arXiv subjects

Pooja Gupta

Publications and source records attributed to Pooja Gupta.

At least 19 recordsLinked to original sources

arXiv2026

Building the Harness Automatically: Self-Play in Code Distills a Text Harness for Black-Box Optimization

Can an agent learn a numerical search strategy through executable practice and then transfer that strategy as text? We study low-budget black-box optimization, where unaided language models remain well below strong classical optimizers. During development, an agent repeatedly writes and evaluates optimizer programs. It then distills the resulting program and practice record once into a 197-word primary Harness A, which is frozen before evaluation. Harness A reduces Gemini Flash regret by 48\% in an independent $N=30$ study ($p<.001$), enters the GP-BO performance range on the practice family, and lowers mean regret on all three held-out BBOB landscapes. The same text improves every tested Gemini executor and transfers to Claude Sonnet, reducing regret by 43\% and 49\% ($p\leq.005$). An independent end-to-end replication produces Harness B, a different program and text at the same performance tier. The same framework also attains the lowest regret on a sealed YouTube reward-tuning production benchmark. Executable practice is thus a viable way to discover a search policy, and language a portable medium for deploying it.

cs.LG↗

arXiv2025

Effect of Underlayer Induced Charge Carrier Substitution on the Superconductivity of Ti40V60 Alloy Thin Films

The influence of metallic and semiconducting (V, Al, and Si) under-layer induced charge carrier substitution on the superconducting properties of the Ti40V60 alloy thin films are studied and also compared with a pristine reference film without any under-layer. All the films exhibit metallic behavior in the normal state and a superconducting transition at low temperatures, where the superconducting transition temperature is tunable between 4.77 K and 5.73 K. Hall measurements on the films reveal that the under-layer strongly affects the charge carrier type and density, leading to a correlation between increasing carrier concentration and decreasing TC. The Si under-layer introduces the highest disorder, yet yields the highest TC. This indicates that in the Ti40V60 alloys, a moderate amount of disorder suppresses the spin-fluctuations (inherent to the alloy system) induced pair breaking, thereby enhancing the superconductivity. The comparable TC of the film with V under-layer and the film without under-layer, and the much smaller coherence length (~6.2 nm) as compared to the film thickness (25 nm), confirm the absence of any significant proximity effects. These findings demonstrate that under-layer engineering provides an effective route to tune the superconducting properties of Ti-V alloy thin films.

cond-mat.supr-con↗

arXiv2025

Modified Kantorovich-type Sampling Series in Orlicz Space Frameworks

This study examines a modified Kantorovich approach applied to generalized sampling series. The paper establishes that the approximation order to a function using these modified operators is atleast as good as that achieved by classical methods by using some graphs. The analysis focuses on these series within the context of Orlicz space $ L^{\eta}(\mathbb{R}) $, specifically looking at irregularly spaced samples. This is crucial for real-world applications, especially in fields like signal processing and computational mathematics, where samples are often not uniformly spaced. The paper also establishes a result on modular convergence for functions $ g \in L^{\eta}(\mathbb{R}) $, which includes specific cases like convergence in $ L^{p}(\mathbb{R}) $-spaces, $ L \log L $-spaces, and exponential spaces. The study then explores practical applications of the modified sampling series, notably for discontinuous functions and provides graphs to illustrate the results.

math.FA↗

arXiv2025

Sputtering Current Driven Growth & Transport Characteristics of Superconducting Ti40V60 Alloy Thin Films

The room temperature growth, characterization, and electrical transport properties of magnetron sputtered superconducting Ti40V60 alloy thin films are presented. The films exhibit low surface roughness and tunable transport properties. As the sputtering current increases, the superconducting transition move towards higher temperatures. Rietveld refinement of two dimensional XRD (2D XRD) pattern reveals the presence of stress in the films, which shifts from tensile to compressive as the sputtering current increases. Additionally, the crystallite size of the films increases with higher sputtering currents. The films exhibit a strong preferential orientation, contributing to their texturing. The crystallite size and texturing are found to be correlated with the superconducting transition temperature (TC) of the films. As the crystallite size and texturing increase, the TC of the films also rises.

cond-mat.supr-con↗

arXiv2024

Growth-Induced Unconventional Magnetic Anisotropy in Co/Fullerene (C60) Bilayer Systems; Insights from a Two-Grain Stoner-Wohlfarth Model

