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Vapor-pressure mismatched materials such as transition metal chalcogenides have emerged as electronic, photonic, and quantum materials with scientific and technological importance. However, epitaxial growth of vapor-pressure mismatched materials are challenging due to differences in the reactivity, sticking coefficient, and surface adatom mobility of the mismatched species constituting the material, especially sulfur containing compounds. Here, we report a novel approach to grow chalcogenides - hybrid pulsed laser deposition - wherein an organosulfur precursor is used as a sulfur source in conjunction with pulsed laser deposition to regulate the stoichiometry of the deposited films. Epitaxial or textured thin films of sulfides with variety of structure and chemistry such as alkaline metal chalcogenides, main group chalcogenides, transition metal chalcogenides and chalcogenide perovskites are demonstrated, and structural characterization reveal improvement in thin film crystallinity, and surface and interface roughness compared to the state-of-the-art. The growth method can be broadened to other vapor-pressure mismatched chalcogenides such as selenides and tellurides. Our work opens up opportunities for broader epitaxial growth of chalcogenides, especially sulfide-based thin film technological applications., Comment: 27 pages

A class of integrable models, such as the one-dimensional transverse-field Ising model, respond nonmonotonically to a periodic drive with respect to the driving parameters and freezes almost absolutely for certain combinations of the latter. In this paper, we go beyond the two-band structure of the Ising-like models studied previously and ask whether such unusual nonmonotonic response and near-absolute freezing occur in integrable systems with a higher number of bands. To this end, we consider a tight-binding model for bilayer graphene subjected to an interlayer potential difference. We find that when the potential is driven periodically, the system responds nonmonotonically to variations in the driving amplitude $V_0$ and frequency $\omega$ and shows near absolute freezing for certain values of $V_0/\omega$. However, the freezing occurs only in the presence of a constant bias in the driving, i.e., when $V= V'+V_0 \cos{\omega t}$. When $V'=0$, the freezing is switched off for all values of $V_0/\omega$. We support our numerical results with analytical calculations based on a rotating wave approximation. We also give a proposal to realize the driven bilayer system via ultracold atoms in an optical lattice, where the driving can be implemented by shaking the lattice., Comment: 12 pages, 6 figures

We used the asymmetric superconducting quantum interference device (SQUID) technique to extract the current phase relation (CPR) of a Josephson junction with a 3D-topological insulator (TI) Bi2Se3 nanobelt as the barrier. The obtained CPR shows deviations from the standard sinusoidal CPR with a pronounced forward skewness. At temperatures below 200 mK, the junction skewness values are above the zero temperature limit for short diffusive junctions. Fitting of the extracted CPR shows that most of the supercurrent is carried by ballistic topological surface states (TSSs), with a small contribution of diffusive channels primarily due to the bulk. These findings are instrumental in engineering devices that can fully exploit the properties of the topologically protected surface states of 3D TIs.

We discuss a cosmological scenario with a stochastic background of gravitational waves sourced by the tensor perturbation due to a hybrid inflationary model with cubic potential. The tensor-to-scalar ratio for the present hybrid inflationary model is obtained as $r \approx 0.0006$. Gravitational wave spectrum of this stochastic background, for large-scale CMB modes, $10^{-4}Mpc^{-1}$ to $1Mpc^{-1}$ is studied. The present-day energy spectrum of gravitational waves $\Omega_0^{gw}(f)$ is sensitively related to the tensor power spectrum and r which is, in turn, dependent on the unknown physics of the early cosmos. This uncertainty is characterized by two parameters: $\hat{n_t}(f)$ logarithmic average over the primordial tensor spectral index and $\hat{w}(f)$ logarithmic average over the effective equation of state parameter. Thus, exact constraints in the $\hat{w}(f)$, $\hat{n_t}(f)$ plane can be obtained by comparing theoretical constraints of our model on r and $\Omega_0^{gw}(f)$. We obtain a limit on $\hat{w}(10^{-15}Hz)$<$0.33$ around the modes probed by CMB scales.

