arXiv subjects

Mohit Kumar

Publications and source records attributed to Mohit Kumar.

At least 19 recordsLinked to original sources

arXiv2026

Dispersive-phonon-driven room-temperature Ni1+-Ni2+ polaron hopping in spin-charge coupled rutile niobate

Understanding how lattice dynamics mediate polaron hopping is essential for designing multifunctional correlated oxides. Here, we demonstrate room-temperature dispersive phonon excitations and elucidate the Ni1+-Ni2+ polaron-hopping mechanism and the presence of rare spin-charge-phonon coupling even in a magnetically short-range-ordered state in rutile niobate, a rare room-temperature magnetodielectric system. We reveal room-temperature dispersive phonon excitations using inelastic neutron scattering (INS), complemented by machine-learning-based phonon calculations, to establish the microscopic origin of the polaron-hopping mechanism. Experimental evidence of dispersive phonon-driven polaron hopping is scarce. INS measurements show significant dispersive phonon excitations at 21, 33, and 47 meV, implying collective lattice dynamics that enable delocalized polaron propagation via coupled charge-spin-phonon interactions. Dispersive phonons couple to charge carriers and promote correlated NiO6 lattice distortions, facilitating delocalized polaron hopping. Low-energy magnetic excitations at 4 and 8 meV indicate the presence of local short-range magnetic correlations or spin-orbit-coupling-induced anisotropy in deformed NiO6 octahedra, which are thoroughly discussed. Machine-learning phonon calculations replicate the experimentally observed phonon excitations and demonstrate lattice instability, which is compatible with dynamic local distortions caused by polaron production. These findings provide microscopic evidence for a coupled charge-spin-phonon mechanism that mediates polaron hopping in rutile oxide systems.

cond-mat.mtrl-sci↗

arXiv2026

Interplay of Spin Waves, Crystal-Field Excitations, and Phonons in Multiferroic Ba3HoRu2O9 revealed by Inelastic Neutron Scattering, Crystal-Field Analysis, and Machine-Learned Phonon Calculations

Understanding the microscopic origin of spin-dipole coupling and high-energy excitations in correlated 4d-4f multiferroic oxides is challenging because magnetic, crystal-field, and lattice excitations frequently overlap in energy. The hexagonal 6H perovskite Ba3HoRu2O9 provides an ideal platform to investigate this interplay owing to the coexistence of Ru2O9 molecular units and localized Ho3+ moments. To identify the contributions from these different excitations, we combine inelastic neutron scattering (INS) with linear spin-wave calculations, crystal-field analysis, Raman spectroscopy, and machine-learned force field (MLFF) phonon calculations. A dispersive magnetic excitation below 6.2 meV is accurately reproduced by linear spin-wave theory, establishing its origin as a collective spin-wave excitation of the coupled Ru-Ho magnetic network. At higher energies, broad excitations centered near 20, 39, 70, and 90 meV is observed that are present far above magnetic ordering temperature. Crystal-field calculations based on the Stevens formalism place the strongest Ho3+ transitions within the experimentally observed energy window, while Raman spectroscopy and MLFF phonon calculations identify optical phonons with comparable energies. Together, these complementary results show that the broad INS feature near 39 meV is consistent with overlapping contributions from Ho3+ crystal-field excitations, lattice vibrations, and previously reported Ru2O9 molecular magnetic excitations. These findings establish a microscopic framework for understanding the interplay between spin, crystal-field, and lattice degrees of freedom in this multiferroic 4d-4f compound.

cond-mat.str-el↗

arXiv2026

A Linear alpha-cut intervals based Parsimonious Fuzzy Best-Worst Method with an Application to Warehouse Location Selection

