Search

The $E_G$ statistic provides a valuable tool for evaluating predictions of General Relativity (GR) by probing the relationship between gravitational potential and galaxy clustering on cosmological scales within the observable universe. In this study, we constrain the $E_G$ statistic using photometric redshift data from the Dark Energy Survey (DES) MagLim sample in combination with the Planck 2018 Cosmic Microwave Background (CMB) lensing map. Unlike spectroscopic redshift surveys, photometric redshift measurements are subject to significant redshift uncertainties, making it challenging to constrain the redshift distortion parameter $\beta$ with high precision. We adopt a new definition for this parameter, $\beta(z) = {f\sigma_8(z)}/{b\sigma_8(z)}$. In this formulation, we reconstruct the growth rate of structure, $f\sigma_8(z)$, using Artificial Neural Networks (ANN) method, while simultaneously utilizing model-independent constraints on the parameter $b\sigma_8(z)$, directly obtained from the DES collaboration. After obtaining the angular power spectra $C_\ell^{gg}$ (galaxy-galaxy) and $C_\ell^{g\kappa}$ (galaxy-CMB lensing) from the combination of DES photometric data and Planck lensing, we derive new measurements of the $E_G$ statistic: $E_G = 0.354 \pm 0.146$, $0.452 \pm 0.092$, $0.414 \pm 0.069$, and $0.296 \pm 0.069$ (68$\%$ C.L.) across four redshift bins: $z = 0.30, 0.47, 0.63$, and $0.80$, respectively, which are consistent with the predictions of the standard $\Lambda$CDM model. Finally, we forecast the $E_G$ statistic using future photometric redshift data from the China Space Station Telescope, combined with lensing measurements from the CMB-S4 project, indicating an achievable constraint on $E_G$ of approximately 1$\%$, improving the precision of tests for GR on cosmological scales., Comment: 17 pages, 6 figures, 3 tables, Accepted to ApJS

In this work, we perform a detailed analysis to constrain the Hu-Sawicki $f(R)$ gravity model, using cosmic shear data from three prominent Stage-III weak lensing surveys: DES-Y3, KiDS-1000, and HSC-Y3. To accurately model the nonlinear matter clustering in the analysis of cosmic shear signals, we employ FREmu, a recently developed power spectrum emulator for the $f(R)$ gravity trained on the Quijote-MG simulations. This emulator achieves precise predictions, limiting the errors to 5% on scales of $0.009h\,{\rm Mpc}^{-1} < k < 0.5h\,{\rm Mpc}^{-1}$. Our findings reveal that cosmic shear data alone impose only weak constraints on the $f(R)$ parameter $\log_{10}|f_{R_0}|$. To improve these constraints, we incorporate state-of-the-art external observations, including data from the cosmic microwave background and baryon acoustic oscillations. The inclusion of these external datasets significantly enhances the constraints, yielding an upper limit of $\log_{10}|f_{R_0}| < -4.79$ at the 95% confidence level., Comment: 9 pages, 3 figures, 1 table

This paper leverages the first released catalog from the FAST All Sky \textsc{Hi} Survey (FASHI) to examine the hypothesis of cosmic isotropy in the local Universe. Given the design of the overall FAST survey, the inhomogeneous detection sensitivity of FASHI is likely to introduce significant biases in the statistical properties of the catalog. To mitigate the potential influence of spurious clustering effects due to these sensitivity variations, we focus on extragalactic \textsc{Hi} sources within the sensitivity range of $[0.65, 1.0]$. This refined subsample is divided into ten distinct sky regions, for which we compute the two-point angular correlation functions (2PACF) over angular scales of $0.5^\circ < \theta < 10^\circ$. We apply the Markov chain Monte Carlo method to fit these 2PACFs with a power-law model and assess the statistical significance of the best-fit parameters for the ten FASHI sky regions by comparing them against results from mock catalogs generated under the assumptions of homogeneity and isotropy. Our findings indicate that the local Universe, as traced by the \textsc{Hi} sources in the FASHI survey, aligns with the cosmic isotropy hypothesis within a $2\sigma$ confidence level. We do not detect any statistically significant deviations from cosmic isotropy in the FASHI survey data., Comment: 11 pages, 4 figures, 3 Tables, accept for Astrophysical Journal