Organic spintronics has drawn the interest of the science community due to various applications in spin-valve devices. However, an efficient room-temperature Organic Spin Valve device has not been experimentally realized due to the complicated spin transport at the metal-organic interfaces. The present study focuses on a comprehensive understanding of the interfacial properties essential for advancing device performance and functionality. The structural and magnetic properties of the ultra-thin Cobalt (Co) films deposited on the fullerene (C60) layer are studied to investigate the origin of magnetic anisotropy in the metal-organic bilayer structures. Due to the mechanical softness of C60, penetration of ferromagnetic Co atoms inside the C60 film is confirmed by the X-ray reflectivity and Secondary Ion Mass Spectroscopy measurements. Grazing incidence small-angle X-ray scattering and atomic force microscopy provided information regarding the structural and morphological properties of the Co/C60 bilayers, angular dependent Magneto-optic Kerr effect measurements with varying Co layer thickness provided information about the growth-induced uniaxial magnetic anisotropy. In contrast to the inorganic silicon substrates, magnetic anisotropy in Co film tends to develop at 25 {\AA} thickness on the C60 layer, which further increases with the thickness of Cobalt. The anomalous behavior in coercivity and remanence variation along the nominal hard axis is explained by a two-grain Stoner-Wohlfarth model with intergranular exchange coupling. It is further confirmed by a non-uniform spatial distribution of magnetic domains investigated through Kerr microscopy. These anomalies could be attributed to the distribution of magneto-crystalline anisotropy and inhomogeneous strain caused by the formation of a diffused layer at the Co/C60 interface.

cond-mat.mtrl-sci↗

arXiv2024

Topological Hall-like anomalies from twisted magnetic exchange spring in Nd0.6Sr0.4MnO3 / SrRuO3 heterostructures

In recent times, there has been a surge of interest in utilizing manganite systems for oxide-based heterostructures that host non-trivial spin textures, primarily driven by the Dzyaloshinskii-Moriya interaction (DMI). In these systems, the Topological Hall Effect (THE) manifests as humps or peaks in anomalous Hall Effect (AHE) loops near the coercive field. Numerous studies have reported THE in ruthenate/iridate and ruthenate/manganite heterostructures. Among the manganites, the Nd0.6Sr0.4MnO3 (NSMO) system remains relatively less explored. The strontium ruthenate (SrRuO3 - SRO) system exhibits excellent structural compatibility with NSMO, making NSMO/SRO heterostructures a model system for investigating non-trivial spin textures at oxide-based interfaces. In this work, we have studied the proximity effect of NSMO with SRO through magnetic and magnetotransport studies, varying the SRO layer thicknesses in the NSMO/SRO heterostructures.

cond-mat.mtrl-sci↗

arXiv2023

Asymmetric magnetism at the interfaces of MgO/FeCoB bilayers by exchanging the order of MgO and FeCoB

Interfaces in FeCoB/MgO/FeCoB magnetic tunnel junction play a vital role in controlling their magnetic and transport properties for various applications in spintronics and magnetic recording media. In this work, interface structures of a few nm thick FeCoB layers in FeCoB/MgO and MgO/FeCoB bilayers are comprehensively studied using x-ray standing waves (XSW) generated by depositing bilayers between Pt waveguide structures. High interface selectivity of nuclear resonance scattering (NRS) under the XSW technique allowed measuring structure and magnetism at the two interfaces, namely FeCoB-on-MgO and MgO-on-FeCoB, yielding an interesting result that electron density and hyperfine fields are not symmetric at both interfaces. The formation of a high-density FeCoB layer at the MgO/FeCoB (FeCoB-on-MgO) interface with an increased hyperfine field (~34.65 T) is attributed to the increasing volume of FeCo at the interface due to boron diffusion from 57FeCoB to the MgO layer. Furthermore, it caused unusual angular-dependent magnetic properties in MgO/FeCoB bilayer, whereas FeCoB/MgO is magnetically isotropic. In contrast to the literature, where the unusual angular dependent in FeCoB based system is explained in terms of in-plane magnetic anisotropy, present findings attributed the same to the interlayer exchange coupling between bulk and interface layer within the FeCoB layer.