To address computational intensity and crisp weight limitations in the alpha-cut intervals based Fuzzy Best-Worst Method (alpha-FBWM), this research proposes the Linear alpha-cut intervals based Fuzzy Best-Worst Method (Linear alpha-FBWM). By reformulating the non-linear optimization into a single linear programming model, the framework directly determines criteria weights as Triangular Fuzzy Numbers (TFNs) to retain uncertainty. To evaluate weight alignment with decision-makers' initial fuzzy preferences, an Ordinal Preference Violation (OPV) metric is introduced based on the prominence effect. Numerical examples demonstrate that Linear alpha-FBWM minimizes logical violations and matches or outperforms the original alpha-FBWM. To efficiently handle large-scale datasets, we extend this into the Linear alpha-cut intervals based Parsimonious Fuzzy Best-Worst Method (Linear alpha-PFBWM), embedding the linear formulation. This model allows initial alternative ratings as fuzzy numbers and computes non-reference alternative priorities via fuzzy interpolation without early defuzzification. The framework is validated using a literature example and a real-world warehouse selection case study involving 20 alternatives across Gujarat for a multinational paint firm. The integrated approach reduced the required expert evaluations from 185 to 20 initial ratings and 35 pairwise comparisons. This 81.08% reduction in pairwise comparisons proves the framework to be an efficient, reliable, and scalable tool for complex industrial decision-making.

math.GM↗

arXiv2026

Kernel Affine Hull Machines as Compute-Efficient Encoders for Frozen Semantic Spaces

Transformer-based semantic encoders are effective for retrieval, but in many deployments the recurring bottleneck is online query encoding rather than offline corpus indexing. This paper studies whether, once a strong teacher representation space and corpus index are fixed, repeated neural query encoding can be replaced by a substantially lighter and analytically explicit estimator. We formulate fixed-teacher lexical-to-semantic encoding as a conditional-mean estimation problem in which the target semantic vector is represented as a noisy mixture of semantic prototypes weighted by posterior cluster probabilities. Kernel Affine Hull Machine (KAHM) geometry is used to estimate these posterior weights from inexpensive lexical features in an explicitly identified RKHS hypothesis space, and the semantic prototypes are refined by normalized least-mean-squares updates from noisy teacher embeddings. This yields a backpropagation-free query-side encoder together with an end-to-end error decomposition into posterior-approximation, finite-sample/generalization, and teacher-noise terms. We instantiate the approach on a controlled Austrian-law retrieval benchmark with 5,000 test queries, 84 candidate laws, and 10,762 aligned retrieval units, using law-specific encoders into a frozen Mixedbread embedding space. Among evaluation-matched learned adapters, KAHM achieves the strongest teacher-space reconstruction and the best rank-sensitive retrieval performance at all evaluated cutoffs. At k=20, it obtains MRR@20 = 0.504, Hit@20 = 0.694, and Top-1 Accuracy = 0.411, while reducing online per-query time by 8.53 relative to direct transformer query encoding in the reported CPU setting. The results support KAHMs as compute-efficient encoders for supervised fixed-representation deployment regimes.

cs.LG↗

arXiv2026

Revisiting Code Debloating with Ground Truth-based Evaluation

Program debloating aims to remove unused code to reduce performance overhead, attack surfaces, and maintenance costs. Over time, debloating has evolved across multiple layers (container, library, and application), each building on the principles of application-level debloating. Despite its central role, application-level debloating continues to rely on imperfect proxies for measuring performance, such as test-case-driven evaluation for correctness, code size for runtime efficiency, and gadget count reduction for estimating security posture. While there is widespread skepticism about using such imperfect proxies, the community still lacks standardized methodologies or benchmarks to assess the true performance of application-level software debloating. This experience paper aims to address the gap. We revisit the foundations of application-level debloating through a ground-truth-based evaluation paradigm. Our analysis of eight state-of-the-art debloaters - Blade, Chisel, Cov, CovA, Lmcas, Trimmer, Occam, and Razor - uncovers insights previously unattainable through traditional evaluations. These tools collectively span the spectrum of source-to-source, IR-to-IR, and binary-to-binary transformation paradigms, characterizing a holistic reassessment across abstraction levels. Our analysis reveals that while dynamic analysis-based tools often remove up to 94% of code that should be retained, static analysis-based approaches exhibit the opposite behavior, showing high false retention rates due to coarse-grained dependency over-approximation. Additionally, static analyses may add code by introducing specialized variants of functions. False retentions and removals not only cause functional incorrectness but may also lead to systematic inconsistency, robustness failures, and exploitable vulnerabilities.

