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Arvind Sharma

Publications and source records attributed to Arvind Sharma.

6 recordsLinked to original sources
arXiv2026

CORAL: Constrained Oblique Rotation with Anchored Loadings for Fidelity-Constrained Decorrelation

Decorrelating a multivariate system need not destroy source-variable identity. We introduce Constrained Oblique Rotation with Anchored Loadings (CORAL), which minimizes residual cross-correlation while guaranteeing a declared minimum correlation between each transformed variable and its designated source. For a p-variable correlation matrix $R$, we show that every exact decorrelator can be written as $R^{-1/2}Q$ for some orthogonal matrix $Q$, and define $\rho_\star(R)$ as the maximum common source fidelity compatible with exact decorrelation. Constructive lower bounds and rigorous analytical upper bounds tightly bracket $\rho_\star$ at [0.972,0.976], [0.959,0.962], and [0.949,0.950] in simulations with p={6,18,50}, respectively, compared with PCA's largest achievable minimum correlation between distinct principal components and matched source variables of 0.358, 0.329, and 0.172. Corresponding intervals are [0.751,0.758] for World Development Indicators and [0.826,0.835] for wine chemistry data sets. Thus, loss of source-variable identity is not inherent to exact decorrelation but depends on the decorrelator selected. CORAL uses constrained Riemannian optimization and extends to exact support restrictions.

stat.ME↗
arXiv2026

Retrospective Orthogonal Design: Response-Surface Reconstruction from Observational Data

Regression estimates from observational data can depend on specification under multicollinearity, while sequential sums of squares (SS) depend on term order. We introduce Retrospective Orthogonal Design (ROD), which reconstructs conditional mean surfaces on a probability-balanced lattice. ROD preserves observed cell means, completes unsupported cells, applies weighted tensor-product contrasts, and evaluates the reconstructed surface through piecewise-affine interpolation over Freudenthal polyhedra. Resolution and completion are selected jointly by validation among rank-admissible candidates, followed by refitting and evaluation on an untouched test set. For an admissible lattice, $\mathbf{X}^{\top}\mathbf{W}\mathbf{X}=c\mathbf{I}$, yielding specification-invariant contrast effects and unique, order-independent SS within the retained contrast space. Response-free projection calibration maps the fixed reconstruction onto a declared scientific basis and corrects finite-resolution recovery loss. Across 6,480 simulation conditions spanning nine data-generating processes, ROD matched or exceeded polynomial regression in five processes and performed strongest on threshold, sign-interaction, and localized surfaces. For the quadratic-interaction process, mean out-of-sample $R^2$ differed by only $0.0001$, while calibrated coefficient bias remained small across prespecified targets. A Rao-based information adjustment provides dependence-aware sample-size guidance for ROD planning. In a weighted Mincer application, ROD produced the highest out-of-sample $R^2$ point estimate, with substantial interval overlap with polynomial regression, and provided exhaustive SS allocations invariant to term-entry order.

stat.ME↗
arXiv2026

DTCO of NOR-Type IGZO FeFETs for 3D Heterogeneous AI Memories: A Read-Centric Perspective

InGaZnO (IGZO)-channel FeFETs have attracted notable interest thanks to recent advances in endurance, opening up their application space for read-dominated AI memory tiers. This work evaluates the viability of NOR-type IGZO FeFETs for 3D heterogeneous AI memories from a read-centric design-technology co-optimization (DTCO) perspective, spanning on-chip back-end-of-line (BEOL) RAMs and hybrid-bonded memory chiplets, and off-chip, monolithically integrated 3D FeNOR storage-class memories (SCMs). For on-chip BEOL RAMs and memory chiplets, we demonstrate the cross-node bitcell footprint scalability of IGZO FeFETs capable of delivering down to 10-A SRAM-equivalent bitcell area ($\sim$0.016 $\mu$m$^2$) with 7-nm ground rules while maintaining a sub-5 ns random access latency -- despite their writability challenges. We further identify the sensing margin penalty in NOR FeFET arrays arising from sneak current associated with the negative program-state $V_t$, which requires positive-$V_t$ engineering in order to eliminate the unwanted negative voltage read inhibition -- for example, by ferroelectric layer thinning. Last but not least, we elucidate the read margin implications on 3D FeNOR for SCMs, with the 3D stacking density limited by additional sneak current from neighbor channel shunting.

cs.ET↗
arXiv2025

SOT-MRAM Bitcell Scaling with BEOL Read Selectors: A DTCO Study

This work explores the cross-node scaling potential of SOT-MRAM for last-level caches (LLCs) under heterogeneous system scaling paradigm. We perform extensive Design-Technology Co-Optimization (DTCO) exercises to evaluate the bitcell footprint for different cell configurations at a representative 7 nm technology and to assess their implications on read and write power-performance. We crucially identify the MTJ routing struggle in conventional two-transistor one-resistor (2T1R) SOT-MRAMs as the primary bitcell area scaling challenge and propose to use BEOL read selectors (BEOL RSs) that enable (10 -- 40) % bitcell area reduction and eventually match sub-N3 SRAM. On writability, we affirm that BEOL RS-based bitcells could meet the required SOT switching current, provided the magnetic free layer properties be engineered in line with LLC-specific, (0.1 -- 100) s retention targets. This is particularly to attribute to their (i) more available Si fins for write transistor and (ii) lower bitline resistance at reduced cell width. We nevertheless underscore the read tradeoff associated with BEOL RSs, with the low-drive IGZO-FET selector sacrificing the latency up to (3 -- 5) ns and the imperfectly rectifying diode selectors suffering (2.5 -- 5)$\times$ energy cost relative to 2T1R. This article thus highlights the realistic prospects and hurdles of BEOL RSs towards holistic power-performance-area scaling of SOT-MRAM.

cs.ET↗
arXiv2025

Computational insights into Cobalt-based novel half-Heusler alloy for sustainable energy applications

The quest for efficient and sustainable green energy solutions has led to a growing interest in half Heusler alloys, particularly for thermoelectric and spintronic applications. This study investigates the multifaceted nature of cobalt based half Heusler alloy, CoVAs, employing DFT with advanced computational techniques, such as the FLAPW method. The elastic, electronic, magnetic, thermodynamic, and optical properties of CoVAs are meticulously analyzed. Structural and mechanical evaluations reveal mechanical stability and brittleness under varying pressures. Electronic and magnetic properties are examined through band structure and DOS analysis, revealing a half metallic nature with a minority spin band gap. The total magnetic moment aligns with the Slater Pauling rule, further confirming ferromagnetism and half metallicity. Thermodynamic investigations, based on the quasi-harmonic Debye approximation, provide insights into temperature- and pressure dependent behavior, including thermal expansion, heat capacity, and Debye temperature, establishing CoVAs as a viable candidate for high temperature applications. Additionally, the optical properties underestimate its potential in optoelectronic applications due to high absorption in the UV region, showing a distinct absorption edge corresponding to the electronic band gap. Phonon dispersion relations reflect the stability of the alloy, and the figure of merit confirms the alloy's suitability for thermodynamics applications. The findings highlight the potential of CoVAs as a promising candidate for spintronic photovoltaic and optoelectronic applications, providing insights into its fundamental properties that could facilitate experimental synthesis and industrial implementation for green energy and advanced technological applications.

cond-mat.mtrl-sci↗