Tootfinder

Calibration of VELC detectors on-board Aditya-L1 mission
Shalabh Mishra, K. Sasikumar Raja, Sanal Krishnan V U, Venkata Suresh Narra, Bhavana Hegde S, Utkarsha D., Muthu Priyal V, Pawan Kumar S, Natarajan V, Raghavendra Prasad B, Jagdev Singh, Umesh Kamath P, Kathiravan S, Vishnu T, Suresha, Savarimuthu P, Jalshri H Desai, Rajiv Kumaran, Shiv Sagar, Sumit Kumar, Inderjeet Singh Bamrah, Amit Kumar

Calibration of VELC detectors on-board Aditya-L1 mission
Aditya-L1 is the first Indian space mission to explore the Sun and solar atmosphere with seven multi-wavelength payloads, with Visible Emission Line Coronagraph (VELC) being the prime payload. It is an internally occulted coronagraph with four channels to image the Sun at 5000 Å~ in the field of view 1.05 - 3 \rsun, and to pursue spectroscopy at 5303 Å, 7892 Å~ and 10747 Å~ channels in the FOV (1.05 - 1.5 \rsun). In addition, spectropolarimetry is planned at 10747 Å~ channel. Therefore, VE…

The interaction of gravitational waves with matter
Nigel T. Bishop, Vishnu Kakkat, Amos S. Kubeka, Monos Naidoo, Petrus J. van der Walt
https://arxiv.org/abs/2405.07743

The Massalia asteroid family as the origin of ordinary L chondrites
Micha\"el Marsset, Pierre Vernazza, Miroslav Bro\v{z}, Cristina A. Thomas, Francesca E. DeMeo, Brian Burt, Richard P. Binzel, Vishnu Reddy, Allison McGraw, Chrysa Avdellidou, Benoit Carry, Stephen M. Slivan, David Polishook
https://arxiv.org/abs/2403.08548<…

The Massalia asteroid family as the origin of ordinary L chondrites
Studies of micrometeorites in mid-Ordovician limestones and Earth's impact craters indicate that our planet witnessed a massive infall of ordinary L chondrite material 466 million years (My) ago (Heck et al. 2017, Schmieder & Kring 2020, Kenkmann 2021) that may have been at the origin of the first major mass extinction event (Schmitz et al. 2019). The breakup of a large asteroid in the main belt is the likely cause of this massive infall. In modern times, material originating from this breakup …

Calibration of VELC detectors on-board Aditya-L1 mission
Shalabh Mishra, K. Sasikumar Raja, Sanal Krishnan V U, Venkata Suresh Narra, Bhavana Hegde S, Utkarsha D., Muthu Priyal V, Pawan Kumar S, Natarajan V, Raghavendra Prasad B, Jagdev Singh, Umesh Kamath P, Kathiravan S, Vishnu T, Suresha, Savarimuthu P, Jalshri H Desai, Rajiv Kumaran, Shiv Sagar, Sumit Kumar, Inderjeet Singh Bamrah, Amit Kumar

Calibration of VELC detectors on-board Aditya-L1 mission
Aditya-L1 is the first Indian space mission to explore the Sun and solar atmosphere with seven multi-wavelength payloads, with Visible Emission Line Coronagraph (VELC) being the prime payload. It is an internally occulted coronagraph with four channels to image the Sun at 5000 Å~ in the field of view 1.05 - 3 \rsun, and to pursue spectroscopy at 5303 Å, 7892 Å~ and 10747 Å~ channels in the FOV (1.05 - 1.5 \rsun). In addition, spectropolarimetry is planned at 10747 Å~ channel. Therefore, VE…

The interaction of gravitational waves with matter
Nigel T. Bishop, Vishnu Kakkat, Amos S. Kubeka, Monos Naidoo, Petrus J. van der Walt
https://arxiv.org/abs/2405.07743

The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models
Abeba Birhane, Sepehr Dehdashtian, Vinay Uday Prabhu, Vishnu Boddeti
https://arxiv.org/abs/2405.04623

The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models
Scale the model, scale the data, scale the GPU farms is the reigning sentiment in the world of generative AI today. While model scaling has been extensively studied, data scaling and its downstream impacts on model performance remain under-explored. This is particularly important in the context of multimodal datasets whose main source is the World Wide Web, condensed and packaged as the Common Crawl dump, which is known to exhibit numerous drawbacks. In this paper, we evaluate the downstream im…

Convert any android device into a programmable IoT device with the help of IoT Everywhere Framework
Vishnu Joshi
https://arxiv.org/abs/2405.01568 https://<…

Convert any android device into a programmable IoT device with the help of IoT Everywhere Framework
The world around us is transforming as the field of the Internet of Things is taking over the world faster than we thought. Everyone in the tech industry is building wonderful things with the help of IoT. Smartwatches, smart coffee machines, smart television, smart homes are some of the examples. Building IoT sensor modules with sensors that connect to the internet can be very intimidating for people who have just stepped into the field. Quality components and microcontrollers can be costly too…

