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The field of cosmology and galaxy formation is undergoing a transformative era, driven by unprecedented data from cutting-edge observational campaigns such as the James Webb Space Telescope, the Kilo-Degree Survey (KiDS), the Dark Energy Spectroscopic Instrument (DESI), and the Euclid space mission. These surveys have delivered groundbreaking insights into the large-scale structure of the universe, the physics of galaxy formation and evolution, and the nature of cosmic constituents like dark energy, dark matter, and neutrinos. Recent advancements—including high-precision measurements of baryon acoustic oscillations, enhanced tensions in the fundamental cosmological parameters, evidence for dynamical dark energy, constraints on neutrino masses, and the rapid assembly of galaxies at high redshift—have raised profound questions about the standard cosmological model and spurred urgent interdisciplinary dialogue.
This conference, the 3rd Shanghai Assembly on Cosmology and Structure Formation, is designed to address these pivotal developments. By convening leading experts, early-career researchers, and key contributors to major international collaborations, the assembly will serve as a critical platform to synthesize emerging insights, debate contentious issues, and collectively advance our understanding of the universe’s structure, composition, and evolution. Through these efforts, we aspire to accelerate progress toward resolving cosmology's most pressing puzzles and shape the next generation of cosmic exploration.
The Shanghai Assembly is a biennial conference on cosmology, structure and galaxy formation, organized by the Astronomy department of Shanghai Jiao Tong University. The first edition was held in 2019 while the second edition was resumed in 2023 after the COVID break.
Invited Speakers:
Daniela Galarraga Espinosa (IPMU)
Carlos Frenk (Durham)
Myungkook James Jee (Yonsei)
Donghui Jeong (KIAS/Penn State)
Benjamin Joachimi (UCL)
Massimo Meneghetti (Bologna)
Ramon Miquel (IFAE)
Changbom Park (KIAS)
David Parkinson (KASI)
Yingjie Peng (KIAA/PKU)
Joop Schaye (Leiden)
Xin Wang (NAOC)
Cheng Zhao (Tsinghua)
| SOC: Carlos Frenk (Durham) Yipeng Jing (SJTU) Houjun Mo (UMass) Will Percival (UWaterloo) Changbom Park (KIAS) Ue-Li Pen (CITA/ASIAA) Volker Springel (MPA) Masahiro Takada (IPMU) Alessandro Sonnenfeld (SJTU, co-chair) Yu Yu (SJTU, Co-Chair) Zhongxu Zhai (SJTU, Co-Chair) | LOC: Lisha Duan (TDLI) Jiaxin Han (SJTU) Guoping Liu (SJTU) Alessandro Sonnenfeld (SJTU) Jie Wang (SJTU) Xiaohu Yang (SJTU/TDLI, chair) Yu Yu (SJTU) Zhongxu Zhai (SJTU) Pengjie Zhang (SJTU) |
The LCDM model has the virtue of having strong predictive power in so far as the properties of the dark matter are concerned. For example, the mass function of dark matter halos is known to high precision, from the mass scale of the Earth to that of rich clusters. The predictive power is weakened when baryons are considered because of the complex astrophysical processes to which they can give rise. This shortcoming can be mitigated with detailed modelling which has become increasingly sophisticated over the years. Neglecting such processes is dangerous and this has led to the often voiced view that LCDM suffers from a “small-scale crisis”, that is, that it disagrees with data on the scales of galaxies and below. I will discuss this perceived crisis and focus on claims that the abundance and properties of the galaxies recently discovered at very high redshift by the JWST are inconsistent with LCDM.
The Dark Energy Spectroscopic Instrument (DESI) has constructed the largest 3D map of galaxies and quasars to date, spanning the nearby Universe to a redshift of over 3. Recently, DESI has released cosmological measurements from its third-year (Y3) data, revealing evidences of dynamic dark energy. In this talk, I will review DESI results and discuss future developments.
TBD
Observational surveys of the distribution of matter in the universe are becoming ever more precise and continue to be extended to smaller scales and higher redshifts. To full exploit the observations, similar progress is required on the theoretical side. The redistribution of baryons by galactic winds, which is a major bottleneck in our understanding of the evolution of galaxies and large-scale structure, requires a convergence between models of galaxy formation and cosmology. I will present recent results from the FLAMINGO and COLIBRE suites of cosmological, hydrodynamical simulations, which provide insight into the physics of galaxy formation and the importance of baryonic effects for cosmology.
In this talk, I will present a systematic investigation into the connection between galaxy morphology and the properties of their host dark-matter halos using the IllustrisTNG-50 simulations.
I will briefly introduce a novel kinematic decomposition method that builds upon existing algorithms but features simple yet physical identification of different morphological components. This new method enables robust separation of thin and thick galactic discs. Importantly, the circularity threshold defining thin discs and the energy threshold separating dynamically hotter and colder galaxy regions both depend systematically on halo mass and environment. Applying this method to TNG50, I revisit the question which halo structural parameters constitute the best predictor for disc size, and find that halo spin, halo concentration and accretion rate all impact disc size for a given halo mass, challenging widely used semi-analytical recipes that predict disk size solely on the spin parameter. Employing Random Forest and Symbolic Regression, I predict galaxy morphologies with additional halo parameters. Preliminary results reveal empirical formulae predicting disc mass fractions, half-mass radii, and half-mass heights, with accuracy higher than other commonly used relations, which is super promising in the future semi-analytical models.
With JWST revolutionizing our view of the early Universe, theoretical predictions at high redshifts have become more critical than ever. We investigate the evolution of the galaxy stellar mass function (GSMF) and star formation rates (SFRs) across cosmic time using the new COLIBRE simulations of galaxy formation. COLIBRE improves upon the EAGLE model by incorporating a multiphase interstellar medium, computing radiative cooling rates of primordial elements in non-equilibrium, and employing more sophisticated prescriptions for stellar and AGN feedback. We present the GSMF from the COLIBRE simulations at three resolutions: gas particle masses of $\sim 10^7$, $\sim 10^6$, and $\sim 10^5~\mathrm{M_\odot}$ in cosmological volumes of $400^3$, $200^3$, and $50^3~\mathrm{cMpc}^3$, respectively. We demonstrate that COLIBRE reproduces the observed GSMF over the entire redshift range for which there are observations to compare with ($0
The spatial and dynamical distribution of stars are fundamental to characterise galaxy populations across cosmic time. They reflect the conditions in which those stars formed, and the subsequent evolution experienced by their host galaxies. Hence, stellar morphologies represent a fundamental part of our understanding of galaxy formation. Despite several known correlations between the morphology of a galaxy and its internal and environmental properties, identifying their origin is not trivial. In this sense, galaxy simulations provide a complementary input that can help interpret the observed data.
However, most simulations of representative volumes of the universe suffer from several limiting factors when it comes to stellar morphologies. Gas is artificially prevented from reaching low temperatures and high densities in the interstellar medium, "puffing up" the resulting stellar discs. Additionally, the energy transfer between a dynamically cold stellar disc and a hot dark matter halo is spuriously exacerbated due to different dark matter and star particle masses. This can lead to a secular thickening of the already thicker discs, introducing a bias in the predicted galaxy morphologies.
I will present the first galaxy morphology results from the COLIBRE suite of cosmological simulations. COLIBRE solves the aforementioned issues, and makes several improvements to the baryonic physics relevant to galaxy formation, like using a non-equilibrium chemistry model coupled to a live dust model, and a more refined model for energetic feedback. Altogether, the population of galaxies in COLIBRE is realistic across a variety of observed scaling relations and redshifts. Thanks to the large dynamic range in volume ($V \in [25^{3},200^{3},400^{3}]\,\mathrm{Mpc}^3$) and corresponding mass resolution ($m_{\rm p} \in [10^5, 10^6, 10^7]\,\mathrm{M}_{\odot}$) of the simulation suite, this talk will show a statistical study of galaxy morphologies from dwarf galaxies to galaxy clusters that can complement ongoing surveys like Euclid.
We examine the morphological evolution of galaxies at late cosmic times ($z<4$) using Horizon Run 5 (HR5) cosmological hydrodynamic simulation. Building upon previous analyses, we classify galaxies with stellar mass $M_∗>2×10^9 M_{\odot}$ into disk, spheroid, and irregular types based on non-parametric structural diagnostics, primarily asymmetry and Sérsic index. At $z\sim0.625$, we find that ~80% of galaxies exhibit a Sérsic index less than 1.5, indicative of disk-dominated morphologies. This fraction declines with increasing redshift and stellar mass. In contrast, kinematic classification using the ratio of rotational velocity to stellar velocity dispersion (v/$\sigma$) reveals a predominance of slow rotators (with v/$\sigma>0.55$) in the low-mass regime at the same epoch. Considering the dominance of disk-like morphology based on structural classification, we would expect to see a corresponding dominance of fast rotators (v/$\sigma>0.55$) in the similar mass range. We explore the role of merger history and stellar mass assembly in driving this structural–kinematic discrepancy. Given the remarkable agreement of HR5 results with JWST observations at high redshift, resolving this structural–kinematic discrepancy at low redshift will offer deeper insights into both the galaxy evolutionary process and the predictive power of the simulations.
