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III V semiconductor nanowire based photodetectors have significant potential for remote sensing and LiDAR applications, particularly due to their ability to operate at 1.55 {\mu}m. Achieving room temperature operation and near unity absorption using these nanowires at 1.55 {\mu}m is crucial for single photon detection, which offers a promising solution to the challenges posed by the existing superconducting nanowire single photon detectors. Key materials suited for this wavelength include lattice matched In0.53Ga0.47As and Ga0.5As0.5Sb to InP. This study reports a comparison between InGaAs and GaAsSb nanowires to achieve high absorption efficiency at room temperature. Through optimized nanowire arrangement and geometry, we aim to maximize absorption. Our approach features a comparative analysis of patterned InGaAs and GaAsSb nanowires with absorption characteristics modeled using finite difference time domain simulations to enhance absorption at the target wavelength. We also present the complete workflow for nanowire fabrication, modeling, and simulation, encompassing the production of tapered nanowire structures and measurement of their absorption efficiency. Our experimental results show that tapered InGaAs and GaAsSb nanowires exhibit an absorption efficiency of 93% and 92%, respectively, at room temperature around 1.55 {\mu}m.

Automatic Speech Translation (AST) datasets for Indian languages remain critically scarce, with public resources covering fewer than 10 of the 22 official languages. This scarcity has resulted in AST systems for Indian languages lagging far behind those available for high-resource languages like English. In this paper, we first evaluate the performance of widely-used AST systems on Indian languages, identifying notable performance gaps and challenges. Our findings show that while these systems perform adequately on read speech, they struggle significantly with spontaneous speech, including disfluencies like pauses and hesitations. Additionally, there is a striking absence of systems capable of accurately translating colloquial and informal language, a key aspect of everyday communication. To this end, we introduce BhasaAnuvaad, the largest publicly available dataset for AST involving 13 out of 22 scheduled Indian languages and English spanning over 44,400 hours and 17M text segments. BhasaAnuvaad contains data for English speech to Indic text, as well as Indic speech to English text. This dataset comprises three key categories: (1) Curated datasets from existing resources, (2) Large-scale web mining, and (3) Synthetic data generation. By offering this diverse and expansive dataset, we aim to bridge the resource gap and promote advancements in AST for Indian languages., Comment: Work in Progress

Objective: To assess the antioxidant, wound healing, anti-ulcer, and anti-inflammatory properties of Jatropha maheshwari. Methods: Jatropha maheshwari was collected from Kanyakumari district and authenticated. Ethanol was used for continuous hot percolation extraction of the plant. Antioxidant activity was evaluated using DPPH and ABTS assays. The wound healing potential was assessed through a wound scratch assay using 3T3-L1 murine fibroblast cell lines. Anti-ulcer activity was measured using the acid-neutralizing capacity (ANC) and H+/K+-ATPase inhibitory activity methods. Anti-inflammatory effects were determined through dose-dependent studies of the ethanol extract. Results: Antioxidant Activity: The crude extract exhibited strong antioxidant capacity with percentage inhibition values of 88% (DPPH) and 75.7% (ABTS). Wound Healing Activity: The wound closure rate in treated 3T3-L1 cell lines reached 97.88%, indicating potent wound healing properties. Anti-Ulcer Activity: The extract demonstrated an 80.1% inhibition compared to the control when tested alongside omeprazole. ANC per gram of antacid was recorded at 20 and 26 for oral doses of 10 and 500 {\mu}g/ml, respectively. Anti-Inflammatory Activity: Dose-dependent inhibition percentages of 30.1% (10 {\mu}g/ml) and 96.5% (500 {\mu}g/ml) were observed (p<0.001) relative to inflammation control. Additional percentages of 26.3% (10 {\mu}g/ml) and 42.6% (500 {\mu}g/ml) further confirmed the anti-inflammatory activity. Conclusion: Jatropha maheshwari demonstrates significant antioxidant, wound healing, anti-ulcer, and anti-inflammatory properties. Further research is warranted to elucidate the mechanisms underlying these pharmacological effects.

For any uniformity $r$ and residue $k$ modulo $r$, we give an exact characterization of the $r$-uniform hypergraphs that homomorphically avoid tight cycles of length $k$ modulo $r$, in terms of colorings of $(r-1)$-tuples of vertices. This generalizes the result that a graph avoids all odd closed walks if and only if it is bipartite, as well as a result of Kam\v cev, Letzter, and Pokrovskiy in uniformity 3. In fact, our characterization applies to a much larger class of families than those of the form $\mathscr C_k^{(r)}=\{\text{$r$-uniform tight cycles of length $k$ modulo $r$}\}$. We also outline a general strategy to prove that, if $\mathscr C$ is a family of tight-cycle-like hypergraphs (including but not limited to the families $\mathscr C_k^{(r)}$) for which the above characterization applies, then all sufficiently long $C\in \mathscr C$ will have the same Tur\'an density. We demonstrate an application of this framework, proving that there exists an integer $L_0$ such that for every $L>L_0$ not divisible by 4, the tight cycle $C^{(4)}_L$ has Tur\'an density $1/2$., Comment: 45 pages and a 6-page appendix. 8 figures