cs.SE↗

arXiv2026

Nanoscale Surface Analysis of High Entropy Alloy

Nanoscale surface analysis of 1 micrometer thick high entropy alloys (HEAs) was carried out using nano-IR for hyperspectral imaging and single point spectroscopy in the 700-1700 1/cm spectral range. Nano-IR is based on the detection of scattered light from an oscillating metal coated nano-tip in one of the arms of the Fourier transform infrared spectrometer and has a resolution defined by the tip radius of the probe, 20 nm, regardless of the excitation wavelength. HEA CuPdAgPtAu showed an absorption and reflection increase at 900-1100 1/cm band, which is consistent with Drude-Lorenz modeling of permittivity, however, could also signify oxide formation as tested by X-ray photoelectron spectroscopy of CuPdAgPtAu and CrFeCoNiCuMo. Realization of polarization analysis for nano-IR nano-spectroscopy in the plane perpendicular to the sample's surface is discussed and modeled. The currently available modality of surface analysis with the excitation-detection mode of the p-pol. antenna can be extended to full 3D analysis of the orientational dependencies of local absorbance and refractive index.

physics.optics↗

arXiv2026

Nonabelian elastic metamaterials using holonomies acquired by crossing degeneracies

Embedding nonabelian features into elastic metamaterials promises remarkable opportunities for wave control in many practical applications such as surface acoustic wave devices, mode multiplexers, and on-material computation. Nevertheless, current realizations are limited to arrangements of coupled resonators with fine-tuned interactions, limiting their applicability to continuous media. This theoretical and numerical study introduces a design principle for continuous nonabelian elastic metamaterial waveguides. The basic configuration consists of a composite waveguide made of multiple cylindrical waveguides coupled by spatially varying elements. These elements are engineered to follow geometrically-controlled parameter variations that cross selected degeneracies and produce a targeted nonabelian holonomy. The strategy based on crossing degeneracies fundamentally differs from abelian geometric phases, where parameters avoid and encircle degeneracies, or nonabelian Wilczek-Zee phases, where parameters are fine-tuned to maintain degeneracies throughout their cycle. The resulting holonomy transfers an input longitudinal excitation in one rod to an output response in another rod. When two such waveguides are concatenated, their ordering dictates the output response, thereby revealing the emergence of nonabelian dynamics. The nonabelian behavior persists across a broad range of frequencies and under perturbations to the geometry of coupling elements or cylinder diameters. These results establish a robust, effective, and practical route to leverage nonabelian physics in elastic metamaterials.

physics.app-ph↗

arXiv2026

Spin-Chain Incipient Magnetocaloric Effect and Rare-Earth Controlled Switching in the Haldane-Chain System, R2BaNiO5

We have experimentally investigated the magnetocaloric effect (MCE) of a prototype spin-frustrated one-dimensional spin-chain system, the famous Haldane-chain system, R2BaNiO5 (R = Nd, Gd, Er, Dy). The significant MCE is observed far above long-range ordering, even in the paramagnetic region, which is attributed to the change in magnetic entropy due to short-range spin correlation arising from (low-dimensional) magnetic frustration. Such a spin-chain incipient MCE above long-range ordering is rarely reported. Interestingly, multiple magnetocaloric switching from conventional to inverse MCE (and vice versa) are observed below long-range magnetic ordering, as a function of temperature and magnetic field, for the R = Nd, Dy, and Er members. However, such MCE switching is absent in the Gd member, which is an S-state atom (orbital moment L = 0). Our systematic investigation of this series demonstrates that the interplay between crystal-electric field (CEF), strong spin-orbit coupling (SOC) and rare earth anisotropy of R-ions play an important role in spin reorientation, leading to multiple MCE switching due to intriguing changes in magnetic and lattice entropy. The maximum change of entropy for Er, Gd, Dy and Nd is 7.8, 6.8, 4.0 and 1.0 J Kg-1 K-1 respectively. Our study presents a pathway for tuning MCE switching and the MCE effect over large temperature regions in d-f coupled spin-frustrated and spin-chain oxide systems.

cond-mat.str-el↗

arXiv2026

Spin-correlation Driven Ferroelectric Quantum Criticality in a Perovskite Quantum Spin-liquid System, Ba3CuSb2O9