TBD
Non-linear cosmological information can be effectively extracted by jointly analyzing the pre- and post-reconstruction power spectra of large-scale structure. In this work, we present measurements of the pre- and post-reconstruction power spectra, as well as cross power spectrum between the density fields before and after the reconstruction in the Luminous Red Galaxies (LRGs) of the DESI DR1 data release. We perform a joint fit to these measurements using an emulator-based modeling framework, thereby, for the first time, capturing complementary non-linear information from the density fields before and after the reconstruction in observational survey data.
We apply a halo velocity bias model, $\gamma_{f}$, within the Aemulus simulation suite for General Relativity (GR) to investigate its efficacy in identifying the signature of assembly bias and Modified Gravity (MG). In the investigation of assembly bias, utilizing galaxy clustering data ranging from scales of $0.1 \sim 60 h^{-1}{\rm {Mpc}}$, we discover that our emulator model accurately recreates the cosmological parameters, $\Omega_m$ and $\sigma_8$, along with the velocity bias $\gamma_{f}$, staying well within the 1-$\sigma$ error margins, provided that assembly bias is considered. Ignoring assembly bias can considerably alter our model constraints on parameters $\Omega_m$ and $\sigma_8$ if the test sample includes assembly bias. Using our emulator for MG simulations, which encompasses two Dvali-Gabadadze-Porrati models (DGP; N1, N5) and two $f(R)$ models (F4, F6), we can effectively identify a robust signature of modified gravity, for models such as DGP-N1 and $f(R)$-F4, as indicated by a noticeable deviation of $\gamma_{f}$ from unity. Using the velocity dispersion of dark matter halos to effectively represent the underlying strength of the velocity field of these MG simulations, we find that the simple $\gamma_{f}$ model can recover the truth with minimal bias. These evaluations indicate that our simple halo-velocity bias model is capable of detecting significant MG characteristics, although additional methodologies should be pursued to improve model constraints.
Accuracy photometric redshift (photo-z) estimation is crucial in imaging surveys. We present the photo-z estimation by the normalizing flow, a powerful deep learning method that can approximate complex probability distribution. We demonstrate that the method is able to give reliable photo-z estimation across a number of datasets. Besides accurate photo-z estimation, the characterization of the true redshift (true-z) distribution of a photo-z sample is also critical for unbiased cosmological parameter inference. By combining an improved self-calibration algorithm with the clustering-z method, we show that we can increase the true-z estimation accuracy, and extend the clustering-based method to higher redshift.
Cosmic shear surveys serve as a powerful tool for mapping the underlying matter density field, including non-visible dark matter. A key challenge in cosmic shear surveys is the accurate reconstruction of lensing convergence (κ) maps from shear catalogs impacted by survey boundaries and masks, which seminal Kaiser-Squires (KS) method are not designed to handle. To overcome these limitations, we previously proposed the Accurate Kappa Reconstruction Algorithm (AKRA), a prior-free maximum likelihood map-making method. AKRA has proven successful in recovering high-precision κ maps from masked shear catalogs, both in flat-sky and full-sky scenarios. More recently, we have applied AKRA to the first-year data release of the Hyper Suprime-Cam (HSC) survey, achieving the first set of κ maps that consistently incorporate masks and heterogeneous noise. We are now extending the method to larger datasets, including DES, to build a wider range of κ-map products for scientific applications such as non-Gaussian statistics. With upcoming surveys like Euclid and CSST, AKRA will provide a promising tool for extracting cosmological information directly from the κ field.
We present an analytic model for gravitational lensing by self-interacting dark matter (SIDM) halos. The model captures the full range of gravothermal evolution and accommodates inner logarithmic density slopes from 0 to –2.5, enabling the construction of complex halo profiles by superimposing components at different evolutionary stages. As an application, we model galaxy–galaxy strong lensing in a cosmological two-component SIDM simulation, demonstrating that SIDM-driven mass segregation can significantly enhance the efficiency of small-scale lenses, potentially resolving a long-standing observational anomaly. We also apply the method to populate low-mass subhalos in lens models and investigate the resulting observational signatures. The analytic model shows percent level agreement with numerical results, while remaining highly efficient for large-scale applications. To support broader use, we have released a public implementation on GitHub.
One of the foundations of the concordance cosmological model is that approximately 85 per cent of the matter content of the Universe is in the form of some yet unknown component that we can detect only through its gravitational effect: dark matter. While the standard Cold Dark Matter model is very successful at explaining the large scale structure distribution of the universe, it has been challenged by observations at the scale of galaxies and below, motivating the exploration of alternative scenarios such as Self-Interacting or Warm Dark Matter.
I will present the first results from the new AIDA-TNG project, where we simulate three cosmological volumes, including six dark matter scenarios together with galaxy formation. Resolving systems from 10^9 to 10^14.5 solar masses, the AIDA-TNG project offers crucial new data to understand the effect of alternative dark matter models on multiple scales and observables. I will present our results on the density profiles of dark matter halos and subhalos, stellar and halo shapes, as well as the effect of SIDM and WDM on the properties of the galaxy general population. Moreover, I will talk about our first insight on large-scale power spectra and the Lyman-alpha emission on large scales, demonstrating the promising potential of this sample.
The clustering of large-scale structures is recognised as a fundamental cosmological probe, offering us the possibility to constrain fundamental parameters such as the matter density content of the Universe. Currently, the most acknowledged cosmological scenario is the ΛCDM model, which assumes that dark matter particles exist in a ‘cold' version, namely in the form of very massive candidates, e.g. WIMPs, or condensates of light axions. It is consistent with observations on scales ranging from the size of the cosmological horizon to the typical intergalactic distances. However, observations at typical galactic and sub-galactic scales, on the order of kpc, have suggested some possible tensions related to the number of satellite galaxies and halo density profiles. One possible solution is provided by complex baryonic feedback. Another possibility is to explore the dark sector, by investigating the macroscopic consequences of alternative cosmological scenarios based on the existence of warm dark matter (WDM) or self-interacting dark matter (SIDM) particles.
In this talk, we analyze some of the macroscopic consequences of alternative dark matter models. In particular, the free streaming of WDM particles on average suppresses the formation of the smallest halos, whereas the most massive perturbations are still able to collapse. This results in a general delay of early galaxy formation and in a reduction of the number density of faint galaxies, which directly impact the timeline of the Reionization process, a fundamental phase transition in the history of the Universe, during which the Intergalactic Medium (IGM) became ionized and therefore transparent to UV photons.
We also analyze the statistical properties and spatial distribution of dark matter halos. For this reason, we make use of the AIDA simulations, a set of dark matter-only boxes of different sizes and resolutions. For each cosmological scenario, we characterize the radial distribution of satellites, finding that a NFW model is not accurate enough to describe the density profile of subhalos. We also adopt the halo occupation distribution (HOD) formalism to model the abundances and the clustering properties of halos in both cold and different WDM and SIDM models. In particular, we find that the small-scale clustering of dark matter halos provides a valid way to discriminate between different cosmological scenarios, in preparation for a more detailed study that fully incorporates baryonic effects, and for a comparison with observational data from galaxy clustering.
We present, for the first time, the gas and HI distributions in and around haloes in the TNG universe for three alternative dark-matter models: SIDM, velocity-dependent SIDM, and WDM. We show how these models affect HI and the resulting Lyman-$\alpha$ spectra. We show how gas and HI density profiles change with halo mass and redshift with alternative DM. Finally, we compute the galaxy–Lyman-$\alpha$ cross-correlation function to test whether observations can distinguish these models.
Using state-of-the-art reduction methods, we analyze the new JWST data acquired by the NIRISS/NIRCam wide-field slitless spectroscopy (WFSS) and NIRSpec in the multi-object slit-stepping spectroscopy mode. These complementary spectroscopic data sets obtained from multiple instruments open up key window on unbiased investigation of star formation, feedback, and ISM properties in and beyond the cosmic noon epoch. We bring forth the first spatially resolved analysis of high-redshift galaxies with JWST WFSS and measure the first gas-phase metallicity radial gradient with sub-kpc resolution at z≥3. We extend such analysis to galaxies in the epoch of reionization, finding a swift mode transition of galaxy mass assembly and chemical enrichment in the early Universe. We invent a novel methodology of conducting 3D spectroscopy of galaxies by stepping the NIRSpec slits across their surfaces, obtaining resolved chemical and dynamical properties for a sample of 26 galaxies at z~1. We find clear evidence for strong rotational support in galaxies showing negative metallicity gradients, consistent with the predictions by the FIRE-2 cosmological zoom-in hydrodynamic simulations.
