Showing 1–46 of 46 results for author: Gayen, S

Quasi-Two-Dimensional Quantum Antiferromagnetism in the Distorted Honeycomb Compound KCuIn(PO4)2

Authors: S. Gayen, S. S. Ali, V. K. Singh, B. Koteswararao, S. K. Panda

Abstract: We investigate the electronic structure and magnetic properties of the distorted honeycomb lattice compound KCuInP2O8 through a combination of experimental measurements, first principles calculations and quantum monte carlo simulations. Density functional theory calculations within the GGA+U framework establishes KCuInP2O8 as an indirect gap insulator with Cu2+ local moments and finite magnetocrys… ▽ More We investigate the electronic structure and magnetic properties of the distorted honeycomb lattice compound KCuInP2O8 through a combination of experimental measurements, first principles calculations and quantum monte carlo simulations. Density functional theory calculations within the GGA+U framework establishes KCuInP2O8 as an indirect gap insulator with Cu2+ local moments and finite magnetocrystalline anisotropy arising from spin orbit coupling. A microscopic evaluation of magnetic exchange interactions using the magnetic force theorem reveals a pronounced hierarchy of couplings, with the next nearest neighbor interaction dominating over the nearest neighbor exchange, while interlayer couplings remain negligible. This exchange hierarchy naturally maps the system onto weakly coupled antiferromagnetic spin chains embedded in a distorted honeycomb lattice. Motivated by the ab initio estimated exchange interactions, we construct an effective spin half Hamiltonian and investigate its magnetic response using large scale quantum Monte Carlo simulations. The calculated temperature dependent susceptibility and field dependent magnetization quantitatively reproduce the experimental behavior and capture key signatures of low dimensional quantum magnetism, including a broad susceptibility maximum and a field induced saturation at low temperatures. Our results establish KCuInP2O8 as a quasi-two-dimensional quantum antiferromagnet composed of coupled spin chains, providing a consistent theoretical framework that links electronic structure, exchange interactions, and collective magnetic behavior. △ Less

Submitted 23 July, 2026; originally announced July 2026.

Comments: Published in Physica Status Solidi (RRL) - Rapid Research Letters

Journal ref: Physica Status Solidi (RRL) 20, e202600001 (2026)

Dirac topology, anomalous Hall response, and giant magnetoresistance in carrier-compensated altermagnetic semimetal NiS

Authors: Shovan Gayen, Sk. Soyeb Ali, S K Panda

Abstract: We combine first-principles density-functional theory, Berry-curvature analysis, semiclassical Boltzmann transport, and atomistic spin dynamics to establish hexagonal NiS as a compensated 3d altermagnetic semimetal in which topology, magnetism, and lattice dynamics are intrinsically intertwined. The rotational coset symmetry of the NiAs lattice produces momentum-dependent spin splitting characteri… ▽ More We combine first-principles density-functional theory, Berry-curvature analysis, semiclassical Boltzmann transport, and atomistic spin dynamics to establish hexagonal NiS as a compensated 3d altermagnetic semimetal in which topology, magnetism, and lattice dynamics are intrinsically intertwined. The rotational coset symmetry of the NiAs lattice produces momentum-dependent spin splitting characteristic of altermagnetism. With spin-orbit coupling, gapped Dirac-like crossings generate intense Berry-curvature hot spots and nearly compensated electron-hole pockets. This leads to a large and anisotropic intrinsic spin Hall conductivity comparable to that of several 4d, 5d metals, a symmetry-allowed anomalous Hall response despite zero net magnetization, and nonsaturating magnetoresistance exceeding 10000 percent. On the magnetic side, first-principles determination of the exchange tensor reveals dominant long-range superexchange and sizable anisotropic interactions, quantitatively reproducing the experimental Neel temperature. Our results identify NiS as a model 3d platform in which carrier compensation, altermagnetic symmetry, Berry-curvature driven transport, and lattice-sensitive magnetism coexist within a single symmetry framework, offering a design principle for multi-functional quantum responses in correlated transition-metal compounds. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Comments: Accepted in Phys. Rev. B Letter

IteRate: Autonomous AI Synthesis of In-Kernel eBPF Wi-Fi Rate Control Algorithms

Authors: James Lynch, Ziqian Liu, Snehadeep Gayen, Om Chabra, Hari Balakrishnan

Abstract: Wi-Fi rate adaptation remains a persistent challenge in wireless networking. Deployed algorithms like Minstrel-HT have remained largely stagnant for over a decade, relying on hand-tuned heuristics that fail to generalize to the complexity of modern wireless environments. We present \name, an autonomous research system that closes the loop on rate control development. IteRate uses a multi-agent AI… ▽ More Wi-Fi rate adaptation remains a persistent challenge in wireless networking. Deployed algorithms like Minstrel-HT have remained largely stagnant for over a decade, relying on hand-tuned heuristics that fail to generalize to the complexity of modern wireless environments. We present \name, an autonomous research system that closes the loop on rate control development. IteRate uses a multi-agent AI architecture to conduct the full scientific cycle: formulating hypotheses, writing eBPF programs that run inside the Linux kernel, deploying them over-the-air to Wi-Fi devices, collecting fine-grained telemetry for analysis, and iterating based on experimental evidence, all without human intervention. IteRate makes three contributions. (1) a novel kernel module that exposes per-frame hardware telemetry including modulation and coding schemes (MCS) and retry counts to eBPF programs, (2) a structured agentic AI architecture employing specialized agents for algorithm design, experiment execution, and data analysis, coordinated via a hypothesis-driven research protocol with persistent knowledge, and (3) a closed-loop pipeline that automates the cross-compilation, deployment, and evaluation of in-kernel logic onto embedded Wi-Fi targets. On a 58-node testbed running five workloads. relative to the well-known Minstrel algorithm, IteRate achieves 21% faster web-page loads, 7% higher video quality of experience (QoE), and 21% higher peak throughput. Our work demonstrates that AI agents, when equipped with appropriate kernel-level hooks and a disciplined scientific workflow, can effectively automate the research required to design Wi-Fi rate controllers. △ Less

Submitted 4 May, 2026; originally announced May 2026.

Calibration requirements for Epoch of Reionization 21-cm signal observations -- IV. Bias and variance with time and frequency correlated residual gains

Authors: Saikat Gayen, Jais Kumar, Prasun Dutta, Khandakar Md Asif Elahi, Samir Choudhuri, Nirupam Roy

Abstract: Observation of multifrequency angular power spectrum of the redshifted 21-cm brightness temperature fluctuation from the neutral hydrogen holds the key to understand the structure formation and its evolution during the reionization and post-reionization era. A major challenge in observing the neutral hydrogen arises from presence of strong foreground signals in the frequency range of interest. Mit… ▽ More Observation of multifrequency angular power spectrum of the redshifted 21-cm brightness temperature fluctuation from the neutral hydrogen holds the key to understand the structure formation and its evolution during the reionization and post-reionization era. A major challenge in observing the neutral hydrogen arises from presence of strong foreground signals in the frequency range of interest. Mitigating the direct effect of foregrounds are being addressed through various techniques in literature. An additional second order effect arises, in presence of foreground, with limited accuracy in time and frequency dependent gain calibrations. This manifests as the residual gain and bandpass error in the observed data, introduces bias and increases uncertainty in the estimates of multifrequency angular power spectrum. In this work, we present an analytic method to estimate the bias and excess uncertainty in the estimates of multifrequency angular power spectrum in presence of residual gain and bandpass errors. We use this framework to estimate the effect of these errors for detection of redshifted 21-cm emission from a redshift of $\sim 8$ with the upcoming SKA1-Low. Due to the high baseline density at the required range of angular multipoles, the SKA1-Low is found to be a tuned instrument for the redshifted 21-cm signal detection. We find that, there are scenario with residual gain and bandpass errors where there can be significant bias in these estimates. Certain foreground mitigation strategies, is expected to reduce a part of the bias. The detailed study of different aspects of gain and bandpass errors and their relative effects are discussed. We find, with assumed models of gain and bandpass errors, signal detection is possible at this redshift with $128$ hours of observations. However, to achieve this one needs to have better calibration accuracy than present day interferometers. △ Less

Submitted 27 May, 2025; v1 submitted 31 March, 2025; originally announced March 2025.

Comments: 29 pages, 8 figures, 1 table, Accepted for publication in JCAP on 20 May 2025

Algorithms and Hardness for Estimating Statistical Similarity

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Abstract: We introduce and study the computational problem of determining statistical similarity between probability distributions. For distributions $P$ and $Q$ over a finite sample space, their statistical similarity is defined as $S_{\mathrm{stat}}(P, Q) := \sum_x \min(P(x), Q(x))$. Despite its fundamental nature as a measure of similarity between distributions, capturing essential concepts such as Bayes… ▽ More We introduce and study the computational problem of determining statistical similarity between probability distributions. For distributions $P$ and $Q$ over a finite sample space, their statistical similarity is defined as $S_{\mathrm{stat}}(P, Q) := \sum_x \min(P(x), Q(x))$. Despite its fundamental nature as a measure of similarity between distributions, capturing essential concepts such as Bayes error in prediction and hypothesis testing, this computational problem has not been previously explored. Recent work on computing statistical distance has established that, somewhat surprisingly, even for the simple class of product distributions, exactly computing statistical similarity is $\#\mathsf{P}$-hard. This motivates the question of designing approximation algorithms for statistical similarity. Our first contribution is a Fully Polynomial-Time deterministic Approximation Scheme (FPTAS) for estimating statistical similarity between two product distributions. Furthermore, we also establish a complementary hardness result. In particular, we show that it is $\mathsf{NP}$-hard to estimate statistical similarity when $P$ and $Q$ are Bayes net distributions of in-degree $2$. △ Less

Submitted 1 June, 2025; v1 submitted 14 February, 2025; originally announced February 2025.