cond-mat.mtrl-sci↗

arXiv2023

Significantly increased magnetic anisotropy in Co nano-columnar multilayer structure via a unique sequential oblique-normal deposition approach

Oblique/normal sequential deposition technique is used to create Co based unique multilayer structure [Co-oblique(4.4nm)/Co-normal (4.2 nm)]x10, where each Co-oblique layer is deposited at an oblique angle of 75deg, to induce large in-plane uniaxial magnetic anisotropy (UMA). Compared to the previous ripple, stress and oblique angle deposition (OAD) related studies on Cobalt in literature, one-order higher UMA with the easy axis of magnetization along the projection of the tilted nano-columns in the multilayer plane is observed. The multilayer retains magnetic anisotropy even after annealing at 450C. The in-plane UMA in this multilayer is found to be the combination of shape, and magneto-crystalline anisotropy (MCA) confirmed by the temperature-dependent grazing incidence small angle X-ray scattering (GISAXS), in situ reflection high energy electron diffraction (RHEED) and grazing incidence X-ray diffraction (GIXRD) measurements. The crystalline texturing of hcp Co in the multilayer minimizes spin-orbit coupling energy along the column direction, which couples with the shape anisotropy energies and results in preferential orientation of the easy magnetic axis along the projection of the columns in the multilayer plane. Reduction in UMA after annealing is attributed to diffusion/merging of columns and annihilating crystallographic texturing. The obtained one-order high UMA demonstrates the potential application of the unique structure engineering technique, which may have far-reaching advantages in magnetic thin films/multilayers and spintronic devices.

cond-mat.mtrl-sci↗

arXiv2023

Effect of surface morphology on magnetization dynamics of cobalt ultrathin films

Growth of Co film on SiO2 substrates with the surface roughness of 0.5 nm and 1.6 nm has been studied in situ using the magneto-optical Kerr effect (MOKE) and four probe resistivity measurements. In-situ measurements jointly suggest the Volmer-Weber growth process and proceed via a nonmagnetic, superparamagnetic and ferromagnetic phase formation on both substrates. Islands are found to coalesce at film thicknesses of 0.6 nm and at 1.5 nm with continuous film formation around film thicknesses of 1.5 nm and 3.0 nm for smooth and rough substrates, respectively. Ferromagnetic long-range ordering i.e., the appearance of a magnetic hysteresis loop in both films, is observed just after coalescing stage. Observed azimuthal angular dependence of coercivity confirmed the presence of a weak uniaxial magnetic anisotropy in both films, whereas the difference in uniaxial magnetic anisotropy with substrate roughness is interpreted in terms of the combined effect of domain wall pinning and internal stresses in the films. The origin of much higher UMA in the case of the Co film deposited on a ripple-patterned substrate of similar root means square roughness is attributed to the modified long-range dipolar stray fields on the surface.

cond-mat.mtrl-sci↗

arXiv2023

Anisotropic magnetic and magnetotransport properties in morphologically distinct Nd0.6Sr0.4MnO3 thin films

We investigate the magnetic and magnetotransport properties of nanostructured Nd0.6Sr0.4MnO3 (NSMO) thin films grown on (100) oriented SrTiO3 (STO) substrates. The thin films fabricated using the pulsed laser deposition technique have been found to possess two distinct surface morphologies: granular and nano rod type. Magnetization measurements have revealed that the films with rod-type morphology exhibit improved in-plane magnetic anisotropy. Magnetotransport studies have revealed that the granular thin films display a characteristic butterfly-shaped low-field magneto-resistive (LFMR) behavior. Furthermore, we investigate the anisotropic magneto-resistive (AMR) phenomenon in the samples and we find that morphology greatly affects AMR. Thin films with rod-type morphology show an enhanced AMR %. Such morphology dependent tunability in magnetoresistance properties over a wide temperature range is potentially interesting for developing oxide-based sensors and devices.

cond-mat.mtrl-sci↗

arXiv2023

Study of magnetism in MgO/FeCoB/MgO trilayers using x-ray standing wave techniques