Building a comprehensive catalog of galaxy clusters is a fundamental task for the studies on the structure formation and galaxy evolution. In this paper, we present COSMIC (Cluster Optical Search using Machine Intelligence in Catalogs), an algorithm utilizing machine learning techniques to efficiently detect galaxy clusters. COSMIC involves two steps, including the identification of the brightest cluster galaxies and the estimation of the cluster richness. We train our models on the galaxy data from the Sloan Digital Sky Survey and WHL galaxy cluster catalog. Validated to a test data in the region of northern Galactic cap, COSMIC algorithm demonstrates a high completeness when cross-matching with previous cluster catalogs. Richness comparison with previous optical and X-ray measurements also demonstrated a tight correlation. Our methodology showcases robust performance in galaxy cluster detection and holds promising prospects for applications in upcoming large-scale surveys., Comment: 22 pages, 18 figures. Accepted for publication in APJS

We investigate the excitation spectra of a spin-1/2 antiferromagnetic Heisenberg trimer spin chain by employing a combination of numerical and theoretical techniques. Utilizing the Krylov-space correction-vector method in density matrix renormalization group (DMRG), we calculate both the direct and indirect resonant inelastic x-ray scattering (RIXS) spectra for the trimer spin chain. To interpret the observed features in the RIXS spectra, we perform a theoretical perturbative analysis to compute the energy dispersions which are then utilized to determine the density of states (DOS) for both the single-particle and the two-particle excitation spectra. Our results show that the single-particle continua of the direct RIXS spectrum align with the energy levels observed in the DOS spectra of spinon, doublon, and quarton excitations. Furthermore, the two-particle continua are revealed in the indirect RIXS process, where all possible single particle excitations combine to form the various two-particle excitations of the trimer spin chain. Based on our calculations, we propose the RIXS mechanism of generating the fractionalized (spinon) and collective (doublon and quarton) excitations in the trimer spin chain at both the $L$-edge and the $K$-edge, including discussing the interplay of these excitations in the RIXS spectrum for various trimer coupling strength. The computed energy range of the excitations suggest the possibility of experimental detection at both the $L$-edge and the $K$-edge within the current capabilities of RIXS instrumentation resolution., Comment: 14 pages, 6 figures

Primordial magnetic fields (PMFs) play a pivotal role in influencing small-scale fluctuations within the primordial density field, thereby enhancing the matter power spectrum within the context of the $\Lambda$CDM model at small scales. These amplified fluctuations accelerate the early formation of galactic halos and stars, which can be observed through advanced high-redshift observational techniques. Therefore, Stellar Mass Density (SMD) observations, which provide significant opportunities for detailed studies of galaxies at small scales and high redshifts, offer a novel perspective on small-scale cosmic phenomena and constrain the characteristics of PMFs. In this study, we compile 14 SMD data points at redshifts $z > 6$ and derive stringent constraints on the parameters of PMFs, which include the amplitude of the magnetic field at a characteristic scale of $\lambda=1\,{\rm Mpc}$, denoted as $B_0$, and the spectral index of the magnetic field power spectrum, $n_{\rm B}$. At 95\% confidence level, we establish upper limits of $B_0 < 4.44$ nG and $n_{\rm B} < -2.24$, along with a star formation efficiency of approximately $f_*^0 \sim 0.1$. If we fix $n_{\rm B}$ at specific values, such as $-2.85$, $-2.9$, and $-2.95$, the 95\% upper limits for the amplitude of the magnetic field can be constrained to 1.33 nG, 2.21 nG, and 3.90 nG, respectively. Finally, we attempt to interpret recent early observations provided by James Webb Space Telescope (JWST) using the theory of PMFs, and find that by selecting appropriate PMF parameters, it is possible to explain these results without significantly increasing the star formation efficiency.