JWST observations reveal a surprising excess of luminous galaxies at z≳10, suggesting a high star formation efficiency. This contrasts with the low star formation efficiency suppressed by feedbacks at later times, indicating a potential paradigm shift. We propose that the high densities and low metallicities at high z guarantee high star-formation efficiency through feedback-free starbursts (FFBs) in the most massive halos. I will discuss the expected conditions for FFBs and the observable predictions for galaxy mass and luminosity functions, sizes, outflows, etc. I will also discuss how the FFB scenario may help to understand the formation of high-z massive quiescent galaxies and blackhole growth.
In this talk I will briefly discuss the present state of the field of galaxy evolution and share the results of opinion polls conducted at the 2021 European Astronomical Society meeting and the 2025 International Astronomical Union meeting. These polls illustrate the significant challenges both observers and theorists/simulators are currently facing. In sight of these apparent limitations I propose a simple approach to study galaxy evolution relying on growth models tested here on Planet earth. The Gamma growth pattern (which combines a power law growth and an exponential decline), a widely used parameterization across diverse scientific fields (ranging from biology to economics) and scales (from bacterial colonies to the spread of infectious diseases), serves to depict/study growth across many disciplines. In this presentation, I put forth the idea that this same Gamma growth pattern can be broadly applied to describe the cosmic star formation rate density, the mass accretion histories of dark matter halos, and the evolution of the Galaxy Stellar Mass Function (GSMF). Many of those results have been published recently to Katsianis et al. 2025. The simplicity, minimal parameters, lack of resolution effects, multidisciplinary approach and the ability to link the smallest and largest scales of star formation provided by our methodology, offers a surprising perspective on the Physics of galaxies that I am looking forward to share in the 3rd Shanghai Assembly on Structure formation meeting.
It is well known that galaxy interactions will trigger star formation, due to the tidal effect. With the observations from ALFALFA and SDSS samples, we show that galaxies with close companions tend to exihibit single-peaked integrated HI profiles, indicating that galaxy interactions lead to more centrally concentrated HI distribution, and trigger star formation.
Besides, it was found that the star formation enhancement only occurs in galaxies with spiral companions. We examine this phenomenon beyond the limited small sample in previous work, with the large galaxy sample from SDSS. We confirm that the star formation enhancement is more pronounced in galaxies with spiral companions and inner regions of galaxies. We also find that host galaxies with spiral companions show lower relative velocity and tend to reside in low-mass halos and under-dense regions. However, after matching halo mass and local density between the two pair samples, the difference in star formation enhancement remains significant. Our analysis indicates that the phenomenon may not be fully explained by the coplanar interaction mentioned in Xu et al. 2021.
Baryon-dominated dwarf galaxies (BDDGs) offer a sensitive probe of energy injection in low-mass halos. Using hydrodynamical simulations of high-velocity collisions between gas-rich ultra-diffuse galaxies, we study how progenitor structure affects BDDG formation. We model systems with varying central density profiles, corresponding to different baryonic binding energies, and introduce a gas stripping parameter, η= W/|Ebind|, where W is the gas’s kinetic energy relative to the target and Ebind its gravitational binding energy. We find that cored progenitors tend to produce higher η and form single, massive, centrally concentrated BDDGs, whereas cuspy ones fragment into multiple low-mass remnants. Intriguingly, although both baryon feedback and (elastic) self-interacting dark matter can generate cores, only feedback significantly reduces baryonic binding, favoring the formation of more massive BDDGs. Our results suggest that BDDGs formed via collisions provide a promising avenue to constrain energy injection mechanisms in dwarf halos. Upcoming imaging (CSST, LSST), HI surveys (FAST), and kinematic follow-up will be crucial for identifying candidates and testing these scenarios.
The accurate modeling of small-scale clustering, specifically the 1-halo term, is crucial for precise redshift-space distortion (RSD) analyses. An interesting solution to this challenge is to reconstruct the halo clustering, which helps mitigate the systematic effects caused by the inclusion of satellite galaxies in clustering analyses. In this work, we explore the cylinder-grouping (CG) method, introduced by Okumura et al. (2017), which allows for systematic corrections more efficiently than previous methods, especially in high-density galaxy samples.
In this study, we apply halo reconstruction to galaxy mocks based on N-body simulations and estimate cosmological parameters using the Effective Field Theory (EFT) framework. Our results show that the systematic corrections associated with the CG method are effectively handled within the EFT framework. Compared to the case without reconstruction, we find that parameter estimation remains stable at higher values of the maximum wavenumber and exhibits smaller errors, demonstrating the potential of halo reconstruction for more accurate cosmological parameter inference. We also discuss the relationship between these systematic corrections and EFT counterterms and stochastic terms, including how appropriate priors for these terms can improve cosmological parameter inference.
We construct the velocity field based on a DESI BGS group catalog. We correct RSD with the traditional linear model, and the group catalog is determined from the DESI BGS sample with the updated DESI Y3 spectroscopic data using an extended halo-based method.
I will present the synergy of galaxy clustering (GC) and kinetic Sunyaev Zel’dovich (kSZ) effect in this talk, discussing its potential on simultaneously constraining cosmology and astrophysics.
We jointly measure the pairwise density-weighted kSZ power spectrum using the CMASS galaxy sample from BOSS DR12 and the temperature map from ACT DR6, and constrain cosmological parameters through joint analysis with the galaxy density power spectrum from CMASS. The constraining power of joint analysis on the growth rate of structure and the two free parameters \alpha_\parallel and \alpha_\perp for the AP test shows significant improvement compared to using galaxy power spectrum analysis alone, with the area of joint posterior distributions reduced by approximately 10% for each pair of parameters. We attempt to investigate the baryon distribution in dark matter halos by comparing the optical depth profiles measured from ACT and CMASS with results from WebSky simulation.
I will present a characterisation of filamentary structures at different scales, from the large-scale cosmic filaments forming the skeleton of the cosmic web, to the smaller-scale filaments playing a crucial role in the circum-galactic medium (CGM). Using the outputs of recent large-scale hydro-dynamical simulations, I will focus on some fundamental properties of filaments at z=0, and show how cosmic filaments evolved since z=4. In the second part of my talk, I will zoom into CGM scales to show how the smaller-scale filaments (or streams) influence the star-formation activity of galaxies at cosmic noon. I will conclude on the importance of understanding multi-scale filaments and discuss prospects for observing these structures with current and future multi-wavelength datasets.
As a component of the cosmic web, filaments are important for us to understand the formation of the large scale structure.
In this work, we study the influence of angular momentum, filament growth history, and cosmic expansion on filament density profiles.
We present two models characterizing dark matter filament growth implementing the stretch of filaments, the power law growth model (the PL model) and the M18 model, in which the growth of filaments is derived from the growth history of halos.
For the PL model, the density profiles follow $\rho\propto r^{-1}$ in the inner region of the filaments for a purely infall case, which is consistent with the results by Fillmore$\&$Goldreich.
We found that in the case of larger tangential velocity, higher growth rate, and stronger expansion, the filament density profiles are more cored.
We also propose a new model for the splashback radius of filaments.
For the M18 model, we found consistence of density profiles with simulation results.
Although future work is needed to calibrate the growth history of filaments, our work could provide a framework for analyzing the formation of filaments as well as the environment around filaments.
As a key component of the Universe’s large-scale structure, the kinematics of cosmic filaments has long been debated. Classical theory holds that filaments exhibit multipolar flows without a net, coherent rotation. However, two independent studies in 2021—one simulation-based and one observational—reported detections of filament rotation, sparking broad discussion in the community.
(1) Using the TNG300 simulation, we introduce a side-by-side analysis of mass-weighted versus volume-weighted velocity fields( just momentum vs. velocity). We show for the first time that the mass-weighted field effectively captures the coherent rotation of filaments (with tangential speeds up to ~100 km s⁻¹), whereas the volume-weighted field predominantly exhibits a quadrupolar flow pattern. Accounting for halos embedded within filaments, our statistics indicate that more massive halos display a stronger tendency to orbit around the filament, and that more massive (denser) filaments rotate faster; rotation correlates positively with mass (density). Even after excising all halos with $M>10^{11}\,h^{-1}M_\odot$, the diffuse material within filaments retains substantial angular momentum (tangential speeds up to ~70 km s⁻¹). By systematically comparing prior methodologies, we further clarify why different statistics yield different filament–spin curves: in roughly 30–40% of cases the inner and outer regions of a filament rotate in opposite senses, and the two commonly used definitions of filament spin direction effectively emphasize the inner versus the outer rotation, respectively.
