arXiv subjects

Yun-Song Piao

Publications and source records attributed to Yun-Song Piao.

At least 19 recordsLinked to original sources

arXiv2026

Searching for gravitational wave echo with group equivariant neural posterior estimation

Current methods for the gravitational-wave (GW) echo searches generally require substantial computational time and resources. Recent advances in group equivariant neural posterior estimation (GNPE) have demonstrated the potential to substantially accelerate posterior inference. In this work, we adopt this framework and train a GNPE model to perform echo searches, significantly improving computational efficiency while maintaining comparable inference accuracy. We apply it to the O4a events and find no significant evidence for the GW echo.

gr-qc↗

arXiv2026

Imprint of swampland-inspired coupled early dark energy

Inspired by the Swampland Distance Conjecture, we investigate the cosmological implications of a fractional coupling between dark matter (DM) and early dark energy (EDE) in light of the recent DESI DR2 BAO data. We use a conditional normalizing flow network to efficiently sample the high-dimensional parameter space, and perform a joint analysis of Planck CMB data, DESI DR2 BAO, PantheonPlus supernovae and SH0ES. We find that the detailed construction of the EDE potential beyond the mere existence of an EDE component possibly alter cosmological constraints on late-time dark energy when the coupling between DM and EDE is considered.

astro-ph.CO↗

arXiv2026

Inverse-k Primordial Oscillations from a Symbolic Regression Search

Oscillatory features in the primordial power spectrum, potential signatures of new physics in the early universe, are usually searched for using fixed templates. In this work, we perform a template-free search for primordial features using symbolic regression. We find that both Planck and the combined Planck+ACT+SPT-3G datasets independently select an inverse-$k$ oscillation, $\cos(B/k)$ with $B\simeq4\,\mathrm{Mpc}^{-1}$, as the leading low-complexity feature. Comparing this inverse-$k$ template with standard linear and logarithmic oscillating templates, we find that it fits the data best, showing a weak preference for a non-zero amplitude. Our results show that symbolic regression as a powerful machine learning technique can provide an interpretable, model-independent approach to cosmological discovery.

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

Constraining supermassive primordial black hole clustering with the angular auto-correlation of $z\simeq 6$ quasars

High-redshift quasars provide a direct probe of the origin and environment of the earliest supermassive black holes. We use their angular auto-correlation function at $z\simeq 6$ to test scenarios in which supermassive primordial black holes (SMPBHs) are associated with the observed quasar population. The evolved PBH correlation functions, for both Poisson fluctuations and initial PBH clustering, are projected over the quasar redshift window and compared with the measured angular correlation function using Markov chain Monte Carlo inference. It is observed that for the Poisson model, the posterior favors a small abundance, $f_{\rm PBH}\sim 10^{-3}$, and a supermassive effective mass scale, $m_{\rm PBH}\sim 10^{12}M_\odot$, interpreted here as a scale controlling quasar host-halo formation and clustering, and for the initially clustered model, the data prefer an effective clustering amplitude $ξ_{\rm eff}\simeq 2.1$ and a top-hat boundary scale $r_{\rm cl}\simeq 76\,{\rm Mpc}$, corresponding to weak relative contraction of PBH pairs in comoving coordinates.

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↗

arXiv2026

Single field slow-roll inflation with step uplift to $n_s=1$

The early dark energy resolution of Hubble tension seems to be suggesting a scale-invariant Harrison-Zeldovich spectrum of primordial scalar perturbation, i.e. $n_s=1$ ($|n_s-1|\sim {\cal O}(0.001)$) for $H_0\sim 73$km/s/Mpc. In this work, we propose a possibility to acquire $n_s=1$ in single field slow-roll models of inflation. In our consideration, the potential of inflaton during inflation still preserve the shape of well-known single field inflation models in deep slow-roll region, but inflation ends suddenly due to a large step of inflaton potential. In particular, we investigate the implication of our scheme for chaotic inflation and Starobinski inflation, and show how they can be compatible with the observation for $n_s=1$.

astro-ph.CO↗

arXiv2026

Black Hole Superradiance of Interacting Multi-Field

We investigate black hole superradiance evolution of the interacting multiple fields. We consider a model of two scalar fields interacting with a cubic coupling, and study the superradiant evolution of the cloud. We demonstrate that superradiance is typically suppressed when the superradiant field couples to another field, even with a very weak coupling strength. This implies that the constraints on dark particles derived from single-field analyses can be revised in the presence of interactions. Moreover, we find that the multi-field superradiant evolution and its corresponding observational signatures can be different across parameter spaces, which makes black hole superradiance an even more powerful probe of the dark sector in particle physics.