Comments: 14 pages

Computational Explorations of Total Variation Distance

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Abstract: We investigate some previously unexplored (or underexplored) computational aspects of total variation (TV) distance. First, we give a simple deterministic polynomial-time algorithm for checking equivalence between mixtures of product distributions, over arbitrary alphabets. This corresponds to a special case, whereby the TV distance between the two distributions is zero. Second, we prove that unle… ▽ More We investigate some previously unexplored (or underexplored) computational aspects of total variation (TV) distance. First, we give a simple deterministic polynomial-time algorithm for checking equivalence between mixtures of product distributions, over arbitrary alphabets. This corresponds to a special case, whereby the TV distance between the two distributions is zero. Second, we prove that unless $\mathsf{NP} \subseteq \mathsf{RP}$, it is impossible to efficiently estimate the TV distance between arbitrary Ising models, even in a bounded-error randomized setting. △ Less

Submitted 13 December, 2024; originally announced December 2024.

Comments: 17 pages

Efficient Sample-optimal Learning of Gaussian Tree Models via Sample-optimal Testing of Gaussian Mutual Information

Authors: Sutanu Gayen, Sanket Kale, Sayantan Sen

Abstract: Learning high-dimensional distributions is a significant challenge in machine learning and statistics. Classical research has mostly concentrated on asymptotic analysis of such data under suitable assumptions. While existing works [Bhattacharyya et al.: SICOMP 2023, Daskalakis et al.: STOC 2021, Choo et al.: ALT 2024] focus on discrete distributions, the current work addresses the tree structure l… ▽ More Learning high-dimensional distributions is a significant challenge in machine learning and statistics. Classical research has mostly concentrated on asymptotic analysis of such data under suitable assumptions. While existing works [Bhattacharyya et al.: SICOMP 2023, Daskalakis et al.: STOC 2021, Choo et al.: ALT 2024] focus on discrete distributions, the current work addresses the tree structure learning problem for Gaussian distributions, providing efficient algorithms with solid theoretical guarantees. This is crucial as real-world distributions are often continuous and differ from the discrete scenarios studied in prior works. In this work, we design a conditional mutual information tester for Gaussian random variables that can test whether two Gaussian random variables are independent, or their conditional mutual information is at least $\varepsilon$, for some parameter $\varepsilon \in (0,1)$ using $\mathcal{O}(\varepsilon^{-1})$ samples which we show to be near-optimal. In contrast, an additive estimation would require $Ω(\varepsilon^{-2})$ samples. Our upper bound technique uses linear regression on a pair of suitably transformed random variables. Importantly, we show that the chain rule of conditional mutual information continues to hold for the estimated (conditional) mutual information. As an application of such a mutual information tester, we give an efficient $\varepsilon$-approximate structure-learning algorithm for an $n$-variate Gaussian tree model that takes $\widetildeΘ(n\varepsilon^{-1})$ samples which we again show to be near-optimal. In contrast, when the underlying Gaussian model is not known to be tree-structured, we show that $\widetilde{Θ}(n^2\varepsilon^{-2})$ samples are necessary and sufficient to output an $\varepsilon$-approximate tree structure. We perform extensive experiments that corroborate our theoretical convergence bounds. △ Less

Submitted 18 November, 2024; originally announced November 2024.

Comments: 47 pages, 16 figures, abstract shortened as per arXiv criteria

Learnability of Parameter-Bounded Bayes Nets

Authors: Arnab Bhattacharyya, Davin Choo, Sutanu Gayen, Dimitrios Myrisiotis

Abstract: Bayes nets are extensively used in practice to efficiently represent joint probability distributions over a set of random variables and capture dependency relations. In a seminal paper, Chickering et al. (JMLR 2004) showed that given a distribution $\mathbb{P}$, that is defined as the marginal distribution of a Bayes net, it is $\mathsf{NP}$-hard to decide whether there is a parameter-bounded Baye… ▽ More Bayes nets are extensively used in practice to efficiently represent joint probability distributions over a set of random variables and capture dependency relations. In a seminal paper, Chickering et al. (JMLR 2004) showed that given a distribution $\mathbb{P}$, that is defined as the marginal distribution of a Bayes net, it is $\mathsf{NP}$-hard to decide whether there is a parameter-bounded Bayes net that represents $\mathbb{P}$. They called this problem LEARN. In this work, we extend the $\mathsf{NP}$-hardness result of LEARN and prove the $\mathsf{NP}$-hardness of a promise search variant of LEARN, whereby the Bayes net in question is guaranteed to exist and one is asked to find such a Bayes net. We complement our hardness result with a positive result about the sample complexity that is sufficient to recover a parameter-bounded Bayes net that is close (in TV distance) to a given distribution $\mathbb{P}$, that is represented by some parameter-bounded Bayes net, generalizing a degree-bounded sample complexity result of Brustle et al. (EC 2020). △ Less

Submitted 4 August, 2024; v1 submitted 30 June, 2024; originally announced July 2024.

Comments: 15 pages, 2 figures

Total Variation Distance for Product Distributions is $\#\mathsf{P}$-Complete

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Abstract: We show that computing the total variation distance between two product distributions is $\#\mathsf{P}$-complete. This is in stark contrast with other distance measures such as Kullback-Leibler, Chi-square, and Hellinger, which tensorize over the marginals leading to efficient algorithms. We show that computing the total variation distance between two product distributions is $\#\mathsf{P}$-complete. This is in stark contrast with other distance measures such as Kullback-Leibler, Chi-square, and Hellinger, which tensorize over the marginals leading to efficient algorithms. △ Less

Submitted 13 May, 2024; originally announced May 2024.

Comments: 5 pages. An extended version of this paper appeared in the proceedings of IJCAI 2023, under the title "On approximating total variation distance" (see https://www.ijcai.org/proceedings/2023/387 and arXiv:2206.07209)

Distribution Learning Meets Graph Structure Sampling

Authors: Arnab Bhattacharyya, Sutanu Gayen, Philips George John, Sayantan Sen, N. V. Vinodchandran

Abstract: This work establishes a novel link between the problem of PAC-learning high-dimensional graphical models and the task of (efficient) counting and sampling of graph structures, using an online learning framework. We observe that if we apply the exponentially weighted average (EWA) or randomized weighted majority (RWM) forecasters on a sequence of samples from a distribution P using the log loss f… ▽ More This work establishes a novel link between the problem of PAC-learning high-dimensional graphical models and the task of (efficient) counting and sampling of graph structures, using an online learning framework. We observe that if we apply the exponentially weighted average (EWA) or randomized weighted majority (RWM) forecasters on a sequence of samples from a distribution P using the log loss function, the average regret incurred by the forecaster's predictions can be used to bound the expected KL divergence between P and the predictions. Known regret bounds for EWA and RWM then yield new sample complexity bounds for learning Bayes nets. Moreover, these algorithms can be made computationally efficient for several interesting classes of Bayes nets. Specifically, we give a new sample-optimal and polynomial time learning algorithm with respect to trees of unknown structure and the first polynomial sample and time algorithm for learning with respect to Bayes nets over a given chordal skeleton. △ Less

Submitted 13 November, 2025; v1 submitted 13 May, 2024; originally announced May 2024.

Comments: Full version (50 pages, 2 figures). Shortened abstract as per arXiv criteria. To be published in NeurIPS 2025

Observing S-Matrix Pole Flow in Resonance Interplay: Cold Collisions of Ultracold Atoms in a Miniature Laser-based Accelerator

Authors: Matthew Chilcott, Samyajit Gayen, James Croft, Ryan Thomas, Niels Kjærgaard

Abstract: We provide an overview of experiments exploring resonances in the collision of ultracold clouds of atoms. Using a laser-based accelerator that capitalizes on the energy resolution provided by the ultracold atomic setting, we unveil resonance phenomena such as Feshbach and shape resonances in their quintessential form by literally photographing the halo of outgoing scattered atoms. We exploit the t… ▽ More We provide an overview of experiments exploring resonances in the collision of ultracold clouds of atoms. Using a laser-based accelerator that capitalizes on the energy resolution provided by the ultracold atomic setting, we unveil resonance phenomena such as Feshbach and shape resonances in their quintessential form by literally photographing the halo of outgoing scattered atoms. We exploit the tunability of magnetic Feshbach resonances to instigate an interplay between scattering resonances. By experimentally recording the scattering in a parameter space spanned by collision energy and magnetic field, we capture the imprint of the $S$-matrix pole flow in the complex energy plane. After revisiting experiments that place a Feshbach resonance in the proximity of a shape resonance and an anti-bound state, respectively, we discuss the possibility of using $S$-matrix pole interplay between two Feshbach resonances to create a bound-state-in-the-continuum. △ Less

Submitted 5 May, 2024; originally announced May 2024.

Comments: European Conference on Few-Body Problems in Physics (EFB25) 2023---Invited Plenary Talk

Journal ref: Few-Body Systems 65, 61 (2024)

Calibration requirement for Epoch of Reionization 21-cm signal observation -- III. Bias and variance in uGMRT ELAIS-N1 field power spectrum

Authors: Saikat Gayen, Rashmi Sagar, Sarvesh Mangla, Prasun Dutta, Nirupam Roy, Arnab Chakraborty, Jais Kumar, Abhirup Datta, Samir Choudhuri

Abstract: Power spectrum of \HI 21-cm radiation is one of the promising probes to study large scale structure of the universe and understand galaxy formation and evolution. The presence of foregrounds, that are orders of magnitude larger in the same frequency range of the redshifted 21-cm signal has been one of the largest observational challenges. The foreground contamination also hinders the calibration p… ▽ More Power spectrum of \HI 21-cm radiation is one of the promising probes to study large scale structure of the universe and understand galaxy formation and evolution. The presence of foregrounds, that are orders of magnitude larger in the same frequency range of the redshifted 21-cm signal has been one of the largest observational challenges. The foreground contamination also hinders the calibration procedures and introduces residual calibration errors in the interferometric data. It has been shown that the calibration errors can introduce bias in the 21-cm power spectrum estimates and introduce additional systematics. In this work, we assess the efficacy of 21-cm power spectrum estimation for the uGMRT Band-3 observations of the ELAIS-N1 field. We first evaluate the statistics of the residual gain errors and perform additional flagging based on these statistics. We then use an analytical method to estimate the bias and variance in the power spectrum. We found that (a) the additional flagging based on calibration accuracy help reduce the bias and systematics in the power spectrum, (b) the majority of the systematics at the lower angular scales, $\ell < 6000$, are due to the residual gain errors, (c) for the uGMRT baseline configuration and system parameters, the variance is always higher than the bias in the power spectrum estimates. Based on our analysis we observe that for an angular multipole of $\ell \sim3000$, $2000$ hours of `on source time' is required with the uGMRT to detect redshifted 21-cm signal at $3-σ$ significance from a redshift of $2.55$. In this work we only consider the power spectrum measurement in the plane of the sky, an assessment of residual gain statistics and its effect on multifrequency angular power spectrum estimation for the uGMRT and the SKA like telescopes will be presented in a companion paper. △ Less

Submitted 27 May, 2025; v1 submitted 28 February, 2024; originally announced February 2024.

