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The local (z=0.0315) AGN Mrk 817, was monitored over more than 500 days with space-borne and ground-based instruments as part of a large international campaign AGN STORM 2. Here, we present a comprehensive analysis of the broad-band continuum variations using detailed modeling of the broad line region (BLR), several types of disk winds classified by their optical depth, and new numerical simulations. We find that diffuse continuum (DC) emission, with additional contributions from strong and broad emission lines, can explain the continuum lags observed in this source during high and low luminosity phases. Disk illumination by the variable X-ray corona contributes only a small fraction of the observed continuum lags. Our BLR models assume radiation pressure-confined clouds distributed over a distance of 2-122 light days. We present calculated mean-emissivity radii of many emission lines, and DC emission, and suggest a simple, transfer-function-dependent method that ties them to cross-correlation lag determinations. We do not find clear indications for large optical depth winds but identify the signature of lower column density winds. In particular, we associate the shortest observed continuum lags with a combination of tau(1 Ryd) approx. 2 wind and a partly shielded BLR. Even smaller optical depth winds may be associated with X-ray absorption features and with noticeable variations in the width and lags of several high ionization lines like HeII and CIV. Finally, we demonstrate the effect of torus dust emission on the observed lags in the i and z bands., Comment: 23 pages, 18 figures. Corrected typographical error in the title of the paper as it appeared in the Metadata

The gravitational wave (GW) event GW190521, likely originating from a binary black hole (BBH) merger within an active galactic nucleus (AGN) disk, is associated with the optical flare ZTF19abanrhr. The remnant BHs from BBH mergers can launch the jet and outflow and then interact with the disk medium, which can be responsible for the associated electromagnetic radiations. In this \textit{letter}, we examine the shock breakout and subsequent cooling emissions from four potential components: the outflow, jet head, jet cocoon, and disk cocoon, all driven by the remnant BH within the AGN disk. Using dynamic models and observational constraints, for GW190521, we identify the parameter space for each component and conclude that either the outflow or the disk cocoon could produce the observed electromagnetic signal, with the disk cocoon requiring more extreme parameters. We present best-fit light curves and spectral energy distributions (SEDs) for both components, showing peak emissions in the UV band for the outflow and spanning optical to UV for the disk cocoon., Comment: 8 pages, 3 figures, 1 tabel, submitted

This paper addresses the prevalent issue of incorrect speech output in audio-visual speech enhancement (AVSE) systems, which is often caused by poor video quality and mismatched training and test data. We introduce a post-processing classifier (PPC) to rectify these erroneous outputs, ensuring that the enhanced speech corresponds accurately to the intended speaker. We also adopt a mixup strategy in PPC training to improve its robustness. Experimental results on the AVSE-challenge dataset show that integrating PPC into the AVSE model can significantly improve AVSE performance, and combining PPC with the AVSE model trained with permutation invariant training (PIT) yields the best performance. The proposed method substantially outperforms the baseline model by a large margin. This work highlights the potential for broader applications across various modalities and architectures, providing a promising direction for future research in this field., Comment: The 27th International Conference of the Oriental COCOSDA

While pre-trained automatic speech recognition (ASR) systems demonstrate impressive performance on matched domains, their performance often degrades when confronted with channel mismatch stemming from unseen recording environments and conditions. To mitigate this issue, we propose a novel channel-aware data simulation method for robust ASR training. Our method harnesses the synergistic power of channel-extractive techniques and generative adversarial networks (GANs). We first train a channel encoder capable of extracting embeddings from arbitrary audio. On top of this, channel embeddings are extracted using a minimal amount of target-domain data and used to guide a GAN-based speech synthesizer. This synthesizer generates speech that faithfully preserves the phonetic content of the input while mimicking the channel characteristics of the target domain. We evaluate our method on the challenging Hakka Across Taiwan (HAT) and Taiwanese Across Taiwan (TAT) corpora, achieving relative character error rate (CER) reductions of 20.02% and 9.64%, respectively, compared to the baselines. These results highlight the efficacy of our channel-aware data simulation method for bridging the gap between source- and target-domain acoustics., Comment: Submitted to ICASSP 2025

In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction. Traditional methods, such as CNN or LSTM, attempt to model the temporal dynamics of full-band and sub-band spectral and spatial features. However, these approaches face limitations in fully modeling complex temporal dependencies, especially in dynamic acoustic environments. To overcome these challenges, we modify the current advanced model McNet by introducing an improved version of Mamba, a state-space model, and further propose MCMamba. MCMamba has been completely reengineered to integrate full-band and narrow-band spatial information with sub-band and full-band spectral features, providing a more comprehensive approach to modeling spatial and spectral information. Our experimental results demonstrate that MCMamba significantly improves the modeling of spatial and spectral features in multichannel speech enhancement, outperforming McNet and achieving state-of-the-art performance on the CHiME-3 dataset. Additionally, we find that Mamba performs exceptionally well in modeling spectral information.

