arXiv subjects

Vaibhav Sharma

Publications and source records attributed to Vaibhav Sharma.

At least 19 recordsLinked to original sources

arXiv2026

Nonlinear Diamagnetic Interactions in Ultrastrongly Coupled 2D Electrons

The quantum Hopfield model is widely used to describe ultrastrong light--matter coupling between cavity photons and collective bosonic excitations in solids, where the diamagnetic interaction is conventionally assumed to be a constant. We experimentally demonstrate that the diamagnetic response of Landau polaritons is reduced under strong terahertz field excitation. We show that this behavior originates from field-driven redistribution of electrons into the nonparabolic regime of the conduction band of GaAs, which reduces the plasma frequency and consequently the diamagnetic interaction strength. A microscopic hot-electron model reproduces the observed nonlinear response. Motivated by this microscopic picture, we propose a nonlinear extension of the Hopfield model with a Kerr-like interaction. Our results establish a route toward nonlinear cavity quantum electrodynamics and driven ultrastrong light--matter coupling beyond the conventional linear Hopfield description, which is capable of creating uniquely quantum optical effects such as squeezed light generation.

quant-ph↗

arXiv2026

Complex Energy-Dependent Behaviour of Quasi-Periodic Oscillation Observed in GRS 1915+105

We present complex energy-resolved properties of quasi-periodic oscillations (QPOs) in the black hole X-ray binary GRS 1915+105 using an observation from the LAXPC instrument onboard AstroSat. Power density spectra (PDSs) are constructed in multiple energy bands and modeled with multi-Lorentzian components to investigate the energy dependence of QPO properties. The QPO frequency shows a modest increase with energy. Dynamic PDS analysis does not reveal clear evidence for time-dependent evolution of the QPO frequency, suggesting that the observed frequency shift is not primarily driven by temporal variability. We perform simultaneous fitting of energy-resolved PDSs and find that a model in which the QPO feature is described by two Lorentzian components provides a better fit. The two components exhibit different evolution in fractional root mean square amplitude as a function of energy. We further examine the phase-lag properties by simultaneously modeling the PDS and the real and imaginary parts of the cross-spectrum and find distinct phase-lag behavior for the two components. Overall, these results indicate that the apparent energy-dependent evolution of the QPO feature may be a result of the presence of more than one variability component.

astro-ph.HE↗

arXiv2026

Technical Report: A Formal Semantics for Java Symbolic Evaluation using Large-Block Encoding

Symbolic execution plays a critical role in software reliability, as they are used to find bugs, generate test cases, and provide correctness guarantees, particularly for safety-critical systems. Yet their own correctness is rarely subject to formal scrutiny, as it is typically established empirically by evaluating tool behavior across many programs. This leaves open the possibility that the tools themselves introduce unsoundness, potentially invalidating the verification results they produce and undermining the very guarantees they are meant to provide. In this paper, we address this gap by providing the formal treatment of symbolic execution with path-merging, an optimization that improves path explosion by summarizing branching code regions into disjunctive constraints rather than exploring each path independently. Specifically, we target Java Ranger, a path-merging tool for Java programs that progressively transforms imperative Java code toward the language of formal logic through a series of code transformations. We formalize each of these transformations and prove their soundness with respect to a simplified version of the Java concrete semantics, establishing that Java Ranger's path-merging process preserves program semantics.

cs.SC↗

arXiv2026

Toric code made subsystem: a framework for topological subsystem codes using anticommuting quantum spin liquids

We introduce a framework of constructing topological subsystem codes based on the class of anticommuting quantum spin liquids described in [Phys. Rev. B 113, 064402 (2026)]. A canonical model from this class can be considered as a spatial modification of the toric code that voids its stabilizer code property. Rather, these models contain an extensive set of anticommuting local conserved operators that lead to an extensive ground state degeneracy. This degeneracy forms the basis of the subsystem degrees of freedom in the associated quantum error correcting code. The code inherits the many-body topological order of the quantum spin liquid, making it a topological subsystem code. We present two concrete and detailed examples for constructing these codes on a square lattice and a kagome lattice geometry, requiring weight-4 and weight-3 local check operator measurements respectively. In contrast to other subsystem codes, a unique property of these codes is the presence of an extensive number of local gauge qubits that are left undisturbed by the check operators apart from the logical qubits. Our construction provides a template for generating this new category of topological subsystem codes on different lattice or graph geometries, suitable for implementation on various quantum hardware platforms.