Comments: 19 pages, 6 figures

Journal ref: Journal of Cosmology and Astroparticle Physics, Volume 2024, May 2024

Total Variation Distance Meets Probabilistic Inference

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Abstract: In this paper, we establish a novel connection between total variation (TV) distance estimation and probabilistic inference. In particular, we present an efficient, structure-preserving reduction from relative approximation of TV distance to probabilistic inference over directed graphical models. This reduction leads to a fully polynomial randomized approximation scheme (FPRAS) for estimating TV d… ▽ More In this paper, we establish a novel connection between total variation (TV) distance estimation and probabilistic inference. In particular, we present an efficient, structure-preserving reduction from relative approximation of TV distance to probabilistic inference over directed graphical models. This reduction leads to a fully polynomial randomized approximation scheme (FPRAS) for estimating TV distances between same-structure distributions over any class of Bayes nets for which there is an efficient probabilistic inference algorithm. In particular, it leads to an FPRAS for estimating TV distances between distributions that are defined over a common Bayes net of small treewidth. Prior to this work, such approximation schemes only existed for estimating TV distances between product distributions. Our approach employs a new notion of $partial$ couplings of high-dimensional distributions, which might be of independent interest. △ Less

Submitted 1 July, 2024; v1 submitted 16 September, 2023; originally announced September 2023.

Comments: 25 pages. This work has been accepted for presentation at the International Conference on Machine Learning (ICML) 2024

Medical Image Retrieval via Nearest Neighbor Search on Pre-trained Image Features

Authors: Deepak Gupta, Russell Loane, Soumya Gayen, Dina Demner-Fushman

Abstract: Nearest neighbor search (NNS) aims to locate the points in high-dimensional space that is closest to the query point. The brute-force approach for finding the nearest neighbor becomes computationally infeasible when the number of points is large. The NNS has multiple applications in medicine, such as searching large medical imaging databases, disease classification, diagnosis, etc. With a focus on… ▽ More Nearest neighbor search (NNS) aims to locate the points in high-dimensional space that is closest to the query point. The brute-force approach for finding the nearest neighbor becomes computationally infeasible when the number of points is large. The NNS has multiple applications in medicine, such as searching large medical imaging databases, disease classification, diagnosis, etc. With a focus on medical imaging, this paper proposes DenseLinkSearch an effective and efficient algorithm that searches and retrieves the relevant images from heterogeneous sources of medical images. Towards this, given a medical database, the proposed algorithm builds the index that consists of pre-computed links of each point in the database. The search algorithm utilizes the index to efficiently traverse the database in search of the nearest neighbor. We extensively tested the proposed NNS approach and compared the performance with state-of-the-art NNS approaches on benchmark datasets and our created medical image datasets. The proposed approach outperformed the existing approach in terms of retrieving accurate neighbors and retrieval speed. We also explore the role of medical image feature representation in content-based medical image retrieval tasks. We propose a Transformer-based feature representation technique that outperformed the existing pre-trained Transformer approach on CLEF 2011 medical image retrieval task. The source code of our experiments are available at https://github.com/deepaknlp/DLS. △ Less

Submitted 5 October, 2022; originally announced October 2022.

On Approximating Total Variation Distance

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

Abstract: Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain $\{0,1\}^n$. In particular, we establish the following results. 1. The problem of exactly computing the TV distance of two product distributions is $\#\mathsf{P}$-co… ▽ More Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain $\{0,1\}^n$. In particular, we establish the following results. 1. The problem of exactly computing the TV distance of two product distributions is $\#\mathsf{P}$-complete. This is in stark contrast with other distance measures such as KL, Chi-square, and Hellinger which tensorize over the marginals leading to efficient algorithms. 2. There is a fully polynomial-time deterministic approximation scheme (FPTAS) for computing the TV distance of two product distributions $P$ and $Q$ where $Q$ is the uniform distribution. This result is extended to the case where $Q$ has a constant number of distinct marginals. In contrast, we show that when $P$ and $Q$ are Bayes net distributions, the relative approximation of their TV distance is $\mathsf{NP}$-hard. △ Less

Submitted 16 August, 2023; v1 submitted 14 June, 2022; originally announced June 2022.

Comments: 20 pages, 1 figure

Journal ref: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (2023) Main Track. Pages 3479-3487

Superconductivity coexisting with ferromagnetism in a quasi-one dimensional non-centrosymmetric (TaSe$_4$)$_3$I

Authors: Arnab Bera, Sirshendu Gayen, Suchanda Mondal, Riju Pal, Buddhadeb Pal, Aastha Vasdev, Sandeep Howlader, Manish Jana, Tanmay Maiti, Rafikul Ali Saha, Biswajit Das, Biswarup Satpati, Atindra Nath Pal, Prabhat Mandal, Goutam Sheet, Mintu Mondal

Abstract: Low-dimensional materials with broken inversion symmetry and strong spin-orbit coupling can give rise to fascinating quantum phases and phase transitions. Here we report coexistence of superconductivity and ferromagnetism below 2.5\,K in the quasi-one dimensional crystals of non-centrosymmetric (TaSe$_4$)$_3$I (space group: $P\bar{4}2_1c$). The unique phase is a direct consequence of inversion sym… ▽ More Low-dimensional materials with broken inversion symmetry and strong spin-orbit coupling can give rise to fascinating quantum phases and phase transitions. Here we report coexistence of superconductivity and ferromagnetism below 2.5\,K in the quasi-one dimensional crystals of non-centrosymmetric (TaSe$_4$)$_3$I (space group: $P\bar{4}2_1c$). The unique phase is a direct consequence of inversion symmetry breaking as the same material also stabilizes in a centro-symmetric structure (space group: $P4/mnc$) where it behaves like a non-magnetic insulator. The coexistence here upfront contradicts the popular belief that superconductivity and ferromagnetism are two apparently antagonistic phenomena. Notably, here, for the first time, we have clearly detected Meissner effect in the superconducting state despite the coexisting ferromagnetic order. The coexistence of superconductivity and ferromagnetism projects non-centrosymmetric (TaSe$_4$)$_3$I as a host for complex ground states of quantum matter including possible unconventional superconductivity with elusive spin-triplet pairing. △ Less

Submitted 30 November, 2021; v1 submitted 29 November, 2021; originally announced November 2021.

Comments: 16 pages, 4 figures, Supplementary Information included in the anc directory

Efficient inference of interventional distributions

Authors: Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, N. V. Vinodchandran

Abstract: We consider the problem of efficiently inferring interventional distributions in a causal Bayesian network from a finite number of observations. Let $\mathcal{P}$ be a causal model on a set $\mathbf{V}$ of observable variables on a given causal graph $G$. For sets $\mathbf{X},\mathbf{Y}\subseteq \mathbf{V}$, and setting ${\bf x}$ to $\mathbf{X}$, let $P_{\bf x}(\mathbf{Y})$ denote the intervention… ▽ More We consider the problem of efficiently inferring interventional distributions in a causal Bayesian network from a finite number of observations. Let $\mathcal{P}$ be a causal model on a set $\mathbf{V}$ of observable variables on a given causal graph $G$. For sets $\mathbf{X},\mathbf{Y}\subseteq \mathbf{V}$, and setting ${\bf x}$ to $\mathbf{X}$, let $P_{\bf x}(\mathbf{Y})$ denote the interventional distribution on $\mathbf{Y}$ with respect to an intervention ${\bf x}$ to variables ${\bf x}$. Shpitser and Pearl (AAAI 2006), building on the work of Tian and Pearl (AAAI 2001), gave an exact characterization of the class of causal graphs for which the interventional distribution $P_{\bf x}({\mathbf{Y}})$ can be uniquely determined. We give the first efficient version of the Shpitser-Pearl algorithm. In particular, under natural assumptions, we give a polynomial-time algorithm that on input a causal graph $G$ on observable variables $\mathbf{V}$, a setting ${\bf x}$ of a set $\mathbf{X} \subseteq \mathbf{V}$ of bounded size, outputs succinct descriptions of both an evaluator and a generator for a distribution $\hat{P}$ that is $\varepsilon$-close (in total variation distance) to $P_{\bf x}({\mathbf{Y}})$ where $Y=\mathbf{V}\setminus \mathbf{X}$, if $P_{\bf x}(\mathbf{Y})$ is identifiable. We also show that when $\mathbf{Y}$ is an arbitrary set, there is no efficient algorithm that outputs an evaluator of a distribution that is $\varepsilon$-close to $P_{\bf x}({\mathbf{Y}})$ unless all problems that have statistical zero-knowledge proofs, including the Graph Isomorphism problem, have efficient randomized algorithms. △ Less

Submitted 27 July, 2021; v1 submitted 24 July, 2021; originally announced July 2021.

