Search

The massive semi-detached binary with a long-term decreasing orbital period may involve a rapid mass-transfer phase in Case A, and thus they are good astrophysical laboratories for investigating the evolution of massive binary stars. In this work, by using the long-term observational light curves from the OGLE project and other data in the low-metallicity LMC, four semi-detached massive binaries with long-term decreases in the orbital periods are detected from 165 EB-type close binaries. It is found that the more massive component in S07798 is filling its Roche lobe where the period decrease is caused by mass transfer from the primary to the secondary. However, the other three (S03065, S12631, S16873) are semi-detached binaries with a lobe-filling secondary where the mass transfer between the components should cause the period to increase if the angular momentum is conservative. The long-term period decreases in these three systems may be caused by the angular momentum loss. Additionally, the orbital periods of three systems (S03065, S07798, S16873) are detected to show cyclic variation with periods shorter than 11 years, which can be plausibly explained by the presence of close-in third bodies in these massive binaries. Based on all of these results, it is suggested that the detected four semi-detached binaries almost have multiplicity. The companion stars are crucial for the origin and evolution of these massive close binaries.

Knowledge Distillation (KD), a learning manner with a larger teacher network guiding a smaller student network, transfers dark knowledge from the teacher to the student via logits or intermediate features, with the aim of producing a well-performed lightweight model. Notably, many subsequent feature-based KD methods outperformed the earliest logit-based KD method and iteratively generated numerous state-of-the-art distillation methods. Nevertheless, recent work has uncovered the potential of the logit-based method, bringing the simple KD form based on logits back into the limelight. Features or logits? They partially implement the KD with entirely distinct perspectives; therefore, choosing between logits and features is not straightforward. This paper provides a unified perspective of feature alignment in order to obtain a better comprehension of their fundamental distinction. Inheriting the design philosophy and insights of feature-based and logit-based methods, we introduce a block-wise logit distillation framework to apply implicit logit-based feature alignment by gradually replacing teacher's blocks as intermediate stepping-stone models to bridge the gap between the student and the teacher. Our method obtains comparable or superior results to state-of-the-art distillation methods. This paper demonstrates the great potential of combining logit and features, and we hope it will inspire future research to revisit KD from a higher vantage point.

Instant Messaging is a popular means for daily communication, allowing users to send text and stickers. As the saying goes, "a picture is worth a thousand words", so developing an effective sticker retrieval technique is crucial for enhancing user experience. However, existing sticker retrieval methods rely on labeled data to interpret stickers, and general-purpose Vision-Language Models (VLMs) often struggle to capture the unique semantics of stickers. Additionally, relevant-based sticker retrieval methods lack personalization, creating a gap between diverse user expectations and retrieval results. To address these, we propose the Personalized Sticker Retrieval with Vision-Language Model framework, namely PerSRV, structured into offline calculations and online processing modules. The online retrieval part follows the paradigm of relevant recall and personalized ranking, supported by the offline pre-calculation parts, which are sticker semantic understanding, utility evaluation and personalization modules. Firstly, for sticker-level semantic understanding, we supervised fine-tuned LLaVA-1.5-7B to generate human-like sticker semantics, complemented by textual content extracted from figures and historical interaction queries. Secondly, we investigate three crowd-sourcing metrics for sticker utility evaluation. Thirdly, we cluster style centroids based on users' historical interactions to achieve personal preference modeling. Finally, we evaluate our proposed PerSRV method on a public sticker retrieval dataset from WeChat, containing 543,098 candidates and 12,568 interactions. Experimental results show that PerSRV significantly outperforms existing methods in multi-modal sticker retrieval. Additionally, our fine-tuned VLM delivers notable improvements in sticker semantic understandings.