(2) Regarding baryons, we find that gas is more prevalent outside halos, while dark matter is more concentrated within halos. Because rotation correlates with density, dark matter rotates faster inside massive halos, whereas gas rotates faster outside halos. The dominant gas phase—the warm-hot component around $\sim 10^6\, K$—co-rotates with the dark matter, but the cold and hot phases exhibit markedly different spin behaviors: cold baryons ($T<2\times10^4\, K$) are distributed mainly in small central halos and in the diffuse outskirts, and kinematically show high rotation only near the filament core; hot baryons ($T>10^7\, K$) reside primarily in massive halos and display higher rotation in the outer regions. For both the cold- and hot-gas filaments, only about 60% share the same sense of rotation as the total gas filament. Moreover, analysis of halo (galaxy) spin orientations across the filament cross-section shows that within quadrupolar-flow regions, halos in the co-rotating sectors exhibit larger spin amplitudes and their spin axes are more closely aligned with the filament spine—features that provide new, independent evidence for filament rotation.
The Milky Way Survey of the Dark Energy Spectroscopic Instrument (DESI) has so far observed three classical dwarf spheroidal galaxies (dSphs): Draco, Sextans and Ursa Minor. Based on the observed line-of-sight velocities and metallicities of their member stars, we apply the axisymmetric Jeans Anisotropic Multi-Gaussian Expansion modeling (JAM) approach to recover their inner dark matter distributions. In particular, both the traditional single-population Jeans model and the multiple population chemodynamical model are adopted. With the chemodynamical model, we divide member stars of each dSph into metal-rich and metal-poor populations. The metal-rich populations are more centrally concentrated and dynamically colder, featuring lower velocity dispersion profiles than the metal-poor populations. We find a diversity of the inner density slopes $\gamma$ of dark matter halos, with the best constraints by single-population or chemodynamical models consistent with each other. The inner density slopes are $0.71^{+0.34}_{-0.35}$, $0.26^{+0.22}_{-0.12}$ and $0.33^{+0.20}_{-0.16}$ for Draco, Sextans and Ursa Minor, respectively. We also present the measured astrophysical J and D factors of the three dSphs. Our results indicate that the study of the dark matter content of dSphs through stellar kinematics is still subject to uncertainties behind both the methodology and the observed data, through comparisons with previous measurements and data sets.
We present an analytical model that embeds the cusp–core transition into the c–M relation of dark matter halos. The model accounts for deviations from scaling relations in galaxies, where central surface densities fall below c–M predictions. In contrast, UFDs retain high central densities consistent with CDM. Assuming supernova (SN) feedback drives the transition, the model predicts it operates within a characteristic halo mass range of 108–1011 M⊙, defining a critical stellar mass and a “forbidden region” where core formation is ineffective. The framework is validated by analysis using SPARC and UFD data. These data confirm that most galaxies lie outside this region and can undergo the transition, while groups, clusters, and UFDs remain trapped within it. The observed diversity in low-mass density profiles likely arises from variations in star formation efficiency and the coupling efficiency between SN feedback and the dark matter potential. By calibrating the coupling efficiency to observed central densities, we find that ~1% of supernova feedback energy is enough to drive the cusp–core transition in SPARC galaxies.
I will provide an overview of the recent final data release of the ESO Kilo-Degree Survey and the associated cosmology results using weak gravitational lensing. As the field transitions to the next generation of surveys with Euclid and Rubin, I will discuss the current state of analysis choices, calibration and validation, and some lessons learnt.
Recent 2σ–4σ deviations from the cosmological constant $\Lambda$ suggest that dark energy (DE) may be dynamical, based on baryon acoustic oscillations and full-shape galaxy clustering analyses. This calls for even tighter DE constraints to narrow down its true nature. In this talk, I present how galaxy intrinsic alignments (IA) can enhance the full-shape galaxy clustering–based DE constraints, using Fisher forecasts on various extensions of dynamical DE models, including scenarios with curvature, massive neutrinos, and modified gravity. Incorporating IA improves the DE figure of merit by 42%–57% and tightens the primordial power spectrum amplitude constraints by 17%–19%. Our findings highlight IA’s potential as a valuable cosmological probe complementary to galaxy clustering.
As underdense regions in the universe, cosmic voids are less affected by non-linear gravitational evolution and baryonic feedback, providing a clean environment for constraining cosmological parameters. In particular, the void density profile is sensitive to cosmology, but remains challenging to measure in observations. In this work, we investigate the method to constrain the void density profile with weak lensing effect, and assess its potential for further cosmological constraints, based on mocks from N-body simulations. As a case study, our result indicates that void lensing provides an independent constraint on neutrino mass as $M_{\nu} < 0.64\ eV$ (95% CL), under observational conditions similar to current surveys. We further study how combining void lensing with other cosmological probes can help to break parameter degeneracies and make forecasts for next-generation surveys. This method serves as an important synergy between spectroscopic and imaging surveys.
Galaxy–mass offsets in cluster collisions were once considered a promising signal for constraining the self-interaction cross-section of dark matter. However, previous studies based on these offsets have been hindered by large measurement uncertainties and poorly constrained merger phases and geometries. In this work, we overcome these challenges and present a robust constraint on the dark matter self-interaction cross-section using a new and powerful method applied to ten cluster collisions hosting double radio relics. By utilizing the relic–relic separation relative to the halo–halo distance as an indicator of dark matter properties, we derive a 68% upper limit of ~0.30 cm² g⁻¹ on the self-interaction cross-section. This represents the first robust result obtained from large halo colliders, incorporating full marginalization over mass uncertainty, viewing angle, collision speed, merger phase, impact parameter, and gas slope.
Strong lensing mass reconstructions of several galaxy clusters obtained by combining imaging from HST and JWST and spectroscopy from MUSE show that cluster galaxies are much more compact than found in high-resolution hydrodynamical simulations. In this talk, I will discuss the possible origins of this discrepancy, whether it can be due to how galaxy formation is modeled in the simulations, to biases in the mass reconstructions, or to wrong assumptions about the nature of dark matter.
Galaxies are embedded within larger halos of (predominantly) dark matter. Although gravitational lensing studies have provided a comprehensive understanding of the distribution of dark matter in these halos, their baryonic content remains less well understood.
One key baryonic component in galactic halos is dust, which can be transported from the interstellar medium to the circumgalactic medium through various mechanisms. In this work, we aim to investigate the amount and distribution of dust in galactic halos by measuring shifts in the observed magnitudes of background galaxies.
Dust particles preferentially absorb and scatter shorter-wavelength light, leading to a reddening of the spectra of background sources. In this study, we investigate this reddening effect by quantifying the dust-induced shift in the apparent magnitudes of galaxies, in multiple photometric bandpasses, with the Kilo-Degree Survey (KiDS) Data Release 4 (DR4). Magnification, which is an achromatic effect, is expected to produce consistent signals in the absence of dust extinction. Our analysis, following previous work, explores the measurement of extinction imprinted upon this otherwise achromatic signal. We explore potential systematic effects in magnification and reddening measurements when using galaxies used as background sources, in contrast to the use of quasars in previous work. We validate our measurement pipeline using mock galaxy catalogues from the MICE2 simulation suite, and subsequently perform an initial measurement of circumgalactic extinction using data from the KiDS DR4.
We validate our analysis pipeline on simulations, recovering input halo and dust masses using galaxy-galaxy lensing, magnification, and extinction, both independently and under joint analyses. We find that, by excluding red galaxies from the source sample, one can suppress systematic effects introduced by galaxy clustering. Additionally, applying specific brightness cuts is crucial to mitigate overlap between lens and source redshift distributions, caused by imprecise line-of-sight binning using photometric redshift estimates. Applying our pipeline to observational data from KiDS, we first validate the achromaticity of our magnification measurements in the absence of extinction, by computing the magnification signal in five near-infrared filters ($ZYJHK_{\rm s}$). In the infrared, our magnification measurements produce constraints of similar accuracy and precision as those measured using galaxy-galaxy lensing (GGL). In a joint analyses of GGL and magnification, now in four optical bands ($ugri$), we constrain the joint probability of halo mass and dust mass at $0.2$dex and $0.4$dex precision, respectively. We measure a dust mass of $6.03^{+0.73}{-0.78} \times 10^7,M\odot$ in the circumgalactic medium, and a mean halo mass of $\log\left(M_{\rm halo}^{\rm DM}/M_\odot\right)=12.39^{+0.04}_{-0.04}$. These measurements are consistent with results from previous studies. Our results represent the first successful measurement of magnification and halo extinction with KiDS data, and confirm previous measurements of using SDSS quasars. These observations provide further evidence that galaxies typically reside in extended baryonic halos, populated by gas and dust ejected by energetic feedback processes.