cond-mat.str-el↗

arXiv2026

Dual-use quantum hardware for quantum resource generation and energy storage

Efficient generation of quantum resources is a central objective of modern quantum technological platforms. Independently, quantum batteries have emerged as nanoscale devices that utilize collective quantum effects to store energy with a charging advantage over classical strategies. Here, we show a direct connection between these two pursuits: protocols for fast generation of resourceful quantum states can simultaneously charge a quantum battery with a collective advantage, and conversely, a quantum battery protocol with a charging advantage rapidly produces resource-rich states. Using this connection, we propose an integrated hardware protocol on superconducting circuits in which each experimental run can interchangeably accomplish either quantum battery charging, or quantum sensing through generation of metrologically useful states. Our results establish that quantum resources and stored energy are distinct yet simultaneously-producible quantities within the same dynamics. This opens the door to polymorphic quantum architectures that dynamically switch between sensing and energy-storage functions, thereby producing additional functionalities without extra hardware cost.

quant-ph↗

arXiv2026

Dicke materials as a resource for quantum squeezing

We study magnetic materials whose low energy physics can be effectively described by a Dicke model, which we term Dicke materials. We show how a Dicke model emerges in such materials due to a coexistence of fast-dispersing and slow-dispersing spins, which are strongly coupled. Analogous to the paradigmatic Dicke model describing light-matter interactions, these materials also exhibit signatures of a superradiant phase transition. The ground state near the superradiant phase transition is expected to be squeezed, making Dicke materials a resource for quantum metrology and witnessing entanglement in solid-state systems. However, as an entanglement measure, squeezing can be sensitive to perturbations that are otherwise irrelevant for usual correlation functions and order parameters. Motivated by the prospect of observing squeezing in such Dicke materials, we study the robustness of ground state squeezing under ubiquitous imperfections such as finite temperature, disorder, and local interactions. Using analytical and numerical techniques, we show that the squeezing obtained is perturbatively stable against these imperfections and quantitatively evaluate regimes promising for experimental observation.

quant-ph↗

arXiv2026

Constraining Spin and Inclination Angle of XTE J2012+381 using AstroSat and NICER

We present a spectral analysis of a black hole X-ray binary XTE J2012+381 during its 2022 outburst, using data from NICER and AstroSat. Combining data from NICER, LAXPC20, and SXT, we extract energy spectra covering the 0.7-10.0 keV range. We model the energy spectra using a series of physical models and find that a reflection-Comptonization model provides the best fit. Given the uncertainties in the black hole mass and source distance, we investigate the stability of the inferred spectral parameters by systematically varying the black hole mass (7.26, 11, and 16.5 M$_\odot$), source distance (3.3, 5.4, and 7.5 kpc), and spectral hardening factor (1.5, 1.7, and 1.9). We find that, across most combinations of these parameters, the spin solutions consistently lie in the high-spin regime, spanning values between $\sim$0.67 and $\sim$0.998, with only a limited subset of configurations favoring lower spins. In contrast, the disk inclination angle remains well constrained over the majority of the explored parameter space, typically ranging between $\sim$50° and $\sim$65°. Only a few parameter combinations yield higher inclination values.

astro-ph.HE↗

arXiv2026

Repulsively Bound Hadrons in a $\mathbb{Z}_2$ Lattice Gauge Theory

The $\mathbb{Z}_2$ lattice gauge theory is a paradigmatic model that exhibits gauge-field-mediated-confinement of pairs of particles into mesons, drawing connections to quantum chromodynamics. In the absence of any additional attractive interactions between particles, mesons are not known to bind in this model. Here, we show that resonant pair-production terms give rise to two separate mechanisms to form stable ``hadron'' bound states of two mesons: either induced by an effective attractive interaction, or a new dynamical binding mechanism induced by an effective repulsion. The repulsively bound hadron is a high-energy state stabilized by being energetically separated from the two-meson continuum through quantum fluctuations of the gauge fields. We study the dynamical formation of this bound state starting from local excitations. We use matrix product state techniques based on the time-evolving block decimation algorithm to perform our numerical simulations and analyze the effect of model parameters on hadron formation. Furthermore, we derive an effective model that explains its formation. Our findings are amenable to experimental observation on modern quantum hardware such as superconducting qubits, trapped ions, and Rydberg atom arrays.

hep-lat↗

arXiv2025

Evolution of the 2021 Outburst of GX 339-4 with AstroSat

We present a comprehensive study of the 2021 outburst of GX 339-4 using AstroSat observations in the hard-intermediate (HIMS) and soft-intermediate states (SIMS). Spectral and timing analyses across these states suggest that during the SIMS, unabsorbed flux (0.1-3 keV), inner disc temperature, and "apparent" inner disc radius do not change, suggesting the stability of the disc. In the SIMS, the photon index decreases from 2.1 to 1.7, indicating spectral hardening. The power density spectra (PDS) suggest the presence of quasi-periodic oscillations (QPOs) in the HIMS and SIMS. The QPO frequency evolves from 0.1 Hz to 0.2 Hz in the HIMS, and further to 5.7 Hz in the SIMS. We also observe a decrease in QPO frequency from 5.7 Hz to 4.5 Hz during the SIMS. We discuss the evolution of the QPO, fractional root mean square (rms) amplitude, and time-lag spectra. We discover that variations in disc normalization, disc temperature, and coronal heating rate can reproduce the observed rms and lag spectra with a time delay between them.