This work is a continuation of the program initiated in [arXiv:2311.18302]. We show how one can define novel gauge-theoretic (holomorphic) Floer homologies of seven, six, and five-manifolds, from the physics of a topologically-twisted 8d $\mathcal{N}=1$ gauge theory on a Spin$(7)$-manifold via its supersymmetric quantum mechanics interpretation. They are associated with $G_2$ instanton, Donaldson-Thomas, and Haydys-Witten configurations on the seven, six, and five-manifolds, respectively. We also show how one can define hyperk\"ahler Floer homologies specified by hypercontact three-manifolds, and symplectic Floer homologies of instanton moduli spaces. In turn, this will allow us to derive Atiyah-Floer type dualities between the various gauge-theoretic Floer homologies and symplectic intersection Floer homologies of instanton moduli spaces. Via a 2d gauged Landau-Ginzburg model interpretation of the 8d theory, one can derive novel Fukaya-Seidel type $A_\infty$-categories that categorify Donaldson-Thomas, Haydys-Witten, and Vafa-Witten configurations on six, five, and four-manifolds, respectively, where an Atiyah-Floer type correspondence for the Donaldson-Thomas case can be established. Last but not least, topological invariance of the theory suggests a relation amongst these Floer homologies and Fukaya-Seidel type $A_\infty$-categories for certain Spin$(7)$-manifolds. Our work therefore furnishes purely physical proofs and generalizations of the conjectures by Donaldson-Thomas [2], Donaldson-Segal [3], Cherkis [4], Hohloch-Noetzel-Salamon [5], Salamon [6], Haydys [7], and Bousseau [8], and more., Comment: 82 pp

The integration of ferroelectrics with semiconductors is crucial for developing functional devices, such as field-effect transistors, tunnel junctions, and nonvolatile memories. However, the synthesis of high-quality single-crystalline ferroelectric nitride perovskites has been limited, hindering a comprehensive understanding of their switching dynamics and potential applications. Here we report the synthesis and characterizations of epitaxial single-phase ferroelectric cerium tantalum nitride (CeTaN3) on both oxides and semiconductors. The polar symmetry of CeTaN3 was confirmed by observing the atomic displacement of central ions relative to the center of the TaN6 octahedra, as well as through optical second harmonic generation. We observed switchable ferroelectric domains in CeTaN3 films using piezo-response force microscopy, complemented by the characterization of square-like polarization-electric field hysteresis loops. The remanent polarization of CeTaN3 reaches approximately 20 uC/cm2 at room temperature, consistent with theoretical calculations. This work establishes a vital link between ferroelectric nitride perovskites and their practical applications, paving the way for next-generation information and energy-storage devices with enhanced performance, scalability, and manufacturability., Comment: 47 pages, 4 figures

Strong gravitational lensing has significantly advanced the study of high-redshift galaxies, particularly those from the very early universe. However, the spectral analysis of lensed galaxies is inevitably affected by the differential magnification effect, which introduces biases into the derived properties. In this work, we investigate such biases in mock lensing systems generated with data from MaNGA survey and IllustrisTNG simulations. We study the changes of several spectral properties (stellar metallicity, age, flux of H$\alpha$ emission line and flux ratios of optical emission lines) before and after being lensed. Our result shows that all of these properties are significantly biased after being lensed and can be either over- or under-estimated, except for the consistently increasing H$\alpha$ flux. We also investigate the variations of biases with different lensing configurations and find that it always exists when part of the source galaxy falls into the strong lensing regime. Considering the prevalence of such biases, we examine two correction methods to recover the intrinsic source properties, with average magnification factor ($\bar{\mu}$) and full ray-tracing, respectively. Our findings reveal that both methods can reduce the overestimation of H$\alpha$ flux while the value corrected with $\bar{\mu}$ shows a larger discrepancy. For stellar population properties and emission line ratios, the $\bar{\mu}$ method fails to correct the biases, whereas the full ray-tracing method works effectively. The application of these two methods to a statistical sample of mock systems further shows their strong dependence on the accuracy of lens modeling. Our study indicates that spatially resolved spectroscopic observations of lensed images and precise lens modeling are crucial for the spectral analysis of strongly lensed high-redshift galaxies., Comment: 15 pages, 12 figures (including 3 in the appendix), 2 tables, submitted to MNRAS

Despite AI advancements, individuals without software or hardware expertise still face barriers in designing wearable electronic devices due to the lack of code-free prototyping tools. To eliminate these barriers, we designed ProtoBot, leveraging large language models, and conducted a case study with four professionals from different disciplines through playful interaction. The study resulted in four unique wearable device concepts, with participants using Protobot to prototype selected components. From this experience, we learned that (1) uncertainty can be turned into a positive experience, (2) the ProtoBot should transform to reliably act as a guide, and (3) users need to adjust design parameters when interacting with the prototypes. Our work demonstrates, for the first time, the use of large language models in rapid prototyping of wearable electronics. We believe this approach will pioneer rapid prototyping without fear of uncertainties for people who want to develop both wearable prototypes and other products., Comment: 12 pages, 2 figures