In our previous study, we introduced a machine-learning technique, namely CMBFSCNN, for the removal of foreground contamination in cosmic microwave background (CMB) polarization data. This method was successfully employed on actual observational data from the Planck mission. In this study, we extend our investigation by considering the CMB lensing effect in simulated data and utilizing the CMBFSCNN approach to recover the CMB lensing B-mode power spectrum from multi-frequency observational maps. Our method is first applied to simulated data with the performance of CMB-S4 experiment. We achieve reliable recovery of the noisy CMB Q (or U) maps with a mean absolute difference of $0.016\pm0.008\ \mu$K (or $0.021\pm0.002\ \mu$K) for the CMB-S4 experiment. To address the residual instrumental noise in the foreground-cleaned map, we employ a "half-split maps" approach, where the entire dataset is divided into two segments sharing the same sky signal but having uncorrelated noise. Using cross-correlation techniques between two recovered half-split maps, we effectively reduce instrumental noise effects at the power spectrum level. As a result, we achieve precise recovery of the CMB EE and lensing B-mode power spectra. Furthermore, we also extend our pipeline to full-sky simulated data with the performance of LiteBIRD experiment. As expected, various foregrounds are cleanly removed from the foreground contamination observational maps, and recovered EE and lensing B-mode power spectra exhibit excellent agreement with the true results. Finally, we discuss the dependency of our method on the foreground models., Comment: 26 pages, 16 figures, 3 table, accepted by ApJS

Within the mass range of $10^{16}-5\times 10^{18}$ g, primordial black holes (PBHs) persist as plausible candidates for dark matter. Our study involves a reassessment of the constraints on PBHs through a comparative analysis of the cosmic X-ray background (CXB) and the emissions arising from their Hawking evaporation. We identify previously overlooked radiation processes across the relevant energy bands, potentially refining the bounds on PBHs. These processes encompass the direct emission from Hawking radiation, in-flight annihilation, the final state of radiation, and positronium annihilation. Thorough consideration is given to all these processes and their respective emission fractions, followed by a precise calculation of the $\mathcal{D}$ factor for observations directed towards the high-latitude Galactic contribution. Furthermore, we integrate the flux originating from extragalactic sources, both of which contribute to the measured isotropic flux. Through a comparative analysis of data derived from previous CXB observations utilizing an Active Galactic Nuclei (AGN) double power-law model, we establish the most stringent constraints for PBHs, thereby excluding the possibility of PBHs constituting the entire dark matter mass within the range of $2.5\times 10^{17}-3 \times 10^{17} $g., Comment: 15 pages, 6 figures

Motivated by recent advancements in theoretical and experimental studies of the high-energy excitations on an antiferromagnetic trimer chain, we numerically investigate the quantum phase transition and composite dynamics in this system by applying a magnetic field. The numerical methods we used include the exact diagonalization, density matrix renormalization group, time-dependent variational principle, and cluster perturbation theory. From calculating the entanglement entropy, we have revealed the phase diagram which includes the XY-I, $1/3$ magnetization plateau, XY-II, and ferromagnetic phases. Both the critical XY-I and XY-II phases are characterized by the conformal field theory with a central charge $c \simeq 1$. By analyzing the dynamic spin structure factor, we elucidate the distinct features of spin dynamics across different phases. In the regime with weak intertrimer interaction, we identify the intermediate-energy and high-energy modes in the XY-I and $1/3$ magnetization plateau phases as internal trimer excitations, corresponding to the propagating of doublons and quartons, respectively. Notably, applying a magnetic field splits the high-energy spectrum into two branches, labeled as the upper quarton and lower quarton. Furthermore, we explore the spin dynamics of a frustrated trimerized model closely related to the quantum magnet \ce{Na_2Cu_3Ge_4O_12}. In the end, we extend our discuss on the possibility of the quarton Bose-Einstein condensation in the trimer systems. Our results are expected to be further verified through the inelastic neutron scattering and resonant inelastic X-ray scattering, and also provide valuable insights for exploring high-energy exotic excitations., Comment: 15+6 pages, 16 figures, to be published in npj Quantum materials

