Publications (25)
Bounds and asymptotic expansions for the radii of convexity and uniform convexity of normalized Bessel functions
Ãrpád Baricz, Pranav Kumar, Sanjeev Singh
This paper explores the asymptotic behaviour of the radii of convexity and uniform convexity for normalized Bessel functions with respect to large order. We provide detailed asympt…
Black holes and the loss landscape in machine learning
Pranav Kumar, Taniya Mandal, Swapnamay Mondal
Understanding the loss landscape is an important problem in machine learning. One key feature of the loss function, common to many neural network architectures, is the presence of…
Density results of biharmonic functions on symmetric tensor fields and their applications to inverse problems
Divyansh Agrawal, Sombuddha Bhattacharyya, Pranav Kumar
In this article we discuss density of products of biharmonic functions vanishing on an arbitrarily small part of the boundary. We prove that one can use three or more such biharmon…
DREMS-OS: An Operating System for Managed Distributed Real-time Embedded Systems
Abhishek Dubey, Gabor Karsai, Aniruddha Gokhale +2
Distributed real-time and embedded (DRE) systems executing mixed criticality task sets are increasingly being deployed in mobile and embedded cloud computing platforms, including s…
Nucleosynthesis in slowly evolving Cosmologies
Pranav Kumar, Daksh Lohiya
We explore aspects of Cosmological Nucleosynthesis in an FRW universe in which the scale factor evolves linearly with time: . A high Lepton number density during the p…
Machine Learning Potentials for Hydrogen Absorption in TiCr Laves Phases
Pranav Kumar, Fritz Körmann, Blazej Grabowski +1
The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCrH Laves phases is investigated for with density functional theory (DFT) and machine l…
An Unsupervised Approach for Overlapping Cervical Cell Cytoplasm Segmentation
Pranav Kumar, S L Happy, Swarnadip Chatterjee +2
The poor contrast and the overlapping of cervical cell cytoplasm are the major issues in the accurate segmentation of cervical cell cytoplasm. This paper presents an automated unsu…
Local data inverse problem for the polyharmonic operator with anisotropic perturbations
Sombuddha Bhattacharyya, Pranav Kumar
In this article, we study an inverse problem with local data for a linear polyharmonic operator with several lower order tensorial perturbations. We consider our domain to have an…
Variable Chaplygin Gas: Constraints from CMBR and SNe Ia
Geetanjali Sethi, Sushil K. Singh, Pranav Kumar +2
We constrain the parameters of the variable Chaplygin gas model, using the location of peaks of the CMBR spectrum and SNe Ia ``gold '' data set. Equation of state of the model is $…
Adding Compilation Metadata To Binaries To Make Disassembly Decidable
Daniel Engel, Freek Verbeek, Pranav Kumar +1
The binary executable format is the standard method for distributing and executing software. Yet, it is also as opaque a representation of software as can be. If the binary format…
Inverse boundary value problem for the Convection-Diffusion equation with local data
Pranav Kumar, Anamika Purohit
We study a local data inverse problem for the time-dependent Convection-Diffusion Equation (CDE) in a bounded domain where a part of the boundary is treated to be inaccessible. Up…
Asymptotic behavior of zeros of Bessel function derivatives
Ãrpád Baricz, Pranav Kumar, Saminathan Ponnusamy
We derive two distinct asymptotic expansions for the zeros of the -th derivative of Bessel function . The first is a McMahon-type expansion for t…
Non-trivial saddles in microscopic description of black holes
Pranav Kumar, Swapnamay Mondal
Non-trivial gravitational saddles have played a key role in the island proposal for the black hole information paradox. It is worth asking if non-trivial saddles exist in microscop…
Hydrogen diffusion in TiCrH Laves phases: A combined ab initio and machine-learning-potential study
Pranav Kumar, Fritz Körmann, Kaveh Edalati +2
The kinetics of hydrogen diffusion in C15 cubic and C14 hexagonal TiCrH (0 < <= 4) Laves-phase hydrogen storage alloys is investigated with density functional theory (D…
A case for nucleosynthesis in slowly evolving models
Geetanjali Sethi, Pranav Kumar, Sanjay Pandey +1
We present a case for Cosmological Nucleosynthesis in an FRW universe in which the scale factor expands linearly with time: . It is demonstrated that adequate amount o…
Incomplete RG: Hawking-Page transition, C-theorem and relevant scalar deformations of global AdS
Pallab Basu, Pranav Kumar, Chuene Mosomane
We discuss relevant scalar deformations of a holographic theory with a compact boundary. An example of such a theory would be the global AdS with its spatially compact boundary…
A Concordant "Freely Coasting Cosmology"
Savita Gehlaut, Pranav Kumar, Geetanjali +1
A strictly linear evolution of the cosmological scale factor is surprisingly an excellent fit to a host of cosmological observations. Any model that can support such a coasting pre…
Classical Unattainability of Extremality in non-BPS D-brane Systems
Pranav Kumar, Swapnamay Mondal
For the worldline theory of an extremal black hole, extremality amounts to vanishing ground state energy. In light of recent gravity results one would expect much like the ground s…
Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature
Shivam Dangwal, Pranav Kumar, Yuji Ikeda +2
High-entropy alloys (HEAs) have received considerable attention for hydrogen storage because of their compositional flexibility; however, designing HEAs with optimal thermodynamics…
Direct and inverse problem for bi-wave equation with time-dependent coefficients from partial data
Sombuddha Bhattacharyya, Pranav Kumar
In this article, we study a direct and an inverse problem for the bi-wave operator along with second and lower order time-dependent perturbations. In the direct problem,…
An Ontology for Machine Learning Interatomic Potentials
Daniel Hernández, Jong Hyun Jung, Yuji Ikeda +11
Machine learning interatomic potentials (MLIPs) approximate quantum-mechanical energies and forces---conventionally computed by density functional theory (DFT) or wave-function met…
Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies
Xinchen Jin, Aditya Chatterjee, Pranav Kumar +1
Vision-Language-Action (VLA) policies translate language and visual inputs into robot actions, where their hidden representations directly shape closed-loop behavior. However, mech…
Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions
Yuji Ikeda, Axel Forslund, Pranav Kumar +4
Machine-learning interatomic potentials (MLIPs) enable large-scale atomistic simulations at moderate computational cost while retaining ab initio accuracy. MLIPs trained on coupled…
The radius of starlikeness of regular Coulomb wave functions
Ãrpád Baricz, Pranav Kumar, Sanjeev Singh
Motivated by the pioneering work of M.S. Robertson [Ro54] and R.K. Brown [Br60], [Br62], who examined the geometric properties of some normalised solutions of second-order homogene…
Diffusion Meets DAgger: Supercharging Eye-in-hand Imitation Learning
Xiaoyu Zhang, Matthew Chang, Pranav Kumar +1
A common failure mode for policies trained with imitation is compounding execution errors at test time. When the learned policy encounters states that are not present in the expert…