The discovery of superconductivity in the Ba-La-Cu-O system (the cuprate) at the 30 K range in 1986 marked a significant breakthrough, as it far exceeded the highest known critical temperature ($T_c$) at the time and surpassed the predicted 30 K limit, which was thought to be the maximum before phonon-mediated electron pairing would break down due to thermal excitation. Despite recent successful observations of superconductivity in nickel-oxide-based compounds (the nickelate), superconductivity above 30 K at ambient pressure in a system that is isostructural and isoelectronic to the cuprate but without copper has remained elusive. Here, we report a superconducting $T_c$ above 35 K under ambient pressure in hole-doped, late rare-earth infinite-layer nickel oxide (Sm-Eu-Ca-Sr)NiO$_2$ thin films. Electron microscopy reveals a small thickness of ~2 nm of infinite-layer phase stabilised at present, which indicates a higher temperature superconductivity should be observable in clean bulk crystals., Comment: Main: 14 pages, 6 figures; Supplementary: 13 pages, 9 figures

Gravitationally strongly lensed quasars (SL-QSO) offer invaluable insights into cosmological and astrophysical phenomena. With the data from ongoing and next-generation surveys, thousands of SL-QSO systems can be discovered expectedly, leading to unprecedented opportunities. However, the challenge lies in identifying SL-QSO from enormous datasets with high recall and purity in an automated and efficient manner. Hence, we developed a program based on a Convolutional Neural Network (CNN) for finding SL-QSO from large-scale surveys and applied it to the Kilo-degree Survey Data Release 5 (KiDS DR5). Our approach involves three key stages: firstly, we pre-selected ten million bright objects (with $r$-band $\tt{MAG\_AUTO} < 22$), excluding stars from the dataset; secondly, we established realistic training and test sets to train and fine-tune the CNN, resulting in the identification of 4195 machine candidates, and the false positive rate (FPR) of $\sim$1/2000 and recall of 0.8125 evaluated by using the real test set containing 16 confirmed lensed quasars; thirdly, human inspections were performed for further selections, and then 272 SL-QSO candidates were eventually found in total, including 16 high-score, 118 median-score, and 138 lower-score candidates, separately. Removing the systems already confirmed or identified in other papers, we end up with 229 SL-QSO candidates, including 7 high-score, 95 median-score, and 127 lower-score candidates, and the corresponding catalog is publicly available online., Comment: 11 Figures, 4 Tables. Submitted to ApJ. Comments Welcome!

Gamma-ray bursts (GRBs) are the most luminous transients in the universe. The interaction of the relativistic jet with the circumburst medium produces an afterglow and generates multiwavelength emission. In this work, we present simultaneous multiband photometry of GRB~240825A with the Multi-channel Photometric Survey Telescope (Mephisto) and analyze its temporal and spectral properties. The measurement began 128 seconds after the GRB trigger and continued until the fourth day when the afterglow essentially diminished and the measured brightness was close to that of the host galaxy. Based on the multiband light curves in the $uvgriz$ bands, we find that the optical flux density satisfies $F_{\nu,{\rm obs}}\propto t^{-1.34}\nu^{-2.48}$ with a spectral index of $2.48$ much larger than those of most other GRBs. To reconcile the measured much softer spectral energy distribution (SED) with that predicted by the standard afterglow model, an extra host-galaxy extinction of $E_{B-V}\sim(0.37-0.57)$ mag is required. We interpreted this excess as arising from a dense circumburst medium. We further find that the SED of the optical afterglow hardened as the afterglow decayed and the color excess $E_{B-V}$ decreased $\sim0.21$ mag in the first 3000 seconds. Finally, we analyze the properties of the host galaxy of GRB~240825A based on data from the SDSS, PanSTARRS and HSC-SSP surveys. For a host redshift of $z=0.659$, the stellar mass and star formation rate of the host galaxy are estimated to be $\log(M_*/M_\odot)=10.0^{+0.3}_{-0.3}$ and $\log({\rm SFR}/M_{\odot}{\rm yr}^{-1})= 0.6^{+0.8}_{-3.3}$, respectively, pointing to a gas-rich, star-forming, medium-size galaxy., Comment: 15 pages, 5 figures, 1 table. Comments welcome!

