arXiv subjects

Kai-Feng Chen

Publications and source records attributed to Kai-Feng Chen.

At least 19 recordsLinked to original sources

arXiv2026

Nulling baryonic feedback in weak lensing surveys using cross-correlations with fast radio bursts

Baryonic feedback is a leading contaminant in studying dark matter and cosmology using cosmic shear. This has meant omitting much of the data during cosmological inference, or forward-modeling the spatial distribution of gas around dark matter halos using analytical or hydrodynamical models for baryonic feedback, which introduces nuisance parameters and model dependence. We propose a novel method of ``baryon nulling'' using cross-correlations between shear maps and fast radio burst (FRB) dispersion measures. By directly subtracting the dark matter--dispersion measure cross-correlation, the sensitivity of our nulled power spectra to feedback effects can be significantly reduced without any explicit feedback modeling. Using the FLAMINGO suite of hydrodynamic simulations, whose power spectra span a wide yet realistic range of feedback variations, we demonstrate that our method reduces sensitivity to feedback modeling at $k \approx 1$ Mpc$^{-1}$ by about an order of magnitude. This points toward a strong synergy between the next generation of sensitive FRB surveys such as CHORD and the DSA-2000, and cosmic shear surveys such as Rubin, Euclid, and Roman.

astro-ph.CO↗

arXiv2026

Weak-lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: III. A precision cosmological sample enabled by optical confirmation

We develop fCAMIRA (forced-mode CAMIRA), a tool for optical cluster confirmation, and apply it to a sample of 129 weak-lensing (WL) shear-selected galaxy clusters identified in aperture-mass maps obtained from the Hyper Suprime-Cam Subaru Strategic Program Three-Year (HSC-SSP Y3) weak-lensing data. fCAMIRA is built upon the CAMIRA cluster-finding algorithm and relies on a red-sequence (RS) galaxy model that is calibrated in a data-driven way. The RS model adopts the metallicity-luminosity relation measured in this work using X-ray-selected clusters up to redshift $z\approx1.3$, followed by the calibration of color offsets using large spectroscopic samples. With the RS model, we build two types of galaxy richness maps, one obtained with a spatial filter matched to a typical cluster size of $R=0.8\,h^{-1}\,\mathrm{Mpc}$ and the other obtained with a fixed angular-size filter identical to that used in constructing the WL aperture-mass maps. The fCAMIRA algorithm utilizes these two richness maps, identifies all optical counterpart candidates along the line of sight of each shear-selected cluster, and measures the cluster photometric redshift from the highest-ranked counterpart. The ranking is determined by the fractional lensing contribution $f_{\mathrm{lens}}$ of each candidate. Using available spectroscopic cluster redshifts, we quantify the mean bias and scatter in the cluster photometric redshifts at levels of approximately 0.005 and 0.008, respectively, demonstrating excellent photometric-redshift performance. We compare the fCAMIRA photometric redshifts with estimates from direct positional cross-matching and find that approximately 8% of the total sample exhibits redshift discrepancies greater than 0.15. This outlier fraction is primarily attributed to projection effects, leading to the misidentification of the optical counterparts. (abridged)

astro-ph.CO↗

arXiv2026

Effective bias expansion for circumventing 21 cm foregrounds

The 21 cm line of neutral hydrogen is a promising probe of the Epoch of Reionization (EoR) but suffers from contamination by spectrally smooth foregrounds, which obscure the large-scale signal along the line of sight. We explore the possibility of indirectly extracting the 21 cm signal in the presence of foregrounds by taking advantage of nonlinear couplings between large and small scales, both at the level of the density field and a biased tracer of that field. When combined with effective field theory techniques, bias expansions allow for a systematic treatment of nonlinear mode-couplings in the map between the underlying density field and the 21 cm field. We apply an effective bias expansion to density information generated with $\texttt{21cmFAST}$ using a variety of assumptions about which information can be recovered by different surveys and density estimation techniques. We find that the 21 cm signal produced by our effective bias expansion, combined with our least optimistic foreground assumptions, produces $\sim30\%$ cross-correlations with the true 21 cm field. Providing complementary density information from high-redshift galaxy surveys yields a cross-correlation of 50-70%. The techniques presented here may be combined with foreground mitigation strategies in order to improve the recovery of the large-scale 21 cm signal.

