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Arpita Dutta

Publications and source records attributed to Arpita Dutta.

8 recordsLinked to original sources

Spectroscopic signatures of Kohn anomaly in a topological crystalline insulator

Topological crystalline insulators extend the concept of topological insulators by hosting surface states protected by crystallographic symmetry. Their topological phase transitions arise from spin-orbit-driven band inversion in the bulk electronic structure, reshaping the low-energy electronic environment and its coupling to lattice excitations. While the electronic aspects of band topology are well established, the corresponding dynamics of lattice and electron-phonon interactions remain largely unexplored. Here, we report a pronounced softening of a low-energy surface phonon mode across the topological phase transition in Pb$_{0.77}$Sn$_{0.23}$Se, revealed by temperature-dependent time-domain terahertz spectroscopy. Unlike the well-known phonon softening in ferroelectrics, this effect does not signal a structural instability but instead reflects electronic reconstruction. We attribute the softening to the spectroscopic manifestations of a Kohn anomaly, indicating a strong coupling between lattice vibrations and Dirac-like surface electrons in the topological phase. Consistently, the phonon linewidth deviates from the standard anharmonic temperature dependence, further evidencing enhanced electron-phonon coupling. The observed changes in phonon frequency and linewidth at around 120 K are consistent with the reported topological phase transition temperature in this material. Our results thus provide a spectroscopic route for the distinct identification of the onset of a topological phase.

cond-mat.str-el

The interplay of crystal-field transitions and exchange spin dynamics in a ferrimagnet

Rare-earth iron garnets offer an ideal platform for exploring the interplay of low-energy excitations and the complex temperature-dependent magnetization dynamics. In these systems, exchange coupling between rare-earth and iron sublattices generates high-frequency collective spin excitations. In addition, the robust spin-orbit coupling of localized 4$f$ electrons triggers the crystal-electric-field (CEF) transitions at THz frequencies. Despite extensive research into the garnet spin dynamics, the interplay between CEF excitations and exchange modes has remained largely unmapped. Using temperature-dependent THz time-domain spectroscopy, we demonstrate a hybridization between the Yb-ion CEF excitation and the Yb-Fe exchange mode in Gd$_{3/2}$Yb$_{1/2}$BiFe$_{5}$O$_{12}$. This coupling is characterized by a significant redistribution of spectral and temporal weights as the material approaches its magnetization compensation temperature. Notably, the Yb-Fe exchange mode exhibits an anomalous redshift upon cooling -- a reversal of the conventional blue shift typically driven by increased exchange coupling. We trace this phenomenon to a modification of Yb-Fe exchange anisotropy, driven by the interplay of the Fe exchange field and Yb CEF excitations. These findings highlight the critical role of CEF-mediated exchange coupling in shaping low-energy spin dynamics, positioning rare-earth garnets as a cornerstone for future THz spintronic technologies.

cond-mat.mtrl-sci

Field-derivative torque induced magnetization reversal in ferrimagnetic Gd$_{3/2}$Yb$_{1/2}$BiFe$_5$O$_{12}$

Understanding the mechanism of spin switching in ferrimagnets via the excitation of THz pulses holds promise for future-generation magnetic memory devices. Such spin switching can be accomplished by the Zeeman torque exerted by the THz pulses on the magnetic spins. Theoretical and experimental works have established that the field-derivative of a terahertz pulse also exerts a torque, field derivative torque (FDT). Here, we investigate the role of the FDT in the spin switching in ferrimagnetic Gd$_{3/2}$Yb$_{1/2}$BiFe$_5$O$_{12}$ using a computational approach. Our results foresee that the spin switching in the presence of the FDT requires less THz magnetic fields than the spin switching without the FDT. Without the FDT terms, the spin switching in the considered system requires an extremely high magnetic field. Furthermore, we compute the switching and non-switching contour diagrams to show that the FDT tremendously enhances the possibility of spin switching. These results not only shed light on the significance of the FDT in magnetization switching but also suggest materials where the switching effect is pronounced.

cond-mat.mtrl-sci

Evidence of relativistic field-derivative torque in nonlinear THz response of magnetization dynamics