The early time observations of Type Ia supernovae (SNe Ia) play a crucial role in investigating and resolving longstanding questions about progenitor stars and the explosion mechanisms of these events. Colors of supernovae (SNe) in the initial days after the explosion can help differentiate between different types of SNe. However, the use of true color information to identify SNe Ia at the early-time explosion is still in its infancy. The Multi-channel Photometric Survey Telescope (Mephisto) is a photometric survey telescope equipped with three CCD cameras, capable of simultaneously imaging the same patch of sky in three bands (\emph{u, g, i} or \emph{v, r, z}), yielding real-time colors of astronomical objects. In this paper, we introduce a new time-series classification tool named Mephisto Early Supernovae Ia Rapid Identifier (\emph{\texttt{Mesiri}}), which for the first time, utilizes real-time color information to distinguish early-time SNe Ia from core-collapse supernovae (CCSNe). \emph{\texttt{Mesiri}} is based on the deep learning approach and can achieve an accuracy of $96.75\pm0.79$\%, and AUC of $98.87\pm0.53$\% in case of single epoch random observation before the peak brightness. These values reach towards perfectness if additional data points on several night observations are considered. The classification with real-time color significantly outperforms that with pseudo-color, especially at the early time, i.e., with only a few points of observations. The architecture of BiLSTM shows the best performance than the others that have been tested in this work., Comment: 30 pages, 17 figures, 4 tables, accepted for publication in RAA

Heartbeat stars (HBSs) with tidally excited oscillations (TEOs) are ideal astrophysical laboratories for studying the internal properties of the systems. In this paper, five new HBSs exhibiting TEOs are discovered using TESS photometric data. The orbital parameters are derived using a corrected version of Kumar et al.'s model based on the Markov Chain Monte Carlo (MCMC) method. The TEOs in these objects are examined, and their pulsation phases and modes are identified. The pulsation phases of the TEOs in TIC 266809405, TIC 266894805, and TIC 412881444 are consistent with the dominant $l=2$, $m=0$, or $\pm2$ spherical harmonic. For TIC 11619404, although the TEO phase is close to the $m=+2$ mode, the $m = 0$ mode cannot be excluded because of the low inclination in this system. The TEO phase in TIC 447927324 shows a large deviation ($>2\sigma$) from the adiabatic expectations, suggesting that it is expected to be a traveling wave rather than a standing wave. In addition, these TEOs occur at relatively low orbital harmonics, and we cautiously suggest that this may be an observational bias. These objects are valuable sources for studying the structure and evolution of eccentricity orbit binaries and extending the TESS HBS catalog with TEOs., Comment: 9pages, 5figures

Heartbeat stars (HBSs) are ideal astrophysical laboratories to study the formation and evolution of binary stars in eccentric orbits and the internal structural changes of their components under strong tidal action. We discover 23 new HBSs based on TESS photometric data. The orbital parameters, including orbital period, eccentricity, orbital inclination, argument of periastron, and epoch of periastron passage of these HBSs are derived by using a corrected version of Kumar et al.'s model based on the Markov Chain Monte Carlo (MCMC) method. The preliminary results show that these HBSs have orbital periods in the range from 2.7 to 20 days and eccentricities in the range from 0.08 to 0.70. The eccentricity-period relation of these objects shows a positive correlation between eccentricity and period, and also shows the existence of orbital circularization. The Hertzsprung-Russell diagram shows that the HBSs are not all located in a particular area. The distribution of the derived parameters suggests a selection bias within the TESS survey towards massive HBSs with shorter orbital periods, higher temperatures and luminosities. These objects are a very useful source to study the structure and evolution of eccentricity orbit binaries and to extend the TESS HBS catalog., Comment: 10 pages, 7 figures

We report on the first measurement of the elemental fragmentation cross sections (EFCSs) of $^{29-33}\mathrm{Si}$ on a carbon target at $\sim$230~MeV/nucleon. The experimental data covering charge changes of $\Delta Z$ = 1-4 are reproduced well by the isospin-dependent quantum molecular dynamics (IQMD) coupled with the evaporation GEMINI (IQMD+GEMINI) model. We further explore the mechanisms underlying the single-proton removal reaction in this model framework. We conclude that the cross sections from direct proton knockout exhibit a overall weak dependence on the mass number of $\mathrm{Si}$ projectiles. The proton evaporation induced after the projectile excitation significantly affects the cross sections for neutron-deficient $\mathrm{Si}$ isotopes, while neutron evaporation plays a crucial role in the reactions of neutron-rich $\mathrm{Si}$ isotopes. It is presented that the relative magnitude of one-proton and one-neutron separation energies is an essential factor that influences evaporation processes., Comment: 7 pages, 4 figures

