Does the non-force-freeness matter for the extrapolation of solar magnetic field?

Magnetic field extrapolation is a fundamental tool to reconstruct the three-dimensional solar coronal magnetic field. However, the prevalently used force-free field model might not be applicable in the lower atmosphere, where plasma \b{eta} is greater than 1. In this work, we perform extrapolation in active region 12158, based on an updated magnetohydrostatic (MHS) method. By comparing the results with those from the force-free field method of Current-Field Iteration in Spherical Coordinates (CFITS), we find that the overall properties, which are characterized by the magnetic free energy and helicity, are roughly the same after volume integral. The major differences lie in the magnetic configuration and the twist number of magnetic flux rope (MFR). A coherent MFR with twist around 1 is reproduced from CFITS. In another manner, two sets of MFR, which are highly twisted and slightly coupled, are derived by the MHS method. The latter one is better constrained by the high-resolution observations, such as the filament fibrils, pre-eruptive braiding characteristics and the eruptive double-J shaped hot channel. Overall, our work shows the MHS method is more promising to reproduce the magnetic fine structures that can well match the observations not only in the chromosphere but also in the corona. This initiates the necessity of reconsidering the simplification of low atmosphere for currently widely used nonlinear force-free extrapolation method, since such assumption will not only omit the magnetic structures at low atmosphere but also affect those obtained in the corona, and therefore bringing in ambiguity in interpreting the solar eruption.Comment: 19 pages, 6 figures, accepted by Ap

Efficient generation of relativistic near-single-cycle mid-infrared pulses in plasmas

Ultrashort intense optical pulses in the mid-infrared (mid-IR) region are very important for broad applications ranging from super-resolution spectroscopy to attosecond X-ray pulse generation and particle acceleration. However, currently, it is still difficult to produce few-cycle mid-IR pulses of relativistic intensities using standard optical techniques. Here, we propose and numerically demonstrate a novel scheme to produce these mid-IR pulses based on laser-driven plasma optical modulation. In this scheme, a plasma wake is first excited by an intense drive laser pulse in an underdense plasma, and a signal laser pulse initially at the same wavelength (1 micron) as that of the drive laser is subsequently injected into the plasma wake. The signal pulse is converted to a relativistic multi-millijoule near-single-cycle mid-IR pulse with a central wavelength of ~5 microns via frequency-downshifting, where the energy conversion efficiency is as high as approximately 30% when the drive and signal laser pulses are both at a few tens of millijoules at the beginning. Our scheme can be realized with terawatt-class kHz laser systems, which may bring new opportunities in high-field physics and ultrafast science

Adaptive Hierarchical Origami Metastructures

Shape-morphing capabilities are crucial for enabling multifunctionality in both biological and artificial systems. Various strategies for shape morphing have been proposed for applications in metamaterials and robotics. However, few of these approaches have achieved the ability to seamlessly transform into a multitude of volumetric shapes post-fabrication using a relatively simple actuation and control mechanism. Taking inspiration from thick origami and hierarchies in nature, we present a new hierarchical construction method based on polyhedrons to create an extensive library of compact origami metastructures. We show that a single hierarchical origami structure can autonomously adapt to over 103 versatile architectural configurations, achieved with the utilization of fewer than 3 actuation degrees of freedom and employing simple transition kinematics. We uncover the fundamental principles governing theses shape transformation through theoretical models. Furthermore, we also demonstrate the wide-ranging potential applications of these transformable hierarchical structures. These include their uses as untethered and autonomous robotic transformers capable of various gait-shifting and multidirectional locomotion, as well as rapidly self-deployable and self-reconfigurable architecture, exemplifying its scalability up to the meter scale. Lastly, we introduce the concept of multitask reconfigurable and deployable space robots and habitats, showcasing the adaptability and versatility of these metastructures

Anomalous Floquet non-Hermitian skin effect in a ring resonator lattice

We present a one-dimensional coupled ring resonator lattice exhibiting a variant of the non- Hermitian skin effect (NHSE) that we call the anomalous Floquet NHSE. Unlike existing approaches to achieving the NHSE by engineering gain and loss on different ring segments, our design uses fixed on-site gain or loss in each ring. The anomalous Floquet NHSE is marked by the existence of skin modes at every value of the Floquet quasienergy, allowing for broadband asymmetric transmission. Varying the gain/loss induces a non-Hermitian topological phase transition, reversing the localization direction of the skin modes. An experimental implementation in an acoustic lattice yields good agreement with theoretical predictions, with a very broad relative bandwidth of around 40%.Comment: 7 pages, 3 figure

Multi-Modal Automatic Prosody Annotation with Contrastive Pretraining of SSWP

In the realm of expressive Text-to-Speech (TTS), explicit prosodic boundaries significantly advance the naturalness and controllability of synthesized speech. While human prosody annotation contributes a lot to the performance, it is a labor-intensive and time-consuming process, often resulting in inconsistent outcomes. Despite the availability of extensive supervised data, the current benchmark model still faces performance setbacks. To address this issue, a two-stage automatic annotation pipeline is novelly proposed in this paper. Specifically, in the first stage, we propose contrastive text-speech pretraining of Speech-Silence and Word-Punctuation (SSWP) pairs. The pretraining procedure hammers at enhancing the prosodic space extracted from joint text-speech space. In the second stage, we build a multi-modal prosody annotator, which consists of pretrained encoders, a straightforward yet effective text-speech feature fusion scheme, and a sequence classifier. Extensive experiments conclusively demonstrate that our proposed method excels at automatically generating prosody annotation and achieves state-of-the-art (SOTA) performance. Furthermore, our novel model has exhibited remarkable resilience when tested with varying amounts of data.Comment: Submitted to ICASSP 202

TranssionADD: A multi-frame reinforcement based sequence tagging model for audio deepfake detection

Thanks to recent advancements in end-to-end speech modeling technology, it has become increasingly feasible to imitate and clone a user`s voice. This leads to a significant challenge in differentiating between authentic and fabricated audio segments. To address the issue of user voice abuse and misuse, the second Audio Deepfake Detection Challenge (ADD 2023) aims to detect and analyze deepfake speech utterances. Specifically, Track 2, named the Manipulation Region Location (RL), aims to pinpoint the location of manipulated regions in audio, which can be present in both real and generated audio segments. We propose our novel TranssionADD system as a solution to the challenging problem of model robustness and audio segment outliers in the trace competition. Our system provides three unique contributions: 1) we adapt sequence tagging task for audio deepfake detection; 2) we improve model generalization by various data augmentation techniques; 3) we incorporate multi-frame detection (MFD) module to overcome limited representation provided by a single frame and use isolated-frame penalty (IFP) loss to handle outliers in segments. Our best submission achieved 2nd place in Track 2, demonstrating the effectiveness and robustness of our proposed system