arXiv subjects

Naman Jain

Publications and source records attributed to Naman Jain.

At least 19 recordsLinked to original sources

arXiv2026

Debiasing the Observed Fast Radio Burst Population with the CHIME/FRB Selection Function

The recent release of CHIME/FRB Catalog~2 provides the largest sample to date with which to investigate the intrinsic distributions of fast radio bursts (FRBs). Leveraging an expanded campaign of 587,367 synethetic bursts injected into the live CHIME/FRB search pipeline, we perform a population analysis of the fluence, scattering timescale, pulse width, and dispersion measure distributions of Catalog~2 FRBs. We first infer the intrinsic population using a resampling-based framework that accounts for instrumental selection effects following previous CHIME/FRB population studies. A central goal of this work is to constrain the intrinsic distribution of scattering timescales, that remained weakly constrained in Catalog~1 owing to limited statistics at moderate and large scattering times ($\tau \gtrsim 10\,\mathrm{ms}$ at 600~MHz) and sparse injection coverage in this regime. Second, we construct an explicit multidimensional selection function by training a logistic regression model on the injected events. This model estimates the detection probability as a function of FRB observable properties, including higher-order interaction terms. We incorporate this selection function into a simulation-based inference framework to refine the inferred intrinsic scattering-timescale distribution. We find evidence for a slight downturn in the intrinsic FRB scattering timescale distribution, though a flat or slightly rising distribution cannot be ruled out, that is further supported through a comparison with the higher-frequency scattering timescale distribution observed by Commensal Real-time ASKAP Fast Transients (CRAFT) survey.

astro-ph.HE↗

arXiv2026

Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB

We present 30 newly discovered repeating fast radio burst (FRB) sources from the second catalog of bursts detected by the FRB backend on the Canadian Hydrogen Intensity Mapping Experiment (CHIME/FRB). These repeaters have extragalactic dispersion measures (DMs) spanning $99.4-1446.0\ \text{pc cm}^{-3}$ and burst rates between $10^{-5.7}$ and $10^{-0.5}$ hr$^{-1}$ scaled to a fluence threshold of 5 Jy ms. We report evidence of monotonic, linear DM variations in four repeaters on years-long timescales. The newly discovered sources bring CHIME/FRB's total number of observed repeating FRBs to 80, 79 of which were discovered by CHIME/FRB, between 2018 July 25 and 2023 September 15. In the full CHIME/FRB sample, only 2.4$\pm 0.4\%$ of sources have been observed to repeat, and we do not find evidence for significant evolution of this value over the duration of the experiment. We find no substantial evidence for bimodal populations of one-off and repeating FRBs in their burst rate distributions; the distribution of upper limits on repeat rates implied from observations of as-yet one-offs is entirely contained within the observed range of repeater burst rates and the distributions do not appear inconsistent. Similarly, using the population analysis framework of C. W. James (2023), we find that our observations of repeating and yet-one-off FRBs are equally well fit assuming a power-law distribution of repeat rates with 50$-$100% of the population repeating.

astro-ph.HE↗

arXiv2026

Composer 2 Technical Report

Composer 2 is a specialized model designed for agentic software engineering. The model demonstrates strong long-term planning and coding intelligence while maintaining the ability to efficiently solve problems for interactive use. The model is trained in two phases: first, continued pretraining to improve the model's knowledge and latent coding ability, followed by large-scale reinforcement learning to improve end-to-end coding performance through stronger reasoning, accurate multi-step execution, and coherence on long-horizon realistic coding problems. We develop infrastructure to support training in the same Cursor harness that is used by the deployed model, with equivalent tools and structure, and use environments that match real problems closely. To measure the ability of the model on increasingly difficult tasks, we introduce a benchmark derived from real software engineering problems in large codebases including our own. Composer 2 is a frontier-level coding model and demonstrates a process for training strong domain-specialized models. On our CursorBench evaluations the model achieves a major improvement in accuracy compared to previous Composer models (61.3). On public benchmarks the model scores 61.7 on Terminal-Bench and 73.7 on SWE-bench Multilingual in our harness, comparable to state-of-the-art systems.