We present a comprehensive numerical investigation into a minor merger event in the Andromeda Galaxy (M31), which we propose as a unified origin for four prominent stellar substructures: the Andromeda Giant Southern Stream (AGSS), Eastern Extent (EE), North-Eastern Shelf (NES), and Western Shelf (WS). This scenario provides a unified and self-consistent framework for understanding their formation, helping to resolve a long-standing issue regarding the relationship between halo substructure and galaxy assembly. Conducting $N$-body simulations, we model the dynamical interaction between M31 and an accreting progenitor, varying the scale radius and mass of the dark matter halo associated with the progenitor around the range predicted by the Lambda cold dark matter model. Our results demonstrate that the progenitor with a dark matter halo mass of several $10^9$ solar masses, which experienced a first collision with M31 around 1 Gyr ago, can simultaneously reproduce the observed spatial distribution of the AGSS, EE, NES, and WS. We find that NES and WS are independent of the gravitational potential of the progenitor’s dark matter halo across the limited range of parameters considered in this study. In contrast, the position of the EE is noticeably affected by variations in the dark matter halo potential of the progenitor, with shallower potential shifts EE farther north. Another important result of our research is the clarification of the spatial relationship between EE and the Stream Cp which is a metal-poor component of the Stream C. Our findings indicate that EE is located several tens of kiloparsecs closer to us than Stream Cp, whose farther distance suggests overlapping debris from distinct collision events, while both remain closely aligned in celestial coordinates. This suggests that caution is required when interpreting their distribution in these coordinates. Moreover, we predict the existence of a previously undetected positive stream along the AGSS, characterized by positive line-of-sight velocities relative to M31. This feature would represent a kinematic counterpart to the already observed negative stream exhibiting negative line-of-sight velocities. Confirming the positive stream would provide strong support for our merger scenario. Moreover, we propose that three stellar streams, namely Stream B, a metal-rich component of Stream C referred to as Stream Cr, and EE, construct the Andromeda Giant Southern Arc (AGSA) connected to the AGSS. While the full extent of the AGSA and the existence of the positive stream remain to be observationally verified, we anticipate that future spectroscopic surveys and advances in theoretical studies will play a crucial role in confirming their nature.
In this study, the progenitor could have been placed on a radial infall trajectory, plunging toward M31 center from north to south at high velocity. This accretion event, traced through its stellar debris, offers insight into the hierarchical growth of galactic halos, contributing to our broader understanding of cosmic structure formation. This progenitor represents a key system for understanding the relationship between satellite accretion and stellar halo formation. Furthermore, M31 is an ideal laboratory for testing these scenarios through high-precision observations due to its proximity and providing a comprehensive view of the entire system.
We apply an extended Alcock–Paczyński (AP) test to the SDSS data to constrain the dark energyequation of state with the Chevallier–Polarski–Linder (CPL) parametrization. The extended AP test method uses the full shape of redshift-space two-point correlation funcion (CF) as the standard shape in order to measure the expansion history of the universe. We calibrate the standard shape by using the cosmology-dependent nonlinear evolution of the CF shape in the Multiverse simulations. Further validation of the method and calibration of possible systematics are performed based on mock samples from the Horizon Run 4 simulation. Using the AP test alone, we constrain the flat CDM plus CPL-type dark energy model (flat wCPLCDM) to have Wm=0.289_-0.029^+0.031, w_0=-0.798_-0.102^0.192 and w_a=-0.165_-0.945^+0.610. The result does not show evidence for a dynamically evolving dark energy model. When combined with other results from the low-redshift universe, such as the PantheonPlus supernova compilation and DESI BAO data, the constraint on w_a becomes w_a=-0.124_-0.368^+0.334, which is still consistent with zero.
The DES Collaboration observed 5000 sq. deg. of the southern sky during six years and measured the position on the sky, photometric redshift and shape of about 200 million galaxies, while simultaneously measuring the light curves of over 1500 type-Ia supernovae (SNe). With these two unprecedented samples, DES has determined cosmological parameters related to the expansion of the universe using SNe and the Baryon Acoustic Oscillations (BAO) feature in the galaxy sample, as well as cosmological parameters related to the growth of structure in the universe using the weak lensing effect in distant galaxies and its combination with the angular distribution of nearby galaxies (the so-called 3x2pt measurement). In this talk, I will present the final DES results on SNe and BAO and their combination, as well as the latest, possibly final, 3x2pt results.
I will present a unified framework for understanding and deriving the many universal laws in the distribution and evolution of dark matter subhalos, across mass scales, redshifts and cosmologies. This framework stems from an extremely simple and intuitive picture that subhalos are accreted unbiasedly from the environment, relative to the accretion of smooth matter. Starting from this, we are able to derive analytically the universal spatial distribution, mass distribution, progenitor distribution and hierarchy distribution of subhalos, which can also be extended to different cosmologies including different dark matter particle types.
The halo model is a powerful tool for understanding the non-linear evolution of the large-scale structure. Conventionally, a dark matter halo is defined as a collapsed object in virial equilibrium, with its boundary set by the virial radius. However, this definition does not appropriately separate the halo and the environment, as a halo is much more extended beyond the virial radius and grows continuously. Consequently, the classical halo model fails in the transition region between the halo edge and the large-scale environment. A better understanding of the halo boundary and a more accurate and explicit halo model are needed in future cosmological analyses.
In this talk, I will present an improved halo model that based on a new characterization of the halo boundary called depletion radius. By selecting halos with new boundary definition, we find that the model ingredients (halo mass function, halo profile, and halo-halo correlation) can be expressed simply and naturally (arXiv: 2303.10886). Coupling all the ingredients our model accurately predicts the multiple statistics of the halo and matter field without ad hoc fixes (arXiv: 2407.08381). I will show the latest progress of our model across a wide cosmological parameter space, and demonstrate the potential applications of our model in cosmological analyses. finally I will compare our model to other existing halo models (e.g., HALOFIT and HMCODE), and highlight the advantages of our model in terms of clarity, interpretability, and versatility.
In the ΛCDM universe, structure formation is generally not a self-similar process, while some self-similarity
remains in certain statistics, which can greatly simplify our description and understanding of the cosmic structures .In this work, we show that the merger tree of dark matter halos is approximately self-similar by investigating the universality of the subhalo peak mass function (PMF) describing the mass distribution of progenitor
halos. Using a set of cosmological simulations and identifying subhalos of different merger levels with HBT+,
we verify that the level-1 subhalo PMF is close to universal across halo mass, redshift, and cosmology. This
approximate self-similarity allows us to analytically derive the subhalo PMF for subhalos accreted at any level
(i.e., for sub-sub...halos) through self-convolutions of the level-1 PMF, and the resulting model shows good
agreement with simulation measurements. We further derive a number of analytical properties on the hierarchical origin of subhalos. We show that higher-level subhalos dominate at progressively lower peak mass in
the PMF and are more likely to originate from major mergers than lower-level ones. At a given merger mass
ratio, the subhalo accretion rates at each level track the growth rate of the host halo. At a fixed final mass
ratio, however, subhalos of higher-level, higher-mass-ratio, and in more massive haloes tend to be accreted more
recently. Matching subhalo peak mass to galaxy mass, these results have direct implications on the hierarchical
origin of satellite galaxies.
We investigate the depletion radius of dark matter haloes by analyzing stacked mass flow rate (MFR) profiles derived from a large N-body cosmological simulation, focusing on its dependence on various halo properties. We find that the depletion radius is primarily determined by the conventional mass accretion rate, defined as the logarithmic growth rate of the virial mass with respect to the scale factor, consistent with similar previous findings. By analyzing the phase-space structure of haloes, we find that this dependence originates from the underestimated halo boundary definition and the crossing of non-smooth accretion material through this boundary. In contrast, the depletion radius associated with smooth accretion component shows high self-similarity and little dependence on the conventional accretion rate. These findings call for revisiting the connection between the spherical collapse model and cosmological simulations to fully understand this dependence.
Cosmological neutrino mass bounds are in tension with laboratory experiments, making studies of a variety of neutrino phenomena imperative. I will describe the scale-dependent cosmological clustering of massive neutrinos, beginning with a non-linear perturbation theory developed by my collaborators and me, called Flows For The Masses (FFTM). It combines three ingredients: multi-fluid perturbation theory, non-linear mode-coupling integrals, and FFT-based acceleration. Using FFTM, I will study neutrinos' clustering around halos and their gravitational lensing of the CMB. I will consider the dependence of neutrino clustering upon their mass ordering, as well as observable consequences of non-standard neutrino models. Finally, I will discuss ongoing and planned work on observable weak lensing predictions and improvements to N-body neutrino simulations.
