arXiv subjects

Garima Gupta

Publications and source records attributed to Garima Gupta.

At least 19 recordsLinked to original sources

arXiv2026

Confined exciton polaron in MoS$_2$ on twisted-hBN

The simple electrostatic picture of a trion is that of an excess charge inducing an exciton polarization and binding closer (farther) to the hole (electron) side of it. Trion formation can be forbidden when such spontaneous rearrangement of charges is not allowed by the application of external perturbation, such as electric field. Here we test this hypothesis experimentally using a non-monotonic electric field. We realize this scenario by imprinting the ferroelectric domains at the AA-stacked twisted-hBN (t-hBN) interface onto a monolayer of MoS2 placed over it. The spatially varying in-plane electric field around the domain wall serves the dual purpose of (a) confining and polarizing the 2D exciton in the domain wall, and (b) depleting the free charge carriers from the domain wall. We observe a large quantized exciton splitting confirming strong exciton confinement in the domain wall. Forced by the confining potential, the electron side of the polarized exciton lies closer to the domain with accumulated free electrons, which should ideally prevent any trion formation. Contrary to the laid hypothesis, we observe signatures of quantized charged exciton emission, with an inter-level splitting that mimics the level-splitting of the quantized excitons. This paradox is explained using the many-body picture of exciton polaron, where a conduction band hole attractively binds the polarized exciton and the electron Fermi sea. The results provide a definitive way to unambiguously discern exciton polaron from trion.

cond-mat.mes-hall↗

arXiv2025

Study on Control Problem of a Impulsive Neutral Integro-Differential Equations with Fading Memory

This article addresses control problems for semilinear impulsive neutral integro-differential equations with memory in a Banach space. It investigates the approximate controllability of linear and semilinear systems and proves the establishment of mild solutions in the semilinear setting. The approach involves constructing a resolvent family for the corresponding integro-differential equation of linear type without memory. The results for the linear system are established first, then extended to the semilinear scenario, followed by a detailed example to illustrate the theoretical findings.

math.OC↗

arXiv2024

The existence and controllability of nonautonomous system influenced by impulses on both state and control

This paper examines impulsive controls related to nonautonomous impulsive integro-differential equations in Hilbert space, highlighting their significance. We establish the existence of the mild solution by using fixed point approach and present conditions for approximate controllability using impulsive resolvent operators and the adjoint problem, supported by an illustrative example.

math.OC↗

arXiv2024

Existence And Approximate Controllability for a class of Fractional Order Hemivariational Inequalities

This paper discusses the approximate controllability of a fractional differential control problem driven by a nonlinear hemivariational inequality in a Hilbert space. First, we prove the existence of a mild solution for a fractional control inclusion problem which is equivalent to a hemivariational inequality by using the nonsmooth analysis and fixed point technique. Further, we established sufficient conditions for the approximate controllability of our inclusion problem by taking corresponding linear system is approximately controllable. The existence and controllability results obtained for the inclusion problem are valid for considered nonlinear hemivariational problem. Finally, we provide an example to illustrate the efficiency of the developed results.

math.OC↗

arXiv2024

Motion of 2D exciton in momentum space leads to pseudospin distribution narrowing on the Bloch Sphere

Motional narrowing implies narrowing induced by motion, for example, in nuclear resonance, the thermally induced random motion of the nuclei in an inhomogeneous environment leads to counter-intuitive narrowing of the resonance line. Similarly, the excitons in monolayer semiconductors experience magnetic inhomogeneity: the electron-hole spin-exchange interaction manifests as an in-plane pseudo-magnetic field with a periodically varying orientation inside the exciton band. The excitons undergo random momentum scattering and pseudospin precession repeatedly in this inhomogeneous magnetic environment - typically resulting in fast exciton depolarization. On the contrary, we show that such magnetic inhomogeneity averages out at high scattering rate due to motional narrowing. Physically, a faster exciton scattering leads to a narrower pseudospin distribution on the Bloch sphere, implying a nontrivial improvement in exciton polarization. The in-plane nature of the pseudo-magnetic field enforces a contrasting scattering dependence between the circularly and linearly polarized excitons - providing a spectroscopic way to gauge the sample quality.