cs.SE↗

arXiv2026

Probing the maximum energy of fast radio bursts using thousands of sources from the Second CHIME/FRB Catalog

Quantifying the maximum energy of fast radio bursts (FRBs) can provide stringent constraints on their emission mechanisms and progenitor models. However, the most energetic bursts are rare, requiring a large sample of FRBs to detect them. In this work, we use the largest available such sample, 2,998 one-off FRBs from the Second CHIME/FRB Catalog, to obtain a lower limit on the maximum energy ($E^{\mathrm{max}}_{\mathrm{iso}}$) of FRBs, assuming isotropic energy distribution from FRB sources. In the absence of known redshifts ($z$) for most sources, we present a framework that uses the dispersion measures (DMs) and fluences of these FRBs, together with the probability distribution of $z$ given DM, to derive the lower limit on $E^{\mathrm{max}}_{\mathrm{iso}}$. We generate simulated FRB samples assuming different parameter values for a log-normal $\mathrm{DM}_{\mathrm{host}}$ distribution and a Schechter function form of the FRB energy function to estimate how many outliers -- FRBs with large DM contributions from the host galaxy or intervening galaxy halos -- could artificially inflate this limit. After accounting for outliers, the lower limit on $E^{\mathrm{max}}_{\mathrm{iso}}$ from Catalog 2 FRBs ranges between $1.2\times10^{41}$ and $1.9\times10^{42}$ erg, with best estimate $1.2\times10^{42}$ erg. This limit is consistent with those derived from much smaller FRB samples. Moreover, inferred energies of hundreds of FRBs appear collectively limited around $\sim10^{42}$ erg, suggesting a physical limit on the energy reservoir of FRB sources. The corresponding isotropic-equivalent FRB source energy is consistent with the total energy available in a magnetar's external dipole magnetic field, supporting magnetars as FRB progenitors.

astro-ph.HE↗

arXiv2026

CHIME/Slow overview and pilot survey: A new backend to search for second-duration radio transients with the CHIME telescope

We present an overview of CHIME/Slow, a real-time transient search backend under development to search for second-duration radio transients using the CHIME telescope, and results obtained from a pilot survey carried out using the prototype version of the search pipeline. The prototype CHIME/Slow pipeline was tested on archival data obtained in December 2022, January 2023 and February 2023 with a total on-sky time of 17 days with an instantaneous Field of View (FoV) of $\sim$13 deg$^2$ . In this pilot survey, we detected nine bursts, one from a new non-repeating source and eight from the known hyperactive repeating source FRB 20220912A. Out of these nine bursts, two bursts from the repeater were not detected by CHIME/FRB, while the non-repeater was detected in the side-lobe of a beam in the CHIME/FRB exhibiting shorter pulse width and narrower bandwidth compared to the CHIME/Slow detection. Here we report properties of the bursts, discuss the sensitivity and completeness of the current version of the CHIME/Slow pipeline, and outline future development to improve its performance. Finally, based on these results, we report the all-sky rate (95% credible region) of radio transients with pulse widths between 16 ms to 5 s, fluence above 5 Jy ms and observing frequency of 600 MHz to be between 184 and 4556 bursts sky$^{-1}$ day$^{-1}$.

astro-ph.IM↗

arXiv2026

The Second CHIME/FRB Catalog of Fast Radio Bursts

We present a catalog of 4539 fast radio bursts (FRBs) observed with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) telescope between 25 July 2018 and 15 September 2023. These bursts originate from 3641 unique sources, including 981 bursts from 83 known repeating sources. For each FRB, the catalog provides a $O(10')$ estimate of sky location along with corresponding measurements of cumulative exposure time and survey sensitivity over the observing period. It includes a total-intensity dynamic spectrum between 400 and 800 MHz at 0.983 ms resolution. From this spectrum, we constrain a model of the burst morphology and measure key parameters such as arrival time, intrinsic temporal width, dispersion measure, scattering time, and flux density. This second catalog includes all FRBs from the first catalog, with every event reprocessed using a uniform and improved analysis framework. We show that previously published inferences remain valid under the updated measurements. We assess consistency of the detection rate across observational parameters, present initial distributions of burst properties, and outline ongoing and future studies that will use this catalog to investigate the nature of FRBs and their utility as astrophysical and cosmological probes.