Emulator and Field Level Inference
In this talk I will introduce Kun, a recently finished high resolution simulation suite for precision cosmology and Chinese Space Station Survey Telescope cosmology science. The Kun suite consists of 129 simulations covering 8 dimensional cosmological parameter space, including dynamic dark energy and massive neutrinos. The CSST Emulator constructed on Kun suite has competitive performance in predicting summary statistics, including matter power spectrum, halo mass function, and basis functions in bias expansion framework. More statistics including weak lensing peak counts are under development. It also provides a base data set for validating the universality of statistics, re-calibrate analytical tools in a wide parameter space, and test the extendability of AI performance.
The nonlinear matter power spectrum is the basic statistic in cosmological analysis. However, the theoretical prediction with percent-level accuracy is only from the expansive numerical simulation, which is feasible in the likelihood analysis. The solution is to construct an emulator using a finite number of simulations in a given parameter space. However, most emulators cannot cover the posterior of recent DESI BAO+CMB constraints at the w0-wa plane. In this talk, we discuss a spectra equivalence method to extend the usable range of the original CSST Emulator for dynamic dark energy models. Simulations with five different cosmologies, located within the DESI DR2+CMB constraint ellipse, are used to validate the accuracy of this method. The accuracy of the CSST Emulator still lies within 1% in the broad extended parameter range.
Persistent homology is a powerful tool from the field of topological data analysis, which has shown promise as a novel statistic for cosmological parameter estimation. Compared with traditional two-point statistics, topological measurement presents information on a wide variety of scales and demonstrates a higher sensitivity to distinguish neutrino mass. We build a FLAMINGO-based topology emulator with 10 varying cosmological parameters and test the constraining power and degeneracy among them. Among these, the highest constraints come from $\beta_2$, which reveal the information in the void structure. Moreover, Betti curves can break the degeneracy between neutrino mass and other cosmological parameters through multi-environment detection. We plan to apply this method to observations, specifically weak lensing observations and galaxy clustering in redshift space using DESI data.
We present a hybrid Lagrangian bias expansion emulator for the upcoming China Space Station Telescope (CSST) survey. We combine the Lagrangian bias expansion and the accurate dynamical evolution from N-body simulation, to predict the power spectrum of the biased tracer in real space. We employ the Kun simulation suite to construct the emulator, emulating across the space of 8 cosmological parameters including dynamic dark energy w_0, w_a, and total neutrino mass. The sample variance due to the finite simulation box is further reduced using the Zel'dovich variance control, and it enables the precise measurement of the Lagrangian basis spectra up to the quadratic order. The emulation of basis spectra realizes 1% level accuracy, covering wavelength k < 1 h/Mpc and redshift 0 < z< 3 up to the quadratic order field.
Many inverse problems are only implicitly defined through a forward simulator.
In such cases, no closed-form likelihood function is known.
In cosmology, the canonical example is parameter inference from higher-order and field-level statistics.
By training neural networks on samples generated by the simulator, one can obtain an approximate likelihood and thus perform parameter inference.
I will present the main ideas in this simulation-based inference and put it in the context of current cosmological problems.
Then, I will turn to the problem of how to perform cosmological inference with realistic simulation budgets.
This issue necessitates multi-fidelity inference, which I will present some approaches to.
Unveiling the 3D shape of the Milky Way’s dark matter halo is critical to understanding its formation history and provides a fundamental test of the ΛCDM cosmological model. Functioning as an intermediary between the Galaxy and its satellites, the shape of dark matter halo also plays a key role in deciphering the long-standing problem of a ‘plane of satellites’ vertically aligned to the Galactic disk. We create an innovative dynamical method with minimal assumptions, by applying the method to 6d phase-space data of halo stars from LAMOST+Gaia, we provide a robust determination of the 3D shape of the halo. We discover a nearly oblate dark-matter halo with its long-intermediate axis plane unexpectedly vertical to the Galactic disk, yet aligned with the satellite plane. This striking configuration suggests that the Galactic disk has flipped, torqued by minor mergers, from an original alignment with the halo and satellite plane. Such disk reorientation is non-trivial yet its physical mechanism is straightforward to comprehend and naturally originates a vertical satellite plane. Our findings offer a unified framework that links halo orientation, satellite alignment, and disk evolution, reinforcing the internal consistency of the Milky Way in 𝚲CDM model.
Barred galaxies are an important branch of the Hubble sequence. In the past decades, significant efforts have been made to understanding the formation and evolution of barred galaxies. We develop a population-orbit superposition method, which can fully utilize stellar kinematics and stellar populations obtained from MUSE-like IFS data, to construct 3D models of edge-on barred galaxies. This method can: (1) recover the pattern speed of edge-on barred galaxies; (2) decompose galaxy structures (e.g. bulge/bar/disk/halo) based on stellar orbits; (3) recover the stellar populations of different structures. We validate this method using simulated galaxies from the Auriga simulations, and confirm its reliability for application to edge-on barred galaxies in real observations (e.g. the GECKOS survey). By linking dynamics and stellar populations, our work provides new tools for understanding the formation and evolution of barred galaxies.
Using K giants selected from DESI Year-3 Milky Way (MW) Survey, we measure the shape, orientation, radial density profile, and spatial anisotropies in the density profile of the MW stellar halo at 8~kpc$
Stellar bars are non-axisymmetric structures located in the inner regions of galaxies; they
play a crucial role in the dynamical evolution of their host galaxies. They are observed in approximately 30\% of disc galaxies in the local Universe. In this study, we analyze the impact of different environments on bar formation and evolution using the TNG100 and TNG50 simulations from the IllustrisTNG project. Our samples consist of 1719 satellite galaxies with stellar masses $M_{\star} \geq 10^{10} \, M_\odot$ for TNG100 and 859 satellite galaxies with $M_{\star} \geq 10^{9} \, M_\odot$ for TNG50 at redshift $z = 0$. To characterize the environments, we classified the host halos by their total mass into three categories: massive ($M_h \geq 10^{14} \, M_\odot$), intermediate ($10^{13} < M_h < 10^{14} \, M_\odot$), and low-mass ($M_h \leq 10^{13} \, M_\odot$) halos. We find that both the bar fraction and bar lengths normalized by the effective radius slightly decrease with increasing clustercentric distance across all halo mass bins, while the bar lengths remain approximately constant. Moreover, at fixed clustercentric distance, the bar fraction increases with halo mass. This trend may be explained by the fact that the most massive galaxies—which are more likely to host bars—tend to reside in more massive halos. Additionally, we observe a strong correlation between bar presence and the stellar assembly history of galaxies. Galaxies that assembled earlier, especially those located within $0.5 \, R_{200}$ of the cluster center, show a higher bar fraction. This suggests that early assembly history could promote bar formation. Our results indicate a mild environmental dependence of bar presence, but a stronger link with stellar assembly history. These findings contribute to a better understanding of the physical mechanisms behind bar formation and their connection to galaxy evolution in diverse environments.
Accurate constraint on the total mass of the Milky Way (MW) is crucial yet remains significantly uncertain after decades of efforts.
In this study, we employ a novel data-driven dynamical modeling method, the empirical distribution function (\empdf), to refine estimates of the Milky Way mass profile using a large sample of halo stars from the Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS). We apply the model to mock data from AuriDESI first. Our model can ensemble unbiasedly recover the mass profile with error-free mock data in the ideal case, but is subject to significant biases when observational errors are included. We thus use the amount of bias in best-fit halo model parameters based on the mock data to calibrate the observational constraints, and we also calibrate our uncertainties to include the systematic source of errors according to the mock tests. After the calibration, we derive an enclosed mass profile consistent with previous studies, with best constrained virial mass and concentration of $\log M_{200c}=12.07_{-0.13}^{+0.17}(_{-0.21}^{+0.24})$ and $\log c_{200c} = 1.16_{-0.14}^{+0.11}(_{-0.26}^{+0.24})$ for BHBs and $\log M_{200c}=12.10_{-0.10}^{+0.10}(_{-0.15}^{+0.14})$ and $\log c_{200c} = 1.24_{-0.09}^{+0.06}(_{-0.18}^{+0.16})$ for RR Lyrae stars. This work demonstrates the ability to combine abundant observed datasets with minimal assumption method to constrain the mass of MW, providing a building block for the precise measurement of MW mass using the bulk of the data.
systematics
DESI DR1 full-shape clustering constrains cosmology from linear to quasi-nonlinear scales but is vulnerable to projection effects from broad nuisance priors. We strengthen the analysis along three axes: (i) HOD-informed priors (HIP), calibrated on high-fidelity mocks, to anchor nuisance parameters to realistic galaxy–halo connections; (ii) nonlinear reparameterization of the nuisance sector (via Generalized Additive Models) to reduce degeneracies and likelihood curvature; and (ii i) a prior-free frequentist pipeline based on profile-likelihood scans that guarantees correct coverage. Applied to the same DESI DR1 data, HIP and reparameterization mitigate projection effects and sharpen constraints, while the frequentist scans provide an independent cross-check, and offers a distinct, likelihood-based interpretation of the data. All three approaches yield consistent results, establishing a robust, projection-resilient DESI full-shape cosmology framework.