This paper describes our recent effort to use virtual reality to simulate threatening emergency evacuation scenarios in which a robot guides a person to an exit. Our prior work has demonstrated that people will follow a robot's guidance, even when the robot is faulty, during an emergency evacuation. Yet, because physical in-person emergency evacuation experiments are difficult and costly to conduct and because we would like to evaluate many different factors, we are motivated to develop a system that immerses people in the simulation environment to encourage genuine subject reactions. We are working to complete experiments verifying the validity of our approach., Comment: Accepted at AAAI Fall Symposium AI-HRI Workshop

Clustering is a usual unsupervised machine learning technique for grouping the data points into groups based upon similar features. We focus here on unsupervised clustering for contaminated data, i.e in the case where K-medians should be preferred to K-means because of its robustness. More precisely, we concentrate on a common question in clustering: how to chose the number of clusters? The answer proposed here is to consider the choice of the optimal number of clusters as the minimization of a risk function via penalization. In this paper, we obtain a suitable penalty shape for our criterion and derive an associated oracle-type inequality. Finally, the performance of this approach with different types of K-medians algorithms is compared on a simulation study with other popular techniques. All studied algorithms are available in the R package Kmedians on CRAN.

Perovskite chalcogenides have emerged as a new class of semiconductors with tunable band gap in the visible-infrared region. High quality thin films are critical to understand the fundamental properties and realize the potential applications based on these materials. We report growth of quasi-epitaxial thin films of quasi one-dimensional (quasi-1D) hexagonal chalcogenide BaTiS$_3$ by pulsed laser deposition. We identified the optimal growth conditions by varying the growth parameters such as the substrate temperature and H2S partial pressure and examined their effects on the thin film structure. High resolution thin film X-Ray diffraction shows strong texture in the out-of-plane direction, whereas no evidence of in-plane relationship between the film and the substrate is observed. Grazing incidence wide-angle X-ray scattering and scanning transmission electron microscopy studies reveal the presence of weak epitaxial relationships of the film and the substrate, despite a defective interface. Our study opens up a pathway to realize quasi-1D hexagonal chalcogenide thin films and their heterostructures with perovskite chalcogenides., Comment: 25 pages, 6 figures

Accurately simulating the atmospheric turbulence behaviour is always challenging. The well-known FFT based method falls short in correctly predicting both the low and high frequency behaviours. Sub-harmonic compensation aids in low-frequency correction but does not solve the problem for all screen size to outer scale parameter ratios (G/$L_0$). FFT-based simulation gives accurate result only for relatively large screen size to outer scale parameter ratio (G/$L_0$). In this work, we have introduced a Gaussian phase autocorrelation matrix to compensate for any sort of residual errors after applying for a modified subharmonics compensation. With this, we have solved problems such as under sampling at the high-frequency range, unequal sampling/weights for subharmonics addition at low-frequency range and the patch normalization factor. Our approach reduces the maximum error in phase structure-function in the simulation with respect to theoretical prediction to within 1.8\%, G/$L_0$ = 1/1000., Comment: SPIE conference proceedings 2020. arXiv admin note: substantial text overlap with arXiv:2106.01002

The development of the Keck All sky Precision Adaptive optics (KAPA) project was initiated in September 2018 to upgrade the Keck I adaptive optics (AO) system to enable laser tomography adaptive optics (LTAO) with a four laser guide star (LGS) asterism. The project includes the replacement of the existing LMCT laser with a Toptica laser, the implementation of a new real-time controller (RTC) and wavefront sensor optics and camera, and a new daytime calibration and test platform to provide the required infrastructure for laser tomography. The work presented here describes the new daytime calibration infrastructure to test the performance for the KAPA tomographic algorithms. This paper outlines the hardware infrastructure for daytime calibration and performance assessment of tomographic algorithms. This includes the implementation of an asterism simulator having fiber-coupled light sources simulating four Laser Guide Stars (LGS) and two Natural Guide Stars (NGS) at the AO bench focus, as well as the upgrade of the existing TelSim on the AO bench to simulate focal anisoplanatism and wind driven atmospheric turbulence. A phase screen, that can be adjusted in effective altitude, is used to simulate wind speeds up to 10 m/s for a duration of upto 3 s., Comment: 15 pages, 13 figures. Publishd as part of SPIE Astronomical telescopes + Instrumentation 2022 proceedings

Electron-lattice coupling effects in low dimensional materials give rise to charge density wave (CDW) order and phase transitions. These phenomena are critical ingredients for superconductivity and predominantly occur in metallic model systems such as doped cuprates, transition metal dichalcogenides, and more recently, in Kagome lattice materials. However, CDW in semiconducting systems, specifically at the limit of low carrier concentration region, is uncommon. Here, we combine electrical transport, synchrotron X-ray diffraction and optical spectroscopy to discover CDW order in a quasi-one-dimensional (1D), dilute d-band semiconductor, BaTiS3, which suggests the existence of strong electron-phonon coupling. The CDW state further undergoes an unusual transition featuring a sharp increase in carrier mobility. Our work establishes BaTiS3 as a unique platform to study the CDW physics in the dilute filling limit to explore novel electronic phases.