Red quasars, often associated with potent [OIII] outflows on both galactic and circumgalactic scales, may play a pivotal role in galactic evolution and black hole feedback. In this work, we explore the [FeII] emission in one such quasar at redshift z = 0.4352, F2M J110648.32+480712.3, using the integral field unit (IFU) mode of the Near Infrared Spectrograph (NIRSpec) aboard the James Webb Space Telescope (JWST). Our observations reveal clumpy [FeII] gas located to the south of the quasar. By comparing the kinematics of [FeII] and [OIII], we find that the clumpy [FeII] gas in the southeast and southwest aligns with the outflow, exhibiting similar median velocities up to v_50 ~ 1200 km/s and high velocity widths W_80 > 1000 km/s. In contrast, the [FeII] gas to the south shows kinematics inconsistent with the outflow, with W_80 ~ 500 km/s, significantly smaller than the [OIII] at the same location, suggesting that the [FeII] may be confined within the host galaxy. Utilizing standard emission-line diagnostic ratios, we map the ionization sources of the gas. According to the MAPPINGS III shock models for [FeII]/Pabeta, the regions to the southwest and southeast of the quasar are primarily photoionized. Conversely, the [FeII] emission to the south is likely excited by shocks generated by the back-pressure of the outflow on the galaxy disk, a direct signature of the impact of the quasar on its host.

Quasar feedback may play a key role in the evolution of massive galaxies. The dust-reddened quasar, F2M110648.35$+$480712 at $z = 0.4352$ is one of the few cases at its redshift that exhibits powerful quasar feedback through bipolar outflows. Our new observation with the integral field unit mode of Near-infrared Spectrograph onboard JWST opens a new window to examine this spectacular outflow through Pa$\alpha$ emission line with $\sim$3$\times$ better spatial resolution than previous work. The morphology and kinematics of the Pa$\alpha$ nebula confirm the existence of a bipolar outflow extending on a scale of $\sim$17$\times$14 kpc and with a velocity reaching $\sim$1100 km s$^{-1}$. The higher spatial resolution of our new observation leads to more reliable measurements of outflow kinematics. Considering only the spatially resolved outflow and assuming an electron density of 100 cm$^{-2}$, the mass, momentum and kinetic energy outflow rates are $\sim$50-210 M$_{\odot}$ yr$^{-1}$, $\sim$0.3-1.7$\times$10$^{36}$ dynes ($\sim$14-78\% of the quasar photon momentum flux) and $\sim$0.16-1.27$\times$10$^{44}$ erg s$^{-1}$ ($\sim$0.02-0.20\% of the quasar bolometric luminosity), respectively. The local instantaneous outflow rates generally decrease radially. We infer that the quasar is powerful enough to drive the outflow, while stellar processes cannot be overlooked as a contributing energy source. The mass outflow rate is $\sim$0.4-1.5 times the star formation rate, and the ratio of kinetic energy outflow rate to the quasar bolometric luminosity is comparable to the minimum value required for negative quasar feedback in simulations. This outflow may help regulate the star formation activity within the system to some extent., Comment: 14 pages, 6 figures, 1 table, ApJ in review

High-speed tactile arrays are essential for real-time robotic control in unstructured environments, but high pixel counts limit readout rates of most large tactile arrays to below 100Hz. We introduce ACTS - adaptive compressive tactile subsampling - a method that efficiently samples tactile matrices and reconstructs interactions using sparse recovery and a learned tactile dictionary. Tested on a 1024-pixel sensor array (32x32), ACTS increased frame rates by 18X compared to raster scanning, with minimal error. For the first time in large-area tactile skin, we demonstrate rapid object classification within 20ms of contact, high-speed projectile detection, ricochet angle estimation, and deformation tracking through enhanced spatiotemporal resolution. Our method can be implemented in firmware, upgrading existing low-cost, flexible, and robust tactile arrays into high-resolution systems for large-area spatiotemporal touch sensing., Comment: 40 pages, 8 main figures, 12 supplemental figures, Videos can be accessed at https://tinyurl.com/TactileSubsampling

This paper describes NLIP Lab's multilingual machine translation system for the WAT24 shared task on multilingual Indic MT task for 22 scheduled languages belonging to 4 language families. We explore pre-training for Indic languages using alignment agreement objectives. We utilize bi-lingual dictionaries to substitute words from source sentences. Furthermore, we fine-tuned language direction-specific multilingual translation models using small and high-quality seed data. Our primary submission is a 243M parameters multilingual translation model covering 22 Indic languages. In the IN22-Gen benchmark, we achieved an average chrF++ score of 46.80 and 18.19 BLEU score for the En-Indic direction. In the Indic-En direction, we achieved an average chrF++ score of 56.34 and 30.82 BLEU score. In the In22-Conv benchmark, we achieved an average chrF++ score of 43.43 and BLEU score of 16.58 in the En-Indic direction, and in the Indic-En direction, we achieved an average of 52.44 and 29.77 for chrF++ and BLEU respectively. Our model\footnote{Our code and models are available at \url{https://github.com/maharajbrahma/WAT2024-MultiIndicMT}} is competitive with IndicTransv1 (474M parameter model)., Comment: WMT 24 WAT Shared Task IndicMultiMT (Best System)

This paper focuses on solving a stochastic variational inequality (SVI) problem under relaxed smoothness assumption for a class of structured non-monotone operators. The SVI problem has attracted significant interest in the machine learning community due to its immediate application to adversarial training and multi-agent reinforcement learning. In many such applications, the resulting operators do not satisfy the smoothness assumption. To address this issue, we focus on the generalized smoothness assumption and consider two well-known stochastic methods with clipping, namely, projection and Korpelevich. For these clipped methods, we provide the first almost-sure convergence results without making any assumptions on the boundedness of either the stochastic operator or the stochastic samples. Furthermore, we provide the first in-expectation convergence rate results for these methods under a relaxed smoothness assumption.