cond-mat.mes-hall↗

arXiv2023

TiO2 multi-leg nanotubes for Surface-enhanced Raman scattering

In the recent past, significant research efforts have been put forth to fabricate low-cost noble metal-free substrates for surface-enhanced Raman spectroscopy (SERS) applications. Here we propose semiconducting TiO2 multi-leg nanotubes (TiO2 MLNTs, with and without the gold nanoparticle coating) as SERS substrates. TiO2 MLNTs show unique multi-leg morphology compared to the conventional non-multi-leg tubes and possess better light-harvesting properties. TiO2 MLNTs are fabricated with a simple and versatile single-step electrochemical anodization method. Remarkable high SERS sensitivity is observed towards the detection of Methylene blue (MB), up to nM concentration (E.F. ~104). The same is attributed to the resonantly matched photonic absorption edge of TiO2 MLNTs with the wavelength of incident laser probe light. On the other hand, gold nanoparticle-coated TiO2 MLNTs demonstrated further enhancement in SERS sensitivity (E.F. ~105, for nM of MB) facilitated by the synergy that exists between the plasmonic modes (LSPRs) of Au and the photonic absorption mode of TiO2 MLNTs.

physics.chem-ph↗

arXiv2023

Polarized and narrow excitonic emission from graphene-capped monolayer WS$_2$ through resonant phonon relaxation

The broadening and polarization of excitonic luminescence in monolayer TMDs largely suffer from inhomogeneity and temperature - an unresolved problem to date. In this work, through few-layer-graphene encapsulation of monolayer WS$_2$, we reduce the inter-excitonic energy separation, which then can have a narrow resonance with a specific phonon mode of our choice. The resulting single-step exciton relaxation with the resonating phonon mode significantly suppresses the inhomogeneous broadening, allowing us to achieve the narrowest exciton linewidth of 1.06 meV (which translates to 0.19 meV after deconvolution with the excitation laser linewidth). The single-phonon resonance helps to achieve a high quantum efficiency despite graphene encapsulation. The technique is powerful in tuning the exciton polarization during relaxation by choosing a specific resonating phonon mode. For example, the valley coherence (polarization) improves from $\sim$68% ($\sim$40%) to $\sim$90% ($\sim$75%) on resonance with 2$A_1$' and $A_1$' modes respectively. We further demonstrate a strong polarization reversal on resonance with a chiral phonon mode. Strikingly, the above features remain robust against temperature (up to 200 K) and sample age (few months in ambient condition). The findings will lead to clean excitonic measurements without requiring cryogenic cooling.

cond-mat.mes-hall↗

arXiv2022

Highly nonlinear biexcitonic photocurrent from ultrafast inter-layer charge transfer

Strong Coulomb interaction in monolayer semiconductors allows them to host optically active large many-body states, such as the five-particle state, charged biexciton. Strong nonlinear light absorption by the charged biexciton under spectral resonance, coupled with its charged nature, makes it intriguing for nonlinear photodetection - an area that is hitherto unexplored. Using the high built-in vertical electric field in an asymmetrically designed few-layer graphene encapsulated 1L-WS$_2$ heterostructure, here we report a large, highly nonlinear photocurrent arising from the strong absorption by two charged biexciton species under zero external bias (self-powered mode). Time-resolved measurement reveals that the generated charged biexcitons transfer to the few-layer graphene in a timescale of sub-5 ps, indicating an ultrafast intrinsic limit of the photoresponse. By using single- and two-color photoluminescence excitation spectroscopy, we show that the two biexcitonic peaks originate from bright-dark and bright-bright exciton-trion combinations. Such innate nonlinearity in the photocurrent due to its biexcitonic origin, coupled with the ultrafast response due to swift inter-layer charge transfer, exemplifies the promise of manipulating many-body effects in monolayers towards viable optoelectronic applications.

cond-mat.mes-hall↗

arXiv2022

Trion-trion annihilation in monolayer WS$_2$

Strong Coulomb interaction in monolayer transition metal dichalcogenides can facilitate nontrivial many-body effects among excitonic complexes. Many-body effects like exciton-exciton annihilation (EEA) have been widely explored in this material system. However, a similar effect for charged excitons (or trions), that is, trion-trion annihilation (TTA), is expected to be relatively suppressed due to repulsive like-charges, and has not been hitherto observed in such layered semiconductors. By a gate-dependent tuning of the spectral overlap between the trion and the charged biexciton through an "anti-crossing"-like behaviour in monolayer WS$_2$, here we present an experimental observation of an anomalous suppression of the trion emission intensity with an increase in gate voltage. The results strongly correlate with time-resolved measurements, and are inferred as a direct evidence of a nontrivial TTA resulting from non-radiative Auger recombination of a bright trion, and the corresponding energy resonantly promoting a dark trion to a charged biexciton state. The extracted Auger coefficient for the process is found to be tunable ten-fold through a gate-dependent tuning of the spectral overlap.

