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Two-dimensional hybrid organic-inorganic perovskites (HOIPs) have emerged as promising materials for light-emitting diode applications. In this study, by using time-of-flight neutron spectroscopy we identified and quantitatively separated the lattice vibrational and molecular rotational dynamics of two perovskites, butylammonium lead iodide (BA)$_{2}$PbI$_{4}$ and phenethyl-ammonium lead iodide (PEA)$_{2}$PbI$_{4}$. By examining the corresponding temperature dependence, we found that the lattice vibrations, as evidenced by neutron spectra, are consistent with the lattice dynamics obtained from Raman scattering. We revealed that the rotational dynamics of organic molecules in these materials tend to suppress their photoluminescence quantum yield (PLQY) while the vibrational dynamics did not show predominant correlations with the same. Additionally, we observed photoluminescence emission peak splitting for both systems, which becomes prominent above certain critical temperatures where the suppression of PLQY begins. This study suggests that the rotational motions of polarized molecules may lead to a reduction in exciton binding energy or the breaking of degeneracy in exciton binding energy levels, enhancing non-radiative recombination rates, and consequently reducing photoluminescence yield. These findings offer a deeper understanding of fundamental interactions in 2D HOIPs and could guide the design of more efficient light-emitting materials for advanced technological applications.

Quantum error correction (QEC) provides a practical path to fault-tolerant quantum computing through scaling to large qubit numbers, assuming that physical errors are sufficiently uncorrelated in time and space. In superconducting qubit arrays, high-energy impact events produce correlated errors, violating this key assumption. Following such an event, phonons with energy above the superconducting gap propagate throughout the device substrate, which in turn generate a temporary surge in quasiparticle (QP) density throughout the array. When these QPs tunnel across the qubits' Josephson junctions, they induce correlated errors. Engineering different superconducting gaps across the qubit's Josephson junctions provides a method to resist this form of QP tunneling. By fabricating all-aluminum transmon qubits with both strong and weak gap engineering on the same substrate, we observe starkly different responses during high-energy impact events. Strongly gap engineered qubits do not show any degradation in T1 during impact events, while weakly gap engineered qubits show events of correlated degradation in T1. We also show that strongly gap engineered qubits are robust to QP poisoning from increasing optical illumination intensity, whereas weakly gap engineered qubits display rapid degradation in coherence. Based on these results, gap engineering removes the threat of high-energy impacts to QEC in superconducting qubit arrays.

Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little is known about the robustness of these algorithms in real-world settings where several factors can lead to a loss of generalizability. Understanding and overcoming these limitations will permit the development of generalizable AI that can aid in the diagnosis of skin conditions across a variety of clinical settings. In this retrospective study, we demonstrate that differences in skin condition distribution, rather than in demographics or image capture mode are the main source of errors when an AI algorithm is evaluated on data from a previously unseen source. We demonstrate a series of steps to close this generalization gap, requiring progressively more information about the new source, ranging from the condition distribution to training data enriched for data less frequently seen during training. Our results also suggest comparable performance from end-to-end fine tuning versus fine tuning solely the classification layer on top of a frozen embedding model. Our approach can inform the adaptation of AI algorithms to new settings, based on the information and resources available.

As HPC system architectures and the applications running on them continue to evolve, the MPI standard itself must evolve. The trend in current and future HPC systems toward powerful nodes with multiple CPU cores and multiple GPU accelerators makes efficient support for hybrid programming critical for applications to achieve high performance. However, the support for hybrid programming in the MPI standard has not kept up with recent trends. The MPICH implementation of MPI provides a platform for implementing and experimenting with new proposals and extensions to fill this gap and to gain valuable experience and feedback before the MPI Forum can consider them for standardization. In this work, we detail six extensions implemented in MPICH to increase MPI interoperability with other runtimes, with a specific focus on heterogeneous architectures. First, the extension to MPI generalized requests lets applications integrate asynchronous tasks into MPI's progress engine. Second, the iovec extension to datatypes lets applications use MPI datatypes as a general-purpose data layout API beyond just MPI communications. Third, a new MPI object, MPIX stream, can be used by applications to identify execution contexts beyond MPI processes, including threads and GPU streams. MPIX stream communicators can be created to make existing MPI functions thread-aware and GPU-aware, thus providing applications with explicit ways to achieve higher performance. Fourth, MPIX Streams are extended to support the enqueue semantics for offloading MPI communications onto a GPU stream context. Fifth, thread communicators allow MPI communicators to be constructed with individual threads, thus providing a new level of interoperability between MPI and on-node runtimes such as OpenMP. Lastly, we present an extension to invoke MPI progress, which lets users spawn progress threads with fine-grained control., Comment: 14 pages. Submitted IJHPCA special issue