Primordial non-Gaussianity is one of the most important signals for probing the physics of the early universe. Over the past decade, constraints on primordial non-Gaussianity (quantified by the parameter fNL) from the Planck experiment have ruled out a number of simple inflationary models. In the coming years, ongoing and upcoming large-scale structure (LSS) surveys (e.g., SPHEREx) will likely achieve constraints on non-Gaussianity several times tighter than Planck, enabling us to test or exclude a broad class of inflationary scenarios—particularly multi-field inflation.
However, current LSS analyses measuring fNL typically neglect the impact of non-Gaussianity in the covariance matrix, which could systematically bias the inferred central value and uncertainty of fNL. This work aims to investigate: Given current survey designs, at what level of fNLsensitivity does ignoring non-Gaussianity in the covariance matrix begin to significantly affect our constraints?
The accurate determination of the true redshift distributions in tomographic bins is critical for cosmological constraints from photometric surveys. We developed a redshift self-calibration method, which utilizes the photometric galaxy clustering alone, is highly convenient and avoids the challenges from incomplete or unrepresentative spectroscopic samples in external calibration. By refining the update rules in the iterative process, the algorithm successfully handled negative values and uncertainties in observational data, markedly improving the accuracy of redshift distributions. Using the luminous red galaxy (LRG) photometric sample of the Dark Energy Spectroscopic Instrument (DESI) survey, we find that the reconstructed results are comparable to the state-of-the-art external calibration. This suggests the exciting prospect of using photometric galaxy clustering to reconstruct redshift distributions in the cosmological analysis of survey data.
Stage IV surveys such as Euclid and LSST will have unprecedented constraining power in cosmological parameters. To achieve this scientific goal, one of the major sources of uncertainties, photometric redshifts of the galaxy sample, needs to be under control. Clustering redshift has been a promising method for photometric redshift calibration, as have been adopted in many stage III surveys, but the lack of high redshift spectroscopic samples means that its application is limited for deeper surveys such as Euclid and LSST. In this talk, we explore the novel idea of using Lyman-alpha (Lya) forests from distant quasar spectra as the reference sample for redshift calibration. Lya forests have the advantage of high `sample density’ covering redshift 2 ~ 3, overlapping with the high redshift tail of typical source galaxy samples for the weak lensing survey. We demonstrate the feasibility of this method using (Lya)CoLoRe simulations, and we assess the signal-to-noise (SNR) of the clustering redshift measurement with increasingly realistic noise and various continuum subtraction procedures, such as Picca, a continuum fitting method, and LyCAN, a novel machine-learning based method. This is a promising avenue to combine Stage IV spectroscopic surveys such as DESI with Euclid and LSST to improve the robustness of its scientific results.
Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the high number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys can potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an r-band 5σ magnitude limit of 24.8 and survey footprint of 1347 deg2, it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an organised random (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOMs) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this SOM+HC method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the 27σ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal set-up suggested by the mock tests.
We investigate the possibility of using the cosmic gravitational focusing (CGF) to probe the minor light dark matter (DM) component whose mass is in the range of $(0.1 \sim 100)$\,eV. Being a purely gravitational effect, the CGF offers a mode-independent probe that is complementary to the existing ways such as Lyman-$\alpha$ and $\Delta N_{\rm eff}$. Such effect finally leads to a dipole density distribution that would affect the galaxy formation and hence can be reconstructed with galaxy surveys such as DESI. Both the free-streaming and clustering limits have been studied with analytical formulas while the region in between is bridged with interpolation. We show the projected sensitivity at DESI with the typical phase space distribution of a freeze-in DM scenario as illustration.
Galaxy clusters are powerful cosmological probes, sensitive to the growth of structure and the matter content of the universe. Using the AMICO algorithm on the KiDS-DR4 dataset, we present a homogeneous catalog of ~8000 clusters with accurate richness and membership estimates up to z ≈ 0.8. We jointly model cluster counts and weak-lensing profiles in KiDS-1000 to calibrate the mass–richness relation and derive cosmological constraints competitive with Planck and KiDS shear measurements. In parallel, we detect the splashback radius in stacked lensing profiles, tracing the transition between infall and virialized regions. Our results validate cluster-based cosmology in the era of precision surveys and offer new avenues to test ΛCDM and structure formation scenarios. These analyses demonstrate the synergy between cluster observables and next-generation surveys such as Euclid and DESI in resolving current cosmological tensions.
I will present cosmological constraints using the abundance of weak-lensing shear-selected galaxy clusters selected in the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The clusters are selected on the mass maps constructed using the latest three-year (Y3) weak-lensing data with an area of ≈ 500 deg2, resulting in a sample size of 129 clusters with a high signal-to-noise ratio 𝜈 of 𝜈 ≥ 4.7. 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. We obtain the fully marginalized constraint on $\hat{S}_8 \equiv \sigma_8 \left(\Omega_{m}/0.3\right)^{0.25} = 0.835^{+0.041}_{-0.044}$ (corresponding to a ~5% constraint) in a flat LCDM model. This work realizes a cosmological probe utilizing weak-lensing shear-selected clusters and paves the way forward in the upcoming LSST era. In the second part of the talk, I will share the latest development of the shear-selected cluster sample in the HSC survey.
We present a joint analysis of galaxy clustering and galaxy-galaxy lensing measurements from BOSS galaxies using the method of simulation-based emulation combined with halo occupation distribution model. Our emulator is constructed with Aemulus $\nu$ simulations, a suite of $w\nu$CDM N-body simulations with massive neutrinos as an independent particle species. We combine the small-scale analysis of galaxy clustering from $0.1h^{-1}$Mpc to $60~h^{-1}$Mpc and galaxy-galaxy lensing from $1.7h^{-1}$Mpc to $60~h^{-1}$Mpc to perform cosmological constraint. We split the BOSS galaxies into three redshift bins to measure their clustering and employ galaxies from Dark Energy Camera Legacy Survey and Hyper Suprime-Cam as source galaxies to measure galaxy-galaxy lensing separately. We find that the addition of galaxy-galaxy lensing will significantly improve constraint power on $S_{8}=\sigma_8(\Omega_m/0.3)^{0.5}$, with weak improvement on the constraint of $f\sigma_{8}$ . Our results of $f\sigma_{8}$ indicate tensions of around $2 \sim 4\sigma$ below the results of CMB observations from Planck. For $S_{8}$, our results from different observational data are also lower than the Planck result, which can be mitigated but not resolved when considering possible systematics in lensing measurement. These tensions with CMB observations in our work are consistent with some recent works of large-scale structure analysis, including measurements of galaxy clustering, galaxy-galaxy lensing, cosmic shear but not all of them. As a byproduct, our analysis also provides a preference of non-zero neutrino mass but without strong enough significance, with the constraining power dominated by the clustering measurement at intermediate to small scales. Given the accuracy of our model and the observational data, it is anticipated that more and better spectroscopic data is able to shed light on the constraints on this fundamental property in the near future.
SKA Science Data Challenge 3b (SDC3b) ended in May 2025 and released the results in August. Participants are required to perform inference on the simulated 21cm power spectrum and imaging to estimate the HI fraction. The simulation represents the SKA-Low observation of the 21cm signal from Cosmic Dawn and Era of Reionization (CD/EoR). YEYE team participated and submitted results on all four challenges, got No.1, No.3, and No.7 in IM1, PS3, and PS2 challenges, respectively. I will briefly introduce what SDC3b is, the algorithm YEYE has developed, and the experience from SDC3b.