cond-mat.mes-hall↗

arXiv2022

Probing biexciton in monolayer WS$_2$ through controlled many-body interaction

The monolayers of semiconducting transition metal dichalcogenides host strongly bound excitonic complexes and are an excellent platform for exploring many-body physics. Here we demonstrate a controlled kinetic manipulation of the five-particle excitonic complex, the charged biexciton, through a systematic dependence of the biexciton peak on excitation power, gate voltage, and temperature using steady-state and time-resolved photoluminescence (PL). With the help of a combination of the experimental data and a rate equation model, we argue that the binding energy of the charged biexciton is less than the spectral separation of its peak from the neutral exciton. We also note that while the momentum-direct radiative recombination of the neutral exciton is restricted within the light cone, such restriction is relaxed for a charged biexciton recombination due to the presence of near-parallel excited and final states in the momentum space.

cond-mat.mes-hall↗

arXiv2022

Electrically Tunable Localized versus Delocalized Intralayer Moir\'e Excitons and Trions in a Twisted MoS$_2$ Bilayer

Moir\'e superlattice-induced sub-bands in twisted van der Waals homo- and hetero-structures govern their optical and electrical properties, rendering additional degrees of freedom such as twist angle. Here, we demonstrate the moir\'e superlattice effects on the intralayer excitons and trions in a twisted bilayer of MoS$_2$ of H-type stacking at marginal twist angles. We identify the emission from localized and multiple delocalized sub-bands of intralayer moir\'e excitons and show their electrical modulation by the corresponding trion formation. The electrical control of the oscillator strength of the moir\'e excitons also results in a strong tunability of resonant Raman scattering. We find that the gate-induced doping significantly modulates the electronic moir\'e potential, however leaves the excitonic moir\'e confinement unaltered. This effect, coupled with variable moir\'e trap filling by tuning the optical excitation density, allows us to delineate the different phases of localized and delocalized moir\'e trions. We demonstrate that the moir\'e excitons exhibit strong valley coherence that changes in a striking non-monotonic W-shape with gating due to motional narrowing. These observations from the simultaneous electrostatic control of quasiparticle-dependent moir\'e potential will lead to exciting effects of tunable many-body phenomena in moir\'e superlattices.

cond-mat.mes-hall↗

arXiv2022

DRTCI: Learning Disentangled Representations for Temporal Causal Inference

Medical professionals evaluating alternative treatment plans for a patient often encounter time varying confounders, or covariates that affect both the future treatment assignment and the patient outcome. The recently proposed Counterfactual Recurrent Network (CRN) accounts for time varying confounders by using adversarial training to balance recurrent historical representations of patient data. However, this work assumes that all time varying covariates are confounding and thus attempts to balance the full state representation. Given that the actual subset of covariates that may in fact be confounding is in general unknown, recent work on counterfactual evaluation in the static, non-temporal setting has suggested that disentangling the covariate representation into separate factors, where each either influence treatment selection, patient outcome or both can help isolate selection bias and restrict balancing efforts to factors that influence outcome, allowing the remaining factors which predict treatment without needlessly being balanced.

cs.LG↗

arXiv2021

Observation of ~100% valley-coherent excitons in monolayer MoS2 through giant enhancement of valley coherence time

In monolayer transition metal dichalcogenide semiconductors, valley coherence degrades rapidly due to a combination of fast scattering and inter-valley exchange interaction. This leads to a sub-picosecond valley coherence time, making coherent manipulation of exciton a highly challenging task. Using monolayer MoS2 sandwiched between top and bottom graphene, here we demonstrate fully valley coherent excitons by observing ~100% degree of linear polarization in steady state photoluminescence. This is achieved in this unique design through a combined effect of (a) suppression in exchange interaction due to enhanced dielectric screening, (b) reduction in exciton lifetime due to a fast inter-layer transfer to graphene, and (c) operating in the motional narrowing regime. We disentangle the role of the key parameters affecting valley coherence by using a combination of calculation (solutions of Bethe-Salpeter and Maialle-Silva-Sham equations) and a careful choice of design of experiments using four different stacks with systematic variation of screening and exciton lifetime. To the best of our knowledge, this is the first report in which the excitons are found to be valley coherent in the entire lifetime in monolayer semiconductors, allowing optical readout of valley coherence possible.

cond-mat.mes-hall↗

arXiv2020

CAMTA: Causal Attention Model for Multi-touch Attribution

Advertising channels have evolved from conventional print media, billboards and radio advertising to online digital advertising (ad), where the users are exposed to a sequence of ad campaigns via social networks, display ads, search etc. While advertisers revisit the design of ad campaigns to concurrently serve the requirements emerging out of new ad channels, it is also critical for advertisers to estimate the contribution from touch-points (view, clicks, converts) on different channels, based on the sequence of customer actions. This process of contribution measurement is often referred to as multi-touch attribution (MTA). In this work, we propose CAMTA, a novel deep recurrent neural network architecture which is a casual attribution mechanism for user-personalised MTA in the context of observational data. CAMTA minimizes the selection bias in channel assignment across time-steps and touchpoints. Furthermore, it utilizes the users' pre-conversion actions in a principled way in order to predict pre-channel attribution. To quantitatively benchmark the proposed MTA model, we employ the real world Criteo dataset and demonstrate the superior performance of CAMTA with respect to prediction accuracy as compared to several baselines. In addition, we provide results for budget allocation and user-behaviour modelling on the predicted channel attribution.