astro-ph.HE↗

arXiv2025

Fractal structure of multipartite entanglement in monitored quantum circuits

We study the structure of multipartite entanglement in monitored quantum circuits exhibiting measurement-induced phase transitions (MIPTs). Using a one-dimensional Clifford circuit subject to local measurements with a probability $p$, we show numerically that the entanglement depth, corresponding to the size of the largest cluster of entangled qubits scales as a power law with system size on both sides of the transition. The power law exponent is 1 in the entangling phase and continuously decreases to 0 as $p \to 1$ in the disentangling phase. In addition, we find that the spatial support of the largest cluster exhibits an approximate fractal geometry with a tunable fractal dimension controlled by the measurement rate. We argue that this structure arises from a competition between unitary-driven coagulation of entangled clusters and measurement-induced fragmentation, giving rise to a fractal steady state reminiscent of classical coagulation-fragmentation models. Away from the MIPT critical point, the fractal dimension matches the entanglement depth power law exponent. These results show that multipartite entanglement structure provides a fresh perspective on the emergent quantum correlations in monitored quantum circuits and noisy quantum dynamics.

quant-ph↗

arXiv2025

Leveraging the Cross-Domain & Cross-Linguistic Corpus for Low Resource NMT: A Case Study On Bhili-Hindi-English Parallel Corpus

The linguistic diversity of India poses significant machine translation challenges, especially for underrepresented tribal languages like Bhili, which lack high-quality linguistic resources. This paper addresses the gap by introducing Bhili-Hindi-English Parallel Corpus (BHEPC), the first and largest parallel corpus worldwide comprising 110,000 meticulously curated sentences across Bhili, Hindi, and English. The corpus was created with the assistance of expert human translators. BHEPC spans critical domains such as education, administration, and news, establishing a valuable benchmark for research in low resource machine translation. To establish a comprehensive Bhili Machine Translation benchmark, we evaluated a wide range of proprietary and open-source Multilingual Large Language Models (MLLMs) on bidirectional translation tasks between English/Hindi and Bhili. Comprehensive evaluation demonstrates that the fine-tuned NLLB-200 distilled 600M variant model outperforms others, highlighting the potential of multilingual models in low resource scenarios. Furthermore, we investigated the generative translation capabilities of multilingual LLMs on BHEPC using in-context learning, assessing performance under cross-domain generalization and quantifying distributional divergence. This work bridges a critical resource gap and promotes inclusive natural language processing technologies for low-resource and marginalized languages globally.

cs.CL↗

arXiv2025

POSESTITCH-SLT: Linguistically Inspired Pose-Stitching for End-to-End Sign Language Translation

Sign language translation remains a challenging task due to the scarcity of large-scale, sentence-aligned datasets. Prior arts have focused on various feature extraction and architectural changes to support neural machine translation for sign languages. We propose POSESTITCH-SLT, a novel pre-training scheme that is inspired by linguistic-templates-based sentence generation technique. With translation comparison on two sign language datasets, How2Sign and iSign, we show that a simple transformer-based encoder-decoder architecture outperforms the prior art when considering template-generated sentence pairs in training. We achieve BLEU-4 score improvements from 1.97 to 4.56 on How2Sign and from 0.55 to 3.43 on iSign, surpassing prior state-of-the-art methods for pose-based gloss-free translation. The results demonstrate the effectiveness of template-driven synthetic supervision in low-resource sign language settings.

cs.CL↗

arXiv2025

Dimension Mask Layer: Optimizing Embedding Efficiency for Scalable ID-based Models

In modern recommendation systems and social media platforms like Meta, TikTok, and Instagram, large-scale ID-based features often require embedding tables that consume significant memory. Managing these embedding sizes can be challenging, leading to bulky models that are harder to deploy and maintain. In this paper, we introduce a method to automatically determine the optimal embedding size for ID features, significantly reducing the model size while maintaining performance. Our approach involves defining a custom Keras layer called the dimension mask layer, which sits directly after the embedding lookup. This layer trims the embedding vector by allowing only the first N dimensions to pass through. By doing this, we can reduce the input feature dimension by more than half with minimal or no loss in model performance metrics. This reduction helps cut down the memory footprint of the model and lowers the risk of overfitting due to multicollinearity. Through offline experiments on public datasets and an online A/B test on a real production dataset, we demonstrate that using a dimension mask layer can shrink the effective embedding dimension by 40-50\%, leading to substantial improvements in memory efficiency. This method provides a scalable solution for platforms dealing with a high volume of ID features, optimizing both resource usage and model performance.

