arXiv subjects

Jun-Qian Jiang

Publications and source records attributed to Jun-Qian Jiang.

At least 19 recordsLinked to original sources

arXiv2026

Finding the distribution of matter using lenses - I: deconvolution-based reconstruction with CMB lensing

The matter power spectrum is one of the primary statistical descriptors of the large-scale distribution of matter in the Universe and provides a powerful probe of cosmic structure formation. Measurements of cosmic microwave background (CMB) lensing offer an integrated view of the matter distribution over a wide range of redshifts, enabling the reconstruction of the underlying matter power spectrum. In this work, we reconstruct the reference linear matter power spectrum $ P_\text{lin}(k,0)$ from the baseline joint CMB lensing measurements of Planck PR4, ACT DR6, and SPT-3G using a covariance-weighted modified Richardson-Lucy(MRL) deconvolution algorithm. The reconstructed spectrum is found to be consistent with the fiducial linear prediction on large scales, while exhibiting a systematic enhancement for $k \gtrsim 0.1\,{\rm Mpc}^{-1}$, where nonlinear gravitational evolution becomes important. To investigate this behavior, we introduce a scale-dependent correction factor, $A(k)$, defined through $P(k)=A(k)\,P_{\rm nl}(k),$ where $P_{\rm nl}(k)$ is the fiducial nonlinear matter power spectrum obtained from 2LPT simulations. The reconstructed correction factor remains consistent with unity within $2σ$ confidence over the reconstructed range, indicating that the observed enhancement is well explained by the standard nonlinear evolution of the matter power spectrum. In addition, the reconstruction shows agreement with the fiducial BAO template around the BAO feature at $k\sim(0.04-0.06)\ {\rm Mpc}^{-1}$, indicating that some BAO-scale information survives the lensing projection.

astro-ph.CO↗

arXiv2026

Finding the distribution of matter using lenses - II: deconvolution-based reconstruction with 3x2pt measurements

We present a deconvolution-based framework for testing scale-dependent departures of the late-time matter power spectrum from a fiducial cosmological model using $3\times2$pt measurements. We introduce a free-form scale-dependent modulation $A(k)$ of the fiducial nonlinear matter power spectrum and construct the linear response of binned galaxy-clustering, galaxy-galaxy-lensing, and cosmic-shear spectra to the discretized modulation $A(k)$. The response is evaluated with full-sky, beyond-Limber kernels including density, redshift-space-distortion, gravitational-shear, and intrinsic-alignment contributions. We reconstruct $A(k)$ using a regularized modified Richardson-Lucy algorithm, with weak diffusion in $\ln k$ and selection of the minimum-$χ^2$ solution along the iteration history. Using Rubin/LSST Year 10-like synthetic data, we find that oscillatory modulations with amplitudes $\gtrsim1\%$ can be recovered over $0.1\lesssim k\lesssim0.5\,{\rm Mpc}^{-1}$, provided the oscillation frequency $f\lesssim10$ on $\log_{10}[k/(0.2\,{\rm Mpc}^{-1})]$. We further introduce a posterior-weighted consistency statistic calibrated with posterior-predictive null mocks, thereby accounting for cosmological and nuisance-parameter uncertainties without relying on Wilks' theorem. The null case is consistent with $A(k)=1$, while a $1\%$ oscillatory modulation is detected at $\sim 2.6σ$. These results demonstrate the potential of regularized deconvolution as a model-independent consistency test of the matter power spectrum in future $3\times2$pt surveys.

astro-ph.CO↗

arXiv2026

Is Dark Matter Really Matter?

In the standard model of cosmology, it is assumed that dark matter is pressureless with equation of state $w=0$ and dark energy has $w=-1$. We test these assumptions jointly using DESI DR2 distance measurements, including the recent Lyman-$α$ full-shape Alcock-Paczynski (AP) information, DES supernovae, and two complementary CMB treatment. When constant $w_{dm}$ and $w_{de}$ are varied together, we find $w_{dm}=0.000968^{+0.000501}_{-0.000496}$ and $w_{de}=-0.9380^{+0.0259}_{-0.0262}$ (68%). With an alternative CMB treatment that marginalizes over the lensing spectrum, the corresponding constraints are $w_{dm}=0.000870^{+0.000408}_{-0.000410}$ and $w_{de}=-0.9353^{+0.0258}_{-0.0254}$. Both standard $Λ$CDM values are disfavored at approximately $2σ$ in the joint extension. Neither parameter departs significantly from its standard value when only that parameter is varied. This behavior arises because late-time distances favor $w_{de}>-1$, while maintaining the early-Universe physical matter density requires a compensating positive $w_{dm}$, which changes the mapping to the matter density today. Allowing dynamical dark energy clarify further on complexity of the situation: phantom crossing for dark energy makes $w_{dm}=0$ consistent with the data, whereas a positive $w_{dm}$ preference persists when crossing is forbidden. Interestingly, the Pad'e-$w$ parameterization that provides a flexible description of a class of quintessence models (with no phantom crossing), along with $w_{dm}$ free, is even mildly favored over the phantom-crossing $w_0w_a$ model according to both the best-fit $χ^2$ and the DIC under both CMB treatments. One can conclude that the apparent preference for phantom crossing may instead reflect deviations in the dark-matter sector rather than dark-energy dynamics alone. [abridged]