On generators of $k$-PSD closures of the positive semidefinite cone
Avinash Bhardwaj, Vishnu Narayanan, Abhishek Pathapati
https://arxiv.org/abs/2405.01208

On generators of $k$-PSD closures of the positive semidefinite cone
Positive semidefinite (PSD) cone is the cone of positive semidefinite matrices, and is the object of interest in semidefinite programming (SDP). A computational efficient approximation of the PSD cone is the $k$-PSD closure, $1 \leq k < n$, cone of $n\times n$ real symmetric matrices such that all of their $k\times k$ principal submatrices are positive semidefinite. For $k=1$, one obtains a polyhedral approximation, while $k=2$ yields a second order conic (SOC) approximation of the PSD cone. Th…

Predicting positon solutions of a family of Nonlinear Schr\"{o}dinger equations through Deep Learning algorithm
K. Thulasidharan, N. Vishnu Priya, S. Monisha, M. Senthilvelan
https://arxiv.org/abs/2405.04968

Predicting positon solutions of a family of Nonlinear Schrödinger equations through Deep Learning algorithm
We consider a hierarchy of nonlinear Schrödinger equations (NLSEs) and forecast the evolution of positon solutions using a deep learning approach called Physics Informed Neural Networks (PINN). Notably, the PINN algorithm accurately predicts positon solutions not only in the standard NLSE but also in other higher order versions, including cubic, quartic and quintic NLSEs. The PINN approach also effectively handles two coupled NLSEs and two coupled Hirota equations. In addition to the above, we…

Complete and Near-Optimal Robotic Crack Coverage and Filling in Civil Infrastructure
Vishnu Veeraraghavan, Kyle Hunte, Jingang Yi, Kaiyan Yu
https://arxiv.org/abs/2403.00613

Complete and Near-Optimal Robotic Crack Coverage and Filling in Civil Infrastructure
We present a simultaneous sensor-based inspection and footprint coverage (SIFC) planning and control design with applications to autonomous robotic crack mapping and filling. The main challenge of the SIFC problem lies in the coupling of complete sensing (for mapping) and robotic footprint (for filling) coverage tasks. Initially, we assume known target information (e.g., crack) and employ classic cell decomposition methods to achieve complete sensing coverage of the workspace and complete robot…

Predicting positon solutions of a family of Nonlinear Schr\"{o}dinger equations through Deep Learning algorithm
K. Thulasidharan, N. Vishnu Priya, S. Monisha, M. Senthilvelan
https://arxiv.org/abs/2405.04968

Predicting positon solutions of a family of Nonlinear Schrödinger equations through Deep Learning algorithm
We consider a hierarchy of nonlinear Schrödinger equations (NLSEs) and forecast the evolution of positon solutions using a deep learning approach called Physics Informed Neural Networks (PINN). Notably, the PINN algorithm accurately predicts positon solutions not only in the standard NLSE but also in other higher order versions, including cubic, quartic and quintic NLSEs. The PINN approach also effectively handles two coupled NLSEs and two coupled Hirota equations. In addition to the above, we…

The population of small near-Earth objects: composition, source regions and rotational properties
Juan A. Sanchez, Vishnu Reddy, Audrey Thirouin, William F. Bottke, Theodore Kareta, Mario De Florio, Benjamin N. L. Sharkey, Adam Battle, David C. Cantillo, Neil Pearson
https://arxiv.org/abs/2404.18263

The population of small near-Earth objects: composition, source regions and rotational properties
The study of small ($<$300 m) near-Earth objects (NEOs) is important because they are more closely related than larger objects to the precursors of meteorites that fall on Earth. Collisions of these bodies with Earth are also more frequent. Although such collisions cannot produce massive extinction events, they can still produce significant local damage. Here we present the results of a photometric and spectroscopic survey of small NEOs, which include near-infrared (NIR) spectra of 84 objects w…

Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross, Vishnu Boddeti, Nalini Ratha
https://arxiv.org/abs/2404.16255

Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption
Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templates in a face recognition system. These embeddings are susceptible to data leakage and, in some cases, can even be used to reconstruct the original face image. To prevent compromising identities, template protection schemes are commonly employed. However, these schemes may still not prevent the leakage of soft biomet…

Block and Detail: Scaffolding Sketch-to-Image Generation
Vishnu Sarukkai, Lu Yuan, Mia Tang, Maneesh Agrawala, Kayvon Fatahalian
https://arxiv.org/abs/2402.18116