The LCDM model has long served as the cornerstone of modern cosmology, successfully explaining a wide range of observations. However, with the advent of precision cosmology, emerging discrepancies among key parameters have highlighted its limitations in comprehensively describing the universe’s evolution. To address these challenges, my research explores interacting dark sector models, investigating the capabilities of interacting dark energy as an alternative framework to alleviate the persistent H0 and S8 tensions in cosmology. In this talk, I will present the development of the background and perturbation evolution equations for an interaction model of dark matter and quintessence dark energy. I will further discuss the model’s analysis using a combination of low- and high-redshift observational datasets. Given the uncertainties in both the physics of dark energy and current observational measurements, our results reveal a dataset-dependent variation in the mean value and constraining power of the Hubble constant, H0. By allowing the interaction parameter to evolve freely, the analysis indicates that although the interaction strength remains small, it is not disfavoured by the data at late times. Additionally, I will compare the results obtained under the assumption of spatial flatness with those derived within the framework of a curved geometry (Coupled+Omega_k model). This comparison provides insights into the role of spatial curvature in addressing the ongoing H0 and S8 tensions. I will delve deeper into how these findings within the Coupled+Omega_k picture suggest that relaxing the flatness assumption in coupled dark sector models leads to more precise constraints on both H0 and S8.
We present the reconstruction of the Cosmic Web from the galaxy distribution using the convolutional-neural-network-based deep-learning algorithm. We find the mapping between the position and velocity of galaxies and the Cosmic Web using the results of the state-of-the-art cosmological galaxy simulations, and demonstrate the cosmic web structure across the sky, and even some connections passing through the galactic plane across the zone of avoidance.
Low-mass dark matter halos perturb the Einstein rings of strong gravitational lenses. By means of high-resolution imaging and precision modeling, we can directly measure the masses, abundances, and internal density profiles of these halos. In this talk I will present a systematic overview of our multi-year effort to detect dark subhalos: from the development of the PyAutoLens software suite, through mock-lens validation driven by hydrodynamical simulations, to the discoveries of several dark-subhalo candidates in HST and JWST data. I will focus on how these perturbations serve as “dark-matter probes” to distinguish among cold, warm, and self-interacting dark matter (SIDM) models. In particular, I will report our latest constraint on the dark-matter self-interaction cross section derived from a compact subhalo identified in the SLACS0946, the "Jackpot" lens system.
Understanding how galaxies connect to their host dark matter halos is key to uncovering the physics of galaxy formation and the growth of cosmic structure. In this talk, I present two recent studies that use weak gravitational lensing and galaxy clustering to explore this connection from complementary perspectives. In the first part, we go beyond the traditional stellar–halo mass relation and investigate galaxy morphology—quantified by the Sérsic index—as a secondary tracer of halo properties. We find that more concentrated galaxies tend to reside in more massive and more concentrated halos, suggesting that galaxy structure retains memory of the coevolution between galaxies and their halos. In the second part, we examine luminosity-dependent assembly bias for central galaxies, finding a clear detection at the 3σ level: brighter centrals typically inhabit more concentrated halos that formed earlier but are less strongly clustered. Together, these results shed new light on how galaxy properties reflect the formation history of their dark matter halos.
The tidal field of the host halo strips not only the dark matter of the subhalo but also its embedded satellite galaxies. This process alters the stellar-mass–halo-mass relation for satellites compared to isolated galaxies. The co-evolution of stellar and dark matter components determines the fate of the faintest galaxies: will they be disrupted along with their host subhalo, or survive as dark-matter-deficient galaxies? In this talk, I will address these questions by examining satellite tidal evolution in the latest hydrodynamical simulation, COLIBRE.
Dark matter is proposed to dominate the mass-energy content of the Universe, and its nature can be studied via large-scale structure probes, such as the unresolved gamma-ray background (UGRB) using cosmological methods. We investigate the cross-correlation between energy-binned intensity maps of the UGRB from 15 years of Fermi-LAT data and tomographic weak gravitational lensing data from the fourth data release of the Kilo Degree Survey (KiDS-DR4), covering 1006 square degrees. The measurements are performed using the angular power spectrum, and the covariance is calculated using a weighted jackknife estimation. Based on the non-detection of a cross-correlation signal, we derive upper limit constraints on the decay rate $\Gamma_{\rm dec}$ and velocity-averaged annihilation cross-section $\left<\sigma_{\rm ann} v\right>$ of weakly interacting massive particle (WIMP) dark matter as a function of mass. We present the 95 \% upper bounds on the WIMP decay rate and annihilation cross-section and compare them with previous results from other cosmological tracers and local structure observations. Our study provides significant complementary constraints, particularly for low-mass ($ \rm GeV/TeV$) dark matter. The forecast for the 95\% upper bounds from an \textit{Euclid}-like survey cross-correlated with Fermi-LAT indicates that the constraints could be an order of magnitude stronger, showing the potential of future surveys to further constrain dark matter properties.
The magnitude gap between the central and satellite galaxies encodes information about the mass accretion history of a dark matter halo, and serves as a useful observational probe for the mass distribution in a halo. In this work, we perform the first weak lensing test of the connections between the magnitude gap and the halo profile. We measure the halo profiles of isolated central galaxies (ICGs) selected primarily from the SDSS Main Galaxy Sample. Halo mass and concentration are inferred by fitting stacked lensing profiles in bins of central luminosity, $L_\mathrm{c}$, and the central-satellite magnitude gap, $L_\mathrm{gap}$. We detect dependence on the magnitude gap in both halo properties. The dependence is the strongest in the ICG luminosity range of $10^{10.3}
Conditional Luminosity Function (CLF) means the Luminosity Function (LF) of a similar dark halo mass. It is more meaningful from the perspective of the galaxy-halo connection. CLFs of halo mass $M_h > 10^{12} 𝑀_\odot$ at z~0 have been measured down to rather faint luminosity reliably. In this work, we combined the DESI SV3 spectroscopic group central galaxies and the HSC photometric galaxies, and measured CLFs of central and satellite galaxies, red and blue populations separately, for groups with halo mass $\sim 10^{12}𝑀_\odot$ to $\sim 10^{15}𝑀_\odot$ , from redshift z∼0 to z∼1, towards an unprecedentedly faint magnitude limit. We found that the red satellite CLFs show a significant faint-end upturn in all halo mass and redshift bins, with a hardly evolved faint-end slope, implying that the red dwarf satellites have already been in place by z ∼ 1. We also found the evolution of bright end of CLFs is consistent with the passive evolution. The fraction of red (old) satellites as a function of stellar mass minimizes at a characteristic mass scale, $𝑀_* \sim 10^9𝑀_\odot$, from z∼0 to z∼1, indicating a dichotomy of quenching mechanisms for the satellite population. Besides higher redshift, we also expanded the CLF measurements to the unprecedented scale of low-mass halos $\sim 10^{10}𝑀_\odot$ at z < 0.2, by using spectroscopic dwarf galaxies combined with HSC deep layer and CLAUDS survey. We found that the faint-end slopes of the satellite CLFs of both blue and red populations, and the fraction of red (old) satellites in low-mass halos show a similar performance as their higher-mass halo counterparts.
Morphology is one of the fundamental characteristics of galaxies, yet reproducing it has long been a challenge for semi-analytic models. These models typically overpredict bulge-dominated massive galaxies and disk-dominated low-mass galaxies. I will introduce how we improve the model performance by modifying the bulge formation through galaxy mergers.
The improved approach takes use of the scaling relation summarised from the hydrodynamical simulation TNG, which correlates bulge-to-total ratio (B/T) with orbital angle, primary galaxy stellar mass, and other properties. The updated model shows good agreement with the B/T distribution observed in SDSS. This method helps to confirm key factors driving bulge formation and can be easily applied to other models.
Understanding how galaxies form and evolve is essential for advancing our knowledge of cosmic structure formation. However, generating large ensembles of mock galaxy catalogs through traditional semi-analytic models (SAMs) remains computationally prohibitive, especially when exploring wide ranges of physical parameters. In this work, we present a graph-neural-network-based emulator that efficiently reproduces SAM outputs by learning the mapping from dark matter halo merger trees and model parameters to galaxy properties.
Our framework is trained on large-scale data derived from the UchuuMicro simulation (with a 100 Mpc/h box size) and conditioned on outputs from the Galacticus SAM spanning 10,000 distinct parameter sets. The core innovation lies in a shared GNN backbone that effectively captures hierarchical and temporal information from complex merger trees. Crucially, we integrate the physical SAM parameters using a Feature-wise Linear Modulation (FiLM) mechanism, allowing the network to condition its feature learning on diverse physical priors. A multi-headed decoder simultaneously predicts multiple galaxy properties, including stellar mass, star formation rate, gas metal abundance, and black hole mass.
In an independent test set containing 600 SAM realizations (each generating 10,000 galaxies), the emulator reproduces the SAM stellar mass predictions with an average scatter of ~0.33 dex, and emulates all six galaxy properties for the entire 6 million-galaxy test set in just 9 seconds, an orders-of-magnitude acceleration over traditional approaches. This framework provides a fast and physically informed avenue for generating realistic galaxy catalogs and accelerating cosmological modeling pipelines.