This work investigates two strategies for zero-shot non-intrusive speech assessment leveraging large language models. First, we explore the audio analysis capabilities of GPT-4o. Second, we propose GPT-Whisper, which uses Whisper as an audio-to-text module and evaluates the naturalness of text via targeted prompt engineering. We evaluate assessment metrics predicted by GPT-4o and GPT-Whisper examining their correlations with human-based quality and intelligibility assessments, and character error rate (CER) of automatic speech recognition. Experimental results show that GPT-4o alone is not effective for audio analysis; whereas, GPT-Whisper demonstrates higher prediction, showing moderate correlation with speech quality and intelligibility, and high correlation with CER. Compared to supervised non-intrusive neural speech assessment models, namely MOS-SSL and MTI-Net, GPT-Whisper yields a notably higher Spearman's rank correlation with the CER of Whisper. These findings validate GPT-Whisper as a reliable method for accurate zero-shot speech assessment without requiring additional training data (speech data and corresponding assessment scores).

Scaling up quantum dots to two-dimensional (2D) arrays is a crucial step for advancing semiconductor quantum computation. However, maintaining excellent tunability of quantum dot parameters, including both nearest-neighbor and next-nearest-neighbor couplings, during 2D scaling is challenging, particularly for silicon quantum dots due to their relatively small size. Here, we present a highly controllable and interconnected 2D quantum dot array in planar silicon, demonstrating independent control over electron fillings and the tunnel couplings of nearest-neighbor dots. More importantly, we also demonstrate the wide tuning of tunnel couplings between next-nearest-neighbor dots,which plays a crucial role in 2D quantum dot arrays. This excellent tunability enables us to alter the coupling configuration of the array as needed. These results open up the possibility of utilizing silicon quantum dot arrays as versatile platforms for quantum computing and quantum simulation.

Electron spin qubits in silicon are a promising platform for fault-tolerant quantum computing. Low-frequency noise, including nuclear spin fluctuations and charge noise, is a primary factor limiting gate fidelities. Suppressing this noise is crucial for high-fidelity qubit operations. Here, we report on a two-qubit quantum device in natural silicon with universal qubit control, designed to investigate the upper limits of gate fidelities in a non-purified Si/SiGe quantum dot device. By employing advanced device structures, qubit manipulation techniques, and optimization methods, we have achieved single-qubit gate fidelities exceeding 99% and a two-qubit Controlled-Z (CZ) gate fidelity of 91%. Decoupled CZ gates are used to prepare Bell states with a fidelity of 91%, typically exceeding previously reported values in natural silicon devices. These results underscore that even natural silicon has the potential to achieve high-fidelity gate operations, particularly with further optimization methods to suppress low-frequency noise.

This study investigates the efficacy of data augmentation techniques for low-resource automatic speech recognition (ASR), focusing on two endangered Austronesian languages, Amis and Seediq. Recognizing the potential of self-supervised learning (SSL) in low-resource settings, we explore the impact of data volume on the continued pre-training of SSL models. We propose a novel data-selection scheme leveraging a multilingual corpus to augment the limited target language data. This scheme utilizes a language classifier to extract utterance embeddings and employs one-class classifiers to identify utterances phonetically and phonologically proximate to the target languages. Utterances are ranked and selected based on their decision scores, ensuring the inclusion of highly relevant data in the SSL-ASR pipeline. Our experimental results demonstrate the effectiveness of this approach, yielding substantial improvements in ASR performance for both Amis and Seediq. These findings underscore the feasibility and promise of data augmentation through cross-lingual transfer learning for low-resource language ASR.

We present the third edition of the VoiceMOS Challenge, a scientific initiative designed to advance research into automatic prediction of human speech ratings. There were three tracks. The first track was on predicting the quality of ``zoomed-in'' high-quality samples from speech synthesis systems. The second track was to predict ratings of samples from singing voice synthesis and voice conversion with a large variety of systems, listeners, and languages. The third track was semi-supervised quality prediction for noisy, clean, and enhanced speech, where a very small amount of labeled training data was provided. Among the eight teams from both academia and industry, we found that many were able to outperform the baseline systems. Successful techniques included retrieval-based methods and the use of non-self-supervised representations like spectrograms and pitch histograms. These results showed that the challenge has advanced the field of subjective speech rating prediction., Comment: Accepted to SLT2024

Cross-domain speech enhancement (SE) is often faced with severe challenges due to the scarcity of noise and background information in an unseen target domain, leading to a mismatch between training and test conditions. This study puts forward a novel data simulation method to address this issue, leveraging noise-extractive techniques and generative adversarial networks (GANs) with only limited target noisy speech data. Notably, our method employs a noise encoder to extract noise embeddings from target-domain data. These embeddings aptly guide the generator to synthesize utterances acoustically fitted to the target domain while authentically preserving the phonetic content of the input clean speech. Furthermore, we introduce the notion of dynamic stochastic perturbation, which can inject controlled perturbations into the noise embeddings during inference, thereby enabling the model to generalize well to unseen noise conditions. Experiments on the VoiceBank-DEMAND benchmark dataset demonstrate that our domain-adaptive SE method outperforms an existing strong baseline based on data simulation., Comment: Accepted to IEEE SLT 2024

