two orthorhombic phases emerge and coexist above this pressure.} This second structural transition corresponds to a first-order phase transition involving a significant reduction in unit cell volume of approximately 17.5$\%$. The bulk compressibility of CTO-Sp and its HP post-spinel phases is almost equal to the average polyhedral compressibility within each phase. DFT calculations reveal a high-spin to low-spin transition, accompanied by the collapse of local magnetic moments in the $Cmcm$ orthorhombic phase, leading to the sample's pressure-induced metallization. △ Less

Submitted 28 June, 2025; v1 submitted 1 April, 2025; originally announced April 2025.

Reliable Traffic Monitoring Using Low-Cost Doppler Radar Units

Authors: Mishay Naidoo, Stephen Paine, Amit Kumar Mishra, Mohammed Yunus Abdul Gaffar

Abstract: Road traffic monitoring typically involves the counting and recording of vehicles on public roads over extended periods. The data gathered from such monitoring provides useful information to municipal authorities in urban areas. This paper presents a low-cost, widely deployable sensing subsystem based on Continuous Wave Doppler radar. The proposed system can perform vehicle detection and speed est… ▽ More Road traffic monitoring typically involves the counting and recording of vehicles on public roads over extended periods. The data gathered from such monitoring provides useful information to municipal authorities in urban areas. This paper presents a low-cost, widely deployable sensing subsystem based on Continuous Wave Doppler radar. The proposed system can perform vehicle detection and speed estimation with a total cost of less than 100 USD. The sensing system (including the hardware subsystem and the algorithms) is designed to be placed on the side of the road, allowing for easy deployment and serviceability. △ Less

Submitted 31 March, 2025; originally announced March 2025.

Statistical Study of Sensor Data and Investigation of ML-based Calibration Algorithms for Inexpensive Sensor Modules: Experiments from Cape Point

Authors: Travis Barrett, Amit Kumar Mishra

Abstract: In this paper we present the statistical analysis of data from inexpensive sensors. We also present the performance of machine learning algorithms when used for automatic calibration such sensors. In this we have used low-cost Non-Dispersive Infrared CO$_2$ sensor placed at a co-located site at Cape Point, South Africa (maintained by Weather South Africa). The collected low-cost sensor data and si… ▽ More In this paper we present the statistical analysis of data from inexpensive sensors. We also present the performance of machine learning algorithms when used for automatic calibration such sensors. In this we have used low-cost Non-Dispersive Infrared CO$_2$ sensor placed at a co-located site at Cape Point, South Africa (maintained by Weather South Africa). The collected low-cost sensor data and site truth data are investigated and compared. We compare and investigate the performance of Random Forest Regression, Support Vector Regression, 1D Convolutional Neural Network and 1D-CNN Long Short-Term Memory Network models as a method for automatic calibration and the statistical properties of these model predictions. In addition, we also investigate the drift in performance of these algorithms with time. △ Less

Submitted 9 March, 2025; originally announced March 2025.

Soft mode induced structural phase transition in Ba$_2$ZnTeO$_6$ at high pressure

Authors: Bidisha Mukherjee, Surajit Adhikari, Mrinmay Sahu, Asish Kumar Mishra, Bhagyashri Giri, Priya Johari, Konstantin Glazyrin, Goutam Dev Mukherjee

Abstract: In this paper, we present a thorough investigation of vibrational, structural, and electronic properties of perovskite-type rhombohedral Ba$_2$ZnTeO$_6$ (BZTO) under systematic application of pressure. To carry out the analysis, we have performed pressure-dependent Raman spectroscopic measurements, synchrotron XRD, and density functional theory-based calculations. At ambient conditions, BZTO stabi… ▽ More In this paper, we present a thorough investigation of vibrational, structural, and electronic properties of perovskite-type rhombohedral Ba$_2$ZnTeO$_6$ (BZTO) under systematic application of pressure. To carry out the analysis, we have performed pressure-dependent Raman spectroscopic measurements, synchrotron XRD, and density functional theory-based calculations. At ambient conditions, BZTO stabilizes in $R\bar{3}m$ space group, which under pressure undergoes a structural transition to a monoclinic phase with space group $C2/m$ at around 18~GPa. In-depth Raman analysis reveals softening of a phonon mode E$_g$ ($\sim $ 28cm$^{-1}$) leads to the structural phase transition. First principle DFT calculations also indicate that the doubly degenerate soft mode associated with the in-phase TeO$_6$ octahedral rotation drives the structure to a lower symmetry phase $C2/m$. △ Less

Submitted 14 March, 2025; originally announced March 2025.

