arXiv subjects

Rui Shi

Publications and source records attributed to Rui Shi.

At least 73 records · Page 4Linked to original sources

arXiv2024

Sensitivity-Improved Polarization Maps at 40 GHz with CLASS and WMAP data

Improved polarization measurements at frequencies below 70 GHz with degree-level angular resolution are crucial for advancing our understanding of the Galactic synchrotron radiation and the potential polarized anomalous microwave emission and ultimately benefiting the detection of primordial $B$ modes. In this study, we present sensitivity-improved 40 GHz polarization maps obtained by combining the CLASS 40 GHz and WMAP $Q$-band data through a weighted average in the harmonic domain. The decision to include WMAP $Q$-band data stems from similarities in the bandpasses. Leveraging the accurate large-scale measurements from WMAP $Q$ band and the high-sensitivity information from CLASS 40 GHz band at intermediate scales, the noise level at $\ell\in[30, 100]$ is reduced by a factor of $2-3$ in the map space. A pixel domain analysis of the polarized synchrotron spectral index ($β_s$) using WMAP $K$ band and the combined maps (mean and 16/84th percentile across the $β_s$ map: $-3.08_{-0.20}^{+0.20}$) reveals a stronger preference for spatial variation (PTE for a uniform $β_s$ hypothesis smaller than 0.001) than the results obtained using WMAP $K$ and $Ka$ bands ($-3.08_{-0.14}^{+0.14}$). The cross-power spectra of the combined maps follow the same trend as other low-frequency data, and validation through simulations indicates negligible bias introduced by the combination method (sub-percent level in the power spectra). The products of this work are publicly available on $\mathtt{LAMBDA}$.

astro-ph.CO↗

arXiv2024

Cosmology Large Angular Scale Surveyor (CLASS): 90 GHz Telescope Pointing, Beam Profile, Window Function, and Polarization Performance

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over ~75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale CMB polarization to constrain the tensor-to-scalar ratio and the optical depth to last scattering. This paper presents the optical characterization of the 90GHz telescope, which has been observing since July 2018. Observations of the Moon establish the pointing while dedicated observations of Jupiter are used for beam calibration. The standard deviations of the pointing error in azimuth, elevation, and boresight angle are 1.3, 2.1, and 2.0 arcminutes, respectively, over the first 3 years of observations. This corresponds to a pointing uncertainty ~7% of the beam's full width at half maximum (FWHM). The effective azimuthally-symmetrized instrument 1D beam estimated at 90 GHz has an FWHM of 0.620+/-0.003 deg and a solid angle of 138.7+/-0.6(stats.)+/-1.1(sys.) usr integrated to a radius of 4 deg. The corresponding beam window function drops to b_ell^2 = 0.93, 0.71, 0.14 at ell = 30, 100, 300, respectively. Far-sidelobes are studied using detector-centered intensity maps of the Moon and measured to be at a level of 10^-3 or below relative to the peak. The polarization angle of Tau A estimated from preliminary survey maps is 149.6+/-0.2(stats.) deg in equatorial coordinates. The instrumental temperature-to-polarization (T-to-P) leakage fraction, inferred from per-detector demodulated Jupiter scan data, has a monopole component at the level of 1.7 x 10^-3, a dipole component with an amplitude of 4.3 x 10^-3, with no evidence of quadrupolar leakage.

astro-ph.IM↗

arXiv2024

How does the velocity anisotropy of halo stars, dark matter and satellite galaxies depend on host halo properties?