Comments: 16 pages, 2 figures

Learning Sparse Fixed-Structure Gaussian Bayesian Networks

Authors: Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang

Abstract: Gaussian Bayesian networks (a.k.a. linear Gaussian structural equation models) are widely used to model causal interactions among continuous variables. In this work, we study the problem of learning a fixed-structure Gaussian Bayesian network up to a bounded error in total variation distance. We analyze the commonly used node-wise least squares regression (LeastSquares) and prove that it has a nea… ▽ More Gaussian Bayesian networks (a.k.a. linear Gaussian structural equation models) are widely used to model causal interactions among continuous variables. In this work, we study the problem of learning a fixed-structure Gaussian Bayesian network up to a bounded error in total variation distance. We analyze the commonly used node-wise least squares regression (LeastSquares) and prove that it has a near-optimal sample complexity. We also study a couple of new algorithms for the problem: - BatchAvgLeastSquares takes the average of several batches of least squares solutions at each node, so that one can interpolate between the batch size and the number of batches. We show that BatchAvgLeastSquares also has near-optimal sample complexity. - CauchyEst takes the median of solutions to several batches of linear systems at each node. We show that the algorithm specialized to polytrees, CauchyEstTree, has near-optimal sample complexity. Experimentally, we show that for uncontaminated, realizable data, the LeastSquares algorithm performs best, but in the presence of contamination or DAG misspecification, CauchyEst/CauchyEstTree and BatchAvgLeastSquares respectively perform better. △ Less

Submitted 18 October, 2022; v1 submitted 22 July, 2021; originally announced July 2021.

Comments: 30 pages, 11 figures, acknowledgement added

Testing Product Distributions: A Closer Look

Authors: Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran

Abstract: We study the problems of identity and closeness testing of $n$-dimensional product distributions. Prior works by Canonne, Diakonikolas, Kane and Stewart (COLT 2017) and Daskalakis and Pan (COLT 2017) have established tight sample complexity bounds for non-tolerant testing over a binary alphabet: given two product distributions $P$ and $Q$ over a binary alphabet, distinguish between the cases… ▽ More We study the problems of identity and closeness testing of $n$-dimensional product distributions. Prior works by Canonne, Diakonikolas, Kane and Stewart (COLT 2017) and Daskalakis and Pan (COLT 2017) have established tight sample complexity bounds for non-tolerant testing over a binary alphabet: given two product distributions $P$ and $Q$ over a binary alphabet, distinguish between the cases $P = Q$ and $d_{\mathrm{TV}}(P, Q) > ε$. We build on this prior work to give a more comprehensive map of the complexity of testing of product distributions by investigating tolerant testing with respect to several natural distance measures and over an arbitrary alphabet. Our study gives a fine-grained understanding of how the sample complexity of tolerant testing varies with the distance measures for product distributions. In addition, we also extend one of our upper bounds on product distributions to bounded-degree Bayes nets. △ Less

Submitted 26 May, 2021; v1 submitted 29 December, 2020; originally announced December 2020.

Comments: A version appears in ALT 2021

Near-Optimal Learning of Tree-Structured Distributions by Chow-Liu

Authors: Arnab Bhattacharyya, Sutanu Gayen, Eric Price, N. V. Vinodchandran

Abstract: We provide finite sample guarantees for the classical Chow-Liu algorithm (IEEE Trans.~Inform.~Theory, 1968) to learn a tree-structured graphical model of a distribution. For a distribution $P$ on $Σ^n$ and a tree $T$ on $n$ nodes, we say $T$ is an $\varepsilon$-approximate tree for $P$ if there is a $T$-structured distribution $Q$ such that $D(P\;||\;Q)$ is at most $\varepsilon$ more than the best… ▽ More We provide finite sample guarantees for the classical Chow-Liu algorithm (IEEE Trans.~Inform.~Theory, 1968) to learn a tree-structured graphical model of a distribution. For a distribution $P$ on $Σ^n$ and a tree $T$ on $n$ nodes, we say $T$ is an $\varepsilon$-approximate tree for $P$ if there is a $T$-structured distribution $Q$ such that $D(P\;||\;Q)$ is at most $\varepsilon$ more than the best possible tree-structured distribution for $P$. We show that if $P$ itself is tree-structured, then the Chow-Liu algorithm with the plug-in estimator for mutual information with $\widetilde{O}(|Σ|^3 n\varepsilon^{-1})$ i.i.d.~samples outputs an $\varepsilon$-approximate tree for $P$ with constant probability. In contrast, for a general $P$ (which may not be tree-structured), $Ω(n^2\varepsilon^{-2})$ samples are necessary to find an $\varepsilon$-approximate tree. Our upper bound is based on a new conditional independence tester that addresses an open problem posed by Canonne, Diakonikolas, Kane, and Stewart~(STOC, 2018): we prove that for three random variables $X,Y,Z$ each over $Σ$, testing if $I(X; Y \mid Z)$ is $0$ or $\geq \varepsilon$ is possible with $\widetilde{O}(|Σ|^3/\varepsilon)$ samples. Finally, we show that for a specific tree $T$, with $\widetilde{O} (|Σ|^2n\varepsilon^{-1})$ samples from a distribution $P$ over $Σ^n$, one can efficiently learn the closest $T$-structured distribution in KL divergence by applying the add-1 estimator at each node. △ Less

Submitted 22 July, 2021; v1 submitted 8 November, 2020; originally announced November 2020.

Comments: 33 pages, 3 figures

Question-Driven Summarization of Answers to Consumer Health Questions

Authors: Max Savery, Asma Ben Abacha, Soumya Gayen, Dina Demner-Fushman

Abstract: Automatic summarization of natural language is a widely studied area in computer science, one that is broadly applicable to anyone who routinely needs to understand large quantities of information. For example, in the medical domain, recent developments in deep learning approaches to automatic summarization have the potential to make health information more easily accessible to patients and consum… ▽ More Automatic summarization of natural language is a widely studied area in computer science, one that is broadly applicable to anyone who routinely needs to understand large quantities of information. For example, in the medical domain, recent developments in deep learning approaches to automatic summarization have the potential to make health information more easily accessible to patients and consumers. However, to evaluate the quality of automatically generated summaries of health information, gold-standard, human generated summaries are required. Using answers provided by the National Library of Medicine's consumer health question answering system, we present the MEDIQA Answer Summarization dataset, the first summarization collection containing question-driven summaries of answers to consumer health questions. This dataset can be used to evaluate single or multi-document summaries generated by algorithms using extractive or abstractive approaches. In order to benchmark the dataset, we include results of baseline and state-of-the-art deep learning summarization models, demonstrating that this dataset can be used to effectively evaluate question-driven machine-generated summaries and promote further machine learning research in medical question answering. △ Less

Submitted 20 May, 2020; v1 submitted 18 May, 2020; originally announced May 2020.

Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning

Authors: Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, N. V. Vinodchandran

Abstract: We design efficient distance approximation algorithms for several classes of structured high-dimensional distributions. Specifically, we show algorithms for the following problems: - Given sample access to two Bayesian networks $P_1$ and $P_2$ over known directed acyclic graphs $G_1$ and $G_2$ having $n$ nodes and bounded in-degree, approximate $d_{tv}(P_1,P_2)$ to within additive error $ε$ usin… ▽ More We design efficient distance approximation algorithms for several classes of structured high-dimensional distributions. Specifically, we show algorithms for the following problems: - Given sample access to two Bayesian networks $P_1$ and $P_2$ over known directed acyclic graphs $G_1$ and $G_2$ having $n$ nodes and bounded in-degree, approximate $d_{tv}(P_1,P_2)$ to within additive error $ε$ using $poly(n,ε)$ samples and time - Given sample access to two ferromagnetic Ising models $P_1$ and $P_2$ on $n$ variables with bounded width, approximate $d_{tv}(P_1, P_2)$ to within additive error $ε$ using $poly(n,ε)$ samples and time - Given sample access to two $n$-dimensional Gaussians $P_1$ and $P_2$, approximate $d_{tv}(P_1, P_2)$ to within additive error $ε$ using $poly(n,ε)$ samples and time - Given access to observations from two causal models $P$ and $Q$ on $n$ variables that are defined over known causal graphs, approximate $d_{tv}(P_a, Q_a)$ to within additive error $ε$ using $poly(n,ε)$ samples, where $P_a$ and $Q_a$ are the interventional distributions obtained by the intervention $do(A=a)$ on $P$ and $Q$ respectively for a particular variable $A$. Our results are the first efficient distance approximation algorithms for these well-studied problems. They are derived using a simple and general connection to distribution learning algorithms. The distance approximation algorithms imply new efficient algorithms for {\em tolerant} testing of closeness of the above-mentioned structured high-dimensional distributions. △ Less

Submitted 13 February, 2020; v1 submitted 13 February, 2020; originally announced February 2020.

Comments: 24 pages, 1 figure

Learning and Sampling of Atomic Interventions from Observations

Authors: Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, N. V. Vinodchandran

Abstract: We study the problem of efficiently estimating the effect of an intervention on a single variable (atomic interventions) using observational samples in a causal Bayesian network. Our goal is to give algorithms that are efficient in both time and sample complexity in a non-parametric setting. Tian and Pearl (AAAI `02) have exactly characterized the class of causal graphs for which causal effects… ▽ More We study the problem of efficiently estimating the effect of an intervention on a single variable (atomic interventions) using observational samples in a causal Bayesian network. Our goal is to give algorithms that are efficient in both time and sample complexity in a non-parametric setting. Tian and Pearl (AAAI `02) have exactly characterized the class of causal graphs for which causal effects of atomic interventions can be identified from observational data. We make their result quantitative. Suppose P is a causal model on a set $\vec{V}$ of n observable variables with respect to a given causal graph G with observable distribution $P$. Let $P_x$ denote the interventional distribution over the observables with respect to an intervention of a designated variable X with x. Assuming that $G$ has bounded in-degree, bounded c-components ($k$), and that the observational distribution is identifiable and satisfies certain strong positivity condition, we give an algorithm that takes $m=\tilde{O}(nε^{-2})$ samples from $P$ and $O(mn)$ time, and outputs with high probability a description of a distribution $\hat{P}$ such that $d_{\mathrm{TV}}(P_x, \hat{P}) \leq ε$, and: 1. [Evaluation] the description can return in $O(n)$ time the probability $\hat{P}(\vec{v})$ for any assignment $\vec{v}$ to $\vec{V}$ 2. [Generation] the description can return an iid sample from $\hat{P}$ in $O(n)$ time. We also show lower bounds for the sample complexity showing that our sample complexity has an optimal dependence on the parameters $n$ and $ε$, as well as if $k=1$ on the strong positivity parameter. △ Less

Submitted 5 August, 2020; v1 submitted 11 February, 2020; originally announced February 2020.