Agile Climate-Sensor Design and Calibration Algorithms Using Machine Learning: Experiments From Cape Point

Authors: Travis Barrett, Amit Kumar Mishra

Abstract: In this paper, we describe the design of an inexpensive and agile climate sensor system which can be repurposed easily to measure various pollutants. We also propose the use of machine learning regression methods to calibrate CO2 data from this cost-effective sensing platform to a reference sensor at the South African Weather Service's Cape Point measurement facility. We show the performance of th… ▽ More In this paper, we describe the design of an inexpensive and agile climate sensor system which can be repurposed easily to measure various pollutants. We also propose the use of machine learning regression methods to calibrate CO2 data from this cost-effective sensing platform to a reference sensor at the South African Weather Service's Cape Point measurement facility. We show the performance of these methods and found that Random Forest Regression was the best in this scenario. This shows that these machine learning methods can be used to improve the performance of cost-effective sensor platforms and possibly extend the time between manual calibration of sensor networks. △ Less

Submitted 9 March, 2025; originally announced March 2025.

Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, K. Ackley, S. Adhicary, N. Adhikari, R. X. Adhikari, V. K. Adkins, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, I. Aguilar, L. Aiello, A. Ain, P. Ajith, T. Akutsu, S. Albanesi, R. A. Alfaidi, A. Al-Jodah, C. Alléné , et al. (1794 additional authors not shown)

Abstract: Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent ana… ▽ More Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory. △ Less

Submitted 26 September, 2025; v1 submitted 2 January, 2025; originally announced January 2025.

Comments: main paper: 12 pages, 6 figures, 4 tables

Report number: LIGO-P2400315

Journal ref: Astrophys.J. 983 (2025) 2, 99

Probing Spacetime Symmetries Using Gravitational Wave Ringdown

Authors: Rajes Ghosh, Akash K Mishra, Sudipta Sarkar

Abstract: The uniqueness and rigidity theorems assert that the asymptotically flat, vacuum, stationary rotating black hole solution in general relativity must be the Kerr solution, exhibiting novel symmetries such as axisymmetry and circularity. In our analysis of post-merger ringdown signal from coalescing black hole binary systems, we identify potential observational signatures for deviations from these K… ▽ More The uniqueness and rigidity theorems assert that the asymptotically flat, vacuum, stationary rotating black hole solution in general relativity must be the Kerr solution, exhibiting novel symmetries such as axisymmetry and circularity. In our analysis of post-merger ringdown signal from coalescing black hole binary systems, we identify potential observational signatures for deviations from these Kerr symmetries. Utilizing ringdown data from the gravitational wave event GW150914, we place significant constraints on such deviations. Our analysis introduces a new and novel approach for testing spacetime symmetries through gravitational wave observations. △ Less

Submitted 12 December, 2024; originally announced December 2024.

Comments: 5+7 pages, 6 figures

Radio Halo Detection in MWA Data using Deep Neural Networks and Generative Data Augmentation

Authors: Ashutosh K. Mishra, Emma Tolley, Shreyam Parth Krishna, Jean-Paul Kneib

Abstract: Detecting diffuse radio emission, such as from halos, in galaxy clusters is crucial for understanding large-scale structure formation in the universe. Traditional methods, which rely on X-ray and Sunyaev-Zeldovich (SZ) cluster pre-selection, introduce biases that limit our understanding of the full population of diffuse radio sources. In this work, we provide a possible resolution for this astroph… ▽ More Detecting diffuse radio emission, such as from halos, in galaxy clusters is crucial for understanding large-scale structure formation in the universe. Traditional methods, which rely on X-ray and Sunyaev-Zeldovich (SZ) cluster pre-selection, introduce biases that limit our understanding of the full population of diffuse radio sources. In this work, we provide a possible resolution for this astrophysical tension by developing a machine learning (ML) framework capable of unbiased detection of diffuse emission, using a limited real dataset like those from the Murchison Widefield Array (MWA). We generate for the first time radio halo images using Wasserstein Generative Adversarial Networks (WGANs) and Denoising Diffusion Probabilistic Models (DDPMs), and apply them to train a neural network classifier independent of pre-selection methods. The halo images generated by DDPMs are of higher quality than those produced by WGANs. The diffusion-supported classifier with a multi-head attention block achieved the best average validation accuracy of 95.93% over 10 runs, using 36 clusters for training and 10 for testing, without further hyperparameter tuning. Using our classifier, we rediscovered 9/12 halos (75% detection rate) from the MeerKAT Galaxy Cluster Legacy Survey (MGCLS) Catalogue, and 5/8 halos (63% detection rate) from the Planck Sunyaev-Zeldovich Catalogue 2 (PSZ2) within the GaLactic and Extragalactic All-sky MWA (GLEAM) survey. In addition, we identify 11 potential new halos, minihalos, or candidates in the COSMOS field using XMM-chandra-detected clusters in GLEAM data. This work demonstrates the potential of ML for unbiased detection of diffuse emission and provides labeled datasets for further study. △ Less

