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The high redshift 21-cm signal promises to be a crucial probe of the state of the intergalactic medium (IGM). Understanding the connection between the observed 21-cm power spectrum and the physical quantities intricately associated with the IGM is crucial to fully understand the evolution of our Universe. In this study, we develop an emulator using artificial neural network (ANN) to predict the 21-cm power spectrum from a given set of IGM properties, namely, the bubble size distribution and the volume averaged ionization fraction. This emulator is implemented within a standard Bayesian framework to constrain the IGM parameters from a given 21-cm power spectrum. We compare the performance of the Bayesian method to an alternate method using ANN to predict the IGM parameters from a given input power spectrum, and find that both methods yield similar levels of accuracy, while the ANN is significantly faster. We also use this ANN method of parameter estimation to predict the IGM parameters from a test set contaminated with noise levels expected from the SKA-LOW instrument after 1000 hours of observation. Finally, we train a separate ANN to predict the source parameters from the IGM parameters directly, at a redshift of $z=9.1$, demonstrating the possibility of a non-analytic inference of the source parameters from the IGM parameters for the first time. We achieve high accuracies, with R2-scores ranging between $0.898-0.978$ for the ANN emulator and between $0.966-0.986$ and $0.817-0.981$ for the predictions of IGM parameters from 21-cm power spectrum and source parameters from IGM parameters, respectively. The predictions of the IGM parameters from the Bayesian method incorporating the ANN emulator leads to tight constraints with error bars around $\pm{0.14}$ on the IGM parameters.

Large Language Models (LLMs) have significantly advanced user-bot interactions, enabling more complex and coherent dialogues. However, the prevalent text-only modality might not fully exploit the potential for effective user engagement. This paper explores the impact of multi-modal interactions, which incorporate images and audio alongside text, on user engagement in chatbot conversations. We conduct a comprehensive analysis using a diverse set of chatbots and real-user interaction data, employing metrics such as retention rate and conversation length to evaluate user engagement. Our findings reveal a significant enhancement in user engagement with multi-modal interactions compared to text-only dialogues. Notably, the incorporation of a third modality significantly amplifies engagement beyond the benefits observed with just two modalities. These results suggest that multi-modal interactions optimize cognitive processing and facilitate richer information comprehension. This study underscores the importance of multi-modality in chatbot design, offering valuable insights for creating more engaging and immersive AI communication experiences and informing the broader AI community about the benefits of multi-modal interactions in enhancing user engagement.

Remote sensing image-text retrieval constitutes a foundational aspect of remote sensing interpretation tasks, facilitating the alignment of vision and language representations. This paper introduces a prior instruction representation (PIR) learning paradigm that draws on prior knowledge to instruct adaptive learning of vision and text representations. Based on PIR, a domain-adapted remote sensing image-text retrieval framework PIR-ITR is designed to address semantic noise issues in vision-language understanding tasks. However, with massive additional data for pre-training the vision-language foundation model, remote sensing image-text retrieval is further developed into an open-domain retrieval task. Continuing with the above, we propose PIR-CLIP, a domain-specific CLIP-based framework for remote sensing image-text retrieval, to address semantic noise in remote sensing vision-language representations and further improve open-domain retrieval performance. In vision representation, Vision Instruction Representation (VIR) based on Spatial-PAE utilizes the prior-guided knowledge of the remote sensing scene recognition by building a belief matrix to select key features for reducing the impact of semantic noise. In text representation, Language Cycle Attention (LCA) based on Temporal-PAE uses the previous time step to cyclically activate the current time step to enhance text representation capability. A cluster-wise Affiliation Loss (AL) is proposed to constrain the inter-classes and to reduce the semantic confusion zones in the common subspace. Comprehensive experiments demonstrate that PIR could enhance vision and text representations and outperform the state-of-the-art methods of closed-domain and open-domain retrieval on two benchmark datasets, RSICD and RSITMD., Comment: 15 pages, 9 figures

The redshifted 21-cm signal from the epoch of reionization (EoR) directly probes the ionization and thermal states of the intergalactic medium during that period. In particular, the distribution of the ionized regions around the radiating sources during EoR introduces scale-dependent features in the spherically-averaged EoR 21-cm signal power spectrum. The goal is to study these scale-dependent features at different stages of reionization using numerical simulations and build a source model-independent framework to probe the properties of the intergalactic medium using EoR 21-cm signal power spectrum measurements. Under the assumption of high spin temperature, we modelled the redshift evolution of the ratio of EoR 21-cm brightness temperature power spectrum and the corresponding density power spectrum using an ansatz consisting of a set of redshift and scale-independent parameters. This set of eight parameters probes the redshift evolution of the average ionization fraction and the quantities related to the morphology of the ionized regions. We have tested this ansatz on different reionization scenarios generated using different simulation algorithms and found that it is able to recover the redshift evolution of the average neutral fraction within an absolute deviation $\lesssim 0.1$. Our framework allows us to interpret 21-cm signal power spectra in terms of parameters related to the state of the IGM. This source model-independent framework can efficiently constrain reionization scenarios using multi-redshift power spectrum measurements with ongoing and future radio telescopes such as LOFAR, MWA, HERA, and SKA. This will add independent information regarding the EoR IGM properties., Comment: 16 pages, 13 figures, 2 tables, Accepted for publication in Astronomy and Astrophysics