We investigate the magnetic excitations of the trimerized Heisenberg models with intra-trimer interaction $J_1$ and inter-trimer interaction $J_2$ on four different two-dimensional lattices using a combination of stochastic series expansion quantum Monte Carlo (SSE QMC) and stochastic analytic continuation methods (SAC), complemented by cluster perturbation theory (CPT). These models exhibit quasi-particle-like excitations when $g=J_2/J_1$ is small, characterized by low-energy magnons, intermediate-energy doublons, and high-energy quartons. The low-energy magnons are associated with the magnetic ground states. They can be described by the linear spin wave theory (LSWT) of the effective block spin model and the original spin model. Doublons and quartons emerge from the corresponding internal excitations of the trimers with distinct energy levels, which can be effectively analyzed using perturbation theory when the ratio of exchange interactions $g$ is small. In this small $g$ regime, we observe a clear separation between the magnon and higher-energy spectra. However, as $g$ increases, these three spectra gradually merge into the magnon modes or continua. Nevertheless, the LSWT fails to provide quantitative descriptions of the higher-energy excitation bands due to significant quantum fluctuations. Notably, in the Collinear II and trimerized hexagon lattice, a broad continuum emerges above the single-magnon spectrum, originating from the quasi-1D physics due to the dilute connections between chains. Our numerical analysis of these 2D trimers yields valuable theoretical predictions and explanations for the inelastic neutron scattering (INS) spectra of 2D magnetic materials featuring trimerized lattices.

In previous works, we proposed to estimate cosmological parameters with the artificial neural network (ANN) and the mixture density network (MDN). In this work, we propose an improved method called the mixture neural network (MNN) to achieve parameter estimation by combining ANN and MDN, which can overcome shortcomings of the ANN and MDN methods. Besides, we propose sampling parameters in a hyper-ellipsoid for the generation of the training set, which makes the parameter estimation more efficient. A high-fidelity posterior distribution can be obtained using $\mathcal{O}(10^2)$ forward simulation samples. In addition, we develop a code-named CoLFI for parameter estimation, which incorporates the advantages of MNN, ANN, and MDN, and is suitable for any parameter estimation of complicated models in a wide range of scientific fields. CoLFI provides a more efficient way for parameter estimation, especially for cases where the likelihood function is intractable or cosmological models are complex and resource-consuming. It can learn the conditional probability density $p(\boldsymbol\theta|\boldsymbol{d})$ using samples generated by models, and the posterior distribution $p(\boldsymbol\theta|\boldsymbol{d}_0)$ can be obtained for a given observational data $\boldsymbol{d}_0$. We tested the MNN using power spectra of the cosmic microwave background and Type Ia supernovae and obtained almost the same result as the Markov Chain Monte Carlo method. The numerical difference only exists at the level of $\mathcal{O}(10^{-2}\sigma)$. The method can be extended to higher-dimensional data., Comment: 24 pages, 8 tables, 17 figures, ApJS, corrected the PReLU formula in Table 5. The code repository is available at https://github.com/Guo-Jian-Wang/colfi

The lensing effect of the cosmic microwave background (CMB) is a powerful tool for our study of the distribution of matter in the universe. Currently, the quadratic estimator (EQ) method, which is widely used to reconstruct lensing potential, has been known to be sub-optimal for the low-noise levels polarization data from next-generation CMB experiments. To improve the performance of the reconstruction, other methods, such as the maximum likelihood estimator and machine learning algorithms are developed. In this work, we present a deep convolutional neural network model named the Residual Dense Local Feature U-net (RDLFUnet) for reconstructing the CMB lensing convergence field. By simulating lensed CMB data with different noise levels to train and test network models, we find that for noise levels less than $5\mu$K-arcmin, RDLFUnet can recover the input gravitational potential with a higher signal-to-noise ratio than the previous deep learning and the traditional QE methods at almost the entire observation scales., Comment: 12 pages, 8 figures, accepted by ApJ