We investigate the mass ($M_{200}$) and concentration ($c_{200}$) dependencies of the velocity anisotropy ($β$) profiles for different components in the dark matter halo, including halo stars, dark matter and subhalos, using systems from the IllustrisTNG simulations. Beyond a critical radius, $β$ becomes more radial with the increase of $M_{200}$, reflecting more prominent radial accretion around massive halos. The critical radius is $r\sim r_s$, $0.3~r_s$ and $r_s$ for halo stars, dark matter and subhalos, with $r_s$ the scale radius of host halos. This dependence on $M_{200}$ is the strongest for subhalos, and the weakest for halo stars. In central regions, $β$ of halo stars and dark matter particles gets more isotropic with the increase of $M_{200}$ in TNG300 due to baryons. By contrast, $β$ of dark matter from the dark matter only TNG300-Dark run shows much weaker dependence on $M_{200}$ within $r_s$. Dark matter in TNG300 is slightly more isotropic than in TNG300-Dark at $0.2~r_s r_s$ as $β_\mathrm{star}-β_\mathrm{DM}=(-0.028 \pm 0.008)\log_{10}M_{200}/M_\odot + (0.690\pm0.010)$.

astro-ph.GA↗

arXiv2024

AU-vMAE: Knowledge-Guide Action Units Detection via Video Masked Autoencoder

Current Facial Action Unit (FAU) detection methods generally encounter difficulties due to the scarcity of labeled video training data and the limited number of training face IDs, which renders the trained feature extractor insufficient coverage for modeling the large diversity of inter-person facial structures and movements. To explicitly address the above challenges, we propose a novel video-level pre-training scheme by fully exploring the multi-label property of FAUs in the video as well as the temporal label consistency. At the heart of our design is a pre-trained video feature extractor based on the video-masked autoencoder together with a fine-tuning network that jointly completes the multi-level video FAUs analysis tasks, \emph{i.e.} integrating both video-level and frame-level FAU detections, thus dramatically expanding the supervision set from sparse FAUs annotations to ALL video frames including masked ones. Moreover, we utilize inter-frame and intra-frame AU pair state matrices as prior knowledge to guide network training instead of traditional Graph Neural Networks, for better temporal supervision. Our approach demonstrates substantial enhancement in performance compared to the existing state-of-the-art methods used in BP4D and DISFA FAUs datasets.

cs.CV↗

arXiv2024

Inferring the mass content of galaxy clusters with satellite kinematics and Jeans Anisotropic modeling

Satellite galaxies can be used to indicate the dynamical mass of galaxy groups and clusters. In this study, we apply the axis-symmetric Jeans Anisotropic Multi-Gaussian Expansion JAM modeling to satellite galaxies in 28 galaxy clusters selected from the TNG300-1 simulation with halo mass of $\log_{10}M_{200}/M_\odot>14.3$. If using true bound satellites as tracers, the best constrained total mass within the half-mass radius of satellites, $M(<r_\mathrm{half})$, and the virial mass, $M_{200}$, have average biases of -0.01 and $0.03$~dex, with average scatters of 0.11~dex and 0.15~dex. If selecting companions in redshift space with line-of-sight depth of 2,000~km/s, the biases are -0.06 and $0.01$~dex, while the scatters are 0.12 and 0.18~dex for $M(<r_\mathrm{half})$ and $M_{200}$. By comparing the best-fitting and actual density profiles, we find $\sim$29% of best-fitting density profiles show very good agreement with the truth, $\sim$32% display over or under estimates at most of the radial range with biased $M(<r_\mathrm{half})$, and 39% show under/over estimates in central regions and over/under estimates in the outskirts, with good constraints on $M(<r_\mathrm{half})$, yet most of the best constraints are still consistent with the true profiles within 1-$σ$ statistical uncertainties for the three circumstances. Using a mock DESI Bright Galaxy Survey catalog with the effect of fiber incompleteness, we find DESI fiber assignments and the choice of flux limits barely modify the velocity dispersion profiles and are thus unlikely to affect the dynamical modeling outcomes. Our results show that with current and future deep spectroscopic surveys, JAM can be a powerful tool to constrain the underlying density profiles of individual massive galaxy clusters.

astro-ph.CO↗

arXiv2024

Design and characterization of a 60-cm reflective half-wave plate for the CLASS 90 GHz band telescope