Over the past three decades, multiple reverberation mapping (RM) campaigns conducted for the quasar PG 2130+099 have exhibited inconsistent findings with time delays ranging from $\sim$10 to $\sim$200 days. To achieve a comprehensive understanding of the geometry and dynamics of the broad-line region (BLR) in PG 2130+099, we continued an ongoing high-cadence RM monitoring campaign using the Calar Alto Observatory 2.2m optical telescope for an extra four years from 2019 to 2022. We measured the time lags of several broad emission lines (including He II, He I, H$\beta$, and Fe II) with respect to the 5100 {\AA} continuum, and their time lags continuously vary through the years. Especially, the H$\beta$ time lags exhibited approximately a factor of two increase in the last two years. Additionally, the velocity-resolved time delays of the broad H$\beta$ emission line reveal a back-and-forth change between signs of virial motion and inflow in the BLR. The combination of negligible ($\sim$10%) continuum change and substantial time-lag variation (over two times) results in significant scatter in the intrinsic $R_{\rm H\beta}-L_{\rm 5100}$ relationship for PG 2130+099. Taking into account the consistent changes in the continuum variability time scale and the size of the BLR, we tentatively propose that the changes in the measurement of the BLR size may be affected by 'geometric dilution'., Comment: 21 pages, 13 figures, 7 tables; accepted for publication in ApJ

Relativistic polarized electron beams can find applications in broad areas of fundamental physics. Here, we propose for the first time that electron spin polarization can be realized efficiently via collective beam-target interactions. When a relativistic unpolarized electron beam is incident onto the surface of a solid target with a grazing angle, strong magnetic fields are induced at the target surface due to the formation of a high reflux of target electrons. This results in violent beam self-focusing and corresponding beam density increase via magnetic pinching. The pinched dense beam in turn further enhances the magnetic fields to the level of a few Giga-Gauss, which is high enough to trigger strong synchrotron radiation of ultrarelativistic electrons. During the interaction, electron spin polarization develops along the magnetic field direction, which is achieved via radiative spin flips in the quantum radiation-dominated regime. As a consequence, the incident electron beam can be effectively polarized via the spin-dependent radiation reaction, for example, the mean polarization of electrons with energy less than 2 GeV can reach above 50% for an initial 5GeV beam. This provides a robust way for the development of polarized electron sources.

We conduct a reverberation mapping (RM) campaign to spectroscopically monitor a sample of selected bright active galactic nuclei with large anticipated broad-line region (BLR) sizes adequate for spectroastrometric observations by the GRAVITY instrument on the Very Large Telescope Interferometer. We report the first results for five objects, IC 4329A, Mrk 335, Mrk 509, Mrk 1239, and PDS 456, among which Mrk 1239 and PDS 456 are for the first time spectroscopically monitored. We obtain multi-year monitoring data and perform multi-component spectral decomposition to extract the broad H$\beta$ profiles. We detect significant time lags between the H$\beta$ and continuum variations, generally obeying the previously established BLR size-luminosity relation. Velocity-resolved H$\beta$ time lags illustrate diverse, possibly evolving BLR kinematics. We further measure the H$\beta$ line widths from mean and rms spectra and the resulting virial products show good consistency among different seasons. Adopting a unity virial factor and the full width at half maximum of the broad H$\beta$ line from the mean spectrum as the measure of velocity, the obtained black hole mass averaged over seasons is $\log M_\bullet/M_\odot=8.02_{-0.14}^{+0.09}$, $6.92_{-0.12}^{+0.12}$, $8.01_{-0.25}^{+0.16}$, $7.44_{-0.14}^{+0.13}$, and $8.59_{-0.11}^{+0.07}$ for the five objects, respectively. The black hole mass estimations using other line width measures are also reported (up to the virial factors). For objects with previous RM campaigns, our mass estimates are in agreement with earlier results. In a companion paper, we will employ BLR dynamical modeling to directly infer the black hole mass and thereby determine the virial factors., Comment: 32 pages, 6 tables, 20 figures. To appear in ApJ

Reverberation mapping (RM) has long been a powerful tool for measuring the masses of supermassive black holes (SMBHs) at the centers of active galactic nuclei (AGNs), but the precision of these mass measurements depends on the so-called virial factors. It has been demonstrated that the virial factors exhibit significant diversity, spanning approximately 1-2 orders of magnitude across different AGNs. However, the underlying physical drivers for the diversity have not yet been finalized. Here, adopting the SMBH mass -- spheroid luminosity relations of inactive galaxies with different bulge classifications, we calibrate the virial factors corresponding to the AGNs with pseudobulges (PB) and classical bulges (or elliptical hosts, CB) using the latest nearby RM sample. We investigate the correlations between virial factors and the AGN spectral properties, and find that for both PB and CB samples, the FWHM-based virial factors exhibit significant anti-correlations with the emission-line widths and profiles, while the $\sigma_{\rm line}$-based virial factors only show moderate anti-correlations with line widths for PB. We attribute these correlations mainly to the inclination angle or opening angle of the broad-line regions. Moreover, we establish new relations to give more precise virial factors and, in combination with the latest iron-corrected radius-luminosity relation, develop tentatively new single-epoch estimators of SMBH masses, which enable more accurate measurements of SMBH masses in large AGN samples., Comment: 57 pages, 15 figures, 6 tables, accepted for publication in the Astrophysical Journal Supplement Series