Here we have experimentally demonstrated spin-correlation-driven ferroelectric quantum criticality in a prototype quantum spin-liquid system, Ba3CuSb2O9, a quantum phenomenon rarely observed. The dielectric constant follows a clear T2 scaling, showing that the material behaves as a quantum paraelectric without developing ferroelectric order. Magnetically, the system avoids long-range order down to 1.8 K and instead displays a T3/2 dependence in its inverse susceptibility, a hallmark of antiferromagnetic quantum critical fluctuations. Together with known spin-orbital-lattice entanglement in this compound, these signatures point to a strong interplay between spin dynamics and the polar lattice. Our pioneering work places this perovskite spin-liquid family at the forefront of this domain and suggest the flexibility of this family in a suitable environment by tuning chemical/ external pressure.

cond-mat.str-el↗

arXiv2025

Intriguing Magnetocaloric Effect in Multiferroic Ba3RRu2O9 (R=Ho, Gd, Tb, Nd) with Strong 4d-4f Correlations

Here we demonstrate the magnetocaloric effect (MCE) of a 4d-4f correlated system, namely Ba3RRu2O9 (R= Ho, Gd, Tb, Nd). The compound Ba3HoRu2O9 antiferromagnetically orders at 50 K where both the Ho and Ru-moments order, followed by another phase transition ~ 10 K. Whereas, the compound Ba3GdRu2O9 and Ba3TbRu2O9 orders at 14.5 and 10.5 K respectively, where the ordering of both R and Ru moments are speculated. Our results reveal robust MCE around low-T magnetic phase transition for all the heavy rare-earth members (Ho, Gd, Tb) in this family. The heavy rare-earth members exhibit an intriguing MCE behavior switching from conventional to non-conventional MCE. Interestingly, the light R-member, Ba3NdRu2O9, orders ferromagnetically below 24 K where Nd-moments order, followed by Ru-ordering below 18 K, exhibits a positive MCE below and above FM-ordering. The compelling MCE are attributed to temperature dependent complex spin-reorientations for different R-members and anisotropy.

cond-mat.str-el↗

arXiv2025

Quasiparticle Dynamics in the 4d-4f Ising-like Double Perovskite Ba2DyRuO6 studied using Neutron Scattering and Machine-Learning Framework

Double perovskites containing 4d--4f interactions provide a platform to study complex magnetic phenomena in correlated systems. Here, we investigate the magnetic ground state and quasiparticle excitations of the fascinating double perovskite system, Ba$_2$DyRuO$_6$, through Time of flight (TOF) neutron diffraction (TOF), inelastic neutron scattering (INS), and theoretical modelling. The compound Ba$_2$DyRuO$_6$ is reported to exhibit a single magnetic transition, in sharp contrast to most of the other rare-earth (R) members in this family, A$_2$RRuO$_6$ (A = Ca/Sr/Ba), which typically show magnetic ordering of the Ru ions, followed by R-ion ordering. Our neutron diffraction results confirm that long-range antiferromagnetic order emerges at $T_\mathrm{N} \approx 47$~K, primarily driven by 4d--4f Ru$^{5+}$--Dy$^{3+}$ exchange interactions, where both Dy and Ru moments start to order simultaneously. The ordered ground state is a collinear antiferromagnet with Ising character, carrying ordered moments of $\mu_{\mathrm{Ru}} = 1.6(1)~\mu_\mathrm{B}$ and $\mu_{\mathrm{Dy}} = 5.1(1)~\mu_\mathrm{B}$ at 1.5~K. Low-temperature INS reveals well-defined magnon excitations below 10~meV. SpinW modelling of the INS spectra evidences complex exchange interactions and the presence of magnetic anisotropy, which governs the Ising ground state and accounts for the observed magnon spectrum. Combined INS and Raman spectroscopy reveal crystal-electric-field (CEF) excitations of Dy$^{3+}$ at 46.5 and 71.8~meV in the paramagnetic region. The observed CEF levels are reproduced by point-charge calculations consistent with the $O_h$ symmetry of Dy$^{3+}$. A complementary machine-learning approach is used to analyse the phonon spectrum and compare with INS data. Together, these results clarify the origin of phonon and magnon excitations and their role in the ground-state magnetism of Ba$_2$DyRuO$_6$.