astro-ph.CO↗

arXiv2026

A Path to an All-Sky Survey with Roman

A deep, space-based, all-sky near-infrared survey carried out with the Nancy Grace Roman Space Telescope would constitute a foundational astronomical infrastructure for decades to come. In this white paper, we present a concrete and feasible path to imaging the entire sky at $\sim0.1''$ resolution, beginning with high-impact fields in Cycle 1 and scaling to ultra-wide coverage within the nominal mission. This first-epoch survey will reach $\mathrm{H}\sim25.5$ AB mag (5$σ$) and maximize synergies with contemporaneous observatories, while preserving substantial time for other ambitious Roman programs. We outline representative scheduling scenarios and an example Cycle 1 program that triples early Roman-LSST overlap and delivers high-value community data products such as LSST forced photometry, joint \textit{Gaia}-Roman astrometry, and catalogs of Galactic substructure, stong lenses, and other rare systems. The Cycle 1 program will lay the foundation for an eventual all-sky survey, while also delivering high-impact early science. We invite broad community participation in shaping and carrying out both the initial program and the long-term vision of an all-sky Roman survey.

astro-ph.IM↗

arXiv2025

Field-level Reconstruction from Foreground-Contaminated 21-cm Maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the "foreground wedge". In this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

astro-ph.CO↗

arXiv2025

First Results from HERA Phase II

We report the first upper limits on the power spectrum of 21-cm fluctuations during the Epoch of Reionization and Cosmic Dawn from Phase II of the Hydrogen Epoch of Reionization Array (HERA) experiment. HERA Phase II constitutes several significant improvements in the signal chain compared to Phase I, most notably resulting in expanded frequency bandwidth, from 50-250 MHz. In these first upper limits, we investigate a small two-week subset of the available Phase II observations, with a focus on identifying new systematic characteristics of the instrument, and establishing an analysis pipeline to account for them. We report 2$σ$ upper limits in eight spectral bands, spanning $5.6 \leq z \leq 24.4$ that are consistent with thermal noise at the $2σ$ level for $k \gtrsim 0.6-0.9 h{\rm Mpc}^{-1}$ (band dependent). Our tightest limit during Cosmic Dawn ($z>12$) is $1.13\times 10^6 {\rm mK}^2$ at ($k=0.55 h{\rm Mpc}^{-1}, z=16.78$), and during the EoR ($5.5<z<12$) it is $1.78\times 10^3 {\rm mK}^2$ at ($k=0.70 h{\rm Mpc}^{-1}, z=7.05$). We find that mutual coupling has become our dominant systematic, leaking foreground power that strongly contaminates the low-$k$ modes, resulting in the loss of modes from $k=0.35-0.55$ compared to Phase I data.

astro-ph.CO↗

arXiv2025

Higgs Production Classifier using Weak Supervision

A reliable determination of the Higgs production mechanism in hadron collider experiments is essential in the program of the measurements of the Higgs couplings. We employ weak supervision, CWoLa in particular, to train deep neural networks using real data of the diphoton events, in the hope of reducing biases resulting from Monte Carlo simulations. Models based on the convolutional neural network and the transformer are tested and compared. In particular, the classification performance gets slightly better when the photon information is removed from training on the low-luminosity region of $H \to γγ$. We explicitly show that the performance can be improved when the training dataset is enlarged by data augmentation using physics-motivated methods. We further demonstrate that the trained model can be successfully applied to the $H \to ZZ$ and $H \to Zγ$ events, showing that such classifiers are agnostic to Higgs decay modes provided they do not involve strong QCD corrections.

hep-ph↗

arXiv2025

Exploring One-point Statistics in HERA Phase I Data: Effects of Foregrounds and Systematics on Measuring One-Point Statistics