We observed the Seyfert 1 galaxy Mrk817 during an intensive multi-wavelength reverberation mapping campaign for 16 months. Here, we examine the behavior of narrow UV absorption lines seen in HST/COS spectra, both during the campaign and in other epochs extending over 14 years. We conclude that while the narrow absorption outflow system (at -3750 km/s with FWHM=177 km/s) responds to the variations of the UV continuum as modified by the X-ray obscurer, its total column density (logNH =19.5 cm-2) did not change across all epochs. The adjusted ionization parameter (scaled with respect to the variations in the Hydrogen ionizing continuum flux) is log UH =-1.0. The outflow is located at a distance smaller than 38 parsecs from the central source, which implies a hydrogen density of nH > 3000 cm-3. The absorption outflow system only covers the continuum emission source and not the broad emission line region, which suggests that its transverse size is small (< 1e16 cm), with potential cloud geometries ranging from spherical to elongated along the line of sight., Comment: 18 pages, 12 Figures, Accepted for publication in ApJ

Decays $B\to DP\ell^+\nu_\ell~(\ell=e,\mu,\tau)$ with the non-resonance, the charmed vector resonances, the charmed scalar resonances and the charmed tensor resonances are calculated by using the SU(3) flavor symmetry. Firstly, the decay amplitudes of different modes are related by the SU(3) flavor symmetry. Then, relevant experiential data are used to constrain nonperturbative coefficients in the non-resonant and various resonant $B\to DP\ell^+\nu_\ell$ decays. Finally, using the constrained nonperturbative coefficients, the branching ratios of not-yet-measured $B\to D^*P\ell^+\nu_\ell$ decays with the non-resonant and various charmed resonant contributions are predicted. Many branching ratios are predicted for the first time. We find that $B\to D\eta'\ell^+\nu_\ell, B_s\to D_s\eta'\ell^+\nu_\ell$ decays only receive the non-resonant contributions, $B\to D_sK\ell^+\nu_\ell$, $B_s\to DK\ell^+\nu_\ell$, $B\to D\eta\ell^+\nu_\ell$ and $B_s\to D_s\eta\ell^+\nu_\ell$ decays receive both non-resonant and charmed tensor resonant contributions, $B^+\to D^-\pi^+\ell^+\nu_\ell$ decays receive the non-resonant, the charmed scalar resonant and the charmed tensor resonant contributions, and other $B\to D\pi\ell^+\nu_\ell$ decays receive all four kinds of contributions. These results can be used to test the SU(3) flavor symmetry approach in the four-body semileptonic decays by the future LHCb and Belle-II experiments., Comment: 16 pages. arXiv admin note: text overlap with arXiv:2403.14929

Representations from pre-trained speech foundation models (SFMs) have shown impressive performance in many downstream tasks. However, the potential benefits of incorporating pre-trained SFM representations into speaker voice similarity assessment have not been thoroughly investigated. In this paper, we propose SVSNet+, a model that integrates pre-trained SFM representations to improve performance in assessing speaker voice similarity. Experimental results on the Voice Conversion Challenge 2018 and 2020 datasets show that SVSNet+ incorporating WavLM representations shows significant improvements compared to baseline models. In addition, while fine-tuning WavLM with a small dataset of the downstream task does not improve performance, using the same dataset to learn a weighted-sum representation of WavLM can substantially improve performance. Furthermore, when WavLM is replaced by other SFMs, SVSNet+ still outperforms the baseline models and exhibits strong generalization ability., Comment: Accepted to INTERSPEECH 2024

With the accurate measurements of $\chi _{cJ}(J=0,1,2)$ charmonium decays, we explore $\chi _{cJ}\to \mathcal{B}_{8}\bar{\mathcal{B}}_{8}$ and $\mathcal{B}_{10}\bar{\mathcal{B}}_{10}$ decays based on the SU(3) flavor symmetry model, where $\mathcal{B}_{8}$ and $\mathcal{B}_{10}$ are light octet and decuplet baryons, respectively. The decay amplitude relations are determined by an effective interaction Hamiltonian. Then using experimental data and the amplitude relations of $\chi _{cJ}\to \mathcal{B}_{8}\bar{\mathcal{B}}_{8}$, $\mathcal{B}_{10}\bar{\mathcal{B}}_{10}$ decays, relative nonperturbative coefficients are constrained, and the branching ratios of unmeasured $\chi _{cJ}\to \mathcal{B}_{8}\bar{\mathcal{B}}_{8},\mathcal{B}_{10}\bar{\mathcal{B}}_{10}$, for examples, $\chi _{cJ}\to n\bar{n}$ and $\chi _{cJ}\to\Lambda \bar{\Sigma}^{0}+\bar{\Lambda} \Sigma^{0}$ channels, are predicted. Moreover, we discuss the case of adding a mixing angle between $\Lambda $ and $\Sigma ^{0}$, which is determined by the quark mass differences. Our results provide valuable insights that will aid in advancing our understanding of the mechanisms and characteristics of $\chi _{cJ}$ decays.