Submitted 23 November, 2024; originally announced November 2024.

Comments: 16 pages, Submitted to MNRAS

Birkhoff's Theorem and Uniqueness: A Peek Beyond General Relativity

Authors: Rajes Ghosh, Akash K Mishra, Avijit Chowdhury

Abstract: In General Relativity, Birkhoff's theorem asserts that any spherically symmetric vacuum solution must be static and asymptotically flat. In this paper, we study the validity of Birkhoff's theorem for a broad class of modified gravity theories in four spacetime dimensions, including quadratic and higher-order gravity models. We demonstrate that the Schwarzschild spacetime remains the unique Einstei… ▽ More In General Relativity, Birkhoff's theorem asserts that any spherically symmetric vacuum solution must be static and asymptotically flat. In this paper, we study the validity of Birkhoff's theorem for a broad class of modified gravity theories in four spacetime dimensions, including quadratic and higher-order gravity models. We demonstrate that the Schwarzschild spacetime remains the unique Einstein branch solution outside any spherically symmetric configuration of these theories. Consequently, unlike black holes, the breakdown of junction conditions at the surface of the star further implies that the actual spacetime metric outside a horizonless star in these modified theories cannot simultaneously be spherically symmetric and remain within the Einstein branch. This insight offers a unique observational probe for theories beyond General Relativity. △ Less

Submitted 6 November, 2025; v1 submitted 14 November, 2024; originally announced November 2024.

Comments: Accepted in Physics Letters B: 8 pages, no figure

Search for gravitational waves emitted from SN 2023ixf

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, K. Ackley, S. Adhicary, N. Adhikari, R. X. Adhikari, V. K. Adkins, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, I. Aguilar, L. Aiello, A. Ain, T. Akutsu, S. Albanesi, R. A. Alfaidi, A. Al-Jodah, C. Alléné, A. Allocca , et al. (1758 additional authors not shown)

Abstract: We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been… ▽ More We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the gravitational-wave emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-4} M_{\odot} c^2$ and luminosity $2.6 \times 10^{-4} M_{\odot} c^2/s$ for a source emitting at 82 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as 1.08, at frequencies above 1200 Hz, surpassing past results. △ Less

Submitted 11 March, 2025; v1 submitted 21 October, 2024; originally announced October 2024.

Comments: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table

Report number: LIGO-P2400125

Journal ref: ApJ 985 183 (2025)

Emission enhancement and bandgap narrowing in $Cs_2TeBr_6$ under pressure

Authors: Debabrata Samanta, Suvashree Mukherjee, Asish Kumar Mishra, Bhagyashri Giri, Sonu Pratap Chaudhary, Konstantin Glazyrin, Sayan Bhattacharyya, Goutam Dev Mukherjee

Abstract: Pressure-induced emission enhancement and bandgap narrowing in vacancy-ordered halide double perovskite $Cs_2TeBr_6$ are extensively investigated through photoluminescence and absorption experiments. The below bandgap broad emission is attributed to self-trapped excitons recombination. The $Cs_2TeBr_6$ crystal, consisting of undistorted octahedra, exhibits substantial emission enhancement due to t… ▽ More Pressure-induced emission enhancement and bandgap narrowing in vacancy-ordered halide double perovskite $Cs_2TeBr_6$ are extensively investigated through photoluminescence and absorption experiments. The below bandgap broad emission is attributed to self-trapped excitons recombination. The $Cs_2TeBr_6$ crystal, consisting of undistorted octahedra, exhibits substantial emission enhancement due to the lowering of the energy barrier between $^3P_1$ and self-trapped exciton states, as well as the suppression of nonradiative energy loss with increasing pressure. In the Raman measurements, the observed behavior of full width at half maximum of all Raman modes implies dominant electron-phonon interactions rather than anharmonic interactions between phonons. The pressure-dependent X-ray diffraction measurements reveal an anomalous behaviour in the normalized pressure as a function of the Eulerian strain. △ Less

Submitted 15 October, 2024; originally announced October 2024.