Comments: 26 pages, 4 figures, a version appeared in ICML 2020

ACM Class: I.2.6

Errors Due to Departure from Independence in Exponential Series System

Authors: Asok K. Nanda, Sanjib Gayen, Shovan Chowdhury

Abstract: In reliability and life testing when the exponentially distributed components are put in series, it is generally assumed that the lifetimes of the components are independently distributed, which leads to some errors if they are not actually independent. In this paper, we study the relative errors incurred in different reliability measures due to such assumptions when actually they follow some biva… ▽ More In reliability and life testing when the exponentially distributed components are put in series, it is generally assumed that the lifetimes of the components are independently distributed, which leads to some errors if they are not actually independent. In this paper, we study the relative errors incurred in different reliability measures due to such assumptions when actually they follow some bivariate exponential distributions. △ Less

Submitted 28 January, 2019; originally announced February 2019.

Suppression of transport spin-polarization of surface states with emergence of ferromagnetism in Mn-doped Bi2Se3

Authors: Suman Kamboj, Shekhar Das, Anshu Sirohi, Rajeswari Roy Chowdhury, Sirshendu Gayen, Vishal K. Maurya, Satyabrata Patnaik, Goutam Sheet

Abstract: The surface states of topological insulators (TI) are protected by time reversal symmetry and they display intrinsic spin helicity where the momentum of the charge carriers decides their spin states. As a consequence, a current injected through the surface states becomes spin polarized and this transport spin-polarization leads to a proportionate suppression of Andreev reflection in superconductor… ▽ More The surface states of topological insulators (TI) are protected by time reversal symmetry and they display intrinsic spin helicity where the momentum of the charge carriers decides their spin states. As a consequence, a current injected through the surface states becomes spin polarized and this transport spin-polarization leads to a proportionate suppression of Andreev reflection in superconductor/TI junctions. Here we show that upon doping Bi2Se3 with Mn, the transport spin-polarization is seen to be monotonically suppressed. The parent compound Bi2Se3 is found to exhibit a transport spin-polarization of about 63% whereas crystals with 10% Mn doping show transport spin-polarization of about 48%. This suppression is accompanied by an increasing ferromagnetic order of the crystals with Mn doping. Scanning tunneling spectroscopy shows that the topological protection of the surface states reduce due to Mn doping. The net measured transport spin-polarization is due to a competition of this effect with the increased magnetization on Mn doping. The present results provide important insights for the choice of magnetic topological insulators for spintronic applications. △ Less

Submitted 18 July, 2018; originally announced July 2018.

Comments: Accepted in Journal of Physics: Condensed Matter, 5 PAGES, 5 FIGURES

Journal ref: Journal of Physics: Condensed Matter 30 355001 (2018)

Mixed type I and type II superconductivity due to intrinsic electronic inhomogeneities in the type II Dirac semimetal PdTe2

Authors: Anshu Sirohi, Shekhar Das, Rajeswari Roy Chowdhuri, Amit, Yogesh Singh, Sirshendu Gayen, Goutam Sheet

Abstract: The type II Dirac semimetal PdTe$_2$ is unique in the family of topological parent materials because it displays a superconducting ground state below 1.7 K. Despite wide speculations on the possibility of an unconventional topological superconducting phase, tunneling and heat capacity measurements revealed that the superconducting phase of PdTe$_2$ follows predictions of the microscopic theory of… ▽ More The type II Dirac semimetal PdTe$_2$ is unique in the family of topological parent materials because it displays a superconducting ground state below 1.7 K. Despite wide speculations on the possibility of an unconventional topological superconducting phase, tunneling and heat capacity measurements revealed that the superconducting phase of PdTe$_2$ follows predictions of the microscopic theory of Bardeen, Cooper and Shriefer (BCS) for conventional superconductors. The superconducting phase in PdTe$_2$ is further interesting because it also displays properties that are characteristics of type-I superconductors and are generally unexpected for binary compounds. Here, from scanning tunneling spectroscopic measurements we show that the surface of PdTe$_2$ displays intrinsic electronic inhomegenities in the normal state which leads to a mixed type I and type II superconducting behaviour along with a spatial distribution of critical fields in the superconducting state. Understanding of the origin of such inhomogeneities may be important for understanding the topological properties of PdTe$_2$ in the normal state. △ Less

Submitted 28 April, 2018; originally announced April 2018.

Comments: 3 Figures

Tip-induced Superconductivity Coexisting with Preserved Topological Properties in Line-nodal Semimetal ZrSiS

Authors: Leena Aggarwal, Chandan K. Singh, Mohammad Aslam, Ratnadwip Singha, Arnab Pariari, Sirshendu Gayen, Mukul Kabir, Prabhat Mandal, Goutam Sheet

Abstract: ZrSiS was recently shown to be a new material with topologically non-trivial band structure which exhibits multiple Dirac nodes and a robust linear band dispersion up to an unusually high energy of 2\,eV. Such a robust linear dispersion makes the topological properties of ZrSiS insensitive to perturbations like carrier doping or lattice distortion. Here we show that a novel superconducting phase w… ▽ More ZrSiS was recently shown to be a new material with topologically non-trivial band structure which exhibits multiple Dirac nodes and a robust linear band dispersion up to an unusually high energy of 2\,eV. Such a robust linear dispersion makes the topological properties of ZrSiS insensitive to perturbations like carrier doping or lattice distortion. Here we show that a novel superconducting phase with a remarkably high $T_c$ of 7.5\,K can be induced in single crystals of ZrSiS by a non-superconducting metallic tip of Ag. From first-principles calculations we show that the observed superconducting phase might originate from dramatic enhancement of density of states due to the presence of a metallic tip on ZrSiS. Our calculations also show that the emerging tip-induced superconducting phase co-exists with the well preserved topological properties of ZrSiS. △ Less

Submitted 22 February, 2018; originally announced February 2018.

Comments: with supplementary materials

Discovery of highly spin-polarized conducting surface states in the strong spin-orbit coupling semiconductor Sb$_2$Se$_3$

Authors: Shekhar Das, Suman Kamboj, Anshu Sirohi, Aastha Vasdev, Sirshendu Gayen, Prasenjit Guptasarma, Goutam Sheet

Abstract: Majority of the A$_2$B$_3$ type chalcogenide systems with strong spin-orbit coupling, like Bi$_2$Se$_3$, Bi$_2$Te$_3$ and Sb$_2$Te$_3$ etc., are topological insulators. One important exception is Sb$_2$Se$_3$, where a topological non-trivial phase was argued to be possible under ambient conditions, but such a phase could be detected to exist only under pressure. In this Letter, we show that like B… ▽ More Majority of the A$_2$B$_3$ type chalcogenide systems with strong spin-orbit coupling, like Bi$_2$Se$_3$, Bi$_2$Te$_3$ and Sb$_2$Te$_3$ etc., are topological insulators. One important exception is Sb$_2$Se$_3$, where a topological non-trivial phase was argued to be possible under ambient conditions, but such a phase could be detected to exist only under pressure. In this Letter, we show that like Bi$_2$Se$_3$, Sb$_2$Se$_3$, displays generation of highly spin-polarized current under mesoscopic superconducting point contacts as measured by point contact Andreev reflection spectroscopy. In addition, we observe a large negative and anisotropic magnetoresistance in Sb$_2$Se$_3$, when the field is rotated in the basal plane. However, unlike in Bi$_2$Se$_3$, in case of Sb$_2$Se$_3$ a prominent quasiparticle interference (QPI) pattern around the defects could be obtained in STM conductance imaging. Thus, our experiments indicate that Sb$_2$Se$_3$ is a regular band insulator under ambient conditions, but due to it's high spin-orbit coupling, non-trivial spin-texture exists on the surface and the system could be on the verge of a topological insulator phase. △ Less

Submitted 3 January, 2018; originally announced January 2018.

Comments: 5 pages, 4 figures, supplemental material not included

Journal ref: Phys. Rev. B 97, 235306 (2018)

Conventional Superconductivity in Type II Dirac Semimetal PdTe$_2$

Authors: Shekhar Das, Amit, Anshu Sirohi, Lalit Yadav, Sirshendu Gayen, Yogesh Singh, Goutam Sheet

Abstract: The transition metal dichalcogenide PdTe$_2$ was recently shown to be a unique system where a type II Dirac semimetallic phase and a superconducting phase co-exist. This observation has led to wide speculation on the possibility of the emergence of an unconventional topological superconducting phase in PdTe$_2$. Here, through direct measurement of the superconducting energy gap by scanning tunneli… ▽ More The transition metal dichalcogenide PdTe$_2$ was recently shown to be a unique system where a type II Dirac semimetallic phase and a superconducting phase co-exist. This observation has led to wide speculation on the possibility of the emergence of an unconventional topological superconducting phase in PdTe$_2$. Here, through direct measurement of the superconducting energy gap by scanning tunneling spectroscopy (STS), and temperature and magnetic field evolution of the same, we show that the superconducting phase in PdTe$_2$ is conventional in nature. The superconducting energy gap is measured to be 326 $μ$eV at 0.38 K and it follows a temperature dependence that is well described within the framework of Bardeen-Cooper-Schriefer's (BCS) theory of conventional superconductivity. This is surprising because our quantum oscillation measurements confirm that at least one of the bands participating in transport has topologically non-trivial character. △ Less

Submitted 12 January, 2018; v1 submitted 11 December, 2017; originally announced December 2017.