Strong gravitationally lensed supernovae (SNe) are a powerful probe for cosmology and stellar physics. The relative time delays between lensed SN images provide an independent way of measuring a fundamental cosmological parameter -- the Hubble constant -- , the value of which is currently under debate. The time delays also serve as a ``time machine'', offering a unique opportunity to capture the extremely early phase of the SN explosion, which can be used to constrain the SN progenitor and explosion mechanism. Although there are only a handful of strongly lensed SN discoveries so far, which greatly hinders scientific applications, the sample size is expected to grow substantially with next-generation surveys. In this work, we investigate the capability of detecting strongly lensed SNe with the China Space Station Telescope (CSST), a two-meter space telescope to be launched around 2026. Through Monte Carlo simulations, we predict that CSST can detect 1008.53 and 51.78 strongly lensed SNe from its Wide Field Survey (WFS, covering 17,500 deg$^2$) and Deep Field Survey (DFS, covering 400 deg$^2$) over the course of ten years. In both surveys, about 35\% of the events involve Type Ia SNe as the background sources. Our results suggest that the WFS and DFS of CSST, although not designed or optimized for discovering transients, can still make a great contribution to the strongly lensed SNe studies., Comment: 14 pages, 13 figures

To detect additional bodies in binary systems, we performed a potent approach of orbital period variation analysis. In this work, we present 90 new mid-eclipse times of a short-period eclipsing binary system. Observations were made using two telescopes from 2014 to 2024, extending the time span of the O-C diagram to 24 years. The data obtained in the last seven years indicate significant deviations in the O-C diagram from the models obtained in previous studies. We investigated whether this variation could be explained by mechanisms such as the LTT effect or Applegate. To investigate the cyclic behaviour observed in the system with the LTT effect, we modelled the updated O-C diagram using different models including linear/quadratic terms and additional bodies. The updated O-C diagram is statistically consistent with the most plausible solutions of models that include multiple brown dwarfs close to each other. However, it has been found that the orbit of the system is unstable on short time scales. Using three different theoretical definitions, we have found that the Applegate mechanism cannot explain the variation in the orbital period except for the model containing the fifth body. Therefore, due to the complex nature of the system, further mid-eclipse time is required before any conclusions can be drawn about the existence of additional bodies., Comment: 10 pages, 5 figures, accepted for publication in PASA

We consider a distributed learning problem, where agents minimize a global objective function by exchanging information over a network. Our approach has two distinct features: (i) It substantially reduces communication by triggering communication only when necessary, and (ii) it is agnostic to the data-distribution among the different agents. We can therefore guarantee convergence even if the local data-distributions of the agents are arbitrarily distinct. We analyze the convergence rate of the algorithm and derive accelerated convergence rates in a convex setting. We also characterize the effect of communication drops and demonstrate that our algorithm is robust to communication failures. The article concludes by presenting numerical results from a distributed LASSO problem, and distributed learning tasks on MNIST and CIFAR-10 datasets. The experiments underline communication savings of 50% or more due to the event-based communication strategy, show resilience towards heterogeneous data-distributions, and highlight that our approach outperforms common baselines such as FedAvg, FedProx, and FedADMM., Comment: 29 pages, 12 figures

SN 2023ixf, recently reported in the nearby galaxy M101 at a distance of $6.85~{\rm Mpc}$, was one of the closest and brightest core-collapse supernovae (CCSNe) in the last decade. In this work, we present multi-wavelength photometric observation of SN 2023ixf with the Multi-channel Photometric Survey Telescope (Mephisto) in $uvgr$ bands and with the twin 50-cm telescopes in $griz$ bands. We find that the bolometric luminosity reached the maximum value of $3\times10^{43}~{\rm erg~s^{-1}}$ at 3.9 days after the explosion and fully settled onto the radioactive tail at $\sim90$ days. The effective temperature decreased from $3.2\times10^4~{\rm K}$ at the first observation and approached to a constant of $\sim(3000-4000)~{\rm K}$ after the first two months. The evolution of the photospheric radius is consistent with a homologous expansion with a velocity of $8700~{\rm km~s^{-1}}$ in the first two months, and it shrunk subsequently. Based on the radioactive tail, the initial nickel mass is about $M_{\rm Ni}\sim 0.098M_\odot$. The explosion energy and the ejecta mass are estimated to be $E\simeq(1.0-5.7)\times10^{51}~{\rm erg}$ and $M_{\rm ej}\simeq(3.8-16)M_\odot$, respectively. The peak bolometric luminosity is proposed to be contributed by the interaction between the ejecta and the circumstellar medium (CSM). We find a shocked CSM mass of $M_{\rm CSM}\sim0.013M_\odot$, a CSM density of $\rho_{\rm CSM}\sim2.5\times10^{-13}~{\rm g~cm^{-3}}$ and a mass loss rate of the progenitor of $\dot M\sim0.022M_\odot~{\rm yr^{-1}}$., Comment: 15 pages, 7 figures, 3 tables. Accepted for publication in ApJ. Comments welcome!