Primordial B-mode detection is one of the main goals of next-generation cosmic microwave background (CMB) experiments. Primordial B-modes are a unique signature of primordial gravitational waves (PGWs). However, the gravitational interaction of CMB photons with large-scale structures will distort the primordial E modes, adding a lensing B-mode component to the primordial B-mode signal. Removing the lensing effect (`delensing') from observed CMB polarization maps will be necessary to improve the constraint of PGWs and obtain a primordial E-mode signal. Here, we introduce a deep convolutional neural network model named multi-input multi-output U-net (MIMO-UNet) to perform CMB delensing. The networks are trained on simulated CMB maps with size $20^{\circ} \times 20^{\circ}$. We first use MIMO-UNet to reconstruct the unlensing CMB polarization ($Q$ and $U$) maps from observed CMB maps. The recovered E-mode power spectrum exhibits excellent agreement with the primordial EE power spectrum. The recovery of the primordial B-mode power spectrum for noise levels of 0, 1, and 2 $\mu$K-arcmin is greater than 98\% at the angular scale of $\ell<150$. We additionally reconstruct the lensing B map from observed CMB maps. The recovery of the lensing B-mode power spectrum is greater than roughly 99\% at the scales of $\ell>200$. We delens observed B-mode power spectrum by subtracting reconstructed lensing B-mode spectrum. The recovery of tensor B-mode power spectrum for noise levels of 0, 1, 2 $\mu$K-arcmin is greater than 98 \% at the angular scales of $\ell<120$. Even at $\ell=160$, the recovery of tensor B-mode power spectrum is still around 71 \%., Comment: 18 pages, 14 figures, 1 table, accepted by ApJS

Primordial B-mode detection is one of the main goals of current and future cosmic microwave background (CMB) experiments. However, the weak B-mode signal is overshadowed by several Galactic polarized emissions, such as thermal dust emission and synchrotron radiation. Subtracting foreground components from CMB observations is one of the key challenges in searching for the primordial B-mode signal. Here, we construct a deep convolutional neural network (CNN) model, called \texttt{CMBFSCNN} (Cosmic Microwave Background Foreground Subtraction with CNN), which can cleanly remove various foreground components from simulated CMB observational maps at the sensitivity of the CMB-S4 experiment. Noisy CMB Q (or U) maps are recovered with a mean absolute difference of $0.018 \pm 0.023\ \mu$K (or $0.021 \pm 0.028\ \mu$K). To remove the residual instrumental noise from the foreground-cleaned map, inspired by the needlet internal linear combination method, we divide the whole data set into two ``half-split maps,'' which share the same sky signal, but have uncorrelated noise, and perform a cross-correlation technique to reduce the instrumental noise effects at the power spectrum level. We find that the CMB EE and BB power spectra can be precisely recovered with significantly reduced noise effects. Finally, we apply this pipeline to current Planck observations. As expected, various foregrounds are cleanly removed from the Planck observational maps, with the recovered EE and BB power spectra being in good agreement with the official Planck results., Comment: 9 pages, 4 figures, 1 table

In this $\textit{Letter}$, we search for the signal of the primordial black holes (PBHs) by correlating the $\gamma$-ray emissions in the MeV energy band produced by the Hawking evaporation and the lensing effect of the cosmic microwave background (CMB). We use the conservative case of the astrophysical model as much as possible in the calculations, since the potential astrophysical origins dominate the observed emission in the MeV energy band. By carefully discussing the appropriate energy bands corresponding to different PBHs masses, it is worth expecting a tight constraint on the fraction of the Schwarzschild PBHs in the mass range of $10^{16} - 5\times10^{17}\,{\rm g}$, by simulations of the sensitivity of the future CMB-S4 project and the $\gamma$-ray telescope e-ASTROGAM. Furthermore, we also consider the PBHs model with spins, and find that the constraining ability of the PBHs fraction from the correlation between CMB lensing and $\gamma$-ray emissions can be improved by another order of magnitude, which could importantly fill the gaps with PBHs fraction limits in the mass range of $5\times 10^{17} - 2\times 10^{18}\,{\rm g}$., Comment: 7 pages, 4 figures, accepted for publication in ApJL

The cosmological principle states that our Universe is statistically homogeneous and isotropic at large scales. However, due to the relative motion of the Solar System, an additional kinematic dipole can be detected in the distribution of galaxies, which should be consistent with the dipole observed in the cosmic microwave background temperature. In this paper, we forecast the mock number count maps from the China Space Station Telescope photometric survey to reconstruct the kinematic dipole. Using the whole photometric mock data, we obtain a positive evidence for the dipole signal detection at 3 sigma confidence level, and the significance would be increased to 4 sigma when we only use the high-redshift samples with z = 1.8 to 4. This result can provide a good consistency check between the kinematic dipoles measured in the CMB and that from the large scale structure, which can help us to verify the basic cosmological principle.