astro-ph.HE↗

arXiv2026

Reconstruction Guided Few-shot Network For Remote Sensing Image Classification

Few-shot remote sensing image classification is challenging due to limited labeled samples and high variability in land-cover types. We propose a reconstruction-guided few-shot network (RGFS-Net) that enhances generalization to unseen classes while preserving consistency for seen categories. Our method incorporates a masked image reconstruction task, where parts of the input are occluded and reconstructed to encourage semantically rich feature learning. This auxiliary task strengthens spatial understanding and improves class discrimination under low-data settings. We evaluated the efficacy of EuroSAT and PatternNet datasets under 1-shot and 5-shot protocols, our approach consistently outperforms existing baselines. The proposed method is simple, effective, and compatible with standard backbones, offering a robust solution for few-shot remote sensing classification. Codes are available at https://github.com/stark0908/RGFS.

cs.CV↗

arXiv2025

Programmable Assembly of Ground State Fermionic Tweezer Arrays

We demonstrate deterministic preparation of arbitrary two-component product states of fermionic $^6$Li atoms in an 8$\times$8 optical tweezer array, achieving motional ground-state fidelities above $98.5\,\%$. Leveraging the large differential magnetic moments for spin-resolution, with parallelized site- and number-resolved control, our approach addresses key challenges for low-entropy quantum state engineering. Combined with high-fidelity spin-, site-, and density-resolved readout within a single $20\,\mathrm{\mu s}$ exposure, and $3\,\mathrm{s}$ experimental cycles, these advances establish a fast, scalable, and programmable architecture for fermionic quantum simulation.

cond-mat.quant-gas↗

arXiv2025

Agribot: agriculture-specific question answer system

India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24* 7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal.

cs.CL↗

arXiv2025

FRB 20250316A: A Brilliant and Nearby One-Off Fast Radio Burst Localized to 13 parsec Precision

Precise localizations of a small number of repeating fast radio bursts (FRBs) using very long baseline interferometry (VLBI) have enabled multiwavelength follow-up observations revealing diverse local environments. However, the 2--3\% of FRB sources that are observed to repeat may not be representative of the full population. Here we use the VLBI capabilities of the full CHIME Outriggers array for the first time to localize a nearby (40 Mpc), bright (kJy), and apparently one-off FRB source, FRB 20250316A, to its environment on 13-pc scales. We use optical and radio observations to place deep constraints on associated transient emission and the properties of its local environment. We place a $5\sigma$ upper limit of $L_{\mathrm{9.9~\mathrm{GHz}}} < 2.1\times10^{25}~\mathrm{erg~s^{-1}~Hz^{-1}}$ on spatially coincident radio emission, a factor of 100 lower than any known compact persistent radio source associated with an FRB. Our KCWI observations allow us to characterize the gas density, metallicity, nature of gas ionization, dust extinction and star-formation rate through emission line fluxes. We leverage the exceptional brightness and proximity of this source to place deep constraints on the repetition of FRB 20250316A, and find it is inconsistent with all well-studied repeaters given the non-detection of bursts at lower spectral energies. We explore the implications of a measured offset of 190$\pm20$ pc from the center of the nearest star-formation region, in the context of progenitor channels. FRB 20250316A marks the beginning of an era of routine localizations for one-off FRBs on tens of mas-scales, enabling large-scale studies of their local environments.

astro-ph.HE↗

arXiv2025

GSO: Challenging Software Optimization Tasks for Evaluating SWE-Agents

Developing high-performance software is a complex task that requires specialized expertise. We introduce GSO, a benchmark for evaluating language models' capabilities in developing high-performance software. We develop an automated pipeline that generates and executes performance tests to analyze repository commit histories to identify 102 challenging optimization tasks across 10 codebases, spanning diverse domains and programming languages. An agent is provided with a codebase and performance test as a precise specification, and tasked to improve the runtime efficiency, which is measured against the expert developer optimization. Our quantitative evaluation reveals that leading SWE-Agents struggle significantly, achieving less than 5% success rate, with limited improvements even with inference-time scaling. Our qualitative analysis identifies key failure modes, including difficulties with low-level languages, practicing lazy optimization strategies, and challenges in accurately localizing bottlenecks. We release the code and artifacts of our benchmark along with agent trajectories to enable future research.