We present early-phase good-cadence (hour-to-day) simultaneous multiband ($ugi$ and $vrz$ bands) imaging of the nearby supernova SN~2024ggi, which exploded in the nearby galaxy, NGC 3621. A quick follow-up was conducted within less than a day after the explosion and continued $\sim$23 days. The $uvg$ band light curves display a rapid rise ($\sim$1.4 mag day$^{-1}$) to maximum in $\sim$4 days and absolute magnitude $M_{g}\sim$--17.75 mag. The post-peak decay rate in redder bands is $\sim$0.01 mag day$^{-1}$. Different colors (e.g., $u-g$ and $v-r$) of SN~2024ggi are slightly redder than SN 2023ixf. A significant rise ($\sim$12.5 kK) in black-body temperature (optical) was noticed within $\sim$2 days after the explosion, which successively decreased, indicating shock break out inside a dense circumstellar medium (CSM) surrounding the progenitor. Using semianalytical modeling, the ejecta mass and progenitor radius were estimated as 1.2 $M_\odot$ and $\sim$550 $R_\odot$. The archival deep images ($g,r,i and z$ bands) from the Dark Energy Camera Legacy Survey were examined, and a possible progenitor was detected in each band ($\sim$22--22.5 mag) and had a mass range of 14--17 $M_\odot$., Comment: Pages 12, Table 1, Figures 7

We present the eclipsing Heartbeat Star KIC 9704906 with tidally excited oscillations (TEOs) and gamma Doradus/delta Scuti hybrid pulsations. The derived parameters show that it has an orbital period of $P$=8.7529108(1) days, a high eccentricity of $e$=0.467(3), and a high inclination of $i$=78$^{\circ}$.81(6). The mass ratio $q$=0.981(5), the relative radii (radius divided by semi-major axis) $r_1$=0.0639(2), and $r_2$=0.0715(4) indicate that the secondary component has a less mass and a larger radius, and may have evolved off the main sequence. The eight derived TEO candidates, $n$ = 3, 4, 5, 6, 7, 12, 40, and 44 harmonics, are consistent with or close to the dominant spherical harmonic $l=2$, $m=0$, or $\pm2$, assuming that the spin and orbital axes are aligned, and the pulsations are adiabatic and standing waves. We also identify ten independent frequency candidates, but one of them, $\mathit{f_{7}}$, is more like a modulation of a quasi-periodic signal and the orbits. According to the g-mode frequencies, we find that the rotation period of one component is 11.52(29) days. Although the masses and radii cannot be further constrained due to the lack of sufficient high-precision spectra, the fascinating phenomena in the Fourier spectra are evident and valuable in this system.

Whilst holding great promise for low noise, ease of operation and networking, useful photonic quantum computing has been precluded by the need for beyond-state-of-the-art components, manufactured by the millions. Here we introduce a manufacturable platform for quantum computing with photons. We benchmark a set of monolithically-integrated silicon photonics-based modules to generate, manipulate, network, and detect photonic qubits, demonstrating dual-rail photonic qubits with $99.98\% \pm 0.01\%$ state preparation and measurement fidelity, Hong-Ou-Mandel quantum interference between independent photon sources with $99.50\%\pm0.25\%$ visibility, two-qubit fusion with $99.22\%\pm0.12\%$ fidelity, and a chip-to-chip qubit interconnect with $99.72\%\pm0.04\%$ fidelity, not accounting for loss. In addition, we preview a selection of next generation technologies, demonstrating low-loss silicon nitride waveguides and components, fabrication-tolerant photon sources, high-efficiency photon-number-resolving detectors, low-loss chip-to-fiber coupling, and barium titanate electro-optic phase shifters., Comment: 8 pages, 5 figures

