arXiv subjects

Akhil Nair

Publications and source records attributed to Akhil Nair.

5 recordsLinked to original sources

arXiv2026

Stochastic Variability of Binary Accretion

We measure the power spectral density (PSD) of the accretion rate time series in an unequal mass (q = 0.2) binary surrounded by a circumbinary gas disk, using very high-resolution 2D hydrodynamics simulations. Our aim is to identify new signposts of supermassive black hole (SMBH) binaries in active galactic nuclei (AGN), based on the shape of the continuum PSD, to complement well-studied line features in the PSD (periodicities). We find that the continuum PSD is a broken power-law, transitioning from flat (white noise) to a slope of -4 at a break frequency generically ~5 times the binary orbital frequency. This form is expected when (a) delivery of gas from the circumbinary disk to the individual "minidisks" is a damped random walk with correlation time equal to binary orbital period and (b) the minidisks function as low-pass filters acting at the Kepler frequency of the outer edge of the smaller black hole's minidisk; we show numerical evidence for both. The broken power-law PSD is attained in a limit where the secondary black hole is much smaller than its minidisk, realized numerically by a sufficiently small "sink" region; larger sinks lead to excess high-frequency noise seen as accretion rate spikes, and we argue these should be regarded as artificial when the black holes themselves are smaller than the sink regions. The broken power-law PSD is reminiscent of stochastic variability in ordinary AGN, inviting the conjecture that canonical AGN variability could result from widespread binarity, however pulsar timing experiments may exclude this possibility.

astro-ph.HE↗

arXiv2025

Theseus: A Distributed and Scalable GPU-Accelerated Query Processing Platform Optimized for Efficient Data Movement

Online analytical processing of queries on datasets in the many-terabyte range is only possible with costly distributed computing systems. To decrease the cost and increase the throughput, systems can leverage accelerators such as GPUs, which are now ubiquitous in the compute infrastructure. This introduces many challenges, the majority of which are related to when, where, and how to best move data around the system. We present Theseus -- a production-ready enterprise-scale distributed accelerator-native query engine designed to balance data movement, memory utilization, and computation in an accelerator-based system context. Specialized asynchronous control mechanisms are tightly coupled to the hardware resources for the purpose of network communication, data pre-loading, data spilling across memories and storage, and GPU compute tasks. The memory subsystem contains a mechanism for fixed-size page-locked host memory allocations to increase throughput and reduce memory fragmentation. For the TPC-H benchmarks at scale factors ranging from 1k to 30k on cloud infrastructure, Theseus outperforms Databricks Photon by up to $4\times$ at cost parity. Theseus is capable of processing all queries of the TPC-H and TPC-DS benchmarks at scale factor 100k (100 TB scale) with as few as 2 DGX A100 640GB nodes.

cs.DC↗

arXiv2025

High-magnitude, spatially programmable, and sustained strain engineering of 2D semiconductors

Crystalline two-dimensional (2D) semiconductors often combine high elasticity and in-plane strength, making them ideal for strain-induced tuning of electronic characteristics, akin to strategies used in silicon electronics. However, existing techniques have not achieved strain in 2D materials that is simultaneously high in magnitude (>1%), stable over long periods, and spatially programmable, meaning the strain level can be deterministically engineered across different regions of a single 2D layer. Here, we apply spatially programmable biaxial strain (e_b) up to 2.2% with spatial resolution of 0.13 %e_b um-1 in monolayer MoS2 via conformal transfer onto patterned substrates fabricated using two-photon lithography. The induced strain is stable for months and enables local band gap tuning of ~0.4 eV in monolayer MoS2, ~25% of its intrinsic band gap. We further extend the approach to bilayer WS2-MoS2 heterostructures. This strain-engineering technique introduces a new regime of strain-enabled control in 2D semiconductors to support the development of wide-spectrum optoelectronic devices and nanoelectronics with engineered electronic landscapes.

cond-mat.mtrl-sci↗

arXiv2023

Studying the Effects of Sex-related Differences on Brain Age Prediction using brain MR Imaging

While utilizing machine learning models, one of the most crucial aspects is how bias and fairness affect model outcomes for diverse demographics. This becomes especially relevant in the context of machine learning for medical imaging applications as these models are increasingly being used for diagnosis and treatment planning. In this paper, we study biases related to sex when developing a machine learning model based on brain magnetic resonance images (MRI). We investigate the effects of sex by performing brain age prediction considering different experimental designs: model trained using only female subjects, only male subjects and a balanced dataset. We also perform evaluation on multiple MRI datasets (Calgary-Campinas(CC359) and CamCAN) to assess the generalization capability of the proposed models. We found disparities in the performance of brain age prediction models when trained on distinct sex subgroups and datasets, in both final predictions and decision making (assessed using interpretability models). Our results demonstrated variations in model generalizability across sex-specific subgroups, suggesting potential biases in models trained on unbalanced datasets. This underlines the critical role of careful experimental design in generating fair and reliable outcomes.

eess.IV↗

arXiv2022

Fraction of broad absorption line quasars in different radio morphologies

In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample of sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalog and Very Large Array (VLA)-Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey. Using the radio cut-out images from the FIRST survey, we first designed a deep learning model using convolutional neural networks (CNN) to classify the quasar radio morphologies into the core-only, young jet, single lobe, or triples. These radio morphologies are further sub-classified into core-dominated and lobe-dominated sources. The CNN models can classify the sources with a high precision of >98% for all the morphological sub-classes. The average BAL fraction in the resolved core, core-dominated, and lobe-dominated quasars are consistent with the BAL fraction inferred from radio and infra-red surveys. We also present the distribution of BAL quasars as a function of quasar orientation by using the radio core-dominance as an orientation indicator. A similar analysis is performed for HiBALs, LoBALs, and FeLoBALs. All the radio morphological sub-classes and BAL sub-classes show an increase in BAL fraction at high orientation angles of the jets with respect to the line of sight. Our analysis suggests that BAL quasars are more likely to be found in viewing angles close to the equatorial plane of the quasar. However, a pure orientation model is inadequate, and a combination of orientation and evolution is probably the best way to explain the complete BAL phenomena.

astro-ph.GA↗