astro-ph.CO↗

arXiv2026

A fast deep-learning approach to probing primordial black hole populations in gravitational wave events

Primordial black holes (PBHs), envisioned as a compelling dark matter candidate and a window onto early-Universe physics, may contribute to some of the gravitational-wave (GW) signals detected by the LIGO-Virgo-KAGRA network. Traditional hierarchical Bayesian analysis, which relies on precise GW-event posterior estimates to extract information on potential PBH populations from GW events, becomes computationally demanding for catalogs with a large number of events. Here, we present a fast deep-learning framework, leveraging Transformer and normalizing flows, that maps GW-event posterior samples to joint posterior distributions over the hyperparameters of the PBH population. Our approach yields credible intervals with acceptable accuracy while delivering an order-of-magnitude speedup. These results highlight the potential of deep learning for fast and accurate PBH population studies, and its applicability to next-generation GW detectors when combined with appropriate event-level inference models.

gr-qc↗

arXiv2026

Late-Time Oscillating Quintessence in Light of DESI

Recent DESI baryon acoustic oscillation measurements, especially when combined with Type Ia supernova and CMB data, sharpen the case for possible low-redshift dynamics in the dark energy sector. We study a simple and physically transparent realization of such dynamics: a quintessence field that is Hubble frozen for most of cosmic history and starts to oscillate around its minimum recently (at a redshift $z\approx 0.1$). This late onset of oscillations can occur in a broad class of models where the quintessence potentials have a shallow slope away from the minimum and steepen near it. This class of models can improve the fit relative to $Λ$CDM, with $Δχ^2\simeq -9$, while remaining competitive with common phenomenological dark energy parameterizations with the same number of parameters. The preference is driven mainly by the background expansion history, and near the best-fit region the resonant growth of quintessence perturbations and the associated Integrated Sachs-Wolfe (ISW) contribution remain small. More precise low-redshift distance measurements, together with late-time probes such as the ISW effect and lensing, may help distinguish this oscillating quintessence scenario from other forms of late-time dark energy dynamics.

astro-ph.CO↗

arXiv2026

DeepInflation: an AI agent for research and model discovery of inflation

We present DeepInflation, an AI agent designed for research and model discovery in inflationary cosmology. Built upon a multi-agent architecture, DeepInflation integrates Large Language Models (LLMs) with a symbolic regression (SR) engine and a retrieval-augmented generation (RAG) knowledge base. This framework enables the agent to automatically explore and verify the vast landscape of inflationary potentials while grounding its outputs in established theoretical literature. We demonstrate that DeepInflation can successfully discover simple and viable single-field slow-roll inflationary potentials consistent with the latest observations (with the ACT DR6 results taken as an example) or any given $n_s$ and $r$, and provide accurate theoretical context for obscure inflationary scenarios. DeepInflation serves as a prototype for a new generation of autonomous scientific discovery engines in cosmology, which enables researchers and non-experts alike to explore the inflationary landscape using natural language. This agent is available at https://github.com/pengzy-cosmo/DeepInflation.

astro-ph.CO↗

arXiv2026

Search for primordial black holes from gravitational wave populations using deep learning

Gravitational waves (GWs) signals detected by the LIGO/Virgo/KAGRA collaboration might be sourced (partly) by the merges of primordial black holes (PBHs). The conventional hierarchical Bayesian inference methods can allow us to study population properties of GW events to search for the hints for PBHs. However, hierarchical Bayesian analysis require an analytic population model, and becomes increasingly computationally expensive as the number of sources grows. In this paper, we present a novel population analysis method based on deep learning, which enables the direct and efficient estimation of PBH population hyperparameters, such as the PBH fraction in dark matter, $f_{\rm PBH}$. Our approach leverages neural posterior estimation combined with conditional normalizing flows and two embedding networks. Our results demonstrate that inference can be performed within seconds, highlighting the promise of deep learning as a powerful tool for population inference with an increasing number of GW signals for next-generation detectors.