Let $G$ be an abelian group. The main theorem of this paper asserts that there exists a Cayley graph on $G$ with chromatic number 3 if and only if $G$ is not of exponent 1, 2, or 4. Although motivated by ideas from algebraic topology, our proof may be expressed purely combinatorially. As a by-product, we derive a topological result which is of independent interest. Suppose $X$ is a connected non-bipartite graph, and let $\mathcal N(X)$ denote its neighborhood complex. We show that if the fundamental group $\pi_1(\mathcal N(X))$ or first homology group $H_1(\mathcal N(X))$ is torsion, then the chromatic number of $X$ is at least 4. This strengthens a classical result of Lov\'asz, which derives the same conclusion if $\pi_1(\mathcal N(X))$ is trivial., Comment: 11 pages

We study gradient methods for solving an optimization problem with an $(L_0, L_1)$-smooth objective function. This problem class generalizes that of Lipschitz-smooth problems and has gained interest recently, as it captures a broader range of machine learning applications. We provide novel insights on the properties of this function class and develop a general framework for analyzing optimization methods for $(L_0, L_1)$-smooth function in a principled manner. While our convergence rate estimates recover existing results for minimizing the gradient norm for nonconvex problems, our approach allows us to significantly improve the current state-of-the-art complexity results in the case of convex problems. We show that both the gradient method with Polyak stepsizes and the normalized gradient method, without any knowledge of the parameters $L_0$ and $L_1$, achieve the same complexity bounds as the method with the knowledge of these constants. In addition to that, we show that a carefully chosen accelerated gradient method can be applied to $(L_0, L_1)$-smooth functions, further improving previously known results. In all cases, the efficiency bounds we establish do not have an exponential dependency on $L_0$ or $L_1$, and do not depend on the initial gradient norm.

The occurrence of neutrino oscillations demands the existence of flavour violation in charged lepton sector. The relation between the branching ratios of different charged lepton flavour violating (CLFV) decay modes depends on the details of the neutrino mass model. In this work, we consider the three types of simple seesaw mechanisms of neutrino masses and study the correlation between the radiative CLFV decays and the meson CLFV decays. We find that the meson CLFV decay branching ratios are negligibly small in type-II seesaw mechanism whereas they are constrained to be at least three (two) orders of magnitude smaller than the radiative CLFV decay branching ratios in the case of type-I (type-III) seesaw mechanism. Thus the relationship between these two modes of CLFV decays helps in distinguishing between different types of seesaw mechanism. If, the branching ratios of CLFV decays of mesons are larger than those of radiative CLFV decays, it provides a strong hint that the neutrino mass generating mechanism is more complicated than simple seesaw., Comment: new references added

In recent years, various materials have been developed to reduce the reliance of industries on Indium, a primary component of transparent conducting oxides (TCOs) used in the current generation of devices. The leading candidates for indium free TCOs are strontium vanadates, niobates and molybdates -- strongly correlated perovskite systems that exhibit high intrinsic electrical conductivity and optimal transparency. In this work, we focus on the strontium niobate thin films and manipulate its optical conductivity by Ti doping, which shifts the plasma frequency and reduces electronic correlations. This allows us to achieve a low resistance for Ti doped SNO thin films, while maintaining a high transparency in the visible spectrum. We obtain the optimal figure-of-merit (FOM) of 10.3 ($10^{-3}\Omega^{-1}$) for $x = 0.3$. This FOM significantly outperforms the optoelectronic capabilities of Tin-doped Indium oxide (ITO) and several other proposed transparent conductor materials. Our research paves the way for designing the next generation of transparent conductors, guided by insights from density-functional theory (DFT) and dynamical mean-field theory (DMFT)., Comment: 35 pages, 14 figure including supplementary figures

In this paper, we describe our system for the WMT 24 shared task of Low-Resource Indic Language Translation. We consider eng $\leftrightarrow$ {as, kha, lus, mni} as participating language pairs. In this shared task, we explore the finetuning of a pre-trained model motivated by the pre-trained objective of aligning embeddings closer by alignment augmentation \cite{lin-etal-2020-pre} for 22 scheduled Indian languages. Our primary system is based on language-specific finetuning on a pre-trained model. We achieve chrF2 scores of 50.6, 42.3, 54.9, and 66.3 on the official public test set for eng$\rightarrow$as, eng$\rightarrow$kha, eng$\rightarrow$lus, eng$\rightarrow$mni respectively. We also explore multilingual training with/without language grouping and layer-freezing. Our code, models, and generated translations are available here: https://github.com/pramitsahoo/WMT2024-LRILT., Comment: WMT2024 INDICMT Shared Task

The cost of encoding a system Hamiltonian in a digital quantum computer as a linear combination of unitaries (LCU) grows with the 1-norm of the LCU expansion. The Block Invariant Symmetry Shift (BLISS) technique reduces this 1-norm by modifying the Hamiltonian action on only the undesired electron-number subspaces. Previously, BLISS required a computationally expensive nonlinear optimization that was not guaranteed to find the global minimum. Here, we introduce various reformulations of this optimization as a linear programming problem, which guarantees optimality and significantly reduces the computational cost. We apply BLISS to industrially-relevant homogeneous catalysts in active spaces of up to 76 orbitals, finding substantial reductions in both the spectral range of the modified Hamiltonian and the 1-norms of Pauli and fermionic LCUs. Our linear programming techniques for obtaining the BLISS operator enable more efficient Hamiltonian simulation and, by reducing the Hamiltonian's spectral range, offer opportunities for improved LCU groupings to further reduce the 1-norm.