Using a fixed Eulerian mesh, the phase-field method has been successfully utilized for a broad range of moving boundary problems involving multiphase fluids and single-phase fluid-structure interaction. Nevertheless, multiphase fluids interacting with multiple solids are rarely explored, especially for large-scale finite element simulations with contact dynamics. In this work, we introduce a novel parallelized three-dimensional fully Eulerian variational framework for simulating multiphase fluids interacting with multiple deformable solids subjected to contact dynamics. In the framework, each solid or fluid phase is identified by a standalone phase indicator. Moreover the phase indicators are initialized by the grid cell method, which restricts the calculation to several grid cells. A diffuse interface description is employed for a smooth interpolation of the physical properties across the phases, yielding unified mass and momentum conservation equations for the coupled dynamical interactions. For each solid object, temporal integration is carried out to track the strain evolution in an Eulerian frame of reference. The coupled differential equations are solved in a partitioned iterative manner. We first verify the framework against reference numerical data in a two-dimensional case of a rotational disk in a lid-driven cavity flow. The case is generalized to a rotational sphere in a lid-driven cavity flow to showcase large deformation and rotational motion of solids and examine the convergence in three dimensions. We then simulate the falling of an immersed solid sphere on an elastic block under gravitational force to demonstrate the translational motion and the solid-to-solid contact in a fluid environment. Finally, we demonstrate the framework for a ship-ice interaction problem involving multiphase fluids with an air-water interface and contact between a floating ship and ice floes., Comment: 32 pages, 18 figures

Deep neural networks, including Convolutional Neural Networks (CNNs) and Visual Transformers (ViT), have achieved stunning success in medical image domain. We study thorax disease classification in this paper. Effective extraction of features for the disease areas is crucial for disease classification on radiographic images. While various neural architectures and training techniques, such as self-supervised learning with contrastive/restorative learning, have been employed for disease classification on radiographic images, there are no principled methods which can effectively reduce the adverse effect of noise and background, or non-disease areas, on the radiographic images for disease classification. To address this challenge, we propose a novel Low-Rank Feature Learning (LRFL) method in this paper, which is universally applicable to the training of all neural networks. The LRFL method is both empirically motivated by the low frequency property observed on all the medical datasets in this paper, and theoretically motivated by our sharp generalization bound for neural networks with low-rank features. In the empirical study, using a neural network such as a ViT or a CNN pre-trained on unlabeled chest X-rays by Masked Autoencoders (MAE), our novel LRFL method is applied on the pre-trained neural network and demonstrate better classification results in terms of both multiclass area under the receiver operating curve (mAUC) and classification accuracy.

The underwater radiated noise (URN) emanating from ships presents a significant threat to marine mammals, given their heavy reliance on hearing for essential life activities. The intensity of URN from ships is directly correlated to the speed, making speed reduction a crucial operational mitigation strategy. This paper presents a new multi-objective optimization framework to optimize the ship speed for effective URN mitigation without compromising fuel consumption. The proposed framework addresses a fixed-path voyage scheduling problem, incorporating two objective functions namely (i) noise intensity levels and (ii) fuel consumption. The optimization is performed using the state-of-the-art non-dominated sorting genetic algorithm under voyage constraints. A 2D ocean acoustic environment, comprising randomly scattered marine mammals of diverse audiogram groups and realistic conditions, including sound speed profiles and bathymetry, is simulated. To estimate the objective functions, we consider empirical relations for fuel consumption and near-field noise modeling together with a ray-tracing approach for far-field noise propagation. The optimization problem is solved using the genetic algorithm to determine the Pareto solutions and subsequently the trade-off solution. The effectiveness of the optimization framework is demonstrated via both simplified tests and practical case studies involving a large container ship. A comparative analysis illustrates the adaptability of the optimization framework across different oceanic environments, affirming its potential as a robust tool for reducing the URN from shipping.