Block and Detail: Scaffolding Sketch-to-Image Generation
We introduce a novel sketch-to-image tool that aligns with the iterative refinement process of artists. Our tool lets users sketch blocking strokes to coarsely represent the placement and form of objects and detail strokes to refine their shape and silhouettes. We develop a two-pass algorithm for generating high-fidelity images from such sketches at any point in the iterative process. In the first pass we use a ControlNet to generate an image that strictly follows all the strokes (blocking and …

Unruh effect using Doppler shift method in DSR framework
Vishnu Rajagopal
https://arxiv.org/abs/2403.20146 https://arxiv.org/pdf/2403…

Unruh effect using Doppler shift method in DSR framework
We study the Unruh effect in doubly special relativity (DSR) framework by generalising the Doppler-shift method to DSR. For both the scalar and Dirac particles, we observe a deviation in the power spectrum of Unruh radiation from the standard Bose-Einstein and Fermi-Dirac distributions, respectively, due to the presence of the frame independent length scale of DSR. We further show that this deviation results in the modification of Unruh temperature which then depends non-linearly on the proper …

Surveyor: Facilitating Discovery Within Video Games for Blind and Low Vision Players
Vishnu Nair, Hanxiu 'Hazel' Zhu, Peize Song, Jizhong Wang, Brian A. Smith
https://arxiv.org/abs/2403.10512

Surveyor: Facilitating Discovery Within Video Games for Blind and Low Vision Players
Video games are increasingly accessible to blind and low vision (BLV) players, yet many aspects remain inaccessible. One aspect is the joy players feel when they explore environments and make new discoveries, which is integral to many games. Sighted players experience discovery by surveying environments and identifying unexplored areas. Current accessibility tools, however, guide BLV players directly to items and places, robbing them of that experience. Thus, a crucial challenge is to develop n…

This https://arxiv.org/abs/2311.01747 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Determining the neutron skin thickness by relativistic semi-isobaric collisions
The neutron skin thickness of the benchmark nucleus $^{208}$Pb is crucial for our understanding of the equation of state of nuclear matter. In this paper, we discuss the effect of the neutron skin on the flow ratio observables in the semi-isobaric collisions $^{208}$Pb+$^{208}$Pb and $^{197}$Au+$^{197}$Au using iEBE-VISHNU hydrodynamic simulations. Our results suggest that $^{208}$Pb and $^{197}$Au should have the same magnitude of neutron skin thickness to describe the anisotropic flow ratios …

LAVA: Long-horizon Visual Action based Food Acquisition
Amisha Bhaskar, Rui Liu, Vishnu D. Sharma, Guangyao Shi, Pratap Tokekar
https://arxiv.org/abs/2403.12876

LAVA: Long-horizon Visual Action based Food Acquisition
Robotic Assisted Feeding (RAF) addresses the fundamental need for individuals with mobility impairments to regain autonomy in feeding themselves. The goal of RAF is to use a robot arm to acquire and transfer food to individuals from the table. Existing RAF methods primarily focus on solid foods, leaving a gap in manipulation strategies for semi-solid and deformable foods. This study introduces Long-horizon Visual Action (LAVA) based food acquisition of liquid, semisolid, and deformable foods. L…

Synchronized Opto-Electro-Mechanical Measurements for Energy Loss Estimation in Thin-Film-Piezoelectric-on-Substrate MEMS/NEMS Devices
Vishnu Kumar, Sudhanshu Tiwari, Gayathri Pillai, Rudra Pratap, Saurabh Chandorkar
https://arxiv.org/abs/2403.10845

Synchronized Opto-Electro-Mechanical Measurements for Energy Loss Estimation in Thin-Film-Piezoelectric-on-Substrate MEMS/NEMS Devices
Piezoelectric micro-electro-mechanical systems have significant market potential owing to their superior capabilities of transduction to those of standard capacitive and piezoresistive devices. However, piezoelectric films are often lossy, which reduces the quality factor of devices and affects their performance. It is thus important to examine all sources of energy losses in such devices and accurately determine them based on experimental data. Currently used methods to quantify energy loss fr…

Numerical Study of a Strongly Coupled Two-scale System with Nonlinear Dispersion
Surendra Nepal, Vishnu Raveendran, Michael Eden, Rainey Lyons, Adrian Muntean
https://arxiv.org/abs/2402.09607

This https://arxiv.org/abs/2401.15723 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Exploring the compactness of $α$ cluster in the $^{16}$O nuclei with relativistic $^{16}$O+$^{16}$O collisions
Probing the $α$ cluster of $^{16}$O with the relativistic $^{16}$O+$^{16}$O collisions has raised great interest in the heavy ion community. However, the effects of the $α$ cluster on the soft hadron observables are largely different for these previous studies. In this paper, we explain the differences by the compactness of the $α$ cluster in oxygen, using iEBE-VISHNU hydrodynamic simulations with different initial state $α$ cluster configurations. We also find several observables, such as …