In order to solve problems of practical importance, quantum computers will likely need to incorporate quantum error correction, where a logical qubit is redundantly encoded in many noisy physical qubits. The large physical-qubit overhead typically associated with error correction motivates the search for more hardware-efficient approaches. Here, using a microfabricated superconducting quantum circuit, we realize a logical qubit memory formed from the concatenation of encoded bosonic cat qubits with an outer repetition code of distance $d=5$. The bosonic cat qubits are passively protected against bit flips using a stabilizing circuit. Cat-qubit phase-flip errors are corrected by the repetition code which uses ancilla transmons for syndrome measurement. We realize a noise-biased CX gate which ensures bit-flip error suppression is maintained during error correction. We study the performance and scaling of the logical qubit memory, finding that the phase-flip correcting repetition code operates below threshold, with logical phase-flip error decreasing with code distance from $d=3$ to $d=5$. Concurrently, the logical bit-flip error is suppressed with increasing cat-qubit mean photon number. The minimum measured logical error per cycle is on average $1.75(2)\%$ for the distance-3 code sections, and $1.65(3)\%$ for the longer distance-5 code, demonstrating the effectiveness of bit-flip error suppression throughout the error correction cycle. These results, where the intrinsic error suppression of the bosonic encodings allows us to use a hardware-efficient outer error correcting code, indicate that concatenated bosonic codes are a compelling paradigm for reaching fault-tolerant quantum computation., Comment: Comments on the manuscript welcome!

Due to the absorption of high energetic ultraviolet (UV) photons by the surface layers of the cold molecular clouds, only low energetic photons are able to penetrate into the inner regions of these clouds. This leads to lower photo-ionization yield of molecules of higher ionization potential in these environments. However, here we have experimentally shown the ionization of Benzonitrile molecule using 266nm (4.66eV) photons. The low intensity and unfocused laser irradiation of benzonitrile molecules results extensive fragmentation. Moreover, the ion-neutral reactions among the cationic fragments and neutral fragments shows promising molecular mass growth.

The demand for innovation in product design necessitates a prolific ideation phase. Conversational AI (CAI) systems that use Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer) have been shown to be fruitful in augmenting human creativity, providing numerous novel and diverse ideas. Despite the success in ideation quantity, the qualitative assessment of these ideas remains challenging and traditionally reliant on expert human evaluation. This method suffers from limitations such as human judgment errors, bias, and oversight. Addressing this gap, our study introduces a comprehensive mathematical framework for automated analysis to objectively evaluate the plethora of ideas generated by CAI systems and/or humans. This framework is particularly advantageous for novice designers who lack experience in selecting promising ideas. By converting the ideas into higher dimensional vectors and quantitatively measuring the diversity between them using tools such as UMAP, DBSCAN and PCA, the proposed method provides a reliable and objective way of selecting the most promising ideas, thereby enhancing the efficiency of the ideation phase., Comment: 20 pages, 12 figures, 5 tables

Coulomb interactions among charge carriers that occupy an electronic flat band have a profound impact on the macroscopic properties of materials. At sufficient strength, these interactions can give rise to captivating phenomena such as quantum criticality, Mott-Hubbard states, and unconventional superconductivity. The appearance of these characteristics sensitively depends on the number of electrons occupying the flat band states. In this work, we present experimental evidence obtained from scanning tunneling microscopy measurements for a cascade of strongly correlated states appearing in the partially occupied kagome flat bands of Co$_{1-x}$Fe$_x$Sn whose filling can be controlled by the Fe-doping level $x$. At elevated temperatures ($T\geq16\,K$), we detect a nematic electronic state across a broad doping range $0.05100\,$meV) blend the states of two $3d$-orbital derived flat bands and impart a nematic order parameter. This state serves as the parent phase of a strongly correlated phase diagram: At lower temperatures $T<16\,$K, we find spectroscopic evidence for an orbital-selective Mott state enabled by the $3d$-orbital degeneracy of the Co atom. This state can only be detected in samples with ideal Fe doping ($x=0.17$) and descends into pseudogap phases upon electron and hole doping. At $T<8\,$K, the pseudogap phase evolves into another nematic low temperature state. Our observations demonstrate that the electronic ground state of a kagome flat band depends on the complex interplay between strong Coulomb repulsion, $3d$-orbital degeneracy, and flat band filling fraction at different temperatures., Comment: 13 pages, 5 figures

We study the intravalley spin-polarized superconductivity in rhombohedral tetralayer graphene, which has been discovered experimentally in Han $et$ $al$ arXiv:2408.15233. We construct a minimal model for the intravalley spin-polarized superconductivity, assuming a simplified anisotropic interaction that depends only on the angle between the incoming and outgoing momenta. Despite the absence of Fermi surface nesting, we show that the superconductivity appears near the Van Hove singularity with the maximal $T_c$ near a bifurcation point of the peaks in the density of states. We identify the topological $p+ip$, topological $h+ih$, and the non-topological nodal $f$-wave pairings as the possible states, which are all pair density wave orders due to the intravalley nature. Furthermore, these pair density wave orders require a finite attractive threshold for superconductivity, resulting in narrow superconducting regions, consistent with experimental findings. We discuss the possible pairing mechanisms and point out that the Kohn-Luttinger mechanism is a plausible explanation for the intravalley spin-polarized superconductivity in the rhombohedral tetralayer graphene., Comment: 7+5 pages, 3+2 figures