cs.SE↗

arXiv2025

The CHIME/FRB Discovery of the Extremely Active Fast Radio Burst Source FRB 20240114A

Among the thousands of observed fast radio bursts (FRBs), a few sources exhibit exceptionally high burst activity observable by many telescopes across a broad range of radio frequencies. Almost all of these highly active repeaters have been discovered by CHIME/FRB, due to its daily observations of the entire Northern sky as a transit radio telescope. FRB 20240114A is a source discovered and reported by CHIME/FRB to the community in January 2024; given its low declination, even the detection of a few bursts hints at a high burst rate. Following the community announcement of this source as a potentially active repeater, it was extensively followed up by other observatories and has emerged as one of the most prolific FRB repeaters ever observed. This paper presents the five bursts CHIME/FRB observed from FRB 20240114A, with channelized raw voltage data saved for two bursts. We do not observe changes in the DM of the source greater than ~1.3 pc cm$^{-3}$ in our observations over nearly a year baseline. We find an RM of ~ +320 rad m$^{-2}$. We do not find evidence for scattering at the level of < 0.3 ms in the bursts, and we find no evidence for astrophysical scintillation. In our observations of FRB 20240114A, we see a burst rate ~49x higher than the median burst rate of apparent non-repeaters also discovered by CHIME/FRB. Each discovery of highly active FRBs provides a valuable opportunity to investigate whether there is a fundamental difference between repeating and apparently non-repeating sources.

astro-ph.HE↗

arXiv2025

R2E-Gym: Procedural Environments and Hybrid Verifiers for Scaling Open-Weights SWE Agents

Improving open-source models on real-world SWE tasks (solving GITHUB issues) faces two key challenges: 1) scalable curation of execution environments to train these models, and, 2) optimal scaling of test-time compute. We introduce AgentGym, the largest procedurally-curated executable gym environment for training real-world SWE-agents, consisting of more than 8.7K tasks. AgentGym is powered by two main contributions: 1) SYNGEN: a synthetic data curation recipe that enables scalable curation of executable environments using test-generation and back-translation directly from commits, thereby reducing reliance on human-written issues or unit tests. We show that this enables more scalable training leading to pass@1 performance of 34.4% on SWE-Bench Verified benchmark with our 32B model. 2) Hybrid Test-time Scaling: we provide an in-depth analysis of two test-time scaling axes; execution-based and execution-free verifiers, demonstrating that they exhibit complementary strengths and limitations. Test-based verifiers suffer from low distinguishability, while execution-free verifiers are biased and often rely on stylistic features. Surprisingly, we find that while each approach individually saturates around 42-43%, significantly higher gains can be obtained by leveraging their complementary strengths. Overall, our approach achieves 51% on the SWE-Bench Verified benchmark, reflecting a new state-of-the-art for open-weight SWE-agents and for the first time showing competitive performance with proprietary models such as o1, o1-preview and sonnet-3.5-v2 (with tools). We will open-source our environments, models, and agent trajectories.

cs.SE↗

arXiv2025

Challenges and Paths Towards AI for Software Engineering

AI for software engineering has made remarkable progress recently, becoming a notable success within generative AI. Despite this, there are still many challenges that need to be addressed before automated software engineering reaches its full potential. It should be possible to reach high levels of automation where humans can focus on the critical decisions of what to build and how to balance difficult tradeoffs while most routine development effort is automated away. Reaching this level of automation will require substantial research and engineering efforts across academia and industry. In this paper, we aim to discuss progress towards this in a threefold manner. First, we provide a structured taxonomy of concrete tasks in AI for software engineering, emphasizing the many other tasks in software engineering beyond code generation and completion. Second, we outline several key bottlenecks that limit current approaches. Finally, we provide an opinionated list of promising research directions toward making progress on these bottlenecks, hoping to inspire future research in this rapidly maturing field.