In relativistic hydrodynamics with spin, following de Groot--van Leeuwen--van Weert's energy-momentum and spin tensor definitions, we analyze the propagation of spin degrees of freedom. We deduce an analytical formula for spin wave velocity, finding that it approaches half the speed of light in the ultra-relativistic limit. Only transverse degrees of freedom propagate, similar to electromagnetic waves. Additionally, we explore dissipative effects and determine the damping coefficients for Maxwell-J\"uttner statistics.

MPI+Threads, embodied by the MPI/OpenMP hybrid programming model, is a parallel programming paradigm where threads are used for on-node shared-memory parallelization and MPI is used for multi-node distributed-memory parallelization. OpenMP provides an incremental approach to parallelize code, while MPI, with its isolated address space and explicit messaging API, affords straightforward paths to obtain good parallel performance. However, MPI+Threads is not an ideal solution. Since MPI is unaware of the thread context, it cannot be used for interthread communication. This results in duplicated efforts to create separate and sometimes nested solutions for similar parallel tasks. In addition, because the MPI library is required to obey message-ordering semantics, mixing threads and MPI via MPI_THREAD_MULTIPLE can easily result in miserable performance due to accidental serializations. We propose a new MPI extension, MPIX Thread Communicator (threadcomm), that allows threads to be assigned distinct MPI ranks within thread parallel regions. The threadcomm extension combines both MPI processes and OpenMP threads to form a unified parallel environment. We show that this MPIxThreads (MPI Multiply Threads) paradigm allows OpenMP and MPI to work together in a complementary way to achieve both cleaner codes and better performance.

We investigate the spacetime evolution of spin polarization within a hydrodynamic framework based on the de Groot--van Leeuwen--van Weert expressions for energy-momentum and spin tensors. The system's deviation from boost invariance results in the interplay of different spin polarization components, impacting spin observables. We specifically examine the transverse momentum, azimuthal angle, and rapidity dependence of the mean spin polarization vector of $\Lambda$ hyperons. Our results qualitatively align with other models and experimental data on global spin polarization rapidity dependence. While the quadrupole structure is absent in the longitudinal component at midrapidity, our analysis reveals non-trivial signal at forward rapidities that differs from predictions based on the Bjorken expansion., Comment: Contribution to SPIN 2023

We expand the classical phase-space distribution function to incorporate couplings between spin and electromagnetic fields. This extension has led to the derivation of modified constitutive relations for the charge current, energy-momentum tensor, and spin tensor. Due to these couplings, the new tensors are revised from their perfect fluid analogues, creating an interplay between the background and spin fluid equations of motion. The corrections introduced in our framework have the potential to shed light on the experimentally observed discrepancies in the spin polarization measurements of Lambda hyperons., Comment: Contribution to SPIN 2023 conference

Binary kagome compounds TmXn (T = Mn, Fe, Co; X = Sn, Ge; m:n = 3:1, 3:2, 1:1) have garnered recent interest owing to the presence of both topological band crossings and flat bands arising from the geometry of the metal-site kagome lattice. To exploit these electronic features for potential applications in spintronics, the growth of high quality heterostructures is required. Here we report the synthesis of Fe/FeSn and Co/FeSn bilayers on Al2O3 substrates using molecular beam epitaxy to realize heterointerfaces between elemental ferromagnetic metals and antiferromagnetic kagome metals. Structural characterization using high-resolution X-ray diffraction, reflection high-energy electron diffraction, and electron microscopy reveals the FeSn films are flat and epitaxial. Rutherford backscattering spectroscopy was used to confirm the stoichiometric window where the FeSn phase is stabilized, while transport and magnetometry measurements were conducted to verify metallicity and magnetic ordering in the films. Exchange bias was observed, confirming the presence of antiferromagnetic order in the FeSn layers, paving the way for future studies of magnetism in kagome heterostructures and potential integration of these materials into devices., Comment: The following article has been submitted to the Journal of Applied Physics