The 21-cm line emitted by neutral hydrogen is the most promising probe of the Epoch of Reionization (EoR). Multiple radio interferometric instruments are on the cusp of detecting its power spectrum. It is therefore essential to deliver robust theoretical predictions, enabling sound inference of the coeval Universe properties. The nature of this signal traditionally required the modelling of $\mathcal{O}(10^{7-8} \, {\rm Mpc}^3)$ volumes to suppress the impact of cosmic variance. However, the recently-proposed Fixed & Paired (F&P) approach uses carefully-crafted simulation pairs to achieve equal results in smaller volumes. In this work, we thoroughly test the applicability of and improvement granted by this technique to different observables of the 21-cm signal from the EoR. We employ radiation-magneto-hydrodynamics simulations to ensure the most realistic physical description of this epoch, greatly improving over previous studies using a semi-numerical approach without accurate galaxy formation physics and radiative transfer. We estimate the statistical improvement granted by the F&P technique on predictions of the skewness, power spectrum, bispectrum and ionized regions size distribution of the 21-cm signal at redshift $7 \leq z \leq 10$ (corresponding to $\geq80\%$ of the gas being neutral). We find that the effective volume of F&P simulations is at least 3.5 times larger than traditional simulations. This directly translates into an equal improvement in the computational cost (in terms of time and memory). Finally, we confirm that a combination of different observables like skewness, power spectrum and bispectrum across different redshifts can be utilised to maximise the improvement., Comment: 13 pages, 11 figures, 2 tables. Accepted for publication in the Monthly Notices of the Royal Astronomical Society (MNRAS)

Image-text retrieval has developed rapidly in recent years. However, it is still a challenge in remote sensing due to visual-semantic imbalance, which leads to incorrect matching of non-semantic visual and textual features. To solve this problem, we propose a novel Direction-Oriented Visual-semantic Embedding Model (DOVE) to mine the relationship between vision and language. Our highlight is to conduct visual and textual representations in latent space, directing them as close as possible to a redundancy-free regional visual representation. Concretely, a Regional-Oriented Attention Module (ROAM) adaptively adjusts the distance between the final visual and textual embeddings in the latent semantic space, oriented by regional visual features. Meanwhile, a lightweight Digging Text Genome Assistant (DTGA) is designed to expand the range of tractable textual representation and enhance global word-level semantic connections using less attention operations. Ultimately, we exploit a global visual-semantic constraint to reduce single visual dependency and serve as an external constraint for the final visual and textual representations. The effectiveness and superiority of our method are verified by extensive experiments including parameter evaluation, quantitative comparison, ablation studies and visual analysis, on two benchmark datasets, RSICD and RSITMD., Comment: 14 pages, 11 figures

The study of quasi-periodic oscillations (QPOs) and power density spectra (PDS) continuum properties can help shed light on the still illusive emission physics of magnetars and as a window into the interiors of neutron stars using asteroseismology. In this work, we employ a Bayesian method to search for the QPOs in the hundreds of X-ray bursts from SGR J1935+2154 observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to January 2022. Although no definitive QPO signal (significance $>3\sigma$) is detected in individual bursts or the averaged periodogram of the bursts grouped by duration, we identify several bursts exhibiting possible QPO at $\sim$ 40 Hz, which is consistent with that reported in the X-ray burst associated with FRB 200428. We investigate the PDS continuum properties and find that the distribution of the PDS slope in the simple power-law model peaks $\sim$ 2.5, which is consistent with other magnetars but higher than 5/3 commonly seen in gamma-ray bursts. Besides, the distribution of the break frequency in the broken power-law model peaks at $\sim$ 60 Hz. Finally, we report that the power-law index of PDS has an anti-correlation and power-law dependence on the burst duration as well as the minimum variation timescale., Comment: comments welcome

The minimum variation timescale (MVT) of soft gamma-ray repeaters can be an important probe to estimate the emission region in pulsar-like models, as well as the Lorentz factor and radius of the possible relativistic jet in gamma-ray burst (GRB)-like models, thus revealing their progenitors and physical mechanisms. In this work, we systematically study the MVTs of hundreds of X-ray bursts (XRBs) from SGR J1935+2154 observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to Jan 2022 through the Bayesian Block algorithm. We find that the MVTs peak at $\sim$ 2 ms, corresponding to a light travel time size of about 600 km, which supports the magnetospheric origin in pulsar-like models. The shock radius and the Lorentz factor of the jet are also constrained in GRB-like models. Interestingly, the MVT of the XRB associated with FRB 200428 is $\sim$ 70 ms, which is longer than that of most bursts and implies its special radiation mechanism. Besides, the median of MVTs is 7 ms, shorter than the median MVTs of 40 ms and 480 ms for short GRBs or long GRBs, respectively. However, the MVT is independent of duration, similar to GRBs. Finally, we investigate the energy dependence of MVT and suggest that there is a marginal evidence for a power-law relationship like GRBs but the rate of variation is at least about an order of magnitude smaller. These features may provide an approach to identify bursts with a magnetar origin., Comment: accepted for publication in ApJS