Within a scotogenic neutrino mass model we explore the cogenesis of matter from the CP violating decay of a heavy $\mathbb{Z}_2$-odd right handed neutrino that simultaneously populates the visible and a multipartite dark sector. The quantum of CP violation sets the baryon asymmetry in the visible sector driven by leptogenesis. The relic density of a sub-GeV scale freeze-in dark matter is generated by the late time decay of the next to lightest dark particle dynamically regulated by its interplay with the thermal scattering processes., Comment: 9 pages, 5 figures, 2 tables

This paper presents a novel conversational AI-enabled active ideation interface as a creative idea-generation tool to assist novice designers in mitigating the initial latency and ideation bottlenecks that are commonly observed. It is a dynamic, interactive, and contextually responsive approach, actively involving a large language model (LLM) from the domain of natural language processing (NLP) in artificial intelligence (AI) to produce multiple statements of potential ideas for different design problems. Integrating such AI models with ideation creates what we refer to as an Active Ideation scenario, which helps foster continuous dialogue-based interaction, context-sensitive conversation, and prolific idea generation. A pilot study was conducted with thirty novice designers to generate ideas for given problems using traditional methods and the new CAI-based interface. The key parameters of fluency, novelty, and variety were used to compare the outcomes qualitatively by a panel of experts. The findings demonstrated the effectiveness of the proposed tool for generating prolific, diverse and novel ideas. The interface was enhanced by incorporating a prompt-engineered structured dialogue style for each ideation stage to make it uniform and more convenient for the designers. The resulting responses of such a structured CAI interface were found to be more succinct and aligned towards the subsequent design stage, namely conceptualization. The paper thus established the rich potential of using Generative AI (Gen-AI) for the early ill-structured phase of the creative product design process., Comment: 21 pages, 16 figures, AIEDAM Journal Article

The putative Kitaev material Na$_2$Co$_2$TeO$_6$ has recently been proposed to enter a quantum spin disordered state when magnetic fields are applied in parallel to the honeycomb layers. In this report we uncover signatures of a quantum critical endpoint (QCEP) associated with the assumed order-disorder transition by means of high-resolution capacitance dilatometry. At the critical field $B_\mathrm{C} \simeq 6$~T , a sign change of the out-of-plane thermal expansion coefficient $\alpha_c$ indicates accumulation of entropy upon crossing the phase boundary. The proportional relationship between isothermal magnetisation and magnetostriction signals that the QCEP can be tuned by magnetic field and pressure simultaneously. The presented results expand the material classes that exhibit metamagnetic quantum criticality to honeycomb antiferromagnets with possible Kitaev interactions., Comment: 20 pages, 13 figures, submitted to PRB

Spectroscopic identification of distinct nonlinear photocurrents unveils quantum geometric properties of electron wavefunctions and the momentum-space topological structures. This is especially interesting, but still puzzling, for chiral topological semimetals with possibilities of hosting giant quantized circular photogalvanic effect. Here we report a comprehensive terahertz (THz) emission spectroscopic analysis of nonlinear photoconductivity of chiral multifold CoSi at 0.26 ~ 1 eV. We find a large linear shift conductivity (17 {\mu}A/V2), and confirm a giant injection conductivity (167 {\mu}A/V2) as a consequence of strongly interfered non-quantized contributions from the vicinity of multifold nodes with opposite chiralities. The bulk injection current excited by the pump field with a complex wavevector is shown to carry both longitudinal and transverse components. Symmetry analyses further unveil weak nonlocal photon drag effect in addition to the photogalvanic effect. This work not only highlights chiral transition metal monosilicides for mid-infrared photovoltaic applications via various nonlinear optical channels, but also consolidates the THz spectroscopy for quantitative photovoltaic research.

Recent advancements in text-to-speech (TTS) synthesis show that large-scale models trained with extensive web data produce highly natural-sounding output. However, such data is scarce for Indian languages due to the lack of high-quality, manually subtitled data on platforms like LibriVox or YouTube. To address this gap, we enhance existing large-scale ASR datasets containing natural conversations collected in low-quality environments to generate high-quality TTS training data. Our pipeline leverages the cross-lingual generalization of denoising and speech enhancement models trained on English and applied to Indian languages. This results in IndicVoices-R (IV-R), the largest multilingual Indian TTS dataset derived from an ASR dataset, with 1,704 hours of high-quality speech from 10,496 speakers across 22 Indian languages. IV-R matches the quality of gold-standard TTS datasets like LJSpeech, LibriTTS, and IndicTTS. We also introduce the IV-R Benchmark, the first to assess zero-shot, few-shot, and many-shot speaker generalization capabilities of TTS models on Indian voices, ensuring diversity in age, gender, and style. We demonstrate that fine-tuning an English pre-trained model on a combined dataset of high-quality IndicTTS and our IV-R dataset results in better zero-shot speaker generalization compared to fine-tuning on the IndicTTS dataset alone. Further, our evaluation reveals limited zero-shot generalization for Indian voices in TTS models trained on prior datasets, which we improve by fine-tuning the model on our data containing diverse set of speakers across language families. We open-source all data and code, releasing the first TTS model for all 22 official Indian languages., Comment: Accepted to NeurIPS 2024 Datasets and Benchmarks track