A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, K. Ackley, S. Adhicary, N. Adhikari, R. X. Adhikari, V. K. Adkins, D. Agarwal, M. Agathos, M. Aghaei Abchouyeh, O. D. Aguiar, I. Aguilar, L. Aiello, A. Ain, P. Ajith, T. Akutsu, S. Albanesi, R. A. Alfaidi, A. Al-Jodah, C. Alléné , et al. (1758 additional authors not shown)

Abstract: The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by… ▽ More The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs. △ Less

Submitted 21 May, 2025; v1 submitted 11 October, 2024; originally announced October 2024.

Comments: 15 pages of text including references, 4 figures, 5 tables

Report number: LIGO-P2400192

Journal ref: ApJ 977 255 (2024)

Connecting quasi-normal modes with causality in Lovelock theories of gravity

Authors: Avijit Chowdhury, Akash K Mishra, Sumanta Chakraborty

Abstract: The eikonal correspondence between the quasi-normal modes (QNMs) of asymptotically flat static spherically symmetric black holes and the properties of unstable null circular geodesics is studied in the case of higher dimensional Lovelock black holes (BHs). It is known that such correspondence does not generically hold for gravitational QNMs associated with BHs in Lovelock theories. In the present… ▽ More The eikonal correspondence between the quasi-normal modes (QNMs) of asymptotically flat static spherically symmetric black holes and the properties of unstable null circular geodesics is studied in the case of higher dimensional Lovelock black holes (BHs). It is known that such correspondence does not generically hold for gravitational QNMs associated with BHs in Lovelock theories. In the present work, we revisit this correspondence and establish the relationship between the eikonal QNMs and the causal properties of the gravitational field equations in Lovelock theories of gravity. △ Less

Submitted 4 January, 2025; v1 submitted 11 October, 2024; originally announced October 2024.

Comments: 13 pages, 2 figures, 4 table, Matches published version

Journal ref: Phys. Lett. B 861 (2025) 139219

Transdisciplinary collaborations for advancing sustainable and resilient agricultural systems

Authors: Vesna Bacheva, Imani Madison, Mathew Baldwin, Mark Beilstein, Douglas F. Call, Jessica A. Deaver, Kirill Efimenko, Jan Genzer, Khara Grieger, April Z. Gu, Mehmet Mert Ilman, Jen Liu, Sijin Li, Brooke K. Mayer, Anand Kumar Mishra, Juan Claudio Nino, Gloire Rubambiza, Phoebe Sengers, Robert Shepherd, Jesse Woodson, Hakim Weatherspoon, Margaret Frank, Jacob Jones, Rosangela Sozzani, Abraham Stroock

Abstract: Feeding the growing human population sustainably amidst climate change is one of the most important challenges in the 21st century. Current practices often lead to the overuse of agronomic inputs, such as synthetic fertilizers and water, resulting in environmental contamination and diminishing returns on crop productivity. The complexity of agricultural systems, involving plant-environment interac… ▽ More Feeding the growing human population sustainably amidst climate change is one of the most important challenges in the 21st century. Current practices often lead to the overuse of agronomic inputs, such as synthetic fertilizers and water, resulting in environmental contamination and diminishing returns on crop productivity. The complexity of agricultural systems, involving plant-environment interactions and human management, presents significant scientific and technical challenges for developing sustainable practices. Addressing these challenges necessitates transdisciplinary research, involving intense collaboration among fields such as plant science, engineering, computer science, and social sciences. Here, we present five case studies from two research centers demonstrating successful transdisciplinary approaches toward more sustainable water and fertilizer use. These case studies span multiple scales. Starting from whole-plant signaling, we explore how reporter plants can transform our understanding of plant communication and enable efficient application of water and fertilizers. We then show how new fertilizer technologies could increase the availability of phosphorus in the soil. To accelerate advancements in breeding new cultivars, we discuss robotic technologies for high-throughput plant screening in different environments at a population scale. At the ecosystem scale, we investigate phosphorus recovery from aquatic systems and methods to minimize phosphorus leaching. Finally, as agricultural outputs affect all people, we show how to integrate stakeholder perspectives and needs into the research. With these case studies, we hope to encourage the scientific community to adopt transdisciplinary research and promote cross-training among biologists, engineers, and social scientists to drive discovery and innovation in advancing sustainable agricultural systems. △ Less

Submitted 18 September, 2024; originally announced September 2024.