This paper describes current progress on developing an ethical architecture for robots that are designed to follow human ethical decision-making processes. We surveyed both regular adults (folks) and ethics experts (experts) on what they consider to be ethical behavior in two specific scenarios: pill-sorting with an older adult and game playing with a child. A key goal of the surveys is to better understand human ethical decision-making. In the first survey, folk responses were based on the subject's ethical choices ("folk morality"); in the second survey, expert responses were based on the expert's application of different formal ethical frameworks to each scenario. We observed that most of the formal ethical frameworks we included in the survey (Utilitarianism, Kantian Ethics, Ethics of Care and Virtue Ethics) and "folk morality" were conservative toward deception in the high-risk task with an older adult when both the adult and the child had significant performance deficiencies., Comment: in TRAITS Workshop Proceedings (arXiv:2206.08270) held in conjunction with Companion of the 2022 ACM/IEEE International Conference on Human-Robot Interaction, March 2022, Pages 1284-1286

We introduce a novel evolutionary method that takes leverage from the MCMC method that can be used for constraining the parameters and theoretical models of Cosmology. Unlike the MCMC technique, which is essentially a non-parallel algorithm by design, the newly proposed algorithm is able to obtain the full potential of multi-core machines. With this algorithm, we could obtain the best-fit parameters of the Lambda CDM cosmological model and identify the discrepancy in the Hubble parameter $H_0$. In the present work we discuss the design principle of this novel approach and also the results from the analysis of Pantheon, OHD and Planck datasets are reported here. The estimation of parameters shows significant consistency with the previously reported values as well as a higher computational performance compared to the other similar exercises., Comment: 10 figues

Heat exchanger tube rows can influence the thermoacoustic instability behaviour of combustion systems since they act as both acoustic scatterers and unsteady heat sinks. Therefore, with careful tuning of their thermoacoustic properties, heat exchangers have the potential to act as passive control devices. In this work, we focus on (only) the acoustic scattering behaviour of heat exchanger tubes. We present a comparison of existing acoustic models for tube rows and slits, models for the latter having the advantage of incorporating frequency dependence. We then propose a new model that enables the adaptation of slit models for tube rows. This model is validated against experiments and Linearised Navier Stokes Equations (LNSE) predictions for the transmission and reflection coefficients, including phase information. The model predictions show very good agreement with the experimental and numerical validations, especially for low frequencies (Strouhal number < 0.5, based on tube radius and excitation frequency), with mean differences less than 2% for the transmission coefficients (the reflection coefficient errors are somewhat larger since their magnitudes are very close to zero)., Comment: 23 pages, 10 figures, to be published in the Journal of Sound and Vibration

Malware authors reuse the same program segments found in other applications for performing the similar kind of malicious activities such as information stealing, sending SMS and so on. Hence, there may exist several semantically similar malware samples in a family/dataset. Many researchers unaware about these semantically similar apps and use their features in their ML models for evaluation. Hence, the performance measures might be seriously affected by these similar kinds of apps. In this paper, we study the impact of semantically similar applications in the performance measures of ML based Android malware detectors. For this, we propose a novel opcode subsequence based malware clustering algorithm to identify the semantically similar malware and goodware apps. For studying the impact of semantically similar apps in the performance measures, we tested the performance of distinct ML models based on API call and permission features of malware and goodware application with/without semantically similar apps. In our experimentation with Drebin dataset, we found that, after removing the exact duplicate apps from the dataset (? = 0) the malware detection rate (TPR) of API call based ML models is dropped from 0.95 to 0.91 and permission based model is dropped from 0.94 to 0.90. In order to overcome this issue, we advise the research community to use our clustering algorithm to get rid of semantically similar apps before evaluating their malware detection mechanism., Comment: 9 Pages