For a positive integer $m$ and a finite non-negative Borel measure $\mu$ on the unit circle, we study the Hadamard multipliers of higher order weighted Dirichlet-type spaces $\mathcal H_{\mu, m}$. We show that if $\alpha>\frac{1}{2},$ then for any $f$ in $\mathcal H_{\mu, m},$ the sequence of generalized Ces{\`a}ro sums $\{\sigma_n^{\alpha}[f]\}$ converges to $f$. We further show that if $\alpha=\frac{1}{2}$ then for the Dirac delta measure supported at any point on the unit circle, the previous statement breaks down for every positive integer $m$., Comment: 14 pages, comments and suggestions are welcome

We present a finite element framework for the numerical prediction of cavitating turbulent flows interacting with flexible structures. The vapor-fluid phases are captured through a homogeneous mixture model, with a scalar transport equation governing the spatio-temporal evolution of cavitation dynamics. High-density gradients in the two-phase cavitating flow motivate the use of a positivity-preserving Petrov-Galerkin stabilization method in the variational framework. A mass transfer source term introduces local compressibility effects arising as a consequence of phase change. The turbulent fluid flow is modeled through a dynamic subgrid-scale method for large eddy simulations. The flexible structure is represented by a set of eigenmodes, obtained through the modal analysis of the linear elasticity equations. A partitioned iterative approach is adopted to couple the structural dynamics and cavitating fluid flow, where the deforming flow domain is described by an arbitrary Lagrangian-Eulerian frame of reference. Through the numerical validation study, we establish the fidelity of the proposed framework by comparing it against experimental and numerical studies for both rigid and flexible hydrofoils in cavitating flows. Based on the validation study conducted over a flexible NACA66 rectangular hydrofoil, we elucidate the role of cavity and vortex shedding in governing the structural dynamics of a flexible hydrofoil., Comment: 37 pages, 18 figures, 8 tables

In this work, we investigate angular observables such as the longitudinal polarization of charged leptons, $\tau$-polarization, and forward-backward asymmetry in semileptonic $B_c$ decays. Additionally, we provide predictions for lepton flavor violating observables, the $\mathcal{R}$ ratios in the decay channels $B_c \rightarrow \eta_c (J/\psi) l \nu_l$ and $B_c \rightarrow D (D^*) l \nu_l$ across the entire $q^2$ region. Our analysis is conducted within the Relativistic Independent Quark Model, focusing on the potential model-dependent aspects of these observables. We compare our model predictions with existing lattice predictions, highlighting the strong applicability of our framework in describing $B_c$ decays. Considering the forthcoming experimental upgrades and the Run 3 data results on $B_c$ meson decays, rapid confirmation of these quantities could indicate significant discoveries of physics beyond the Standard Model. This will open up new avenues for understanding the complex flavor dynamics in heavy meson decays., Comment: Accepted version in Physical Review D

Noise generated by vortices is a sensible measure of the strength of wakes generated in a flow field. This paper presents an innovative approach to actively control wakes and noise generated in a flow past a cylinder using deep reinforcement learning (DRL) as a continuously learning active control algorithm with noise levels recorded using acoustic level around the wake region. The two primary objectives of this study is to investigate the feasibility and effectiveness of use of acoustic level as controlling parameter and employing DRL algorithms to optimize the control of flow dynamics. A hydrophone array is utilised to capture the wake pattern along the flow field downstream of a circular cylinder in the form of acoustic signals. The collected data are used to create a real-time feedback loop for a DRL agent to adjust jet actuators strategically placed on the cylinder's surface. This approach enables the agent to learn and adapt its control strategy based on the observed acoustic feedback, resulting in a closed-loop control system. We demonstrate that the DRL-based flow control strategy can effectively reduce wake amplitude and the noise generated. The noise level reduces by an appreciable 6.9\% and 9.5\% in the given setting for two control configurations. Similarly, the drag coefficient reduces by a remarkable 15.9\% and 23.8\% respectively. Specifically, it reduces the oscillation amplitude in drag and noise. The proposed method offers promising results in terms of reducing flow-induced vibration. The paper highlights the potential for using DRL, jets, and hydrophone arrays in active flow control, opening new avenues for optimizing flow control in practical engineering applications.