The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the incidence of misinterpretation and is difficult to distinguish from genuine content. Currently, machine learning techniques have been extensively studied for automatically detecting deepfakes. However, human perception has been less explored. Malicious deepfakes could ultimately cause public and social problems. Can we humans correctly perceive the authenticity of the content of the videos we watch? The answer is obviously uncertain; therefore, this paper aims to evaluate the human ability to discern deepfake videos through a subjective study. We present our findings by comparing human observers to five state-ofthe-art audiovisual deepfake detection models. To this end, we used gamification concepts to provide 110 participants (55 native English speakers and 55 non-native English speakers) with a webbased platform where they could access a series of 40 videos (20 real and 20 fake) to determine their authenticity. Each participant performed the experiment twice with the same 40 videos in different random orders. The videos are manually selected from the FakeAVCeleb dataset. We found that all AI models performed better than humans when evaluated on the same 40 videos. The study also reveals that while deception is not impossible, humans tend to overestimate their detection capabilities. Our experimental results may help benchmark human versus machine performance, advance forensics analysis, and enable adaptive countermeasures.

Stars and compact objects embedded in accretion disks of active galactic nuclei (AGNs), dubbed as ``accretion-modified star" (AMS), often experience hyper-Eddington accretion in the dense gas environment, resulting in powerful outflows as the Bondi explosion and formation of cavities. The varying gas properties across different regions of the AGN disk can give rise to diverse and intriguing phenomena. In this paper, we conduct a study on the characteristics of AMSs situated in the outer, middle, and inner regions of the AGN disk, where growth of the AMSs during the shift inwards is considered. We calculate their multiwavelength spectral energy distributions (SEDs) and thermal light curves. Our results reveal that the thermal luminosity of Bondi explosion occurring in the middle region leads to UV flares with a luminosity of $\sim 10^{44}\rm \,erg\,s^{-1}$. The synchrotron radiation of Bondi explosion in the middle and inner regions peaks at the X-ray band with luminosities of $\sim 10^{43}$ and $\sim 10^{42}\rm \,erg\,s^{-1}$, respectively. The $\gamma$-ray luminosity of inverse Compton radiation spans from $10^{42}$ to $10^{43}\rm \,erg\,s^{-1}$ peaked at $\sim 10\,$MeV (outer region) and $\sim$ GeV (middle and inner regions) bands. The observable flares of AMS in the middle region exhibits a slow rise and rapid Gaussian decay with a duration of months, while in the inner region, it exhibits a fast rise and slow Gaussian decay with a duration of several hours. These various SED and light curve features provides valuable insights into the various astronomical transient timescales associated with AGNs., Comment: 20 pages, 5 figures, 2 tables. Accepted for publication in ApJ

We test the potential of Bayesian synthesis of upcoming multi-instrument data to extract orbital parameters and individual light curves of close binary supermassive black holes (CB-SMBH) with subparsec separations. Next generation (ng) interferometers, will make possible the observation of astrometric wobbles in CB-SMBH. Combining them with periodic variable time-domain data from surveys like the Vera C. Rubin Legacy Survey of Space and Time (LSST), allows for a more information on CB-SMBH candidates compared to standalone observational methods. Our method reliably determines binary parameters and component fluxes from binary total flux across long-term, intermediate and short-term binary dynamics and observational configurations, assuming ten annual observations, even in short period "q-accrete" objects. Expected CB-SMBH astrometric wobbles constructed from binary dynamical parameters, might serve in refining observational strategies for CB-SMBH. Combination of inferred mass ratio, light curves of binary components, and observed photocenter wobbles can be a proxy for the activity states of CB-SMBH components., Comment: The article was accepted for publication in the ApJ

Two-color laser induced plasma filamentation in air could serve as tabletop sources of broadband terahertz (THz) pulses. Ubiquitous air in the earth facilitates its widespread utilities, particularly, in wireless communication and remote sensing, exploiting the unique advantage of the air-based scheme that the THz sources can be delivered over standoff distances via the pump laser propagation in air. However, the THz emission pattern inevitably has a conical angular profile with a dip in the propagation axis, therefore, THz energy concentration, propagation directionality, and accuracy of signal demodulation are significantly impaired, greatly limiting its direct applications. Here, we successfully eliminate the unfavorable conical profile by experiments and meanwhile enhance THz directionality and intensity by 17 folds by use of abruptly-autofocusing laser beams. Our theory and simulations show that these observations are attributed to efficient suppression of the dephasing effect appearing in previous investigations with ordinary Gaussian laser beams. This scheme is easily accessible since the abruptly-autofocusing beam can be achieved by imposing a spatial light modulator on the input Gaussian beam. This study solves a long-standing problem in the two-color laser scheme and clarifies the underlying physics of the conical angular profile formation., Comment: 22 pages, 4 figures, 1 table