Measuring one-point statistics in redshifted 21 cm intensity maps offers an opportunity to explore non-Gaussian features of the early universe. We assess the impact of instrumental effects on measurements made with the Hydrogen Epoch of Reionization Array (HERA) by forward modeling observational and simulation data. Using HERA Phase I observations over 94 nights, we examine the second (m2, variance) and third (m3) moments of images. We employ the DAYENU-filtering method for foreground removal and reduce simulated foreground residuals to 10% of the 21 cm signal residuals. In noiseless cosmological simulations, the amplitudes of one-point statistics measurements are significantly reduced by the instrument response and further reduced by wedge-filtering. Analyses with wedge-filtered observational data, along with expected noise simulations, show that systematics alter the probability distribution of the map pixels. Likelihood analysis based on the observational data shows m2 measurements disfavor the cold reionization model characterized by inefficient X-ray heating, in line with other power spectra measurements. Small signals in m3 due to the instrument response of the Phase I observation and wedge-filtering make it challenging to use these non-Gaussian statistics to explore model parameters. Forecasts with the full HERA array predict high signal-to-noise ratios for m2, m3, and S3 assuming no foregrounds, but wedge-filtering drastically reduces these ratios. This work demonstrates conclusively that a comprehensive understanding of instrumental effects on m2 and m3 is essential for their use as a cosmological probe, given their dependence on the underlying model.

astro-ph.CO↗

arXiv2025

Stacking 21-cm Maps around Lyman-$α$ Emitters during Reionization: Prospects for a Cross-correlation Detection with the Hydrogen Epoch of Reionization Array

Observations of the redshifted 21-cm line during the Epoch of Reionization will open a new window to probe the intergalactic medium during the formation of the first stars, galaxies, and black holes. A particularly promising route to an initial detection is to cross-correlate tomographic 21-cm maps with spectroscopically confirmed Lyman-$α$ emitters (LAEs). High-redshift LAEs preferentially reside in ionized bubbles that are strongly anticorrelated with the surrounding neutral regions traced by 21-cm observations. In this work, we study the prospect of detecting such a cross-correlation signal by stacking 21-cm image cubes around LAEs using a current-generation 21-cm instrument -- the Hydrogen Epoch of Reionization Array (HERA). Our forecast adopts a realistic mapping pipeline to generate foreground-free 21-cm image cubes. The statistical properties of these images, arising from the complex instrumental response, are carefully accounted for. We further introduce a physically motivated signal template calibrated on the THESAN radiation-hydrodynamic simulations, which connects the cross-correlation amplitude to the global neutral fraction. Our results show that a sample of ~50 spectroscopically confirmed LAEs is sufficient to begin constraining the reionization history. These results represent an important preparatory step toward joint analyses of 21-cm experiments with upcoming wide-area, high-redshift galaxy surveys from Euclid and the Nancy Grace Roman Space Telescope.

astro-ph.CO↗

arXiv2025

A demonstration of the effect of fringe-rate filtering in the Hydrogen Epoch of Reionization Array delay power spectrum pipeline

Radio interferometers targeting the 21cm brightness temperature fluctuations at high redshift are subject to systematic effects that operate over a range of different timescales. These can be isolated by designing appropriate Fourier filters that operate in fringe-rate (FR) space, the Fourier pair of local sidereal time (LST). Applications of FR filtering include separating effects that are correlated with the rotating sky vs. those relative to the ground, down-weighting emission in the primary beam sidelobes, and suppressing noise. FR filtering causes the noise contributions to the visibility data to become correlated in time however, making interpretation of subsequent averaging and error estimation steps more subtle. In this paper, we describe fringe rate filters that are implemented using discrete prolate spheroidal sequences, and designed for two different purposes -- beam sidelobe/horizon suppression (the `mainlobe' filter), and ground-locked systematics removal (the `notch' filter). We apply these to simulated data, and study how their properties affect visibilities and power spectra generated from the simulations. Included is an introduction to fringe-rate filtering and a demonstration of fringe-rate filters applied to simple situations to aid understanding.