In this work, we propose using the mixture density network (MDN) to estimate cosmological parameters. We test the MDN method by constraining parameters of the $\Lambda$CDM and $w$CDM models using Type Ia supernovae and the power spectra of the cosmic microwave background. We find that the MDN method can achieve the same level of accuracy as the Markov Chain Monte Carlo method, with a slight difference of $\mathcal{O}(10^{-2}\sigma)$. Furthermore, the MDN method can provide accurate parameter estimates with $\mathcal{O}(10^3)$ forward simulation samples, which are useful for complex and resource-consuming cosmological models. This method can process either one data set or multiple data sets to achieve joint constraints on parameters, extendable for any parameter estimation of complicated models in a wider scientific field. Thus, the MDN provides an alternative way for likelihood-free inference of parameters., Comment: 17 pages, 4 tables, 15 figures, match the published version. The code repository is available at https://github.com/Guo-Jian-Wang/mdncoper

Through the relationship between dispersion measures (DM) and redshifts, fast radio bursts (FRBs) are considered to be very promising cosmological probes. In this paper, we attempted to use the DM-z relationship of FRBs to study the helium abundance ($Y_{\rm He}$) in the universe. First, we used 17 current FRBs with known redshifts for our study. Due to their low redshifts and the strong degeneracy between $Y_{\rm He}$ and $\Omega_bh^2$, however, this catalog could not provide a good constraint on the helium abundance. Then, we simulated 500 low redshift FRB mock data with $z\in[0,\,1.5]$ to forecast the constraining ability on $Y_{\rm He}$. In order to break the degeneracy between $Y_{\rm He}$ and $\Omega_bh^2$ further, we introduced the shift parameters of the Planck measurement $(R,l_A,\Omega_bh^2)$ as a prior, where $\Omega_bh^2$ represents the baryon density parameter, and $R$ and $l_A$ correspond to the scaled distance to recombination and the angular scale of the sound horizon at recombination, respectively. We obtained the standard deviation for the helium abundance: $\sigma({Y_{\rm He}}) = 0.025$. Finally, we considered 2000 higher redshift FRB data with the redshift distribution of $[0,\,3]$ and found that the constraining power for $Y_{\rm He}$ would be improved by more than 2 times, $\sigma({Y_{\rm He}}) = 0.011$, which indicates that the FRB data with high redshift can provide a better constraint on the helium abundance. Hopefully, large FRB samples with high redshift from the Square Kilometre Array can provide high-precision measurements of the helium abundance in the near future., Comment: 12 pages, 4 figures

The cosmic microwave background (CMB), carrying the inhomogeneous information of the very early universe, is of great significance for understanding the origin and evolution of our universe. However, observational CMB maps contain serious foreground contaminations from several sources, such as galactic synchrotron and thermal dust emissions. Here, we build a deep convolutional neural network (CNN) to recover the tiny CMB signal from various huge foreground contaminations. Focusing on the CMB temperature fluctuations, we find that the CNN model can successfully recover the CMB temperature maps with high accuracy, and that the deviation of the recovered power spectrum $C_\ell$ is smaller than the cosmic variance at $\ell>10$. We then apply this method to the current Planck observation, and find that the recovered CMB is quite consistent with that disclosed by the Planck collaboration, which indicates that the CNN method can provide a promising approach to the component separation of CMB observations. Furthermore, we test the CNN method with simulated CMB polarization maps based on the CMB-S4 experiment. The result shows that both the EE and BB power spectra can be recovered with high accuracy. Therefore, this method will be helpful for the detection of primordial gravitational waves in current and future CMB experiments. The CNN is designed to analyze two-dimensional images, thus this method is not only able to process full-sky maps, but also partial-sky maps. Therefore, it can also be used for other similar experiments, such as radio surveys like the Square Kilometer Array., Comment: 20 pages, 25 figures, and 3 tables, updated citations in section 1. The code repository is available at https://github.com/Guo-Jian-Wang/cmbNNCS