In this work, we introduce a lightweight discourse connective detection system. Employing gradient boosting trained on straightforward, low-complexity features, this proposed approach sidesteps the computational demands of the current approaches that rely on deep neural networks. Considering its simplicity, our approach achieves competitive results while offering significant gains in terms of time even on CPU. Furthermore, the stable performance across two unrelated languages suggests the robustness of our system in the multilingual scenario. The model is designed to support the annotation of discourse relations, particularly in scenarios with limited resources, while minimizing performance loss., Comment: 7 pages, 2 figures, 5 tables

The Multi-channel Photometric Survey Telescope (Mephisto) is a real-time, three-color photometric system designed to capture the color evolution of stars and transients accurately. This telescope system can be crucial in cosmological distance measurements of low-redshift (low-$z$, $z$ $\lesssim 0.1$) Type Ia supernovae (SNe Ia). To optimize the capabilities of this instrument, we perform a comprehensive simulation study before its official operation is scheduled to start. By considering the impact of atmospheric extinction, weather conditions, and the lunar phase at the observing site involving the instrumental features, we simulate the light curves of SNe Ia obtained by the Mephisto. The best strategy in the case of SN Ia cosmology is to take the image at an exposure time of 130 s with a cadence of 3 days. In this condition, Mephisto can obtain hundreds of high-quality SNe Ia to achieve a distance measurement better than $4.5\%$. Given the on-time spectral classification and monitoring of the Lijiang 2.4 m Telescope at the same observatory, Mephisto, in the whole operation, can significantly enrich the well-calibrated sample of supernovae at low-$z$ and improve the calibration accuracy of high-$z$ SNe Ia., Comment: 15 pages, 7 figures

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine learning algorithms and applied to cut-out-centered galaxies. However, according to the design and survey strategy of optical surveys by CSST, preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual Transformer with a sliding window technique to search for strong lensing systems within entire images. Moreover, given that multi-color images of strong lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong lensing systems in images with any number of channels. As evaluated using CSST mock data based on an Semi-Analytic Model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. 61 new strong lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements., Comment: The paper is accepted by the AJ. The complete code could be downloaded with DOI of: 10.12149/101393. Comments are welcome

While computer vision has achieved tremendous success with multimodal encoding and direct textual interaction with images via chat-based large language models, similar advancements in medical imaging AI, particularly in 3D imaging, have been limited due to the scarcity of comprehensive datasets. To address this critical gap, we introduce CT-RATE, the first dataset that pairs 3D medical images with corresponding textual reports. CT-RATE comprises 25,692 non-contrast 3D chest CT scans from 21,304 unique patients. Through various reconstructions, these scans are expanded to 50,188 volumes, totaling over 14.3 million 2D slices. Each scan is accompanied by its corresponding radiology report. Leveraging CT-RATE, we develop CT-CLIP, a CT-focused contrastive language-image pretraining framework designed for broad applications without the need for task-specific training. We demonstrate how CT-CLIP can be used in two tasks: multi-abnormality detection and case retrieval. Remarkably, in multi-abnormality detection, CT-CLIP outperforms state-of-the-art fully supervised models across all key metrics, effectively eliminating the need for manual annotation. In case retrieval, it efficiently retrieves relevant cases using either image or textual queries, thereby enhancing knowledge dissemination. By combining CT-CLIP's vision encoder with a pretrained large language model, we create CT-CHAT, a vision-language foundational chat model for 3D chest CT volumes. Finetuned on over 2.7 million question-answer pairs derived from the CT-RATE dataset, CT-CHAT surpasses other multimodal AI assistants, underscoring the necessity for specialized methods in 3D medical imaging. Collectively, the open-source release of CT-RATE, CT-CLIP, and CT-CHAT not only addresses critical challenges in 3D medical imaging but also lays the groundwork for future innovations in medical AI and improved patient care.

Detecting problematic research articles timely is a vital task. This study explores whether Twitter mentions of retracted articles can signal potential problems with the articles prior to retraction, thereby playing a role in predicting future retraction of problematic articles. A dataset comprising 3,505 retracted articles and their associated Twitter mentions is analyzed, alongside 3,505 non-retracted articles with similar characteristics obtained using the Coarsened Exact Matching method. The effectiveness of Twitter mentions in predicting article retraction is evaluated by four prediction methods, including manual labelling, keyword identification, machine learning models, and ChatGPT. Manual labelling results indicate that there are indeed retracted articles with their Twitter mentions containing recognizable evidence signaling problems before retraction, although they represent only a limited share of all retracted articles with Twitter mention data (approximately 16%). Using the manual labelling results as the baseline, ChatGPT demonstrates superior performance compared to other methods, implying its potential in assisting human judgment for predicting article retraction. This study uncovers both the potential and limitation of social media events as an early warning system for article retraction, shedding light on a potential application of generative artificial intelligence in promoting research integrity.