Stellar black holes (sBHs) are widely believed to exist in the accretion disks of active galactic nuclei (AGNs). Previous studies often focus on the transient emission produced by embedded sBHs. Here, we explore the possible observational consequences of an AGN accretion disk that contains a population of accreting sBHs. Embedded accreting sBHs change the effective temperature distribution of the AGN accretion disk by heating gas in the outer regions. Two possible observational consequences are presented. First, the spectral energy distribution has a turnover feature at $\sim 4700\ \textrm{\AA}$ when the supermassive black hole (SMBH) mass is $\sim 10^8\ M_{\odot}$, which can help explain the observed shallow spectral shape at wavelengths $>5000\ \textrm{\AA}$ for the Sloan Digital Sky Survey quasar composite spectrum. Second, the half-light radius of a given relatively long wavelength is significantly larger than for an AGN disk without sBHs, which can be tested by microlensing observations. With appropriate sBH distributions, the model can be reconciled with quasar microlensing disk sizes. We propose that the half-light radius-wavelength relation can be utilized to investigate the distributions of embedded sBHs in AGN accretion disks., Comment: 11 pages, 5 figures, Accepted to ApJL

We report first-time reverberation mapping results for 14 AGNs from the ongoing Monitoring AGNs with H$\beta$ Asymmetry campaign (MAHA). These results utilize optical spectra obtained with the Long Slit Spectrograph on the Wyoming Infrared 2.3m Telescope between 2017 November-2023 May. MAHA combines long-duration monitoring with high cadence. We report results from multiple observing seasons for 9 of the 14 objects. These results include H$\beta$ time lags, supermassive black hole masses, and velocity-resolved time lags. The velocity-resolved lags allow us to investigate the kinematics of the broad-line region., Comment: 35 pages, 19 figures, accepted for publication in ApJ Supplement

Semileptonic three-body $D \to A\ell^+\nu_\ell$ decays, nonleptonic $A \to VP$ decays and semileptonic four-body $D \to A(A \to VP)\ell^+\nu_\ell$ strong or electromagnetic decays are analyzed by the SU(3) flavor symmetry/breaking approach, where $A$ denotes the axial-vector meson, $V$ denotes the vector meson, and $P$ denotes pseudoscalar meson. In terms of the SU(3) flavor symmetry/breaking, the decay amplitudes of the $D \to A \ell^+ \nu_\ell$ decays or the vertex coefficients of the $A \to VP$ decays are related. The relevant nonperturbative parameters are constrained by the present experimental data. Then the branching ratios of the $D \to A \ell^+ \nu_\ell $, $A \to VP$ and $D\to A(A\to VP)\ell^+\nu_\ell$ decays are predicted by the constrained parameters. We find that some branching ratios are large and they might be measured in the near future experiments. Moreover, the sensitivities of the branching ratios of $D \to A \ell^+ \nu_\ell $ and $A \to VP$ decays to the parameters are also shown, and some decay branching ratios are sensitive to the nonperturbative parameters., Comment: 29 pages, 6 figures

The recently proposed visually grounded speech model SpeechCLIP is an innovative framework that bridges speech and text through images via CLIP without relying on text transcription. On this basis, this paper introduces two extensions to SpeechCLIP. First, we apply the Continuous Integrate-and-Fire (CIF) module to replace a fixed number of CLS tokens in the cascaded architecture. Second, we propose a new hybrid architecture that merges the cascaded and parallel architectures of SpeechCLIP into a multi-task learning framework. Our experimental evaluation is performed on the Flickr8k and SpokenCOCO datasets. The results show that in the speech keyword extraction task, the CIF-based cascaded SpeechCLIP model outperforms the previous cascaded SpeechCLIP model using a fixed number of CLS tokens. Furthermore, through our hybrid architecture, cascaded task learning boosts the performance of the parallel branch in image-speech retrieval tasks., Comment: Accepted to ICASSP 2024, Self-supervision in Audio, Speech, and Beyond (SASB) workshop

ENN Science and Technology Development Co., Ltd. (ENN) is committed to generating fusion energy in an environmentally friendly and cost-effective manner, which requires abundant aneutronic fuel. Proton-boron ( p-$^{11}$B or p-B) fusion is considered an ideal choice for this purpose. Recent studies have suggested that p-B fusion, although challenging, is feasible based on new cross-section data, provided that a hot ion mode and high wall reflection can be achieved to reduce electron radiation loss. The high beta and good confinement of the spherical torus (ST) make it an ideal candidate for p-B fusion. By utilizing the new spherical torus energy confinement scaling law, a reactor with a major radius $R_0=4$ m, central magnetic field $B_0=6$ T, central temperature $T_{i0}=150$ keV, plasma current $I_p=30$ MA, and hot ion mode $T_i/T_e=4$ can yield p-B fusion with $Q>10$. A roadmap for p-B fusion has been developed, with the next-generation device named EHL-2. EHL stands for ENN He-Long, which literally means ``peaceful Chinese Loong". The main target parameters include $R_0\simeq1.05$ m, $A\simeq1.85$, $B_0\simeq3$ T, $T_{i0}\simeq30$ keV, $I_p\simeq3$ MA, and $T_i/T_e\geq2$. The existing ST device EXL-50 was simultaneously upgraded to provide experimental support for the new roadmap, involving the installation and upgrading of the central solenoid, vacuum chamber, and magnetic systems. The construction of the upgraded ST fusion device, EXL-50U, was completed at the end of 2023, and it achieved its first plasma in January 2024. The construction of EHL-2 is estimated to be completed by 2026., Comment: 16 pages, 8 figures