astro-ph.CO↗

arXiv2025

Evolution of Massive Red Galaxies in Clusters from z=1.0 to z=0.3

A critical issue in studying the evolution of galaxy clusters is to find ways that enable meaningful comparisons of clusters observed at different redshifts, as well as in various stages of their growth. Studies in the past have typically suffered from uncertainties in cluster mass estimates due to the scatter between cluster observables and mass. Here we propose a novel and general approach that uses the probability distribution function of an observable-cluster mass relation, together with dark matter halo merger trees extracted from numerical simulations, such that one can trace the evolution in a self-contained fashion, for clusters chosen to lie in a specified range in mass and redshift. This method, when applied to clusters of different mass ranges, further allows one to examine the evolution of various observable-cluster mass scaling relations. We illustrate the potential of this method by studying the stellar mass content of red cluster member galaxies, as well as the growth of brightest cluster galaxies, from z=1.0 to z=0.3, using a large optically-detected cluster sample from the Subaru Hyper Suprime-Cam Survey, finding good agreement with previous studies.

astro-ph.GA↗

arXiv2025

Flow-based sampling for multimodal and extended-mode distributions in lattice field theory

Recent results have demonstrated that samplers constructed with flow-based generative models are a promising new approach for configuration generation in lattice field theory. In this paper, we present a set of training- and architecture-based methods to construct flow models for targets with multiple separated modes (i.e.~vacua) as well as targets with extended/continuous modes. We demonstrate the application of these methods to modeling two-dimensional real and complex scalar field theories in their symmetry-broken phases. In this context we investigate different flow-based sampling algorithms, including a composite sampling algorithm where flow-based proposals are occasionally augmented by applying updates using traditional algorithms like HMC.

hep-lat↗

arXiv2025

matvis: A matrix-based visibility simulator for fast forward modelling of many-element 21 cm arrays

Detection of the faint 21 cm line emission from the Cosmic Dawn and Epoch of Reionisation will require not only exquisite control over instrumental calibration and systematics to achieve the necessary dynamic range of observations but also validation of analysis techniques to demonstrate their statistical properties and signal loss characteristics. A key ingredient in achieving this is the ability to perform high-fidelity simulations of the kinds of data that are produced by the large, many-element, radio interferometric arrays that have been purpose-built for these studies. The large scale of these arrays presents a computational challenge, as one must simulate a detailed sky and instrumental model across many hundreds of frequency channels, thousands of time samples, and tens of thousands of baselines for arrays with hundreds of antennas. In this paper, we present a fast matrix-based method for simulating radio interferometric measurements (visibilities) at the necessary scale. We achieve this through judicious use of primary beam interpolation, fast approximations for coordinate transforms, and a vectorised outer product to expand per-antenna quantities to per-baseline visibilities, coupled with standard parallelisation techniques. We validate the results of this method, implemented in the publicly-available matvis code, against a high-precision reference simulator, and explore its computational scaling on a variety of problems.

astro-ph.IM↗

arXiv2025

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: I. Cluster Catalog, Selection Function and Mass--Observable Relation

We present the first step toward deriving cosmological constraints through the abundances of galaxy clusters selected in a $510\,\mathrm{deg}^2$ weak-lensing aperture mass map, constructed with the Year-Three shear catalog from the Hyper Suprime-Cam Subaru Strategic Program. We adopt a conservative source galaxy selection to construct a sample of $129$ weak-lensing peaks with a signal-to-noise ratio above $4.7$. We use semi-analytical injection simulations to derive the selection function and the mass--observable relation of our sample. These results take into account complicated uncertainties associated with weak-lensing measurements, such as the non-uniform survey depth and the complex survey geometry, projection effects from uncorrelated large-scale structures, and the intrinsic alignment of source galaxies. We also propose a novel modeling framework to make parts of the mass--observable relation insensitive to assumed cosmological parameters. Such a framework not only offers a great computational advantage to cosmological studies, but can also benefit future astrophysical studies using shear-selected clusters. Our results are an important step toward utilizing these cluster samples that are constructed nearly independent of any baryonic assumptions in upcoming deep-and-wide lensing surveys from the Vera Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

astro-ph.CO↗

arXiv2024

Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment.