Due to the non-linear ionizing and heating processes, the 21-cm signals from epoch of reionization (EoR) are expected to have strong non-Gaussian fluctuations. In this paper, we use the semi-numerical simulations to study the non-Gaussian statistics i.e. skew spectrum and smoothed skewness of the 21-cm signals from EoR. We find the 21-cm skew spectrum and smoothed skewness have similar evolution features with the 21-cm bispectrum. All of them are sensitive to the EoR models, while not too much to the cosmic volume applied. With the SKA1-low telescope as reference, we find both the skew spectrum and smoothed skewness have much higher S/N ratios than the 21-cm bispectrum., Comment: 7 pages, 5 figures, mnras accepted

To self-consistently model galactic properties, reionization of the intergalactic medium, and the associated 21-cm signal, we have developed the algorithm polar by integrating the one-dimensional radiative transfer code grizzly with the semi-analytical galaxy formation code L-Galaxies 2020. Our proof-of-concept results are consistent with observations of the star formation rate history, UV luminosity function and the CMB Thomson scattering optical depth. We then investigate how different galaxy formation models affect UV luminosity functions and 21-cm power spectra, and find that while the former are most sensitive to the parameters describing the merger of halos, the latter have a stronger dependence on the supernovae feedback parameters, and both are affected by the escape fraction model., Comment: MNRAS accepted

The determination of the absolute and relative position of a spacecraft is critical for its operation, observations, data analysis, scientific studies, as well as deep space exploration in general. A spacecraft that can determine its own absolute position autonomously may perform more than that must rely on transmission solutions. In this work, we report an absolute navigation accuracy of $\sim$ 20 km using 16-day Crab pulsar data observed with $Fermi$ Gamma ray Burst Monitor (GBM). In addition, we propose a new method with the inverse process of the triangulation for joint navigation using repeated bursts like that from the magnetar SGR J1935+2154 observed by the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) and GBM., Comment: accepted for publication in ApJS

Spectral lag of the low-energy photons with respect to the high-energy ones is a common astrophysical phenomenon (such as Gamma-ray bursts and the Crab pulsar) and may serve as a key probe to the underlying radiation mechanism. However, spectral lag in keV range of the magnetar bursts has not been systematically studied yet. In this work, we perform a detailed spectral lag analysis with the Li-CCF method for SGR J1935+2154 bursts observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to Jan 2022. We discover that the spectral lags of about 61\% (non-zero significance >1$\sigma$) bursts from SGR J1935+2154 are linearly dependent on the photon energy ($E$) with $t_{\rm lag}(E)=\alpha (E/{\rm keV})+C$, which may be explained by a linear change of the temperature of the blackbody-emitting plasma with time. The distribution of the slope ($\alpha$) approximately follows a Gaussian function with mean and standard deviation of 0.02 ms/keV (i.e. high-energy photons arrive earlier) and 0.02 ms/keV, respectively. We also find that the distribution can be well fitted with three Gaussians with mean values of $\sim$ -0.009, 0.013 and 0.039 ms/keV, which may correspond to different origins of the bursts. These spectral lag features may have important implications on the magnetar bursts., Comment: accepted for publication in MNRAS

The precursors of short and long Gamma Ray Bursts (SGRBs and LGRBs) can serve as probes of their progenitors, as well as shedding light on the physical processes of mergers or core-collapse supernovae. Some models predict the possible existence of Quasi-Periodically Oscillations (QPO) in the precursors of SGRBs. Although many previous studies have performed QPO search in the main emission of SGRBs and LGRBs, so far there was no systematic QPO search in their precursors. In this work, we perform a detailed QPO search in the precursors of SGRBs and LGRBs detected by Fermi/GBM from 2008 to 2019 using the power density spectrum (PDS) in frequency domain and Gaussian processes (GP) in time domain. We do not find any convinced QPO signal with significance above 3 $\sigma$, possibly due to the low fluxes of precursors. Finally, the PDS continuum properties of both the precursors and main emissions are also studied for the first time, and no significant difference is found in the distributions of the PDS slope for precursors and main emissions in both SGRBs and LGRBs., Comment: submitted

We use a set of 3D radiative transfer simulations to study the effect that a large fraction of binary stars in galaxies during the epoch of reionization has on the physical properties of the intergalactic medium (i.e. the gas temperature and the ionization state of hydrogen and helium), on the topology of the ionized bubbles and on the 21 cm power spectra. Consistently to previous literature, we find that the inclusion of binary stars can speed up the reionization process of HI and HeI, while HeII reionization is still dominated by more energetic sources, especially accreting black holes. The earlier ionization attained with binary stars allows for more time for cooling and recombination, so that gas fully ionized by binary stars is typically colder than that ionized by single stars at any given redshift. With the same volume averaged ionization fraction, the inclusion of binary stars results in fewer small ionized bubbles and more large ones, with visible effects also on the large scales of the 21 cm power spectrum., Comment: 14 pages, 11 figures, MNRAS accepted