Many studies have shown that high-energy $\gamma$-photon beams can be efficiently generated via nonlinear Compton scattering driven by laser pulses with intensities $> 10^{22}\rm{W/cm^2}$ recently available in laboratories. Here, we propose a laserless scheme to efficiently generate high-energy polarized $\gamma$-photon beams by collision of two ultrarelativistic electron beams. The self-generated field of a dense driving electron beam provides the strong deflection field for the other ultrarelativistic seeding electron beam. A QED Monte Carlo code based on the locally constant field approximation is employed to simulate the collision process, and the polarization properties of produced $\gamma$ photons are investigated. The simulation results and theoretical analysis indicate that the photon polarization, including both linear and circular polarizations, can be tuned by changing the initial polarization of the seeding beam. If an unpolarized seeding beam is used, linearly polarized photons with an average polarization of 55\% can be obtained. If the seeding beam is transversely (longitudinally) polarized, the linear (circular) polarization of photons above 3 GeV can reach 90\% (67\%), which is favorable for highly polarized, high-energy $\gamma$ photon sources., Comment: 12 pages, 8 figures

Stable transport of laser beams in highly over-dense plasmas is of significance in fast ignition of inertial confinement fusion, relativistic electrons generation, and powerful electromagnetic emission, but hard to realize. Early in 1996, Harris proposed an electromagnetically induced transparency (EIT) mechanism, analogous to the concept in atom physics, to transport a low-frequency (LF) laser in over-dense plasmas aided by a high-frequency pump laser. However, subsequent investigations show that EIT cannot occur in real plasmas with boundaries. Here, our particle-in-cell simulations show that EIT can occur in strongly-relativistic regime and results in stable propagation of a LF laser in bounded plasmas with tens of its critical density. A relativistic three-wave coupling model is developed, and the criteria and frequency passband for EIT occurrence are presented. The passband is sufficiently wide in strongly-relativistic regime, allowing EIT to work sustainably. Nevertheless, it is narrowed to nearly an isolated point in weakly-relativistic regime, which can explain the quenching of EIT in bounded plasmas found in previous investigations.

This paper introduces HAAQI-Net, a non-intrusive deep learning model for music audio quality assessment tailored for hearing aid users. Unlike traditional methods like the Hearing Aid Audio Quality Index (HAAQI), which rely on intrusive comparisons to a reference signal, HAAQI-Net offers a more accessible and efficient alternative. Using a bidirectional Long Short-Term Memory (BLSTM) architecture with attention mechanisms and features from the pre-trained BEATs model, HAAQI-Net predicts HAAQI scores directly from music audio clips and hearing loss patterns. Results show HAAQI-Net's effectiveness, with predicted scores achieving a Linear Correlation Coefficient (LCC) of 0.9368, a Spearman's Rank Correlation Coefficient (SRCC) of 0.9486, and a Mean Squared Error (MSE) of 0.0064, reducing inference time from 62.52 seconds to 2.54 seconds. Although effective, feature extraction via the large BEATs model incurs computational overhead. To address this, a knowledge distillation strategy creates a student distillBEATs model, distilling information from the teacher BEATs model during HAAQI-Net training, reducing required parameters. The distilled HAAQI-Net maintains strong performance with an LCC of 0.9071, an SRCC of 0.9307, and an MSE of 0.0091, while reducing parameters by 75.85% and inference time by 96.46%. This reduction enhances HAAQI-Net's efficiency and scalability, making it viable for real-world music audio quality assessment in hearing aid settings. This work also opens avenues for further research into optimizing deep learning models for specific applications, contributing to audio signal processing and quality assessment by providing insights into developing efficient and accurate models for practical applications in hearing aid technology.

During the ultraintense laser interaction with solids (overdense plasmas), the competition between two possible quantum electrodynamics (QED) mechanisms responsible for $e^\pm$ pair production, i.e., linear and nonlinear Breit-Wheeler (BW) processes, remains to be studied. Here, we have implemented the linear BW process via a Monte Carlo algorithm into the QED particle-in-cell (PIC) code YUNIC, enabling us to self-consistently investigate both pair production mechanisms in the plasma environment. By a series of 2D QED-PIC simulations, the transition from the linear to the nonlinear BW process is observed with the increase of laser intensities in the typical configuration of a linearly polarized laser interaction with solid targets. A critical normalized laser amplitude about $a_0\sim$ 400-500 is found under a large range of preplasma scale lengths, below which the linear BW process dominates over the nonlinear BW process. This work provides a practicable technique to model linear QED processes via integrated QED-PIC simulations. Moreover, it calls for more attention to be paid to linear BW pair production in near future 10-PW-class laser-solid interactions., Comment: 8 pages, 3 figures