The recent experimental observation of fractional quantum anomalous Hall (FQAH) states in rhombohedral multilayer graphene has attracted significant attention. One of the most intriguing observations is that the FQAH states at various fractional fillings give way to IQAH states as the temperature is lowered. In this work, we propose a mechanism for the appearance of FQAH states within a finite temperature range in a toy model. The model consists of a flat Chern band and impurities, and we analyze the effects of impurities on the system's behavior at finite temperatures. We believe that the crossover may arise from the competition between the energy penalty for thermal excitations and the increase in entropy. We support our theoretical argument with numerical calculations using exact diagonalization. Our results suggest that impurities may play a crucial role in the crossover from the FQAH to IQAH states in rhombohedral pentalayer graphene., Comment: 5 pages, 4 figures. Comments are welcome

We predict large regions of the charge stability diagram using a multi-band and multi-electron configuration interaction model of a double quantum dot system. We account for many-body interactions within each quantum dot using full configuration interaction and solve for single-particle density operators. This allows charge states to be predicted more accurately than the extensively used classical capacitance model or the single-band Hubbard model. The resulting single-particle mixed states then serve as inputs into an atomic orbital picture that allows for the explicit calculation of the underlying Hubbard model parameters by performing the appropriate integrals. This numerical approach allows for arbitrary choices of electrostatic potential and gate geometry. A common assumption when calculating charge stability diagrams from the Hubbard model is that the charge stability diagrams are periodic, but we find that the tunnel couplings for valence electrons in dots with $N=3$ electrons are significantly enhanced when compared to single-electron dots. This difference is apparent in the charge stability diagram for higher occupancy Coulomb diamonds. We also quantitatively explore how the barrier gate strength and dot pitch impact this behavior. Our work should help improve the future realistic modeling of semiconductor-dot-based quantum circuits., Comment: 13 pages, 13 figures

We examine the behavior of singular leading and sub-leading logarithms, commonly referred to as the soft-virtual (SV) and next-to-soft-virtual (NSV) terms, in the production of the Higgs boson via the bottom quark annihilation channel. We derive analytic expressions at the SV+NSV resummed level, up to next-to-next-to-next-to-leading logarithmic (N3LL) accuracy in perturbative QCD, applicable to both the inclusive production cross-section and rapidity distribution. This has been achieved using an existing resummation formalism based on factorization and renormalization group (RG) invariance. A phenomenological analysis of our resummed results is performed for the 13 TeV Large Hadron Collider. Furthermore, we present the SV coefficients at the fourth order in the strong coupling and explore the impact of next-to-next-to-next-to-next-to-leading logarithmic (N4LL) resummation on the total cross-section., Comment: 45 pages, 7 figures

The time-to-recovery or time-to-death for various infectious diseases can vary significantly among individuals, influenced by several factors such as demographic differences, immune strength, medical history, age, pre-existing conditions, and infection severity. To capture these variations, time-since-infection dependent recovery and death rates offer a detailed description of the epidemic. However, obtaining individual-level data to estimate these rates is challenging, while aggregate epidemiological data (such as the number of new infections, number of active cases, number of new recoveries, and number of new deaths) are more readily available. In this article, a new methodology is proposed to estimate time-since-infection dependent recovery and death rates using easily available data sources, accommodating irregular data collection timings reflective of real-world reporting practices. The Nadaraya-Watson estimator is utilized to derive the number of new infections. This model improves the accuracy of epidemic progression descriptions and provides clear insights into recovery and death distributions. The proposed methodology is validated using COVID-19 data and its general applicability is demonstrated by applying it to some other diseases like measles and typhoid.

Alloying stands out as a pivotal technological method employed across various compounds, be they metallic, magnetic, or semiconducting, serving to fine-tune their properties to meet specific requirements. Ternary semiconductors represent a prominent example of such alloys. They offer fine-tuning of electronic bands, the band gap in particular, thus granting the technology of semiconductor heterostructures devices, key elements in current electronics and optoelectronics. In the realm of magnetically ordered systems, akin to electronic bands in solids, spin waves exhibit characteristic dispersion relations, featuring sizeable magnon gaps in many antiferromagnets. The engineering of the magnon gap constitutes a relevant direction in current research on antiferromagnets, aiming to leverage their distinct properties for THz technologies, spintronics, or magnonics. In this study, we showcase the tunability of the magnon gap across the THz spectral range within an alloy comprising representative semiconducting van-der-Waals antiferromagnets FePS$_3$ and NiPS$_3$. These constituents share identical in-plane crystal structures, magnetic unit cells and the direction of the magnetic anisotropy, but differ in the amplitude and sign of the latter. Altogether these attributes result in the wide tunability of the magnon gap in the Fe$_{1-x}$Ni$_x$PS$_3$ alloy in which the magnetic order is imposed by stronger, perpendicular anisotropy of iron., Comment: 6 pages, 1 figure, to be published in Phys. Rev. B