Comments: Accepted for publication in Physical Review B

Journal ref: Phys. Rev. B 97, 014523 (2018)

Possible multigap Type-I superconductivity in the layered Boride RuB$_2$

Authors: Jaskaran Singh, Anooja Jayaraj, D. Srivastava, S. Gayen, A. Thamizhavel, Yogesh Singh

Abstract: The structure of the layered transition-metal Borides $A$B$_2$ ($A =$ Os, Ru) is built up by alternating $T$ and B layers with the B layers forming a puckered honeycomb. Here we report superconducting properties of RuB$_2$ with a $T_c \approx 1.5$K using measurements of the magnetic susceptibility versus temperature $T$, magnetization $M$ versus magnetic field $H$, resistivity versus $T$, and heat… ▽ More The structure of the layered transition-metal Borides $A$B$_2$ ($A =$ Os, Ru) is built up by alternating $T$ and B layers with the B layers forming a puckered honeycomb. Here we report superconducting properties of RuB$_2$ with a $T_c \approx 1.5$K using measurements of the magnetic susceptibility versus temperature $T$, magnetization $M$ versus magnetic field $H$, resistivity versus $T$, and heat capacity versus $T$ at various $H$. We observe a reduced heat capacity anomaly at $T_c$ given by $ΔC/γT_c \approx 1.1$ suggesting multi-gap superconductivity. Strong support for this is obtained by the successful fitting of the electronic specific heat data to a two-gap model with gap values $Δ_1/k_BT_c \approx 1.88$ and $Δ_2/k_BT_c \approx 1.13$. Additionally, $M$ versus $H$ measurements reveal a behaviour consistent with Type-I superconductivity. This is confirmed by estimates of the Ginzburg-Landau parameter $κ\approx 0.1$--$0.66$. These results strongly suggest multi-gap Type-I superconductivity in RuB$_2$. We also calculate the band structure and obtain the Fermi surface for RuB$_2$. The Fermi surface consists of one quasi-two-dimensional sheet and two nested ellipsoidal sheets very similar to OsB$_2$. An additional small $4^{\rm th}$ sheet is also found for RuB$_2$. RuB$_2$ could thus be a rare example of a multi-gap Type-I superconductor. △ Less

Submitted 20 September, 2017; originally announced September 2017.

Comments: 8 pages, 8 figures

Journal ref: Phys. Rev. B 97, 054506 (2018)

Giant Enhancement of Superconductivity in Zr Point Contacts

Authors: Mohammad Aslam, Chandan K. Singh, Shekhar Das, Ritesh Kumar, Soumya Datta, Soumyadip Halder, Sirshendu Gayen, Mukul Kabir, Goutam Sheet

Abstract: For certain complex superconducting systems, the superconducting properties get enhanced under mesoscopic point contacts made of elemental non-superconducting metals. However, understanding of the mechanism through which such contact induced local enhancement of superconductivity happens has been limited due to the complex nature of such compounds. In this paper we present giant enhancement of sup… ▽ More For certain complex superconducting systems, the superconducting properties get enhanced under mesoscopic point contacts made of elemental non-superconducting metals. However, understanding of the mechanism through which such contact induced local enhancement of superconductivity happens has been limited due to the complex nature of such compounds. In this paper we present giant enhancement of superconducting transition temperature (T$_c$) and superconducting energy gap ($Δ$) in a simple elemental superconductor Zr. While bulk Zr shows a critical temperature around 0.6\,K, superconductivity survives at Ag/Zr and Pt/Zr point contacts up to 3\,K with a corresponding five-fold enhancement of $Δ$. From first principles calculations we show that the enhancement in superconducting properties can be attributed to a modification in the electron-phonon coupling accompanied by an enhancement of the density of states which involves the appearance of a new electron band at the Ag/Zr interfaces. △ Less

Submitted 14 September, 2017; originally announced September 2017.

Comments: 5 pages, 5 figures

Journal ref: J. Phys.: Condens. Matter 30 255002 2018

Enhanced zero-bias conductance peak and splitting at mesoscopic interfaces between an $s$-wave superconductor and a 3D Dirac semimetal

Authors: Leena Aggarwal, Sirshendu Gayen, Shekhar Das, Gohil S. Thakur, Ashok K. Ganguli, Goutam Sheet

Abstract: Mesoscopic point contacts between elemental metals and the topological 3D Dirac semimetal Cd$_3$As$_2$ have been recently shown to be superconducting with unconventional pairing while Cd$_3$As$_2$ itself does not superconduct. Here we show that the same superconducting phase at mesoscopic interfaces on Cd$_3$As$_2$ can be induced with a known conventional superconductor Nb where a pronounced zero-… ▽ More Mesoscopic point contacts between elemental metals and the topological 3D Dirac semimetal Cd$_3$As$_2$ have been recently shown to be superconducting with unconventional pairing while Cd$_3$As$_2$ itself does not superconduct. Here we show that the same superconducting phase at mesoscopic interfaces on Cd$_3$As$_2$ can be induced with a known conventional superconductor Nb where a pronounced zero-bias conductance peak is observed which undergoes splitting in energy under certain conditions. The observations are consistent with the theory of the emergence of Andreev bound states (ABS) due to the presence of a pair potential with broken time reversal symmetry. The data also indicate the possibility of Majorana bound states as expected at the interfaces between $s$-wave superconductors and topologically non-trivial materials with high degree of spin-orbit coupling. △ Less

Submitted 29 December, 2016; originally announced December 2016.

Comments: 10 pages, 3figures

Journal ref: Appl. Phys. Lett. 109, 252602 (2016)

Mesoscopic superconductivity and high spin polarization coexisting at metallic point contacts on the Weyl semimetal TaAs

Authors: Leena Aggarwal, Sirshendu Gayen, Shekhar Das, Ritesh Kumar, Vicky Süß, Chandra Shekhar, Claudia Felser, Goutam Sheet

Abstract: A Weyl semimetal is a topologically non-trivial phase of matter that hosts mass-less Weyl fermions, the particles that remained elusive for more than 80 years since their theoretical discovery. The Weyl semimetals exhibit unique transport and magneto-transport properties and remarkably high surface spin polarization. Here we show that a unique mesoscopic superconducting phase with a critical tempe… ▽ More A Weyl semimetal is a topologically non-trivial phase of matter that hosts mass-less Weyl fermions, the particles that remained elusive for more than 80 years since their theoretical discovery. The Weyl semimetals exhibit unique transport and magneto-transport properties and remarkably high surface spin polarization. Here we show that a unique mesoscopic superconducting phase with a critical temperature up to 7 K can be realized by forming metallic point contacts with silver (Ag) on single crystals of TaAs, while neither Ag nor TaAs are superconductors. The Andreev reflection spectra obtained from such point contacts are fitted well within a modified Blonder-Tinkham-Klapwijk (BTK) model with a superconducting energy gap up to 1.2 meV. The analysis within this model also reveals high transport spin polarization up to 60\% indicating a spin polarized supercurrent flowing through the point contacts on TaAs. Such point contacts also show a large anisotropic magnetoresistance (AMR) originating from the spin polarized current. Therefore, apart from the discovery of a novel mesoscopic superconducting phase and it's coexistence with a large spin polarization, our results also show that the point contacts on Weyl semimetals are potentially important for applications in spintronics. △ Less

Submitted 18 July, 2016; originally announced July 2016.

Comments: Contains supplemental materials at the end

Journal ref: Nature Communications 8, 13974 (2017)

Unexpected superconductivity at nanoscale junctions made on the topological crystalline insulator Pb$_{0.6}$Sn$_{0.4}$Te

Authors: Shekhar Das, Leena Aggarwal, Subhajit Roychowdhury, Mohammad Aslam, Sirshendu Gayen, Kanishka Biswas, Goutam Sheet

Abstract: Discovery of exotic phases of matter from the topologically non-trivial systems not only makes the research on topological materials more interesting but also enriches our understanding of the fascinating physics of such materials. Pb$_{0.6}$Sn$_{0.4}$Te was recently shown to be a topological crystalline insulator. Here we show that by forming a mesoscopic point-contact using a normal non-supercon… ▽ More Discovery of exotic phases of matter from the topologically non-trivial systems not only makes the research on topological materials more interesting but also enriches our understanding of the fascinating physics of such materials. Pb$_{0.6}$Sn$_{0.4}$Te was recently shown to be a topological crystalline insulator. Here we show that by forming a mesoscopic point-contact using a normal non-superconducting elemental metal on the surface of Pb$_{0.6}$Sn$_{0.4}$Te a novel superconducting phase is created locally in a confined region under the point-contact. This happens while the bulk of the sample remains to be non-superconducting and the superconducting phase emerges as a nano-droplet under the point-contact. The superconducting phase shows a high transition temperature $T_c$ that varies for different point-contacts and falls in a range between 3.7 K and 6.5 K. Therefore, this Letter presents the discovery of a new superconducting phase on the surface of a topological crystalline insulator and the discovery is expected to shed light on the mechanism of induced superconductivity in topologically non-trivial systems in general. △ Less

Submitted 6 July, 2016; originally announced July 2016.