Front-end polarization modulation enables improved polarization measurement stability by modulating the targeted signal above the low-frequency $1/f$ drifts associated with atmospheric and instrumental instabilities and diminishes the impact of instrumental polarization. In this work, we present the design and characterization of a new 60-cm diameter Reflective Half-Wave Plate (RHWP) polarization modulator for the 90 GHz band telescope of the Cosmology Large Angular Scale Surveyor (CLASS) project. The RHWP consists of an array of parallel wires (diameter $50~\mathrm{μm}$, $175~\mathrm{μm}$ pitch) positioned $0.88~\mathrm{mm}$ from an aluminum mirror. In lab tests, it was confirmed that the wire resonance frequency ($f_\mathrm{res}$) profile is consistent with the target, $139~\mathrm{Hz}<f_\mathrm{res}<154~\mathrm{Hz}$ in the optically active region (diameter smaller than $150~\mathrm{mm}$), preventing the wire vibration during operation and reducing the RHWP deformation under the wire tension. The mirror tilt relative to the rotating axis was controlled to be $<15''$, corresponding to an increase in beam width due to beam smearing of $<0.6''$, negligible compared to the beam's full-width half-maximum of $36'$. The median and 16/84th percentile of the wire--mirror separation residual was $0.048^{+0.013}_{-0.014}~\mathrm{mm}$ in the optically active region, achieving a modulation efficiency $ε=96.2_{+0.5}^{-0.4}\%$ with an estimated bandpass of 34 GHz. The angular velocity of the RHWP was maintained to an accuracy of within $0.005\%$ at the nominal rotation frequency ($2.5~\mathrm{Hz}$). The RHWP has been successfully integrated into the CLASS 90 GHz telescope and started taking data in June 2024, replacing the previous modulator that has been in operation since June 2018.

astro-ph.IM↗

arXiv2024

CLASS Angular Power Spectra and Map-Component Analysis for 40 GHz Observations through 2022

Measurement of the largest angular scale ($\ell < 30$) features of the cosmic microwave background (CMB) polarization is a powerful way to constrain the optical depth to reionization and search for the signature of inflation through the detection of primordial $B$-modes. We present an analysis of maps covering 73.6\% of the sky made from the $40\,\mathrm{GHz}$ channel of the Cosmology Large Angular Scale Surveyor (CLASS) from 2016 August to 2022 May. Taking advantage of the measurement stability enabled by front-end polarization modulation and excellent conditions from the Atacama Desert, we show this channel achieves higher sensitivity than the analogous frequencies from satellite measurements in the range $10 < \ell < 100$. Simulations show the CLASS linear (circular) polarization maps have a white noise level of $125 \,(130)\,\mathrm{μK\, arcmin}$. We measure the Galaxy-masked $EE$ and $BB$ spectra of diffuse synchrotron radiation and compare to space-based measurements at similar frequencies. In combination with external data, we expand measurements of the spatial variations of the synchrotron spectral energy density (SED) to include new sky regions and measure the diffuse SED in the harmonic domain. We place a new upper limit on a background of circular polarization in the range $5 < \ell < 125$ with the first bin showing $D_\ell < 0.023$ $\mathrm{μK^2_{CMB}}$ at 95\% confidence. These results establish a new standard for recovery of the largest-scale CMB polarization from the ground and signal exciting possibilities when the higher sensitivity and higher-frequency CLASS channels are included in the analysis.

astro-ph.CO↗

arXiv2024

Deep Rib Fracture Instance Segmentation and Classification from CT on the RibFrac Challenge

Rib fractures are a common and potentially severe injury that can be challenging and labor-intensive to detect in CT scans. While there have been efforts to address this field, the lack of large-scale annotated datasets and evaluation benchmarks has hindered the development and validation of deep learning algorithms. To address this issue, the RibFrac Challenge was introduced, providing a benchmark dataset of over 5,000 rib fractures from 660 CT scans, with voxel-level instance mask annotations and diagnosis labels for four clinical categories (buckle, nondisplaced, displaced, or segmental). The challenge includes two tracks: a detection (instance segmentation) track evaluated by an FROC-style metric and a classification track evaluated by an F1-style metric. During the MICCAI 2020 challenge period, 243 results were evaluated, and seven teams were invited to participate in the challenge summary. The analysis revealed that several top rib fracture detection solutions achieved performance comparable or even better than human experts. Nevertheless, the current rib fracture classification solutions are hardly clinically applicable, which can be an interesting area in the future. As an active benchmark and research resource, the data and online evaluation of the RibFrac Challenge are available at the challenge website. As an independent contribution, we have also extended our previous internal baseline by incorporating recent advancements in large-scale pretrained networks and point-based rib segmentation techniques. The resulting FracNet+ demonstrates competitive performance in rib fracture detection, which lays a foundation for further research and development in AI-assisted rib fracture detection and diagnosis.