Interfaces in the MgO-FeCoB-MgO trilayer have been studied with grazing incident nuclear resonance scattering (GINRS) using the x-ray standing waves (XSW) technique. High depth selectivity of the present method allows one to measure magnetism and structure at the two interfaces of FeCoB, namely, FeCoB-on-MgO and MgO-on-FeCoB, independently, yielding an intriguing result that both interfaces are not symmetric. A high-density layer with an increased magnetic hyperfine field at the FeCoB-on-MgO interface suggests different growth mechanisms at the two interfaces. The azimuthal angle-dependent magneto-optic Kerr effect measurements reveal the presence of unusual uniaxial magnetic anisotropy (UMA) in the trilayer. An in-situ temperature-dependent study discovered that this UMA systematically reduces with temperature. The trilayer becomes isotropic at 450C with an order-of-magnitude increase in coercivity. The asymmetry at the interfaces is, in turn, explained by boron diffusion from the FeCoB interface layer into the nearby MgO layer. Stress-induced UMA is observed in the boron-deficient FeCoB layer, superimposed with the bulk FeCoB layer, and found to be responsible for unusual UMA. The temperature-dependent variation in the UMA and coercivity can be understood in terms of variations in the internal stresses and coupling between FeCoB bulk and the interface layer.

cond-mat.mtrl-sci↗

arXiv2023

Exploring the substrate-driven morphological changes in Nd0.6Sr0.4MnO3 thin films

Manganite thin films are promising candidates for studying the strongly correlated electron systems. Understanding the growth-and morphology-driven changes in the physical properties of manganite thin films is vital for their applications in oxitronics. This work reports the morphological, structural, and electrical transport properties of nanostructured Nd0.6Sr0.4MnO3 (NSMO) thin films fabricated using the pulsed laser deposition technique. Scanning electron microscopy (SEM) imaging of the thin films revealed two prominent surface morphologies: a granular and a unique crossed-nano-rod-type morphology. From X-ray diffraction (XRD) and atomic force microscopy (AFM) analysis, we found that the observed nanostructures resulted from altered growth modes occurring on the terraced substrate surface. Furthermore, investigations on the electrical-transport properties of thin films revealed that the films with crossed-nano-rod type morphology showed a sharp resistive transition near the metal-to-insulator transition (MIT). An enhanced temperature coefficient of resistance (TCR) of up to one order of magnitude was also observed compared to the films with granular morphology. Such enhancement in TCR % by tuning the morphology makes these thin films promising candidates for developing oxide-based temperature sensors and detectors.

cond-mat.mtrl-sci↗

arXiv2021

Rawlsian Fair Adaptation of Deep Learning Classifiers

Group-fairness in classification aims for equality of a predictive utility across different sensitive sub-populations, e.g., race or gender. Equality or near-equality constraints in group-fairness often worsen not only the aggregate utility but also the utility for the least advantaged sub-population. In this paper, we apply the principles of Pareto-efficiency and least-difference to the utility being accuracy, as an illustrative example, and arrive at the Rawls classifier that minimizes the error rate on the worst-off sensitive sub-population. Our mathematical characterization shows that the Rawls classifier uniformly applies a threshold to an ideal score of features, in the spirit of fair equality of opportunity. In practice, such a score or a feature representation is often computed by a black-box model that has been useful but unfair. Our second contribution is practical Rawlsian fair adaptation of any given black-box deep learning model, without changing the score or feature representation it computes. Given any score function or feature representation and only its second-order statistics on the sensitive sub-populations, we seek a threshold classifier on the given score or a linear threshold classifier on the given feature representation that achieves the Rawls error rate restricted to this hypothesis class. Our technical contribution is to formulate the above problems using ambiguous chance constraints, and to provide efficient algorithms for Rawlsian fair adaptation, along with provable upper bounds on the Rawls error rate. Our empirical results show significant improvement over state-of-the-art group-fair algorithms, even without retraining for fairness.

cs.LG↗

arXiv2020

ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis

This work addresses the problem of analyzing multi-channel time series data %. In this paper, we by proposing an unsupervised fusion framework based on %the recently proposed convolutional transform learning. Each channel is processed by a separate 1D convolutional transform; the output of all the channels are fused by a fully connected layer of transform learning. The training procedure takes advantage of the proximal interpretation of activation functions. We apply the developed framework to multi-channel financial data for stock forecasting and trading. We compare our proposed formulation with benchmark deep time series analysis networks. The results show that our method yields considerably better results than those compared against.