Comments: The submission contains 22 pages including supplementary material. The main text contains 3 figures, 36 references and supplementary material contains 11 figures and one table

Report number: 132601

Journal ref: Applied Physics Letters 109, 132601 (2016)

Comment on "Tip induced unconventional superconductivity on Weyl semimetal TaAs" [arXiv:1607.00513]

Authors: Sirshendu Gayen, Leena Aggarwal, Goutam Sheet

Abstract: Recently, Wang $et$ $al.$ have reported the observation of "unconventional superconductivity" in the Weyl semimetal TaAs [arXiv:1607.00513]. The authors have written "\textit{A conductance plateau and sharp double dips are observed in the point contact spectra, indicating p-wave like unconventional superconductivity. Furthermore, the zero bias conductance peak in low temperature regime is detected… ▽ More Recently, Wang $et$ $al.$ have reported the observation of "unconventional superconductivity" in the Weyl semimetal TaAs [arXiv:1607.00513]. The authors have written "\textit{A conductance plateau and sharp double dips are observed in the point contact spectra, indicating p-wave like unconventional superconductivity. Furthermore, the zero bias conductance peak in low temperature regime is detected, suggesting potentially the existence of Majorana zero modes. The experimentally observed tunneling spectra can be interpreted with a novel mirror-symmetry protected topological superconductor induced in TaAs, which can exhibit zero bias and double finite bias peaks, and double conductance dips in the measurements}." In this comment we show that for a superconducting point contact, the features like a zero-bias conductance peak, a plateau and single or multiple conductance dips might arise due to simple contact-heating related effects. Such features are routinely observed in point contacts involving a wide variety of superconductors when the experiments are not performed in the right regime of mesoscopic transport. We also show that the data presented by Wang $et$ $al.$ in a single transport regime of point contact do not confirm tip induced superconductivity (TISC). Even if it is assumed that Wang $et$ $al.$ achieved TISC on TaAs, all the spectra that they have reported show striking similarities with the type of spectra expected in thermal regime of transport. Such data cannot be used for extracting any spectroscopic information and based on such data any discussion on "p-wave" superconductivity or the emergence of Majorana modes should be considered invalid. This version (v2) also includes a brief discussion on the response of Wang $et$ $al.$ to the first version (v1) of this comment. Correct ballistic regime data on TaAs point contacts can be found in arXiv:1607.05131 (2016). △ Less

Submitted 22 July, 2016; v1 submitted 5 July, 2016; originally announced July 2016.

Comments: v2 corrected a claim of simultaneity in arXiv and v3 gives reference to a paper showing correct ballistic regime data on TaAs

Anisotropic superconductivity in La(O,F)BiSeS crystals revealed by field-angle dependent Andreev reflection spectroscopy

Authors: Mohammad Aslam, Sirshendu Gayen, Avtar Singh, Masashi Tanaka, Takuma Yamaki, Yoshihiko Takano, Goutam Sheet

Abstract: From field-angle dependent Andreev reflection spectroscopy on single crystals of La(O,F)BiSeS, which belongs to the recently discovered BiCh 2 (Ch = S, Se) based layered superconductors, we found that the superconductivity in La(O,F)BiSeS is highly anisotropic. We measured a superconducting energy gap of 0.61 meV for current injected along c-axis at 1.5 K. Detailed temperature and magnetic field d… ▽ More From field-angle dependent Andreev reflection spectroscopy on single crystals of La(O,F)BiSeS, which belongs to the recently discovered BiCh 2 (Ch = S, Se) based layered superconductors, we found that the superconductivity in La(O,F)BiSeS is highly anisotropic. We measured a superconducting energy gap of 0.61 meV for current injected along c-axis at 1.5 K. Detailed temperature and magnetic field dependent studies of the gap also reveal the presence of unconventional pairing in La(O,F)BiSeS. We show that the observed anisotropic superconducting properties can be attributed to the anisotropy in the superconducting order parameter with a complex symmetry in superconducting La(O,F)BiSeS. △ Less

Submitted 21 April, 2016; originally announced April 2016.

Comments: 4 figures, references included

Evidence of a pseudogap driven by competing orders of multi-band origin in the ferromagnetic superconductor Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$

Authors: Mohammad Aslam, Arpita Paul, Gohil S. Thakur, Sirshendu Gayen, Ritesh Kumar, Avtar Singh, Shekhar Das, Ashok K. Ganguli, Umesh V. Waghmare, Goutam Sheet

Abstract: From temperature and magnetic field dependent point-contact spectroscopy on the ferromagnetic superconductor Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$ (bulk superconducting $T_c$ = 2.5 K) we observe (a) a pseudogap in the normal state that sustains to a remarkably high temperature of 40 K and (b) two-fold enhancement of $T_c$ upto 5 K in the point-contact geometry. In addition, Andreev reflection spectroscopy… ▽ More From temperature and magnetic field dependent point-contact spectroscopy on the ferromagnetic superconductor Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$ (bulk superconducting $T_c$ = 2.5 K) we observe (a) a pseudogap in the normal state that sustains to a remarkably high temperature of 40 K and (b) two-fold enhancement of $T_c$ upto 5 K in the point-contact geometry. In addition, Andreev reflection spectroscopy reveals a superconducting gap of 6 meV for certain point-contacts suggesting that the mean field $T_c$ of this system could be approximately 40 K, the onset temperature of pseudo-gap. Our results suggest that quantum fluctuations originating from other competing orders in Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$ forbid a global phase coherence at high temperatures thereby suppressing $T_c$. Apart from the known ordering to a ferromagnetic state, our first-principles calculations reveal nesting of a multi-band Fermi surface and a significant electron-phonon coupling that could result in charge density wave-like instabilities. △ Less

Submitted 29 March, 2016; originally announced March 2016.

Comments: This is an author-created, un-copyedited version of an article accepted for publication in Journal of Physics: Cond-mat. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it

High spin polarization and the origin of unique ferromagnetic ground state in CuFeSb

Authors: Anshu Sirohi, Chandan K. Singh, Gohil S. Thakur, Preetha Saha, Sirshendu Gayen, Abhishek Gaurav, Shubhra Jyotsna, Zeba Haque, L. C. Gupta, Mukul Kabir, Ashok K. Ganguli, Goutam Sheet

Abstract: CuFeSb is isostructural to the ferro-pnictide and chalcogenide superconductors and it is one of the few materials in the family that are known to stabilize in a ferromagnetic ground state. Majority of the members of this family are either superconductors or antiferromagnets. Therefore, CuFeSb may be used as an ideal source of spin polarized current in spin-transport devices involving pnictide and… ▽ More CuFeSb is isostructural to the ferro-pnictide and chalcogenide superconductors and it is one of the few materials in the family that are known to stabilize in a ferromagnetic ground state. Majority of the members of this family are either superconductors or antiferromagnets. Therefore, CuFeSb may be used as an ideal source of spin polarized current in spin-transport devices involving pnictide and the chalcogenide superconductors. However, for that the Fermi surface of CuFeSb needs to be sufficiently spin polarized. In this paper we report direct measurement of transport spin polarization in CuFeSb by spin-resolved Andreev reflection spectroscopy. From a number of measurements using multiple superconducting tips we found that the intrinsic transport spin polarization in CuFeSb is high ($\sim$ 47\%). In order to understand the unique ground state of CuFeSb and the origin of large spin polarization at the Fermi level, we have evaluated the spin-polarized band structure of CuFeSb through first principles calculations. Apart from supporting the observed 47\% transport spin polarization, such calculations also indicate that the Sb-Fe-Sb angles and the height of Sb from the Fe plane is strikingly different for CuFeSb than the equivalent parameters in other members of the same family thereby explaining the origin of the unique ground state of CuFeSb. △ Less

Submitted 19 April, 2016; v1 submitted 23 July, 2014; originally announced July 2014.

Comments: 6 pages, 4 figures

A versatile simulator for specular reflectivity study of multi-layer thin films

Authors: Sirshendu Gayen

Abstract: A versatile X-ray/neutron reflectivity (specular) simulator using LabVIEW(National Instruments Corp.) for structural study of a multi-layer thin film having any combination, including the repetitions, of nano-scale layers of different materials is presented here (available to download from the link provided at the end of the paper). Inclusion of absorption of individual layers, inter-layer roughne… ▽ More A versatile X-ray/neutron reflectivity (specular) simulator using LabVIEW(National Instruments Corp.) for structural study of a multi-layer thin film having any combination, including the repetitions, of nano-scale layers of different materials is presented here (available to download from the link provided at the end of the paper). Inclusion of absorption of individual layers, inter-layer roughnesses, background counts, beam width, instrumental resolution and footprint effect due to finite size of the sample makes the simulated reflectivity close to practical one. The effect of multiple reflection is compared with simulated curves following the exact dynamical theory and approximated kinematical theory. The applicability of further approximation (Born theory) that the incident angle does not change significantly from one layer to another due to refraction is also considered. Brief discussion about reflection from liquid surface/interface and reflectivity study using polarized neutron are also included as a part of the review. Auto-correlation function in connection with the data inversion technique is discussed with possible artifacts for phase-loss problem. An experimental specular reflectivity data of multi-layer erbium stearate Langmuir-Blodgett (LB) film is considered to estimate the parameters by simulating the reflectivity curve. △ Less

Submitted 26 September, 2013; v1 submitted 27 May, 2013; originally announced May 2013.

Raman spectra of unfilled and filled carbon nanotubes: Theory

Authors: S. Gayen, S. N. Behera, S. M. Bose

Abstract: The Raman spectra of two G-bands and a radial breathing mode (RBM) of unfilled and filled single-wall semiconducting and metallic carbon nanotubes have been investigated theoretically, in the presence of electron-phonon and phonon-phonon interactions. Excitation of low frequency optical plasmons in the metallic nanotube is responsible for the peak known as the Breit-Wigner-Fano (BWF) line shape… ▽ More The Raman spectra of two G-bands and a radial breathing mode (RBM) of unfilled and filled single-wall semiconducting and metallic carbon nanotubes have been investigated theoretically, in the presence of electron-phonon and phonon-phonon interactions. Excitation of low frequency optical plasmons in the metallic nanotube is responsible for the peak known as the Breit-Wigner-Fano (BWF) line shape in the G-band Raman spectra. In a filled nanotube there is an additional peak due to excitation of the phonon of the filling atom or molecule. Positions, shapes and relative strengths of these Raman peaks depend on the phonon frequencies of the nanotube and that of the filling atoms, and strengths and forms of the plasmon-phonon and phonon-phonon interactions. For example, filling atoms with phonon frequency close to the RBM frequency of the nanotube may broaden and lower the RBM Raman peak to such an extent that it may become barely visible. Hybridization between the G-bands and the filling atom phonon is also strong when these two frequencies are close to each other and it has important effects on the G-band and the BWF line shapes. When the phonon frequency of the filling atom is far from the RBM and G-band frequencies, it gives rise to a separate peak with modest effects on the RBM and G-band spectra. Raman spectra of semiconducting unfilled and filled nanotubes have similar behavior as those of metallic nanotubes except that normally they have Lorentzian line shapes and do not show a BWF line shape. However, if a semiconducting nanotube is filled with donor atoms, it is predicted that the BWF type line shape may be observed near the RBM, or the G-band or the filling atom Raman peak. △ Less

Submitted 2 October, 2007; originally announced October 2007.