cs.LG↗

arXiv2020

Highly tunable layered exciton in bilayer WS$_2$: linear quantum confined Stark effect versus electrostatic doping

In 1H monolayer transition metal dichalcogenide, the inversion symmetry is broken, while the reflection symmetry is maintained. On the contrary, in the bilayer, the inversion symmetry is restored, but the reflection symmetry is broken. As a consequence of these contrasting symmetries, here we show that bilayer WS$_2$ exhibits a quantum confined Stark effect (QCSE) that is linear with the applied out-of-plane electric field, in contrary to a quadratic one for a monolayer. The interplay between the unique layer degree of freedom in the bilayer and the field driven partial inter-conversion between intra-layer and inter-layer excitons generates a giant tunability of the exciton oscillator strength. This makes bilayer WS$_2$ a promising candidate for an atomically thin, tunable electro-absorption modulator at the exciton resonance, particularly when stacked on top of a graphene layer that provides an ultra-fast non-radiative relaxation channel. By tweaking the biasing configuration, we further show that the excitonic response can be largely tuned through electrostatic doping, by efficiently transferring the oscillator strength from neutral to charged exciton. The findings are prospective towards highly tunable, atomically thin, compact and light, on chip, reconfigurable components for next generation optoelectronics.

cond-mat.mes-hall↗

arXiv2020

Hi-CI: Deep Causal Inference in High Dimensions

We address the problem of counterfactual regression using causal inference (CI) in observational studies consisting of high dimensional covariates and high cardinality treatments. Confounding bias, which leads to inaccurate treatment effect estimation, is attributed to covariates that affect both treatments and outcome. The presence of high-dimensional co-variates exacerbates the impact of bias as it is harder to isolate and measure the impact of these confounders. In the presence of high-cardinality treatment variables, CI is rendered ill-posed due to the increase in the number of counterfactual outcomes to be predicted. We propose Hi-CI, a deep neural network (DNN) based framework for estimating causal effects in the presence of large number of covariates, and high-cardinal and continuous treatment variables. The proposed architecture comprises of a decorrelation network and an outcome prediction network. In the decorrelation network, we learn a data representation in lower dimensions as compared to the original covariates and addresses confounding bias alongside. Subsequently, in the outcome prediction network, we learn an embedding of high-cardinality and continuous treatments, jointly with the data representation. We demonstrate the efficacy of causal effect prediction of the proposed Hi-CI network using synthetic and real-world NEWS datasets.

stat.ME↗

arXiv2020

MultiMBNN: Matched and Balanced Causal Inference with Neural Networks

Causal inference (CI) in observational studies has received a lot of attention in healthcare, education, ad attribution, policy evaluation, etc. Confounding is a typical hazard, where the context affects both, the treatment assignment and response. In a multiple treatment scenario, we propose the neural network based MultiMBNN, where we overcome confounding by employing generalized propensity score based matching, and learning balanced representations. We benchmark the performance on synthetic and real-world datasets using PEHE, and mean absolute percentage error over ATE as metrics. MultiMBNN outperforms the state-of-the-art algorithms for CI such as TARNet and Perfect Match (PM).

stat.ME↗

arXiv2019

MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population

Performing inference on data obtained through observational studies is becoming extremely relevant due to the widespread availability of data in fields such as healthcare, education, retail, etc. Furthermore, this data is accrued from multiple homogeneous subgroups of a heterogeneous population, and hence, generalizing the inference mechanism over such data is essential. We propose the MetaCI framework with the goal of answering counterfactual questions in the context of causal inference (CI), where the factual observations are obtained from several homogeneous subgroups. While the CI network is designed to generalize from factual to counterfactual distribution in order to tackle covariate shift, MetaCI employs the meta-learning paradigm to tackle the shift in data distributions between training and test phase due to the presence of heterogeneity in the population, and due to drifts in the target distribution, also known as concept shift. We benchmark the performance of the MetaCI algorithm using the mean absolute percentage error over the average treatment effect as the metric, and demonstrate that meta initialization has significant gains compared to randomly initialized networks, and other methods.

cs.LG↗