After the successful fusion ignition at National Ignition Facility, seeking for a high-gain fusion scheme becomes the next hot-spot in inertial confinement fusion community. Fast ignition provides an alternative due to its potential to reduce the energy of driven lasers and achieve higher target gain, whose core step is generating fast electron beam using picosecond lasers. The properties of the electron beam, such as energy spectra, determines the succeed heating process and the yield. In this study, with 2D particle-in-cell simulations, we find that the energy transfer ratio would significantly increase, and the energy spectra would be lifted up in the dual-color injecting scheme, where an extra weak low-frequency laser is injected with the main pulse. These phenomena are attributed to the longitudinal electric field modulation in low-density region and electromagnetically-induced-transparency process in the microchannels formed near the critical surface. Our results can be applied to fast ignition schemes and experimental designs of super-hot electron generation with different pulse durations. For example, in the DCI project with a fast ignition scheme, such a dual-color intense picosecond laser facility is under construction to control the fast electron generation and enhance the laser transparency., Comment: 24 pages, 8 figures

Relativistic positron sources with high spin polarization have important applications in nuclear and particle physics and many frontier fields. However, it is challenging to produce dense polarized positrons. Here we present a simple and effective method to achieve such a positron source by directly impinging a relativistic high-density electron beam on the surface of a solid target. During the interaction, a strong return current of plasma electrons is induced and subsequently asymmetric quasistatic magnetic fields as high as megatesla are generated along the target surface. This gives rise to strong radiative spin flips and multiphoton processes, thus leading to efficient generation of copious polarized positrons. With three-dimensional particle-in-cell simulations, we demonstrate the production of a dense highly-polarized multi-GeV positron beam with an average spin polarization above 40% and nC-scale charge per shot. This offers a novel route for the studies of laserless strong-field quantum electrodynamics physics and for the development of high-energy polarized positron sources.

Without the need for a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. While deep learning models have been used to develop non-intrusive speech assessment methods with promising results, there is limited research on hearing-impaired subjects. This study proposes a multi-objective non-intrusive hearing-aid speech assessment model, called HASA-Net Large, which predicts speech quality and intelligibility scores based on input speech signals and specified hearing-loss patterns. Our experiments showed the utilization of pre-trained SSL models leads to a significant boost in speech quality and intelligibility predictions compared to using spectrograms as input. Additionally, we examined three distinct fine-tuning approaches that resulted in further performance improvements. Furthermore, we demonstrated that incorporating SSL models resulted in greater transferability to OOD dataset. Finally, this study introduces HASA-Net Large, which is a non-invasive approach for evaluating speech quality and intelligibility. HASA-Net Large utilizes raw waveforms and hearing-loss patterns to accurately predict speech quality and intelligibility levels for individuals with normal and impaired hearing and demonstrates superior prediction performance and transferability.

A novel defect control approach based on laminated HfO$_2$/ZrO$_2$ with multifunctional TiN/Mo/TiOxNy electrode is proposed to significantly improve the endurance and data retention in HZO-based ferroelectric capacitor. The O-rich interface reduces leakage current and prolong the endurance up to 1011 cycles while retaining a 2Pr value of 34 ($\mu$C/cm$^2$ ) at 3.4MV/cm. Using first-principles calculations and experiments, we demonstrate that the enhancement of endurance is ascribed to the higher migration barrier of oxygen vacancies within the laminated HZO film and higher work function of MoO$_x$/TiO$_x$N$_y$ between top electrode and the insulating oxide. This 2.5-nm-thick TiOxNy barrier further increase the grain size of HZO, lowering the activation field and thus improving polarization reversal speed. This interfacial layer further decreases the overall capacitance, increases the depolarization field, thereby enhancing the data retention. By fitting the data using the Arrhenius equation, we demonstrate a 10-year data retention is achieved at 109.6 $^\circ$C, surpassing traditional SS-HZO of 78.2 $^\circ$C with a 450$^\circ$C RTA (required by backend-of-the-line). This work elucidates that interfacial engineering serves as a crucial technology capable of resolving the endurance, storage capability, and high-temperature data retention issues for ferroelectric memory., Comment: 7 pages, 6 figures

Multimodal manipulations (also known as audio-visual deepfakes) make it difficult for unimodal deepfake detectors to detect forgeries in multimedia content. To avoid the spread of false propaganda and fake news, timely detection is crucial. The damage to either modality (i.e., visual or audio) can only be discovered through multi-modal models that can exploit both pieces of information simultaneously. Previous methods mainly adopt uni-modal video forensics and use supervised pre-training for forgery detection. This study proposes a new method based on a multi-modal self-supervised-learning (SSL) feature extractor to exploit inconsistency between audio and visual modalities for multi-modal video forgery detection. We use the transformer-based SSL pre-trained Audio-Visual HuBERT (AV-HuBERT) model as a visual and acoustic feature extractor and a multi-scale temporal convolutional neural network to capture the temporal correlation between the audio and visual modalities. Since AV-HuBERT only extracts visual features from the lip region, we also adopt another transformer-based video model to exploit facial features and capture spatial and temporal artifacts caused during the deepfake generation process. Experimental results show that our model outperforms all existing models and achieves new state-of-the-art performance on the FakeAVCeleb and DeepfakeTIMIT datasets.