Comments: To be published in Physical Review B

Electronic properties of ordered and disordered linear clusters of atoms and molecules

Authors: S N Behera, S Gayen, G V Ravi Prasad, S M Bose

Abstract: The electronic properties of one-dimensional clusters of N atoms or molecules have been studied. The model used is similar to the Kronig-Penney model with the potential offered by each ion being approximated by an attractive delta function. The energy eigenvalues, the eigenstates and the density of states are calculated exactly for a linear cluster of N atoms or molecules. The dependence of thes… ▽ More The electronic properties of one-dimensional clusters of N atoms or molecules have been studied. The model used is similar to the Kronig-Penney model with the potential offered by each ion being approximated by an attractive delta function. The energy eigenvalues, the eigenstates and the density of states are calculated exactly for a linear cluster of N atoms or molecules. The dependence of these quantities on the various parameters of the problem show interesting behavior. Effects of random distribution of the positions of the atoms and random distribution of the strengths of the potential have also been studied. The results obtained in this paper can have direct applications for linear chain of atoms produced on metal surfaces or artificially created chain of atoms by using scanning tunneling microscope or in studying molecular conduction of electrons across one-dimensional barriers. △ Less

Submitted 7 August, 2006; originally announced August 2006.

Comments: A shorter version of this paper to be published in Physica B

Time-Resolved Ring Structure of Backscattered Circularly Polarized Beams from Forward Scattering Media

Authors: Kevin G. Phillips, Min Xu, S. K. Gayen, R. R. Alfano

Abstract: The backscattering of circularly polarized light at normal incidence to a half-space of scattering particles is studied using the Electric Field Monte Carlo (EMC) method. The spatial distribution of the backscattered light intensity is examined for both the time-resolved and continuous-wave cases for large particles with anisotropy factor, g, in the range 0.8 to 0.97. For the time-resolved case,… ▽ More The backscattering of circularly polarized light at normal incidence to a half-space of scattering particles is studied using the Electric Field Monte Carlo (EMC) method. The spatial distribution of the backscattered light intensity is examined for both the time-resolved and continuous-wave cases for large particles with anisotropy factor, g, in the range 0.8 to 0.97. For the time-resolved case, the backscattered light with the same helicity as that of the incident beam (co-polarized) is found to form a ring centered on the point of incidence. The ring expands and simultaneously grows weak as time increases. The intensity of backscattered light with helicity opposite to that of the incident beam (cross-polarized) is found to exhibit a ring behavior for g>=0.85, with significant backscattering at the point of incidence. For the continuous-wave case no such ring pattern is observed in backscattered light for either helicity. The present EMC study suggests that the ring behavior can only be observed in the time domain, in contrast to previous studies of light backscattered from forward scattering media based on the scalar time-independent Fokker-Planck approximation to the radiative transfer equation. The time-dependent ring structure of backscattered light may have potential use in subsurface imaging applications. △ Less

Submitted 16 August, 2005; originally announced August 2005.

Comments: 17 pages, 14 figures (warning: lots of color figures), submitted to Optics Express

Report number: 2005-12

Theory of the tangential G-band feature in the Raman spectra of metallic carbon nanotubes

Authors: S. M. Bose, S. Gayen, S. N. Behera

Abstract: The tangential G-band in the Raman spectra of a metallic single-wall carbon nanotube shows two peaks: a higher frequency component having the Lorentzian shape and a lower-frequency component of lower intensity with a Breit-Wigner-Fano (BWF)-type lineshape. This interesting feature has been analyzed on the basis of phonon-plasmon coupling in a nanotube. It is shown that while the gapless semi-aco… ▽ More The tangential G-band in the Raman spectra of a metallic single-wall carbon nanotube shows two peaks: a higher frequency component having the Lorentzian shape and a lower-frequency component of lower intensity with a Breit-Wigner-Fano (BWF)-type lineshape. This interesting feature has been analyzed on the basis of phonon-plasmon coupling in a nanotube. It is shown that while the gapless semi-acoustic plasmon cannot account for the observed spectra as claimed by other investigators, the low-lying optical plasmon corresponding to the tangential motion of the electrons on the nanotube surface can explain the observed features. In particular, this theory can explain occurrence of both the Lorentzian and BWF lineshapes in the G-band Raman spectra of metallic single-wall carbon nanotubes. Furthermore, the theory shows that the BWF peak moves to higher frequency, has a lower intensity and a lower half width at higher diameters of the nanotube. All these features are in agreement with experimental observations. △ Less

Submitted 25 August, 2005; v1 submitted 31 May, 2005; originally announced June 2005.

Comments: To appear in Physical Review B

Journal ref: Phys. Rev. B 72, 153402 (2005)

Single hole doped strongly correlated ladder with a static impurity

Authors: S. Gayen

Abstract: We consider a strongly correlated ladder with diagonal hopping and exchange interactions described by $t-J$ type hamiltonian. We study the dynamics of a single hole in this model in the presence of a static non-magnetic (or magnetic) impurity. In the case of a non-magnetic (NM) impurity we solve the problem analytically both in the triplet (S=1) and singlet (S=0) sectors. In the triplet sector t… ▽ More We consider a strongly correlated ladder with diagonal hopping and exchange interactions described by $t-J$ type hamiltonian. We study the dynamics of a single hole in this model in the presence of a static non-magnetic (or magnetic) impurity. In the case of a non-magnetic (NM) impurity we solve the problem analytically both in the triplet (S=1) and singlet (S=0) sectors. In the triplet sector the hole doesn't form any bound state with the impurity. However, in the singlet sector the hole forms bound states of different symmetries with increasing $J/t$ values. Binding energies of those impurity-hole bound states are compared with the binding energy of a pair of holes in absence of any impurity. In the case of magnetic impurity the analytical eigenvalue equations are solved for a large (50 X 2) lattice. In this case also, with increasing $J/t$ values, impurity-hole bound states of different symmetries are obtained. Binding of the hole with the impurity is favoured for the case of a ferromagnetic (FM) impurity than in the case of antiferromagnetic (AFM) impurity. However binding energy is found to be maximum for the NM impurity. Comparison of binding energies and various impurity-hole correlation functions indicates a pair breaking mechanism by NM impurity. △ Less

Submitted 17 May, 2005; originally announced May 2005.

Comments: 15 Pages, 6 figures

Journal ref: J. Phys. Condens. Matter 17, 3231 (2005)

Plasmon exchange model for superconductivity in Carbon nanotubes

Authors: S. M. Bose, S. Gayen

Abstract: Recent investigations of superconductivity in carbon nanotubes have shown that a single-wall zigzag nanotube can become superconducting at around 15 K. Theoretical studies of superconductivity in nanotubes using the traditional phonon exchange model, however, give a superconducting transition temperature $T_c$ less than 1K. To explain the observed higher critical temperature we explo re the poss… ▽ More Recent investigations of superconductivity in carbon nanotubes have shown that a single-wall zigzag nanotube can become superconducting at around 15 K. Theoretical studies of superconductivity in nanotubes using the traditional phonon exchange model, however, give a superconducting transition temperature $T_c$ less than 1K. To explain the observed higher critical temperature we explo re the possibility of the plasmon exchange mechanism for superconductivity in nanotubes. We first calculate the effective interaction between electrons in a nanotube mediated by plasmon exchange and show that this interaction can become attractive. Using this attractive interaction in the modified Eliashberg theory for strong coupling superconductors, we then calculate the critical temperature $T_c$ in a nanotube. We find that $T_c$ is sensitively dependent on the dielectric constant of the medium, the effective mass of the electrons an d the radius of the nanotube. Our theoretical results can explain the observed $T_c$ in a nanotube. △ Less

Submitted 20 February, 2004; originally announced February 2004.

Comments: 9 Pages, 3 Figures

Exact ground and excited states of a t-J ladder doped with two holes

Authors: Indrani Bose, Saurabh Gayen

Abstract: A two chain ladder model is considered described by the strong coupling $t-t^\prime-J-J^\prime$ Hamiltonian. For the case of two holes moving in a background of antiferromagnetically interacting spins, exact, analytical results are derived for the ground state energy and low-lying excitation spectrum. The ground state is a bound state of two holes with total spin S=0. The charge excitation is ga… ▽ More A two chain ladder model is considered described by the strong coupling $t-t^\prime-J-J^\prime$ Hamiltonian. For the case of two holes moving in a background of antiferromagnetically interacting spins, exact, analytical results are derived for the ground state energy and low-lying excitation spectrum. The ground state is a bound state of two holes with total spin S=0. The charge excitation is gapless and the spin excitation has a gap. The corresponding wavefunctions are also exactly determined. The bound hole pair is found to have symmetry of the d-wave type. In the limit of strong rung coupling, the model maps onto an effective hard core boson model which exhibits dominant superconducting pairing correlations. △ Less

Submitted 1 July, 1999; v1 submitted 9 December, 1998; originally announced December 1998.

Comments: LaTeX, 15 pages, 5 PS figures, accepted in Journal of Physics: Condensed Matter