By theoretically analyzing the recent temperature dependent transport data in pentalayer graphene [Lu et al., arXiv:2408.10203], we establish that the experimentally observed transition from low-temperature quantum anomalous Hall effect to higher-temperature fractional quantum anomalous Hall effect is a crossover phenomenon arising from the competition between interaction and disorder energy scales, with the likely zero temperature ground state of the system being either a localized insulator or a Chern insulator with a quantized anomalous Hall effect. In particular, the intriguing suppression of FQAHE in favor of QAHE with decreasing temperature is explained as arising from the low-temperature localization of the carriers where disorder overcomes the interaction effects. We provide a detailed analysis of the data in support of the crossover scenario., Comment: Published version

The topological Tur\'an number $\mathrm{ex}_{\hom}(n,X)$ of a 2-dimensional simplicial complex $X$ asks for the maximum number of edges in an $n$-vertex 3-uniform hypergraph containing no triangulation of $X$ as a subgraph. We prove that the Tur\'an exponent of any such space $X$ is at most $8/3$, i.e., that $\mathrm{ex}_{\hom}(n,X)\leq Cn^{8/3}$ for some constant $C=C(X)$. This improves on the previous exponent of $3-1/5$, due to Keevash, Long, Narayanan, and Scott. Additionally, we present new streamlined proofs of the asymptotically tight upper bounds for the topological Tur\'an numbers of the torus and real projective plane, which can be used to derive asymptotically tight upper bounds for all surfaces., Comment: 17 pages

Recent results suggest that highly active, chaotic, non-equilibrium states of living fluids might share much in common with high Reynolds number, inertial turbulence. We now show, by using a hydrodynamical model, the onset of intermittency and the consequent multiscaling of Eulerian and Lagrangian structure functions as a function of the bacterial activity. Our results bridge the worlds of low and high Reynolds number flows as well as open up intriguing possibilities of what makes flows intermittent.

We investigate the fractional quantum anomalous Hall (FQAH) effect in rhombohedral multilayer graphene (RnG) in the presence of a strong applied displacement field. We first introduce the interacting model of RnG, which includes the noninteracting continuum model and the many-body Coulomb interaction. We then discuss the integer quantum anomalous Hall (IQAH) effect in RnG and the role of the Hartree-Fock approach in understanding its appearance. Next, we explore the FQAH effect in RnG for $n=3$--$6$ using a combination of constrained Hartree-Fock and exact diagonalization methods. We characterize the stability of the FQAH phase by the size of the FQAH gap and find that RnG generally has a stable FQAH phase, although the required displacement field varies significantly among different $n$ values. Our work establishes the theoretical universality of both IQAH and FQAH in RnG., Comment: 6 pages, 3 figures. Comments are welcome

The Jovian atmosphere contains a wide diversity of vortices, which have a large range of sizes, colors and forms in different dynamical regimes. The formation processes for these vortices is poorly understood, and aside from a few known, long-lived ovals, such as the Great Red Spot, and Oval BA, vortex stability and their temporal evolution are currently largely unknown. In this study, we use JunoCam data and a citizen-science project on Zooniverse to derive a catalog of vortices, some with repeated observations, through May 2018 to Sep 2021, and analyze their associated properties, such as size, location and color. We find that different colored vortices (binned as white, red, brown and dark), follow vastly different distributions in terms of their sizes and where they are found on the planet. We employ a simplified stability criterion using these vortices as a proxy, to derive a minimum Rossby deformation length for the planet of $\sim1800$ km. We find that this value of $L_d$ is largely constant throughout the atmosphere, and does not have an appreciable meridional gradient., Comment: 21 pages, 30 figures, in press at Planetary Science Journal

We construct a $d$-dimensional Eddy Damped Quasi-Normal Markovian (EDQNM) Closure Model to study dynamo action in arbitrary dimensions. In particular, we find lower $d_L$ and upper $d_U$ critical dimensions for sustained dynamo action in this incompressible problem. Our model is adaptable for future studies incorporating helicity, compressible effects and a wide range of magnetic Reynolds and Prandtl numbers., Comment: 15 pages, 5 figures

This article introduces operator on operator regression in quantum probability. Here in the regression model, the response and the independent variables are certain operator valued observables, and they are linearly associated with unknown scalar coefficient (denoted by $\beta$), and the error is a random operator. In the course of this study, we propose a quantum version of a class of estimators (denoted by $M$ estimator) of $\beta$, and the large sample behaviour of those quantum version of the estimators are derived, given the fact that the true model is also linear and the samples are observed eigenvalue pairs of the operator valued observables.

In this paper, we discuss the Hyers-Ulam stability of mixed-type additive-cubic Jensen functional equation \begin{align*} 2\mathcal{F}\left(\frac{2u+v}{2}\right)+2\mathcal{F}\left(\frac{2u-v}{2}\right)=\frac{1}{4}[\mathcal{F}(u+v)+\mathcal{F}(u-v)]+3\mathcal{F}(u) \end{align*} in non-Archimedean $(n, \beta)$ normed spaces., Comment: 8 pages

In this article, we study whether the slope functions of two functional regression models in two samples are associated with any arbitrary transformation (barring constant and linear transformation) or not along the vertical axis. In order to address this issue, a statistical testing of the hypothesis problem is formalized, and the test statistic is formed based on the estimated second derivative of the unknown transformation. The asymptotic properties of the test statistics are investigated using some advanced techniques related to the empirical process. Moreover, to implement the test for small sample size data, a Bootstrap algorithm is proposed, and it is shown that the Bootstrap version of the test is as good as the original test for sufficiently large sample size. Furthermore, the utility of the proposed methodology is shown for simulated data sets, and DTI data is analyzed using this methodology., Comment: Some typos have been fixed