cs.SE↗

arXiv2025

Simulating Chemistry with Fermionic Optical Superlattices

We show that quantum number preserving Ansätze for variational optimization in quantum chemistry find an elegant mapping to ultracold fermions in optical superlattices. Using native Hubbard dynamics, trial ground states of molecular Hamiltonians can be prepared and their molecular energies measured in the lattice. The scheme requires local control over interactions and chemical potentials and global control over tunneling dynamics, but foregoes the need for optical tweezers, shuttling operations, or long-range interactions. We describe a complete compilation pipeline from the molecular Hamiltonian to the sequence of lattice operations, thus providing a concrete link between quantum simulation and chemistry. Our work enables the application of recent quantum algorithmic techniques, such as Double Factorization and quantum Tailored Coupled Cluster, to present-day fermionic optical lattice systems with significant improvements in the required number of experimental repetitions. We provide detailed quantum resource estimates for small non-trivial hardware experiments.

cond-mat.quant-gas↗

arXiv2025

Copilot Arena: A Platform for Code LLM Evaluation in the Wild

Evaluating in-the-wild coding capabilities of large language models (LLMs) is a challenging endeavor with no clear solution. We introduce Copilot Arena, a platform to collect user preferences for code generation through native integration into a developer's working environment. Copilot Arena comprises a novel interface for comparing pairs of model outputs, a sampling strategy optimized to reduce latency, and a prompting scheme to enable code completion functionality. Copilot Arena has served over 4.5 million suggestions from 10 models and collected over 11k pairwise judgements. Our results highlight the importance of model evaluations in integrated settings. We find that model rankings from Copilot Arena differ from those of existing evaluations, which we attribute to the more realistic distribution of data and tasks contained in Copilot Arena. We also identify novel insights into human preferences on code such as an observed consistency in user preference across programming languages yet significant variation in preference due to task category. We open-source Copilot Arena and release data to enable human-centric evaluations and improve understanding of coding assistants.

cs.SE↗

arXiv2025

QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks

We introduce Quantum Feature Extraction (QuFeX), a novel quantum machine learning module. The proposed module enables feature extraction in a reduced-dimensional space, significantly decreasing the number of parallel evaluations required in typical quantum convolutional neural network architectures. Its design allows seamless integration into deep classical neural networks, making it particularly suitable for hybrid quantum-classical models. As an application of QuFeX, we propose Qu-Net -- a hybrid architecture which integrates QuFeX at the bottleneck of a U-Net architecture. The latter is widely used for image segmentation tasks such as medical imaging and autonomous driving. Our numerical analysis indicates that the Qu-Net can achieve superior segmentation performance compared to a U-Net baseline. These results highlight the potential of QuFeX to enhance deep neural networks by leveraging hybrid computational paradigms, providing a path towards a robust framework for real-world applications requiring precise feature extraction.

quant-ph↗

arXiv2024

Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis

Despite extensive usage in high-performance, low-level systems programming applications, C is susceptible to vulnerabilities due to manual memory management and unsafe pointer operations. Rust, a modern systems programming language, offers a compelling alternative. Its unique ownership model and type system ensure memory safety without sacrificing performance. In this paper, we present Syzygy, an automated approach to translate C to safe Rust. Our technique uses a synergistic combination of LLM-driven code and test translation guided by dynamic-analysis-generated execution information. This paired translation runs incrementally in a loop over the program in dependency order of the code elements while maintaining per-step correctness. Our approach exposes novel insights on combining the strengths of LLMs and dynamic analysis in the context of scaling and combining code generation with testing. We apply our approach to successfully translate Zopfli, a high-performance compression library with ~3000 lines of code and 98 functions. We validate the translation by testing equivalence with the source C program on a set of inputs. To our knowledge, this is the largest automated and test-validated C to safe Rust code translation achieved so far.

cs.SE↗