cs.LG↗

arXiv2020

SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems

This work proposes a supervised multi-channel time-series learning framework for financial stock trading. Although many deep learning models have recently been proposed in this domain, most of them treat the stock trading time-series data as 2-D image data, whereas its true nature is 1-D time-series data. Since the stock trading systems are multi-channel data, many existing techniques treating them as 1-D time-series data are not suggestive of any technique to effectively fusion the information carried by the multiple channels. To contribute towards both of these shortcomings, we propose an end-to-end supervised learning framework inspired by the previously established (unsupervised) convolution transform learning framework. Our approach consists of processing the data channels through separate 1-D convolution layers, then fusing the outputs with a series of fully-connected layers, and finally applying a softmax classification layer. The peculiarity of our framework - SuperDeConFuse (SDCF), is that we remove the nonlinear activation located between the multi-channel convolution layers and the fully-connected layers, as well as the one located between the latter and the output layer. We compensate for this removal by introducing a suitable regularization on the aforementioned layer outputs and filters during the training phase. Specifically, we apply a logarithm determinant regularization on the layer filters to break symmetry and force diversity in the learnt transforms, whereas we enforce the non-negativity constraint on the layer outputs to mitigate the issue of dead neurons. This results in the effective learning of a richer set of features and filters with respect to a standard convolutional neural network. Numerical experiments confirm that the proposed model yields considerably better results than state-of-the-art deep learning techniques for real-world problem of stock trading.

q-fin.CP↗

arXiv2020

DeConFuse : A Deep Convolutional Transform based Unsupervised Fusion Framework

This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well acknowledged. The success of convolutive features owes to convolutional neural network (CNN). However, CNN cannot perform learning tasks in an unsupervised fashion. In a recent work, we show that such shortcoming can be addressed by adopting a convolutional transform learning (CTL) approach, where convolutional filters are learnt in an unsupervised fashion. The present paper aims at (i) proposing a deep version of CTL; (ii) proposing an unsupervised fusion formulation taking advantage of the proposed deep CTL representation; (iii) developing a mathematically sounded optimization strategy for performing the learning task. We apply the proposed technique, named DeConFuse, on the problem of stock forecasting and trading. Comparison with state-of-the-art methods (based on CNN and long short-term memory network) shows the superiority of our method for performing a reliable feature extraction.

cs.LG↗

arXiv2020

Energy-aware Demand Selection and Allocation for Real-time IoT Data Trading

Personal IoT data is a new economic asset that individuals can trade to generate revenue on the emerging data marketplaces. Typically, marketplaces are centralized systems that raise concerns of privacy, single point of failure, little transparency and involve trusted intermediaries to be fair. Furthermore, the battery-operated IoT devices limit the amount of IoT data to be traded in real-time that affects buyer/seller satisfaction and hence, impacting the sustainability and usability of such a marketplace. This work proposes to utilize blockchain technology to realize a trusted and transparent decentralized marketplace for contract compliance for trading IoT data streams generated by battery-operated IoT devices in real-time. The contribution of this paper is two-fold: (1) we propose an autonomous blockchain-based marketplace equipped with essential functionalities such as agreement framework, pricing model and rating mechanism to create an effective marketplace framework without involving a mediator, (2) we propose a mechanism for selection and allocation of buyers' demands on seller's devices under quality and battery constraints. We present a proof-of-concept implementation in Ethereum to demonstrate the feasibility of the framework. We investigated the impact of buyer's demand on the battery drainage of the IoT devices under different scenarios through extensive simulations. Our results show that this approach is viable and benefits the seller and buyer for creating a sustainable marketplace model for trading IoT data in real-time from battery-powered IoT devices.

cs.CR↗

arXiv2019

Excitation of whispering gallery modes with a "point-and-play", fiber-based, optical nano-antenna

We demonstrate the excitation and detection of whispering gallery modes in optical microresonators using a "point-and-play", fiber-based, optical nano-antenna. The coupling mechanism is based on cavity-enhanced Rayleigh scattering. Collected spectra exhibit Lorentzian dips, Fano shapes, or Lorentzian peaks, with a coupling efficiency around 13\%. The spectra are characterized by the coupling gap, polarization, and fiber tip position. The coupling method is simple, low-cost and, most importantly, the \textit{Q}-factor can be maintained at $10^8$ over a wide coupling range, thereby making it suitable for metrology, sensing, or cavity quantum electrodynamics (cQED) experiments.

physics.optics↗