cs.IR↗

arXiv2025

Meson dynamics from locally exciting a particle-conserving $Z_2$ lattice gauge theory

Quantum simulation of lattice gauge theories is an important avenue to gain insights into both particle physics phenomena and constrained quantum many-body dynamics. There is a growing interest in probing analogs of high energy collision phenomena in lattice gauge theories that can be implemented on current quantum simulators. Motivated by this, we characterize the confined mesons that originate from a local high energy excitation in a particle-conserving 1D $Z_2$ lattice gauge theory. We focus on a simple, experimentally accessible setting that does not require preparation of colliding wavepackets and isolates the effects of gauge field confinement strength and initial state energy on the nature of propagating excitations. We find that the dynamics is characterized by the propagation of a superposition of differently sized mesons. The linear confinement leads to meson size oscillations in time. The average meson size and oscillation frequency are controlled by the strength of the gauge field confinement. At a constant confinement field, the average meson length is controlled by the initial excitation's energy. Higher energies produce longer mesons and their effective mass depends strongly on their size: longer mesons propagate more slowly out of the central excitation. Mesons of different sizes get spatially filtered with time due to different speeds. We show that this phenomenology is a consequence of linear confinement and remains valid in both the strong and weak confinement limit. We present simple explanations of these phenomena supported by exact numerics.

quant-ph↗

arXiv2025

Multipartite entanglement structures in quantum stabilizer states

We develop a method for visualizing the internal structure of multipartite entanglement in pure stabilizer states. Our algorithm graphically organizes the many-body correlations in a hierarchical structure. This provides a rich taxonomy from which one can simultaneously extract many quantitative features of a state including some traditional quantities such as entanglement depth, k-uniformity and entanglement entropy. Our method also presents an alternative computational tool for extracting the exact entanglement depth and all separable partitions of a stabilizer state. Our construction is gauge invariant and goes beyond traditional entanglement measures by visually revealing how quantum information and entanglement is distributed. We use this tool to analyze the internal structures of prototypical stabilizer states (GHZ state, cluster state, stabilizer error correction codes) and are able to contrast the complexity of highly entangled volume law states generated by random unitary operators and random projective measurements.

quant-ph↗

arXiv2024

One-dimensional $Z_2$ lattice gauge theory in periodic Gauss-law sectors

We calculate the properties of a one-dimensional $Z_2$ lattice gauge theory in different Gauss law sectors, corresponding to different configurations of static charges set by the orientations of the gauge spins. Importantly, in quantum simulator experiments these sectors can be accessed without adding any additional physical particles or changing the Hamiltonian: The Gauss law sectors are simply set by the initial conditions. We study the interplay between conservation laws and interactions when the static charges are chosen to form periodic patterns. We classify the different Gauss law sectors and use the density matrix renormalization group to calculate the ground state compressibility, density profiles, charge density wave order parameters, and single particle correlation functions as a function of matter density. We find confined and deconfined phases, charge density waves, correlated insulators, and supersolids.

cond-mat.quant-gas↗

arXiv2023

Rotational and translational drags of a Janus particle close to a wall and a lipid membrane

Hypothesis: Measuring rotational and translational Brownian motion of single spherical particles reveals dissipations due to the interaction between the particle and the environment. Experiments: In this article, we show experiments where the in-plane translational and two rotational drag coefficients of a single spherical Brownian particle can be measured. These particle drags are functions of the particle size and the particle-wall distance, and of the viscous dissipations at play. We measure drag coefficients for Janus particles close to a solid wall and close to a lipid bilayer membrane. Findings: For a particle close to wall, we show that according to hydrodynamic models, particlewall distance and particle size can be determined. For a particle partially wrapped by lipid membranes, in absence of strong binding interactions, translational and rotational drags are significantly larger than the ones of non-wrapped particles. Beside the effect of the membrane viscosity, we show that dissipations in the deformed membrane cap region strongly contribute to the drag coefficients.

cond-mat.soft↗

arXiv2023

State Merging with Quantifiers in Symbolic Execution

We address the problem of constraint encoding explosion which hinders the applicability of state merging in symbolic execution. Specifically, our goal is to reduce the number of disjunctions and if-then-else expressions introduced during state merging. The main idea is to dynamically partition the symbolic states into merging groups according to a similar uniform structure detected in their path constraints, which allows to efficiently encode the merged path constraint and memory using quantifiers. To address the added complexity of solving quantified constraints, we propose a specialized solving procedure that reduces the solving time in many cases. Our evaluation shows that our approach can lead to significant performance gains.

cs.SE↗