cond-mat.str-el↗

arXiv2025

Operator-Theoretic Framework for Gradient-Free Federated Learning

Federated learning must address heterogeneity, strict communication and computation limits, and privacy while ensuring performance. We propose an operator-theoretic framework that maps the $L^2$-optimal solution into a reproducing kernel Hilbert space (RKHS) via a forward operator, approximates it using available data, and maps back with the inverse operator, yielding a gradient-free scheme. Finite-sample bounds are derived using concentration inequalities over operator norms, and the framework identifies a data-dependent hypothesis space with guarantees on risk, error, robustness, and approximation. Within this space we design efficient kernel machines leveraging the space folding property of Kernel Affine Hull Machines. Clients transfer knowledge via a scalar space folding measure, reducing communication and enabling a simple differentially private protocol: summaries are computed from noise-perturbed data matrices in one step, avoiding per-round clipping and privacy accounting. The induced global rule requires only integer minimum and equality-comparison operations per test point, making it compatible with fully homomorphic encryption (FHE). Across four benchmarks, the gradient-free FL method with fixed encoder embeddings matches or outperforms strong gradient-based fine-tuning, with gains up to 23.7 points. In differentially private experiments, kernel smoothing mitigates accuracy loss in high-privacy regimes. The global rule admits an FHE realization using $Q \times C$ encrypted minimum and $C$ equality-comparison operations per test point, with operation-level benchmarks showing practical latencies. Overall, the framework provides provable guarantees with low communication, supports private knowledge transfer via scalar summaries, and yields an FHE-compatible prediction rule offering a mathematically grounded alternative to gradient-based federated learning under heterogeneity.

cs.LG↗

arXiv2025

Cross talk between experimental data and simple validation of shell closure in pre-actinides

Two back-to-back experiments, 28Si + 178Hf and 28Si + 186W, were intentionally conducted to validate the role of shell closure in pre-actinides by studying neutron multiplicity in compound nucleus (CN) 206Rn and 214Ra. In the first experiment, Dubey et al. [Phys. Rev. C 112, L011602 (2025)], we established the influence of the neutron shell closure. In the present work, the CN 214Ra was deliberately selected to investigate the dependence of the total neutron multiplicity (Mtotal) on the proton number (Z), while keeping the neutron number constant at N = 126 in the pre-actinide region. The objective of the study is two-fold : (i) to examine the effect of proton shell closure when moving away from Z = 82, and (ii) to correlate the present results on proton shell closure with our previous finding on neutron shell closure. We have also used the previous reported data for N = 126 isotones 210Po, 212Rn, and 213Fr to establish the validation of shell closure. A systematic increase in Mtotal with increasing Z was observed from Z = 82 to Z = 88. Furthermore, comparison of the present results on proton shell closure with our earlier neutron shell closure observation, reveals that the cross-correlation between neutron and proton shell closure shows a systematic increase in Mtotal as one moves away from 208Pb, whether along isotonic or isotopic chains.

nucl-ex↗

arXiv2025

A Generalized Analytical Framework for the Nonlinear Best-Worst Method

The nonlinear model of the best-worst method frequently produces multiple optimal weight sets, which are conventionally determined through optimization software. While an analytical approach exists that provides both a closed-form expression for the optimal interval-weights and a secondary objective function to determine the best optimal weight set, we demonstrate that this approach is only valid when preferences are quantified using the Saaty scale and only a single decision-maker is involved. To tackle this issue, we propose a framework compatible with any scale and any number of decision-makers. We first derive an analytical expression for optimal interval-weights and then select the best optimal weight set. After demonstrating that the values of consistency index for the Saaty scale in the existing literature are not well-defined, we derive a formula of consistency index. We also obtain an analytical expression for the consistency ratio, enabling its use as an input-based consistency indicator. Furthermore, we establish that when multiple best/worst criteria are present, weights may vary among best criteria and among the worst criteria. To address this limitation, we modify the original optimization model for weight computation in such instances, solve it analytically to obtain optimal interval-weights and then select the best optimal weight set using a secondary objective function. Finally, we demonstrate and validate the proposed approach using numerical examples and a real-world case study of ranking barriers to energy efficiency in buildings.