gr-qc↗

arXiv2025

Measuring neutrino masses with joint JWST and DESI DR2 data

Early JWST observations reveal an unexpectedly abundant population of high-redshift candidate massive galaxies at $z \gtrsim 7$, and recent DESI measurements show a preference for dynamical dark energy, which together present a significant challenge to the standard $Λ$CDM cosmology. In this work, we jointly analyze high-redshift galaxy data from JWST, baryon acoustic oscillations data from DESI DR2, and cosmic microwave background (CMB) data from Planck and ACT, measuring the total neutrino mass $\sum m_ν$. We consider three dark energy models ($Λ$CDM, $w$CDM, and $w_0w_a$CDM) and three mass hierarchies. Our results indicate that in the $w_0w_a$CDM model, adding JWST data to CMB+DESI tightens the upper limit of $\sum m_ν$ by about $5.8\%-10.2\%$, and we obtain $\sum m_ν < 0.167~\mathrm{eV}$ ($2σ$) in the normal hierarchy (NH) case. Furthermore, JWST also offers indicative lower limits on star formation efficiency parameter of $f_{*,10} \gtrsim 0.146-0.161$. Bayesian evidence weakly favors the $w_0w_a$CDM+$\sum m_ν$(NH) model relative to the $Λ$CDM+$\sum m_ν$(NH) model using CMB+DESI+JWST data. These results suggest that the joint analysis of high-redshift JWST data and low-redshift DESI data provides compelling constraints on neutrino mass and merits further investigation.

astro-ph.CO↗

arXiv2025

News-Aware Direct Reinforcement Trading for Financial Markets

The financial market is known to be highly sensitive to news. Therefore, effectively incorporating news data into quantitative trading remains an important challenge. Existing approaches typically rely on manually designed rules and/or handcrafted features. In this work, we directly use the news sentiment scores derived from large language models, together with raw price and volume data, as observable inputs for reinforcement learning. These inputs are processed by sequence models such as recurrent neural networks or Transformers to make end-to-end trading decisions. We conduct experiments using the cryptocurrency market as an example and evaluate two representative reinforcement learning algorithms, namely Double Deep Q-Network (DDQN) and Group Relative Policy Optimization (GRPO). The results demonstrate that our news-aware approach, which does not depend on handcrafted features or manually designed rules, can achieve performance superior to market benchmarks. We further highlight the critical role of time-series information in this process.

q-fin.CP↗

arXiv2025

Testing $n_s=1$ in light of the latest ACT and SPT data

It is commonly recognized that the primordial scalar spectral index $n_s$ is approximately $0.96-0.975$, depending on the dataset. However, this view is being completely altered by the early dark energy (EDE) resolutions of the Hubble tension, known as the most prominent tension the standard $Λ$CDM model is suffering from. In corresponding models with pre-recombination EDE, resolving the Hubble tension (i.e., achieving $H_0\sim 73$km/s/Mpc) must be accompanied by a shift of $n_s$ towards unity to maintain consistency with the cosmological data, which thus implies a scale invariant Harrison-Zel'dovich spectrum with $n_s=1$ $(|n_s-1|\simeq {\cal O}(0.001))$. In this work, we strengthen and reconfirm this result with the latest ground-based CMB data from ACT DR6 and SPT-3G D1, the precise measurements at high multipoles beyond the Planck angular resolution and sensitivity. Our work again highlights the importance of re-examining our understanding on the very early Universe within the broader context of cosmological tensions.

astro-ph.CO↗

arXiv2025

Can the sound horizon-free measurement of $H_0$ constrain early new physics?

The sound horizon-independent $H_0$ extracted by using galaxy clustering surveys data through, e.g., EFTofLSS or ShapeFit analyses, is considered to have the potential to constrain the early new physics responsible for solving the Hubble tension. Recent observations, e.g. DESI, have shown that the sound horizon-independent measurement of $H_0$ is consistent with $Λ$CDM. In this work, we clarify some potential misuses and misinterpretations in these analyses. On the one hand, imposing some prior from other cosmological probes is often used to strengthen the constraints on the results, however, these priors are usually derived using the assumption of $Λ$CDM, it is not suitable to apply these so-called $Λ$CDM priors (e.g., the $n_s$ prior from CMB), which would bias the results, to early new physics because these early new physics are usually accompanied by shifts of the $Λ$CDM parameters. On the other hand, the constraints on $H_0$ in the sound horizon-independent EFTofLSS analysis arise from not only the shape of the power spectrum ($k_\text{eq}$-based $H_0$), but also the overall amplitude (when combined with CMB lensing observations) and the relative amplitudes of the BAO wiggles, thus besides $k_\text{eq}$ other information may also play a role in constraining $H_0$. We also make forecasts for an Euclid-like survey, which suggest that ongoing observations will also have difficulty constraining early new physics.