Neutron Star Collapse From Accretion: a Probe of Massive Dark Matter Particles

Authors: Ning Liu, Arvind Kumar Mishra

Abstract: We explore the multi-scatter capturing of the massive dark matter (DM) particle inside the neutron star via a momentum-dependent dark matter-nucleon scattering cross-section. We find that the capturing enhanced for the positive velocity and momentum transfer dependent DM-nucleon scattering in comparison with the constant cross-section case. Further, a large capture of the DM particles can be therm… ▽ More We explore the multi-scatter capturing of the massive dark matter (DM) particle inside the neutron star via a momentum-dependent dark matter-nucleon scattering cross-section. We find that the capturing enhanced for the positive velocity and momentum transfer dependent DM-nucleon scattering in comparison with the constant cross-section case. Further, a large capture of the DM particles can be thermalized and lead to black hole formation and, therefore, destroy the neutron star. Using the observation of the old neutron star in the DM-dominated region, we obtain strong constraints on massive DM parameters. △ Less

Submitted 1 August, 2024; originally announced August 2024.

Comments: 15 pages, 7 figures, Suggestions and comments are welcome

Swift-BAT GUANO follow-up of gravitational-wave triggers in the third LIGO-Virgo-KAGRA observing run

Authors: Gayathri Raman, Samuele Ronchini, James Delaunay, Aaron Tohuvavohu, Jamie A. Kennea, Tyler Parsotan, Elena Ambrosi, Maria Grazia Bernardini, Sergio Campana, Giancarlo Cusumano, Antonino D'Ai, Paolo D'Avanzo, Valerio D'Elia, Massimiliano De Pasquale, Simone Dichiara, Phil Evans, Dieter Hartmann, Paul Kuin, Andrea Melandri, Paul O'Brien, Julian P. Osborne, Kim Page, David M. Palmer, Boris Sbarufatti, Gianpiero Tagliaferri , et al. (1797 additional authors not shown)

Abstract: We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wav… ▽ More We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers. △ Less

Submitted 27 March, 2025; v1 submitted 13 July, 2024; originally announced July 2024.

Comments: Update to version accepted for publication in ApJ. 50 pages, 10 figures, 4 tables

Journal ref: ApJ, Volume 980, 2025, 207

Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing

Authors: Anushrut Jignasu, Kelly O. Marshall, Ankush Kumar Mishra, Lucas Nerone Rillo, Baskar Ganapathysubramanian, Aditya Balu, Chinmay Hegde, Adarsh Krishnamurthy

Abstract: G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the movement of the 3D printer, especially for the nozzle, stage, and extrusion of material for extrusion-based additive manufacturing. Currently, there does not exist a large repository of curated CAD models along with their corr… ▽ More G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the movement of the 3D printer, especially for the nozzle, stage, and extrusion of material for extrusion-based additive manufacturing. Currently, there does not exist a large repository of curated CAD models along with their corresponding G-code files for additive manufacturing. To address this issue, we present Slice-100K, a first-of-its-kind dataset of over 100,000 G-code files, along with their tessellated CAD model, LVIS (Large Vocabulary Instance Segmentation) categories, geometric properties, and renderings. We build our dataset from triangulated meshes derived from Objaverse-XL and Thingi10K datasets. We demonstrate the utility of this dataset by finetuning GPT-2 on a subset of the dataset for G-code translation from a legacy G-code format (Sailfish) to a more modern, widely used format (Marlin). Our dataset can be found at https://github.com/idealab-isu/Slice-100K. Slice-100K will be the first step in developing a multimodal foundation model for digital manufacturing. △ Less

Submitted 5 September, 2025; v1 submitted 4 July, 2024; originally announced July 2024.

Comments: Accepted to NeurIPS 2024. For codebase, see https://github.com/idealab-isu/Slice-100K