eess.IV↗

arXiv2023

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, with the ultimate goal of creating an automated controller capable of providing real-time feedback and calibration of the Spill Regulation System (SRS) parameters on a millisecond timescale. We treat the Mu2e accelerator system as a Markov Decision Process suitable for Reinforcement Learning (RL), utilizing PPO to reduce bias and enhance training stability. A key innovation in our approach is the integration of a neuralized Proportional-Integral-Derivative (PID) controller into the policy function, resulting in a significant improvement in the Spill Duty Factor (SDF) by 13.6%, surpassing the performance of the current PID controller baseline by an additional 1.6%. This paper presents the preliminary offline results based on a differentiable simulator of the Mu2e accelerator. It paves the groundwork for real-time implementations and applications, representing a crucial step towards automated proton beam intensity control for the Mu2e experiment.

cs.LG↗

arXiv2023

CLASS Data Pipeline and Maps for 40 GHz Observations through 2022

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background over 75\% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220~GHz. This paper describes the CLASS data pipeline and maps for 40~GHz observations conducted from August 2016 to May 2022. We demonstrate how well the CLASS survey strategy, with rapid ($\sim10\,\mathrm{Hz}$) front-end modulation, recovers the large-scale Galactic polarization signal from the ground: the mapping transfer function recovers $\sim75$\% of $EE$, $BB$, and $VV$ power at $\ell=20$ and $\sim45$\% at $\ell=10$. We present linear and circular polarization maps over 75\% of the sky. Simulations based on the data imply the maps have a white noise level of $110\,\mathrm{μK\, arcmin}$ and correlated noise component rising at low-$\ell$ as $\ell^{-2.2}$. The transfer-function-corrected low-$\ell$ component is comparable to the white noise at the angular knee frequencies of $\ell\approx16$ (linear polarization) and $\ell\approx12$ (circular polarization). Finally, we present simulations of the level at which expected sources of systematic error bias the measurements, finding sub-percent bias for the $Λ\mathrm{CDM}$ $EE$ power spectra. Bias from $E$-to-$B$ leakage due to the data reduction pipeline and polarization angle uncertainty approaches the expected level for an $r=0.01$ $BB$ power spectrum. Improvements to the instrument calibration and the data pipeline will decrease this bias.

astro-ph.CO↗

arXiv2023

CLASS Observations of Atmospheric Cloud Polarization at Millimeter Wavelengths

The dynamic atmosphere imposes challenges to ground-based cosmic microwave background observation, especially for measurements on large angular scales. The hydrometeors in the atmosphere, mostly in the form of clouds, scatter the ambient thermal radiation and are known to be the main linearly polarized source in the atmosphere. This scattering-induced polarization is significantly enhanced for ice clouds due to the alignment of ice crystals under gravity, which are also the most common clouds seen at the millimeter-astronomy sites at high altitudes. This work presents a multifrequency study of cloud polarization observed by the Cosmology Large Angular Scale Surveyor (CLASS) experiment on Cerro Toco in the Atacama Desert of northern Chile, from 2016 to 2022, at the frequency bands centered around 40, 90, 150, and 220 GHz. Using a machine-learning-assisted cloud classifier, we made connections between the transient polarized emission found in all four frequencies with the clouds imaged by monitoring cameras at the observing site. The polarization angles of the cloud events are found to be mostly $90^\circ$ from the local meridian, which is consistent with the presence of horizontally aligned ice crystals. The 90 and 150 GHz polarization data are consistent with a power law with a spectral index of $3.90\pm0.06$, while an excess/deficit of polarization amplitude is found at 40/220 GHz compared with a Rayleigh scattering spectrum. These results are consistent with Rayleigh-scattering-dominated cloud polarization, with possible effects from supercooled water absorption and/or Mie scattering from a population of large cloud particles that contribute to the 220 GHz polarization.