Recently several reports showing ultra-high electrostrain (> 1 %) have appeared in Pb-free piezoceramics. However, there is lack of clarity on the nature of the ultrahigh strain. Here, we demonsrate that the ultrahigh strain is a consequence of bending of the disc. We show that the propensity for bending arises from the difference in the response magnitude of the grains at the positive and negative surfaces of the piezoceramic when the field is applied., Comment: 8 pages 4 figures

In this paper, we numerically study the oscillatory dynamics associated with the tip vortex cavitation over an elliptical hydrofoil section using our 3D variational multiphase flow solver at a Reynolds number of $Re=8.95 \times 10^5$ via dynamic subgrid-scale modeling and homogeneous mixture theory. To begin, we examine the grid resolution requirements and introduce a length scale that considers both the tip vortex strength and the core radius, which is then employed to non-dimensionalize the spatial resolution in the tip vortex region and establish mesh requirements for large eddy simulation of tip vortex cavitation. We next perform simulations to analyze the dynamical modes of cavity oscillation at different cavitation numbers and compare them with the semi-analytical solution. The breathing mode of cavity surface oscillation is extracted from the results through the definition of an effective radius. The time-averaged effective radius demonstrates that the cavity experiences a growth region followed by decay as it progresses away from the tip. Further examination of the local breathing mode oscillations in these regions indicates the different behavior of cavity oscillations in the growth and decay regions, with the oscillations within the former being characterized by lower frequencies. For representative cavitation numbers $\sigma \in [1.2,2.6]$, we find that pressure fluctuations exhibit a shift of spectrum towards lower frequencies as the cavitation number decreases, similar to its influence on breathing mode oscillations. The results indicate the correlations between the breathing mode oscillations and the pressure fluctuations, with the low-frequency and relatively higher-frequency pressure fluctuations being correlated with the growth and decay regions, respectively., Comment: 30 pages, 21 figures

We present an alternative approach to deriving second-order non-conformal hydrodynamics from the relativistic Boltzmann equation. We demonstrate how constitutive relations for shear and bulk stresses can be transformed into dynamical evolution equations, resulting in Israel-Stewart-like (ISL) hydrodynamics. To understand the far-from-equilibrium applicability of such ISL theories, we investigate the one-dimensional boost-invariant Boltzmann equation using special moments of the distribution function for a system with finite particle mass. Our analysis reveals that the mathematical structure of the ISL equations is akin to that of moment equations, enabling them to approximately replicate even the collisionless dynamics. We conclude that this particular feature is important in extending the applicability of ISL theories beyond the hydrodynamic regime., Comment: Contribution to Quark Matter 2023 (4 pages)

Charged lepton flavor violation (cLFV) processes, potentially important for various Beyond the Standard Model Physics scenarios are analyzed in the Standard Model Effective Field Theory (SMEFT) framework. We consider the most relevant 2 quark-2 lepton $(2q2\ell)$ operators for the leptonic and semi-leptonic LFV B-decay (LFVBD) processes $B_s\to \mu^+e^- , B^+\to K^+\mu^+e^-, B^0\to K^{*0}\mu^+ e^-, {\rm and}~ B_s\to \phi\mu^-e^+$. We analyse the interplay among the Wilson coefficients responsible for these LFVBDs and other cLFV processes like $\rm CR (\mu\to e)$, $\ell_i \to \ell_j \gamma$, $\ell_i \to\ell_j\ell_k\ell_m$ and $Z \to \ell_i \ell_j$, to find the maximal possible LFV effects in $B$-meson decays. We probe the scale of new physics in relation to the constraints imposed by both classes of the LFV decays while considering both the present bounds and future expectations. In view of proposed experiments at LHCb-II and Belle II to study charged LFV processes, we have also provided the upper limits on the indirect constraints on such LFVBDs. For the processes where $B$ meson is decaying to $\mu^{\pm}$ and $e^{\mp}$, we show that new physics can be constrained by an enhancement of 2-4 orders of magnitude on the current sensitivities of the BRs of $B^+\to K^+\mu^+e^-, B^0\to K^{*0}\mu^+ e^- {\rm and}~ B_s\to\phi\mu^{\pm}e^{\mp}$., Comment: Feynman diagram is updated. No change in text or results with respect to the journal version