math.OC↗

arXiv2025

An Analytical Framework for the Linear Best-Worst Method and its Application to Achieve Sustainable Development Goals--Oriented Agri-Food Supply Chains

The Best-Worst Method (BWM) has emerged as a prominent multi-criteria decision-making method for determining the weights of the decision criteria. Among various BWM models, this research focuses on the linear model of the BWM. This model calculates weights by solving an optimization problem, necessitating optimization software. In this article, we present a novel framework that solves this optimization model mathematically, yielding an analytical expression for the resultant weights, thus eliminating the requirement for an optimization software. The proposed approach enhances both the conceptual clarity of the underlying optimization process and the computational efficiency of the model. Based of this framework, we demonstrate the model's limited response to data variations, i.e., its lower data sensitivity. We also compute the values of consistency index for the linear BWM, which are required to calculate the consistency ratio - a consistency indicator used for assessing inconsistency in input data. Finally, we illustrate the validity and applicability of the proposed approach through five numerical examples and a real-world case study that ranks eighteen drivers across three categories - Industry 4.0, sustainability, and circular economy - in relation to sustainable development goals-driven agri-food supply chains.

math.OC↗

arXiv2025

Understanding synchronization between quantum self-sustained oscillators through coherence generation

Understanding the origin of phase synchronization between quantum self-sustained oscillators has garnered significant interest in recent years. In this work, we study phase synchronization in three settings: between two continuous-variable oscillators, between two arbitrary quantum spins, and within a hybrid setup involving a spin and an oscillator. We derive a simple and general condition on the elements of the joint density matrix that must be satisfied for them to contribute to the relative phase distribution. In particular, we identify the subset of coherence elements in the joint density matrix that serve as key resources for enabling quantum phase synchronization. Our theory is validated against the previously proposed interaction models known to induce synchronization between the self-sustained oscillators. Moreover, our approach offers valuable insights into the relationship between phase synchronization and various information-theoretic measures.

quant-ph↗

arXiv2025

To examine the variation in dissipation near the shell closure using neutron multiplicity as a probe

The pre and post-scission neutron multiplicities have been determined for the fission of the compound nucleus (CN) 206Rn, induced by the reaction 28Si+178Hf within the excitation energy interval of 61.0-90.0 MeV. We intentionally formed CN 206 Rn, which is below the shell closure CN, to examine the variation in N/Z with total neutron multiplicity, as data for other CNs of 208,210,212,214,216Rn have already been published in the literature. We identified a new trend in the N/Z ratio, where the total neutron multiplicity initially decreases as we approach the shell closure of the compound nucleus and then starts to increase as we move away from the shell closure. Furthermore, we have observed that below the neutron shell closure, the dissipation in compound nuclei (CN) escalates with rising excitation energy, remains stable at the shell closure CN, and thereafter diminishes with increasing excitation energy above the shell closure CN.

nucl-ex↗

arXiv2025

Embedding 1D BDI topological dynamics into continuous elastic plates

This study presents an approach that leverages the existing knowledge acquired in one-dimensional BDI class discrete metamaterials, such as mass-spring systems or acoustic resonators, and exploits it to realize fully continuous elastic two-dimensional topological waveguides. The design relies on the concept of evanescently coupled waveguides and defect resonances in order to reproduce the equivalent dynamics of prototypical BDI discrete systems, such as the Su-Schrieffer-Heeger (SSH) model. Starting with a continuous plate waveguide based on a periodic distribution of pillars, local resonators and waveguides are created by eliminating selected pillars and by exploiting the concept of point and line defects. The height of selected pillars is adjusted to tune the coupling strength between different resonators. The approach is validated by designing fully continuous elastic analogs of both the SSH chain and ladder systems. Numerical simulations and experimental results confirm the validity of the design by showing the emergence of topological edge modes at the interface of topologically distinct systems. In addition, the edge modes obtained in the elastic analog of the SSH ladder are shown to be Majorana-like modes.

physics.app-ph↗