Coronal mass ejections (CMEs) are powerful drivers of space weather, with magnetic flux ropes (MFRs) widely regarded as their primary precursors. However, the variation in reconnection flux during the evolution of MFR during CME eruptions remains poorly understood. In this paper, we develop a realistic 3D magneto-hydrodynamic model using which we explore the temporal evolution of reconnection flux during the MFR evolution using both numerical simulations and observational data. Our initial coronal configuration features an isothermal atmosphere and a potential arcade magnetic field beneath which an MFR emerges at the lower boundary. As the MFR rises, we observe significant stretching and compression of the overlying magnetic field beneath it. Magnetic reconnection begins with the gradual formation of a current sheet, eventually culminating with the impulsive expulsion of the flux rope. We analyze the temporal evolution of reconnection fluxes during two successive MFR eruptions while continuously emerging the twisted flux rope through the lower boundary. We also conduct a similar analysis using observational data from the Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) for an eruptive event. Comparing our MHD simulation with observational data, we find that reconnection flux play a crucial role in determination of CME speeds. From the onset to the eruption, the reconnection flux shows a strong linear correlation with the velocity. This nearly realistic simulation of a solar eruption provides important insights into the complex dynamics of CME initiation and progression., Comment: 14 pages, 13 figures, Submitted to ApJ

The Kitaev chain can be engineered within a quantum dot-superconductor array, hosting Majorana zero modes at fine-tuned sweet spots. In this work, we propose and simulate the occurrence of Rabi and Ramsey oscillations to feasibly construct a minimal Majorana qubit in the quantum dot setup. Our real-time results incorporate realistic effects, e.g., charge noise and leakage, reflecting the latest experimental progress. We demonstrate that Majorana qubits with larger energy gaps exhibit significantly enhanced performance -- longer dephasing times, higher quality factors, reduced leakage probabilities, and improved visibilities -- compared to those with smaller gaps and with conventional quantum dot-based charge qubits. We introduce a method for reading out Majorana qubits via quantum capacitance measurements. Our work paves the way for future experiments on realizing Majorana qubits in quantum dot-superconductor arrays., Comment: 7 Pages, 4 figures

We release Rasa, the first multilingual expressive TTS dataset for any Indian language, which contains 10 hours of neutral speech and 1-3 hours of expressive speech for each of the 6 Ekman emotions covering 3 languages: Assamese, Bengali, & Tamil. Our ablation studies reveal that just 1 hour of neutral and 30 minutes of expressive data can yield a Fair system as indicated by MUSHRA scores. Increasing neutral data to 10 hours, with minimal expressive data, significantly enhances expressiveness. This offers a practical recipe for resource-constrained languages, prioritizing easily obtainable neutral data alongside smaller amounts of expressive data. We show the importance of syllabically balanced data and pooling emotions to enhance expressiveness. We also highlight challenges in generating specific emotions, e.g., fear and surprise., Comment: Accepted at INTERSPEECH 2024. First two authors listed contributed equally

Foundational Models (FMs) are gaining increasing attention in the biomedical AI ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders, especially those involved in or affected by these clinical and translational applications are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem., Comment: 3 figures, 3 tables

Publicly available TTS datasets for low-resource languages like Hindi and Tamil typically contain 10-20 hours of data, leading to poor vocabulary coverage. This limitation becomes evident in downstream applications where domain-specific vocabulary coupled with frequent code-mixing with English, results in many OOV words. To highlight this problem, we create a benchmark containing OOV words from several real-world applications. Indeed, state-of-the-art Hindi and Tamil TTS systems perform poorly on this OOV benchmark, as indicated by intelligibility tests. To improve the model's OOV performance, we propose a low-effort and economically viable strategy to obtain more training data. Specifically, we propose using volunteers as opposed to high quality voice artists to record words containing character bigrams unseen in the training data. We show that using such inexpensive data, the model's performance improves on OOV words, while not affecting voice quality and in-domain performance., Comment: Accepted at INTERSPEECH 2024

The vast amount of biomedical information available today presents a significant challenge for investigators seeking to digest, process, and understand these findings effectively. Large Language Models (LLMs) have emerged as powerful tools to navigate this complex and challenging data landscape. However, LLMs may lead to hallucinatory responses, making Retrieval Augmented Generation (RAG) crucial for achieving accurate information. In this protocol, we present RUGGED (Retrieval Under Graph-Guided Explainable disease Distinction), a comprehensive workflow designed to support investigators with knowledge integration and hypothesis generation, identifying validated paths forward. Relevant biomedical information from publications and knowledge bases are reviewed, integrated, and extracted via text-mining association analysis and explainable graph prediction models on disease nodes, forecasting potential links among drugs and diseases. These analyses, along with biomedical texts, are integrated into a framework that facilitates user-directed mechanism elucidation as well as hypothesis exploration through RAG-enabled LLMs. A clinical use-case demonstrates RUGGED's ability to evaluate and recommend therapeutics for Arrhythmogenic Cardiomyopathy (ACM) and Dilated Cardiomyopathy (DCM), analyzing prescribed drugs for molecular interactions and unexplored uses. The platform minimizes LLM hallucinations, offers actionable insights, and improves the investigation of novel therapeutics.