arXiv subjects

Xin Xiang

Publications and source records attributed to Xin Xiang.

23 records · Page 2Linked to original sources

arXiv2024

EEG-Driven 3D Object Reconstruction with Style Consistency and Diffusion Prior

Electroencephalography (EEG)-based visual perception reconstruction has become an important area of research. Neuroscientific studies indicate that humans can decode imagined 3D objects by perceiving or imagining various visual information, such as color, shape, and rotation. Existing EEG-based visual decoding methods typically focus only on the reconstruction of 2D visual stimulus images and face various challenges in generation quality, including inconsistencies in texture, shape, and color between the visual stimuli and the reconstructed images. This paper proposes an EEG-based 3D object reconstruction method with style consistency and diffusion priors. The method consists of an EEG-driven multi-task joint learning stage and an EEG-to-3D diffusion stage. The first stage uses a neural EEG encoder based on regional semantic learning, employing a multi-task joint learning scheme that includes a masked EEG signal recovery task and an EEG based visual classification task. The second stage introduces a latent diffusion model (LDM) fine-tuning strategy with style-conditioned constraints and a neural radiance field (NeRF) optimization strategy. This strategy explicitly embeds semantic- and location-aware latent EEG codes and combines them with visual stimulus maps to fine-tune the LDM. The fine-tuned LDM serves as a diffusion prior, which, combined with the style loss of visual stimuli, is used to optimize NeRF for generating 3D objects. Finally, through experimental validation, we demonstrate that this method can effectively use EEG data to reconstruct 3D objects with style consistency.

cs.CV↗

arXiv2024

Investigating the Mass of the Black Hole and Possible Wind Outflow of the Accretion Disk in the Tidal Disruption Event AT2021ehb

Tidal disruption events (TDEs) can potentially probe low-mass black holes in host galaxies that might not adhere to bulge or stellar-dispersion relationships. At least initially, TDEs can also reveal super-Eddington accretion. X-ray spectroscopy can potentially constrain black hole masses, and reveal ionized outflows associated with super-Eddington accretion. Our analysis of XMM-Newton X-ray observations of the TDE AT2021ehb, around 300 days post-disruption, reveals a soft spectrum and can be fit with a combination of multi-color disk blackbody and power-law components. Using two independent disk models with properties suited to TDEs, we estimate a black hole mass at $M \simeq 10^{5.5}~M_{\odot}$, indicating AT2021ehb may expose the elusive low-mass end of the nuclear black hole population. These models offer simple yet robust characterization; more complicated models are not required, but provide important context and caveats in the limit of moderately sensitive data. If disk reflection is included, the disk flux is lower and inferred black hole masses are $\sim$ 0.35 dex higher. Simple wind formulations imply an extremely fast $v_{\mathrm{out}} = -0.2~c$ outflow and obviate a disk continuum component. Assuming a unity filling factor, such a wind implies an instantaneous mass outflow rate of $\dot{M} \simeq 5~M_{\odot}~{\rm yr}^{-1}$. Such a high rate suggests that the filling factor for the Ultra Fast Outflow (UFO) must be extremely low, and/or the UFO phase is ephemeral. We discuss the strengths and limitations of our analysis and avenues for future observations of TDEs.

astro-ph.HE↗

arXiv2022

Report of the Topical Group on Particle Dark Matter for Snowmass 2021

This report summarizes the findings of the CF1 Topical Subgroup to Snowmass 2021, which was focused on particle dark matter. One of the most important scientific goals of the next decade is to reveal the nature of dark matter (DM). To accomplish this goal, we must delve deep, to cover high priority targets including weakly-interacting massive particles (WIMPs), and search wide, to explore as much motivated DM parameter space as possible. A diverse, continuous portfolio of experiments at large, medium, and small scales that includes both direct and indirect detection techniques maximizes the probability of discovering particle DM. Detailed calibrations and modeling of signal and background processes are required to make a convincing discovery. In the event that a candidate particle is found through different means, for example at a particle collider, the program described in this report is also essential to show that it is consistent with the actual cosmological DM. The US has a leading role in both direct and indirect detection dark matter experiments -- to maintain this leading role, it is imperative to continue funding major experiments and support a robust R\&D program.

hep-ph↗

arXiv2022

reXcor: A Model of the X-ray Spectrum of Active Galactic Nuclei that Combines Ionized Reflection and a Warm Corona

The X-ray spectra of active galactic nuclei (AGNs) often exhibit an excess of emission above the primary power-law at energies <~ $2$ keV. Two models for the origin of this `soft excess' are ionized relativistic reflection from the inner accretion disc and Comptonization of thermal emission in a warm corona. Here, we introduce reXcor, a new AGN X-ray ($0.3$-$100$ keV) spectral fitting model that self-consistently combines the effects of both ionized relativistic reflection and the emission from a warm corona. In this model, the accretion energy liberated in the inner disc is distributed between a warm corona, a lamppost X-ray source, and the accretion disc. The emission and ionized reflection spectrum from the inner $400$ $r_g$ of the disc is computed, incorporating the effects of relativistic light-bending and blurring. The resulting spectra predict a variety of soft excess shapes and sizes that depend on the fraction of energy dissipated in the warm corona and lamppost. We illustrate the use of reXcor by fitting to the joint XMM-Newton and NuSTAR observations of the Seyfert 1 galaxies HE 1143-1820 and NGC 4593, and find that both objects require a warm corona contribution to the soft excess. Eight reXcor table models, covering different values of accretion rate, lamppost height and black hole spin, are publicly available through the XSPEC website. Systematic use of reXcor will provide insight into the distribution of energy in AGN accretion flows.

astro-ph.HE↗

arXiv2015

Automatic exploration of structural regularities in networks

Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, not only the group number but also the certain type of structure that a network has are usually unknown in advance. To automatically explore structural regularities in complex networks, without any prior knowledge about the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory and propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to automatically explore structural regularities in networks with a stable and state-of-the-art performance.

cs.SI↗