Understanding the complete light-spin interactions in magnetic systems is the key to manipulating the magnetization using optical means at ultrafast timescales. The selective addressing of spins by terahertz (THz) electromagnetic fields via Zeeman torque is one of the most successful ultrafast means of controlling magnetic excitations. Here we show that this traditional Zeeman torque on the spins is not sufficient, rather an additional relativistic field-derivative torque is essential to realize the observed magnetization dynamics. We accomplish this by exploring the ultrafast nonlinear magnetization dynamics of rare-earth, Bi-doped iron garnet when excited by two co-propagating THz pulses. First, by exciting the sample with an intense THz pulse and probing the magnetization dynamics using magneto-optical Faraday effect, we find the collective exchange resonance mode between rare-earth and transition metal sublattices at 0.48 THz. We further explore the magnetization dynamics via the THz time-domain spectroscopic means. We find that the observed nonlinear trace of the magnetic response cannot be mapped to the magnetization precession induced by the Zeeman torque, while the Zeeman torque supplemented by an additional field-derivative torque follows the experimental evidences. This breakthrough enhances our comprehension of ultra-relativistic effects and paves the way towards novel technologies harnessing light-induced control over magnetic systems.

cond-mat.mtrl-sci

A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages

The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech. The terms and expressions related to hate speech gets updated with changing times which poses an obstacle to policy-makers and researchers in case of hate speech identification. With growing number of individuals using their native languages to communicate with each other, hate speech in these low-resource languages are also growing. Although, there is awareness about the English-related approaches, much attention have not been provided to these low-resource languages due to lack of datasets and online available data. This article provides a detailed survey of hate speech detection in low-resource languages around the world with details of available datasets, features utilized and techniques used. This survey further discusses the prevailing surveys, overlapping concepts related to hate speech, research challenges and opportunities.

cs.CL

Role of material-dependent properties in THz field-derivative-torque-induced nonlinear magnetization dynamics

The traditional Landau-Lifshitz-Gilbert (LLG) equation has often delineated the linear and nonlinear magnetization dynamics, even at ultrashort timescales e.g., femtoseconds. In contrast, several other non-relativistic and relativistic spin torques have been reported as an extension of the LLG spin dynamics. Here, we explore the contribution of the relativistic field-derivative torque (FDT) in the nonlinear THz magnetization dynamics response applied to ferrimagnets with high Gilbert damping and exchange magnon frequency. Our findings suggest that the FDT plays a significant role in magnetization dynamics in both linear and nonlinear regimes, bridging the gap between the traditional LLG spin dynamics and experimental observations. We find that the coherent THz magnon excitation amplitude is enhanced with the field-derivative torque. Furthermore, a phase shift in the magnon oscillation is induced by the FDT term. This phase shift is almost 90 for the antiferromagnet, while it is almost zero for the ferrimagnet under our investigation. Analyzing the dual THz excitation and their FDT, we find that the nonlinear signals can not be distinctly observed without the FDT terms. However, the inclusion of the FDT terms produces distinct nonlinear signals which matches extremely well with the previously reported experimental results.

cond-mat.mtrl-sci

Effective Fault Localization using Probabilistic and Grouping Approach

Context: Fault localization (FL) is the key activity while debugging a program. Any improvement to this activity leads to significant improvement in total software development cost. There is an internal linkage between the program spectrum and test execution result. Conditional probability in statistics captures the probability of occurring one event in relationship to one or more other events. Objectives: The aim of this paper is to use the conception of conditional probability to design an effective fault localization technique. Methods: In the paper, we present a fault localization technique that derives the association between statement coverage information and test case execution result using condition probability statistics. This association with the failed test case result shows the fault containing the probability of that specific statement. Subsequently, we use a grouping method to refine the obtained statement ranking sequence for better fault localization. Results: We evaluated the effectiveness of proposed method over eleven open-source data sets. Our obtained results show that on average, the proposed CGFL method is 24.56% more effective than other contemporary fault localization methods such as D*, Tarantula, Ochiai, Crosstab, BPNN, RBFNN, DNN, and CNN. Conclusion: We devised an effective fault localization technique by combining the conditional probabilistic method with failed test case execution-based approach. Our experimental evaluation shows our proposed method outperforms the existing fault localization techniques.

cs.SE

CNN based Extraction of Panels/Characters from Bengali Comic Book Page Images

Peoples nowadays prefer to use digital gadgets like cameras or mobile phones for capturing documents. Automatic extraction of panels/characters from the images of a comic document is challenging due to the wide variety of drawing styles adopted by writers, beneficial for readers to read them on mobile devices at any time and useful for automatic digitization. Most of the methods for localization of panel/character rely on the connected component analysis or page background mask and are applicable only for a limited comic dataset. This work proposes a panel/character localization architecture based on the features of YOLO and CNN for extraction of both panels and characters from comic book images. The method achieved remarkable results on Bengali Comic Book Image dataset (BCBId) consisting of total $4130$ images, developed by us as well as on a variety of publicly available comic datasets in other languages, i.e. eBDtheque, Manga 109 and DCM dataset.

cs.CV