arXiv subjects

Sambit Ghosh

Publications and source records attributed to Sambit Ghosh.

6 recordsLinked to original sources

arXiv2026

Spin-Orbital Hall Nano-Oscillators using PtCr/NiFe

The orbital Hall effect provides a promising route for generating angular-momentum currents beyond conventional spin Hall physics. PtCr alloys exhibit unusually large current-induced torques, but the contribution of orbital transport and the ability of these torques to sustain coherent nonlinear magnetization dynamics remain unresolved. Here we demonstrate spin-orbital Hall nano-oscillators by exploiting a homogeneous heavy-metal/light-metal alloy in which orbital Hall currents generated by Cr are converted by Pt into spin currents, producing giant spin-orbit torques. Using PtCr/NiFe heterostructures, the effective torque efficiency increases from ~0.14 in Pt/NiFe to ~0.40 in Pt0.38Cr0.62/NiFe despite substantial Pt dilution, enabling coherent auto-oscillations with the threshold current density reduced from ~ 1.07 x 10^12 to ~ 4.4 x 10^11 A m^-2. First-principles calculations show that Cr alloying suppresses the intrinsic spin Hall conductivity while enhancing the orbital Hall conductivity, and reproduce the observed torque enhancement only when orbital transport is included. Our combined experimental and first-principles results show that alloy engineering enables giant spin-orbit torques through an intrinsic orbital-mediated contribution, enabling coherent auto-oscillations without engineered multilayers and establishing a scalable materials platform for low-power nonlinear spintronic and orbitronic devices.

cond-mat.mes-hall↗

arXiv2026

Phase noise analysis and control of VO$_2$-based relaxation type oscillators

VO$_2$-based relaxation oscillators form a rapidly developing field that finds applications in neuromorphic computing, Ising machines, and numerous signal processing concepts. These oscillators operate in a deeply nonlinear relaxation regime based on rapid phase transitions between insulating and metallic states in the VO$_2$ material. This process is governed by thermal effects, which lead to additional voltage fluctuations and contribute to a considerably wide spectral linewidth in the VO$_2$-based oscillator signal. In this work, we thoroughly study the phase noise in VO$_2$-based relaxation oscillators and demonstrate that the broadening of the generation spectrum linewidth at low oscillation frequencies is caused by an increased susceptibility to thermal fluctuations during the incubation phase. We explore the types of noise affecting oscillator stability and show that synchronization with an external square-wave signal improves the phase noise more effectively than a sinusoidal-shape injection locking signal.

physics.app-ph↗

arXiv2026

Do Vision Language Models Need to Process Image Tokens?

Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dense image tokens across deep transformer stacks (incurring substantial computational overhead), it remains fundamentally unclear whether sustained image-token processing is necessary for their performance or visual representations meaningfully evolve from early to later layers. In this work, we systematically investigate the functional role of image tokens in VLMs and show that visual representations rapidly converge to a bounded-complexity regime, \ie their entropy stabilizes, intrinsic dimensionality compresses, and trajectory curvature approaches a near-constant profile. In contrast, textual representations continue to undergo substantial restructuring across depth. Once stabilized, visual representations become largely interchangeable between layers, indicating limited additional transformation in deeper stages. Further, depth-wise visual truncation reveals that the necessity of visual processing is task-dependent, where single-token predictions remain comparatively robust to truncated visual depth, but multi-token generation require sustained access to visual representations. Under deterministic decoding, reducing visual depth perturbs intermediate reasoning trajectories more strongly than final outputs, suggesting that image tokens influence the structure of reasoning more than the ultimate conclusions. Collectively, these findings \textbf{question the assumption} that deeper visual processing is uniformly essential in VLMs, challenging the current paradigm of multimodal LLM architectures.

cs.CV↗

arXiv2025

A Framework for Testing and Adapting REST APIs as LLM Tools

Large Language Models (LLMs) are increasingly used to build autonomous agents that perform complex tasks with external tools, often exposed through APIs in enterprise systems. Direct use of these APIs is difficult due to the complex input schema and verbose responses. Current benchmarks overlook these challenges, leaving a gap in assessing API readiness for agent-driven automation. We present a testing framework that systematically evaluates enterprise APIs when wrapped as Python tools for LLM-based agents. The framework generates data-aware test cases, translates them into natural language instructions, and evaluates whether agents can correctly invoke the tool, handle their inputs, and process its responses. We apply the framework to generate over 2400 test cases across different domains and develop a taxonomy of common errors, including input misinterpretation, output failures, and schema mismatches. We further classify errors to support debugging and tool refinement. Our framework provides a systematic approach to enabling enterprise APIs as reliable tools for agent-based applications.

cs.SE↗

arXiv2024

A frequency tunable low-noise YIG-GGG based oscillator with strong magneto-elastic coupling

We present a frequency tunable magneto-acoustic oscillator (MAO) operating in low-phase-noise and complex dynamical regimes based on a single composite YIG-GGG resonator. The magneto-acoustic resonator (MAR) is based on a YIG (yttrium iron garnet) layer epitaxially grown on a GGG (gadolinium gallium garnet) substrate. By optimizing the YIG thickness, we obtain a high magneto-elastic coupling of around 1 MHz between the ferromagnetic resonance (FMR) in YIG and high overtone acoustic resonances (HBARs) in the YIG-GGG structure in the 1-2 GHz frequency range. It allows to eliminate the need for pre-selectors and bulky circulators, thus simplifying the MAO design while maintaining the possibility to lock to HBAR YIG-GGG modes. With an adjustment in the loop over-amplification parameter, the MAO can be locked either only to high-Q magneto-acoustic HBARs or to both types of resonance including HBARs and the FMR mode of the YIG film. In a low-phase-noise regime, MAO generates only at certain values of the applied field and exhibits discrete frequency tunability with a 3.281 MHz step corresponding to the frequency separation between the adjacent HBAR modes in a YIG-GGG structure. In a complex regime where oscillation conditions expand to include both HBAR and FMR modes, MAO demonstrates continuous generation as the function of the applied field with variable phase noise parameters. Moreover, in low-phase-noise regime, MAO phase noise plot improves by 30 dB compared to the operational regime locked to the pure FMR in YIG which is in agreement with the measured FMR and HBAR Q-factors.

physics.app-ph↗

arXiv2021

Current-driven domain wall dynamics in ferrimagnetic Ni-doped Mn4N films : very large domain wall velocities and reversal of motion direction across the magnetic compensation point

Spin-transfer torque (STT) and spin-orbit torque (SOT) are spintronic phenomena allowing magnetization manipulation using electrical currents. Beyond their fundamental interest, they allow developing new classes of magnetic memories and logic devices, in particular based on domain wall (DW) motion. In this work, we report the study of STT driven DW motion in ferrimagnetic manganese nickel nitride (Mn4-xNixN) films, in which a fine adjustment of the Ni content allows setting the magnetic compensation at room temperature. The reduced magnetization, combined with the large spin polarization of conduction electrons, strongly enhances the STT so that domain wall velocities approaching 3000 m/s can be obtained for Ni compositions close to the compensation point. In addition, a reversal of the domain wall motion direction is observed when the magnetic compensation composition is crossed. This striking feature, related to the change of direction of the spin polarization with respect to that of the net magnetization, is clarified by ab initio band structure calculations.

cond-mat.mtrl-sci↗