astro-ph.CO↗

arXiv2024

Weak-Lensing Shear-Selected Galaxy Clusters from the Hyper Suprime-Cam Subaru Strategic Program: II. Cosmological Constraints from the Cluster Abundance

We present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the three-year (Y3) weak-lensing data with an area of $\approx500~$deg$^2$, resulting in a sample size of $129$ clusters with high signal-to-noise ratios $ν$ of $ν\geq4.7$. Owing to the deep, wide-field, and uniform imaging of the HSC survey, this is by far the largest sample of shear-selected clusters, in which the selection solely depends on gravity and is free from any assumptions about the dynamical state. Informed by the optical counterparts, the shear-selected clusters span a redshift range of $z\lesssim0.7$ with a median of $z\approx0.3$. The lensing sources are securely selected at $z\gtrsim0.7$ with a median of $z\approx1.3$, leading to nearly zero cluster member contamination. We carefully account for (1) the bias in the photometric redshift of sources, (2) the bias and scatter in the weak-lensing mass using a simulation-based calibration, and (3) the measurement uncertainty that is directly estimated on the mass maps using an injection-based method developed in a companion paper (Chen et al. submitted). In a blind analysis, the fully marginalized posteriors of the cosmological parameters are obtained as $Ω_{\mathrm{m}} = 0.50^{+0.28}_{-0.24}$, $σ_8 = 0.685^{+0.161}_{-0.088}$, $\hat{S}_{8}\equivσ_8\left(Ω_{\mathrm{m}}/0.3\right)^{0.25} = 0.835^{+0.041}_{-0.044}$, and $σ_8\left(Ω_{\mathrm{m}}/0.3\right)^{0.5} = 0.993^{+0.084}_{-0.126}$ in a flat $Λ$CDM model. We compare our cosmological constraints with other studies, including those based on cluster abundances, galaxy-galaxy lensing and clustering, and Cosmic Microwave Background observed by $Planck$, and find good agreement at levels of $\lesssim2σ$. [abridged]

astro-ph.CO↗

arXiv2024

Jet Discrimination with Quantum Complete Graph Neural Network

Machine learning, particularly deep neural networks, has been widely used in high-energy physics, demonstrating remarkable results in various applications. Furthermore, the extension of machine learning to quantum computers has given rise to the emerging field of quantum machine learning. In this paper, we propose the Quantum Complete Graph Neural Network (QCGNN), which is a variational quantum algorithm based model designed for learning on complete graphs. QCGNN with deep parametrized operators offers a polynomial speedup over its classical and quantum counterparts, leveraging the property of quantum parallelism. We investigate the application of QCGNN with the challenging task of jet discrimination, where the jets are represented as complete graphs. Additionally, we conduct a comparative analysis with classical models to establish a performance benchmark.

hep-ph↗

arXiv2024

A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey

Superclusters, encompassing environments across a wide range of overdensities, can be regarded as unique laboratories for studying galaxy evolution. Although numerous supercluster catalogs have been published, none of them goes beyond redshift $z=0.7$. In this work, we adopt a physically motivated supercluster definition, requiring that superclusters should eventually collapse even in the presence of dark energy. Applying a friends-of-friends (FoF) algorithm to the CAMIRA cluster sample constructed using the Subaru Hyper Suprime-Cam survey data, we have conducted the first systematic search for superclusters at $z=0.5-1.0$ and identified 673 supercluster candidates over an area of 1027 deg$^2$. The FoF algorithm is calibrated by evolving $N$-body simulations to the far future to ensure high purity. We found that these high-$z$ superclusters are mainly composed of $2-4$ clusters, suggesting the limit of gravitationally bound structures in the younger Universe. In addition, we studied the properties of the clusters and brightest cluster galaxies (BCGs) residing in different large-scale environments. We found that clusters associated with superclusters are typically richer, but no apparent dependence of the BCG properties on large-scale structures is found. We also compared the abundance of observed superclusters with mock superclusters extracted from halo light cones, finding that photometric redshift uncertainty is a limiting factor in the performance of superclusters detection.

astro-ph.CO↗