Medical imaging plays a crucial role in diagnosis, with radiology reports serving as vital documentation. Automating report generation has emerged as a critical need to alleviate the workload of radiologists. While machine learning has facilitated report generation for 2D medical imaging, extending this to 3D has been unexplored due to computational complexity and data scarcity. We introduce the first method to generate radiology reports for 3D medical imaging, specifically targeting chest CT volumes. Given the absence of comparable methods, we establish a baseline using an advanced 3D vision encoder in medical imaging to demonstrate our method's effectiveness, which leverages a novel auto-regressive causal transformer. Furthermore, recognizing the benefits of leveraging information from previous visits, we augment CT2Rep with a cross-attention-based multi-modal fusion module and hierarchical memory, enabling the incorporation of longitudinal multimodal data. Access our code at https://github.com/ibrahimethemhamamci/CT2Rep

We study the $\Lambda(1405)$ resonance with $I(J^{P})=0(1/2^{-}) $ in the context of the pentaquark hypothesis in the nuclear medium. For the investigation of the influence of the nuclear medium on the physical parameters of $\Lambda(1405)$, we propose a molecular-type structure involving $K^{-}p$ and $\bar{K}^{0}n$ admixtures, correlated with the nuclear matter density. Our analysis reveals a substantial shift in both mass and residue, approximately $20\%$ and $38\%$, respectively. These findings have significant implications for experimental researchers aimed at identifying in-medium characteristics of hyperon resonances., Comment: 15 pages, 6 graphs, 3 table

A key open question in the study of layered superconducting nickelate films is the role that hydrogen incorporation into the lattice plays in the appearance of the superconducting state. Due to the challenges of stabilizing highly crystalline square planar nickelate films, films are prepared by the deposition of a more stable parent compound which is then transformed into the target phase via a topotactic reaction with a strongly reducing agent such as CaH$_2$. Recent studies, both experimental and theoretical, have introduced the possibility that the incorporation of hydrogen from the reducing agent into the nickelate lattice may be critical for the superconductivity. In this work, we use secondary ion mass spectrometry to examine superconducting La$_{1-x}$X$_x$NiO$_2$ / SrTiO$_3$ (X = Ca and Sr) and Nd$_6$Ni$_5$O$_{12}$ / NdGaO$_3$ films, along with non-superconducting NdNiO$_2$ / SrTiO$_3$ and (Nd,Sr)NiO$_2$ / SrTiO$_3$. We find no evidence for extensive hydrogen incorporation across a broad range of samples, including both superconducting and non-superconducting films. Theoretical calculations indicate that hydrogen incorporation is broadly energetically unfavorable in these systems, supporting our conclusion that hydrogen incorporation is not generally required to achieve a superconducting state in layered square-planar nickelates., Comment: 23 pages, 21 figures (including supplemental information)

Topotactic reduction utilizing metal hydrides as reagents emerges as an effective approach to achieve exceptionally low oxidization states of metal ions and unconventional coordination networks. This method opens avenues to the development of entirely new functional materials, with one notable example being the infinite-layer nickelate superconductors. However, the reduction effect on the atomic reconstruction and electronic structures -- crucial for superconductivity -- remains largely unresolved. We design two sets of control Nd$_{0.8}$Sr$_{0.2}$NiO$_2$ thin films and implement secondary ion mass spectroscopy to highlight the absence of reduction-induced hydrogen intercalation. X-ray absorption spectroscopy shows a significant linear dichroism with dominant Ni 3d$_{x2{-}y2}$ orbitals on superconducting samples, indicating a Ni single-band nature of infinite-layer nickelates. Consistent with the superconducting $T_c$, the Ni 3d orbitals asymmetry manifests a dome-like reduction duration dependence. Our results unveil the critical role of reduction in modulating the Ni-3d orbital polarization and its impact on the superconducting properties., Comment: Main: 21 pages, 4 figure - Supplementary: 7 pages, 5 figure