astro-ph.IM↗

arXiv2023

Microwave Observations of Venus with CLASS

We report on the disk-averaged absolute brightness temperatures of Venus measured at four microwave frequency bands with the Cosmology Large Angular Scale Surveyor (CLASS). We measure temperatures of 432.3 $\pm$ 2.8 K, 355.6 $\pm$ 1.3 K, 317.9 $\pm$ 1.7 K, and 294.7 $\pm$ 1.9 K for frequency bands centered at 38.8, 93.7, 147.9, and 217.5 GHz, respectively. We do not observe any dependence of the measured brightness temperatures on solar illumination for all four frequency bands. A joint analysis of our measurements with lower frequency Very Large Array (VLA) observations suggests relatively warmer ($\sim$ 7 K higher) mean atmospheric temperatures and lower abundances of microwave continuum absorbers than those inferred from prior radio occultation measurements.

astro-ph.EP↗

arXiv2023

SieveNet: Selecting Point-Based Features for Mesh Networks

Meshes are widely used in 3D computer vision and graphics, but their irregular topology poses challenges in applying them to existing neural network architectures. Recent advances in mesh neural networks turn to remeshing and push the boundary of pioneer methods that solely take the raw meshes as input. Although the remeshing offers a regular topology that significantly facilitates the design of mesh network architectures, features extracted from such remeshed proxies may struggle to retain the underlying geometry faithfully, limiting the subsequent neural network's capacity. To address this issue, we propose SieveNet, a novel paradigm that takes into account both the regular topology and the exact geometry. Specifically, this method utilizes structured mesh topology from remeshing and accurate geometric information from distortion-aware point sampling on the surface of the original mesh. Furthermore, our method eliminates the need for hand-crafted feature engineering and can leverage off-the-shelf network architectures such as the vision transformer. Comprehensive experimental results on classification and segmentation tasks well demonstrate the effectiveness and superiority of our method.

cs.CV↗

arXiv2023

SwinGar: Spectrum-Inspired Neural Dynamic Deformation for Free-Swinging Garments

Our work presents a novel spectrum-inspired learning-based approach for generating clothing deformations with dynamic effects and personalized details. Existing methods in the field of clothing animation are limited to either static behavior or specific network models for individual garments, which hinders their applicability in real-world scenarios where diverse animated garments are required. Our proposed method overcomes these limitations by providing a unified framework that predicts dynamic behavior for different garments with arbitrary topology and looseness, resulting in versatile and realistic deformations. First, we observe that the problem of bias towards low frequency always hampers supervised learning and leads to overly smooth deformations. To address this issue, we introduce a frequency-control strategy from a spectral perspective that enhances the generation of high-frequency details of the deformation. In addition, to make the network highly generalizable and able to learn various clothing deformations effectively, we propose a spectral descriptor to achieve a generalized description of the global shape information. Building on the above strategies, we develop a dynamic clothing deformation estimator that integrates frequency-controllable attention mechanisms with long short-term memory. The estimator takes as input expressive features from garments and human bodies, allowing it to automatically output continuous deformations for diverse clothing types, independent of mesh topology or vertex count. Finally, we present a neural collision handling method to further enhance the realism of garments. Our experimental results demonstrate the effectiveness of our approach on a variety of free-swinging garments and its superiority over state-of-the-art methods.