astro-ph.CO↗

arXiv2025

Status of early dark energy after DESI: the role of $Ω_m$ and $r_s H_0$

The EDE model is one of the promising solutions to the long-standing Hubble tension. This paper investigates the status of several EDE models in light of recent BAO observations from the Dark Energy Spectroscopic Instrument (DESI) and their implications for resolving the Hubble tension. The DESI Y1 BAO results deviate from the CMB and Type Ia supernova (SNeIa) observations in their constraints on the matter density $Ω_m$ and the product of the sound horizon and the Hubble constant $r_s H_0$. Meanwhile, these EDE models happen to tend towards this deviation. Therefore, in this work, it is found that DESI Y1 BAO results strengthen the preference for EDE models and help to obtain a higher $H_0$. Even considering the Pantheon+ observations for SNeIa, which have an opposite tendency, DESI still dominates the preference for EDE. This was unforeseen in past SDSS BAO measurements and therefore emphasizes the role of BAO and SNeIa measurements in Hubble tension.

astro-ph.CO↗

arXiv2025

Scale-dependence in $Λ$CDM parameters inferred from the CMB: a possible sign of Early Dark Energy

The early dark energy (EDE) model is one of the promising solutions to the Hubble tension. One of the successes of the EDE model is that it can provide a similar fit to the $Λ$CDM model for the CMB power spectrum. In this work, I analyze the phenomenology of the EDE and $Λ$CDM parameters on the CMB temperature power spectrum and notice that this cannot hold on all scales. Thus, if the real cosmology is as described by the EDE model, the $Λ$CDM parameters will be scale-dependent when fitting the CMB power spectrum with the $Λ$CDM model, which can be hints for the EDE model. I examine CMB-S4-like observations through mock data analysis and find that parameter shifts are notable. As observations include smaller scales, I find lower $H_0$, $n_s$, $ω_b$ and higher $ω_m$, $A_s e^{-2τ}$, which will also constitute new tensions with other observations. They can serve as a possible signal for the EDE model.

astro-ph.CO↗

arXiv2025

Search for the non-linearities of gravitational wave background in NANOGrav 15-year data set

The recently reported signal of common red noise between pulsars by several pulsar timing array collaborations has been thought as evidence of the stochastic gravitational wave background (SGWB) due to the Helling-Downs correlation. In this Letter, we search for the non-Gaussianity of SGWB through its non-linear effect on the overlap reduction function in NANOGrav 15-year data set. In particular, we focus on a folded component to SGWB whose amplitude is quantified with a single parameter $α$ in the unpolarized case. The resulting Bayes factor of $1.68 \pm 0.01$ ($1.78 \pm 0.01$ in the case of signals from SMBHBs) indicates that there is no evidence of such a non-Gaussianity of SGWB in the NANOGrav 15-year data yet. If it is detected in future PTA experiments, it will impact our understanding on the origin of the detected SGWB.

gr-qc↗

arXiv2025

Neutrino cosmology after DESI: tightest mass upper limits, preference for the normal ordering, and tension with terrestrial observations

The recent DESI Baryon Acoustic Oscillation measurements have led to tight upper limits on the neutrino mass sum, potentially in tension with oscillation constraints requiring $\sum m_ν \gtrsim 0.06\,{\text{eV}}$. Under the physically motivated assumption of positive $\sum m_ν$, we study the extent to which these limits are tightened by adding other available cosmological probes, and robustly quantify the preference for the normal mass ordering over the inverted one, as well as the tension between cosmological and terrestrial data. Combining DESI data with Cosmic Microwave Background measurements and several late-time background probes, the tightest $2σ$ limit we find without including a local $H_0$ prior is $\sum m_ν<0.05\,{\text{eV}}$. This leads to a strong preference for the normal ordering, with Bayes factor relative to the inverted one of $46.5$. Depending on the dataset combination and tension metric adopted, we quantify the tension between cosmological and terrestrial observations as ranging between $2.5σ$ and $5σ$. These results are strenghtened when allowing for a time-varying dark energy component with equation of state lying in the physically motivated non-phantom regime, $w(z) \geq -1$, highlighting an interesting synergy between the nature of dark energy and laboratory probes of the mass ordering. If these tensions persist and cannot be attributed to systematics, either or both standard neutrino (particle) physics or the underlying cosmological model will have to be questioned.