cs.CV↗

arXiv2023

Testing CMB Anomalies in E-mode Polarization with Current and Future Data

In this paper, we explore the power of the cosmic microwave background (CMB) polarization (E-mode) data to corroborate four potential anomalies in CMB temperature data: the lack of large angular-scale correlations, the alignment of the quadrupole and octupole (Q-O), the point-parity asymmetry, and the hemispherical power asymmetry. We use CMB simulations with noise representative of three experiments -- the Planck satellite, the Cosmology Large Angular Scale Surveyor (CLASS), and the LiteBIRD satellite -- to test how current and future data constrain the anomalies. We find the correlation coefficients $ρ$ between temperature and E-mode estimators to be less than $0.1$, except for the point-parity asymmetry ($ρ=0.17$ for cosmic-variance-limited simulations), confirming that E-modes provide a check on the anomalies that is largely independent of temperature data. Compared to Planck component-separated CMB data (SMICA), the putative LiteBIRD survey would reduce errors on E-mode anomaly estimators by factors of $\sim 3$ for hemispherical power asymmetry and point-parity asymmetry, and by $\sim 26$ for lack of large-scale correlation. The improvement in Q-O alignment is not obvious due to large cosmic variance, but we found the ability to pin down the estimator value will be improved by a factor $\gtrsim100$. Improvements with CLASS are intermediate to these.

astro-ph.CO↗

arXiv2023

Dark against luminous matter around isolated central galaxies: a comparative study between modern surveys and Illustris-TNG

Based on independent shear measurements using the DECaLS/DR8 imaging data, we measure the weak lensing signals around isolated central galaxies (ICGs) from SDSS/DR7 at $z\sim0.1$. The projected stellar mass density profiles of surrounding satellite galaxies are further deduced, using photometric sources from the Hyper Suprime-Cam (HSC) survey (pDR3). The signals of ICGs $+$ their extended stellar halos are taken from Wang et al.(2021). All measurements are compared with predictions by the Illustris-TNG300-1 simulation. We find, overall, a good agreement between observation and TNG300. In particular, a correction to the stellar mass of massive observed ICGs is applied based on the calibration of He et al.(2013), which brings a much better agreement with TNG300 predicted lensing signals at $\log_{10}M_\ast/M_\odot>11.1$. In real observation, red ICGs are hosted by more massive dark matter halos, have more satellites and more extended stellar halos than blue ICGs at fixed stellar mass. However, in TNG300 there are more satellites around blue ICGs at fixed stellar mass, and the outer stellar halos of red and blue ICGs are similar. The stellar halos of TNG galaxies are more extended compared with real observed galaxies, especially for blue ICGs with $\log_{10}M_\ast/M_\odot>10.8$. We find the same trend for TNG100 galaxies and for true halo central galaxies. The tensions between TNG and real galaxies might indicate that satellite disruptions are stronger in TNG. In both TNG300 and observation, satellites approximately trace the underlying dark matter distribution beyond $0.1R_{200}$, but the fraction of total stellar mass in TNG300 does not show the same radial distribution as real galaxies.

astro-ph.GA↗

arXiv2023

Towards Relating Fragile-To-Strong Transition to Fragile Glass

Glass formers are in general classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are however notable exceptions such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong respectively at high and low temperatures. In this work, the FTS transition is studied using a distinguishable-particle lattice model previously demonstrated to be capable of simulating both strong and fragile glasses [Phys. Rev. Lett. 125, 265703 (2020)]. Starting with a bimodal pair-interaction distribution appropriate for fragile glasses, we show that by narrowing down the energy dispersion in the low-energy component of the distribution, a FTS transition is observed. The transition occurs at a temperature at which the stretching exponent of the relaxation is minimized, in agreement with previous molecular dynamics simulations.

cond-mat.soft↗

arXiv2022

MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification

We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre-processed into a small size of 28x28 (2D) or 28x28x28 (3D) with the corresponding classification labels so that no background knowledge is required for users. Covering primary data modalities in biomedical images, MedMNIST v2 is designed to perform classification on lightweight 2D and 3D images with various dataset scales (from 100 to 100,000) and diverse tasks (binary/multi-class, ordinal regression, and multi-label). The resulting dataset, consisting of 708,069 2D images and 10,214 3D images in total, could support numerous research / educational purposes in biomedical image analysis, computer vision, and machine learning. We benchmark several baseline methods on MedMNIST v2, including 2D / 3D neural networks and open-source / commercial AutoML tools. The data and code are publicly available at https://medmnist.com/.

cs.CV↗