astro-ph.CO↗

arXiv2024

Explanation of high redshift luminous galaxies from JWST by early dark energy model

Recent observations from the James Webb Space Telescope (JWST) have uncovered massive galaxies at high redshifts, with their abundance significantly surpassing expectations. This finding poses a substantial challenge to both galaxy formation models and our understanding of cosmology. Additionally, discrepancies between the Hubble parameter inferred from high-redshift cosmic microwave background (CMB) observations and those derived from low-redshift distance ladder methods have led to what is known as the ``Hubble tension''. Among the most promising solutions to this tension are Early Dark Energy (EDE) models. In this study, we employ an axion-like EDE model in conjunction with a universal Salpeter initial mass function to fit the luminosity function derived from JWST data, as well as other cosmological probes, including the CMB, baryon acoustic oscillations (BAO), and the SH0ES local distance ladder. Our findings indicate that JWST observations favor a high energy fraction of EDE, $ f_\text{EDE} \sim 0.2 \pm 0.03 $, and a high Hubble constant value of $ H_0 \sim 74.6 \pm 1.2 $ km/s/Mpc, even in the absence of SH0ES data. This suggests that EDE not only addresses the $ H_0 $ tension but also provides a compelling explanation for the observed abundance of massive galaxies identified by JWST.

astro-ph.CO↗

arXiv2024

Nonparametric late-time expansion history reconstruction and implications for the Hubble tension in light of recent DESI and type Ia supernovae data

We nonparametrically reconstruct the late-time expansion history in light of the latest Baryon Acoustic Oscillation (BAO) measurements from DESI combined with various Type Ia Supernovae (SNeIa) catalogs, using interpolation through piece-wise natural cubic splines, and a reconstruction procedure based on Gaussian Processes (GPs). Applied to DESI BAO and PantheonPlus SNeIa data, both methods indicate that deviations from a reference $Λ$CDM model in the $z \lesssim 2$ unnormalized expansion rate $E(z)$ are constrained to be $\lesssim 10\%$, but also consistently identify two features in $E(z)$: a bump at $z \sim 0.5$, and a depression at $z \sim 0.9$, which cannot be simultaneously captured by a $w_0w_a$CDM fit. These features, which are stable against assumptions regarding spatial curvature, interpolation knots, and GP kernel, disappear if one adopts the older SDSS BAO measurements in place of DESI, and decrease in significance when replacing the PantheonPlus catalog with the Union3 and DESY5 ones. We infer $c/(r_dH_0)=29.90 \pm 0.33$, with $r_d$ the sound horizon at baryon drag and $H_0$ the Hubble constant. Breaking the $r_d$-$H_0$ degeneracy with the SH0ES prior on $H_0$, the significance of the tension between our nonparametric determination of $r_d=136.20^{+2.20}_{-2.40}\,{\text{Mpc}}$ and the \textit{Planck} $Λ$CDM-based determination is at the $5σ$ level, slightly lower than the $6σ$ obtained when adopting the older SDSS dataset in place of DESI. This indicates the persistence at very high significance of the ``sound horizon tension'', reinforcing the need for pre-recombination new physics. If substantiated in forthcoming data releases, our results tentatively point to oscillatory/nonmonotonic features in the shape of the expansion rate at $z \lesssim 2$, of potential interest for dark energy model-building.

astro-ph.CO↗

arXiv2024

Multidimensionality of the Hubble tension: the roles of $Ω_m$ and $ω_c$

The Hubble tension is inherently multidimensional, and bears important implications for parameters beyond $H_0$. We discuss the key role of the matter density parameter $Ω_m$ and the physical cold dark matter density $ω_c$. We argue that once $Ω_m$ and the physical baryon density $ω_b$ are calibrated, through Baryon Acoustic Oscillations (BAO) and/or Type Ia Supernovae (SNeIa) for $Ω_m$, and via Big Bang Nucleosynthesis for $ω_b$, any model raising $H_0$ requires raising $ω_c$ and, under minimal assumptions, also the clustering parameter $S_8$. We explicitly verify that this behaviour holds when analyzing recent BAO and SNeIa data. We argue that a calibration of $Ω_m$ as reliable and model-independent as possible should be a priority in the Hubble tension discussion, and an interesting possibility in this sense could be represented by galaxy cluster gas mass fraction measurements.

astro-ph.CO↗