gr-qc↗

arXiv2026

Testing the wormhole echo hypothesis for GW231123

The short-duration gravitational-wave (GW) event GW231123 has inferred component masses in the pair-instability mass gap and exhibits a burst-like morphology with no clearly inspiral, making it an interesting target for tests beyond the standard binary black hole (BBH) interpretation. In this work, motivated by its phenomenological similarity to GW190521, we test whether GW231123 is compatible with a wormhole-echo scenario by modeling a leading echo pulse with a well-motivated phenomenological sine-Gaussian wavepacket. We perform Bayesian model comparison against a BBH baseline described by the IMRPhenomXPHM-SpinTaylor waveform, and obtain the Bayes factor ratio $\ln B^{\rm Echo}_{\rm BBH} = 1.87$, corresponding to weak-to-moderate support for the echo hypothesis. In our previous analysis for GW190521 within the same overall framework, we found $\ln B^{\rm Echo}_{\rm BBH} \approx -2.9$, implying a shift of $Δ\ln B \approx 4.8$ between the two events. This sign change indicates that GW231123 is more compatible with a single-pulse echo description than GW190521.

gr-qc↗

arXiv2026

Is GW190521 a gravitational wave echo of wormhole remnant from another universe?

A particularly compelling aspect of the GW190521 event detected by the LIGO--Virgo--KAGRA (LVK) collaboration is that it has an extremely short duration, and lacks a clearly identifiable inspiral phase usually observed in the binary black holes (BBHs) coalescence. In this work, we hypothesize that GW190521 might represent a single, isolated gravitational wave (GW) echo pulse from the wormhole, which is the postmerger remnant of BBHs in another universe and connected to our universe through a throat. The ringdown signal after BBHs merged in another universe can pass through the throat of wormhole and be detected in our universe as a short-duration echo pulse. Our analysis results indicate that our model yields a network signal-to-noise ratio comparable to that of the standard BBHs merger model reported by the LVK collaboration. For GW190521, Bayesian model selection yields $\ln \mathcal{B}^{\text{Echo}}_{\text{BBH}} \simeq -2.9$, indicating that the data favor the BBH hypothesis over our echo-for-wormhole model.

gr-qc↗

arXiv2026

Impact of a negative cosmological constant on the reconstruction of dark energy in light of DESI BAO data

An anti-de Sitter vacuum, corresponding to a negative cosmological constant (NCC), might coexist with one evolving positive dark energy component at low redshift and is hinted by the latest DESI observations. In this paper, we use two methods, \textit{redshift-binned} and \textit{Gaussian Process-based} reconstructions to investigate the effect of a NCC on the equation of state (EOS) $w(z)$ of evolving dark energy (DE) component. We find that a NCC is slightly preferred in both the two reconstructions by up to $\simeq1σ$. Although the degeneracy between the EOS of evolving DE component and NCC weakens the constraint on the reconstructed $w(z)$, this degeneracy leads to the phantom divide $w=-1$ more consistent with the 1$σ$ posterior of $w(z)$.

astro-ph.CO↗

arXiv2025

Dark energy after pre-recombination early dark energy in light of DESI DR2 and the latest ACT and SPT data

It has been noted that with the pre-recombination early dark energy (EDE) resolution of Hubble tension, the preference of recent datasets for the evolving dark energy (DE) can be suppressed significantly. In this work, we clarify and reconfirm this result with DESI DR2 and the latest ACT DR6 and SPT-3G D1, the tightest small-scale CMB constraints up to date. In the $w_0w_a$CDM model with EDE, a quintessence-like component ($w_0+w_a\geq-1$) can be 1$σ$ consistent with Planck+ACT+SPT+DESI+Pantheon+SH0ES datasets, and $Δχ^2\lesssim -14$ compared with $w_0w_a$CDM model without EDE. This reveals the possibility that when the potential resolutions of Hubble tension are considered, current accelerated expansion can attribute to a canonical evolving scalar field or cosmological constant, and again highlights the importance of re-examining the nature of DE within the broader context of cosmological tensions.

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

Hint of $r\simeq 0.01$ after DESI DR2 ?

In the report by BICEP/Keck collaborations, the tensor-to-scalar ratio is $r_{0.05}<0.036$ (95\% C.L.). However, recent datasets have preferred the evolving dark energy, which thus have significantly shifted the bestfit values of standard $Λ$CDM cosmological parameters. In this paper, we perform the joint analysis of BICEP/Keck cosmic microwave background (CMB) B-mode data, latest DESI DR2 baryon acoustic oscillations and supernova data, combined with Planck PR3 and PR4 CMB data respectively, and find $r_{0.05}=0.0159^{+0.0057}_{-0.014}$ and $r_{0.05}=0.0164^{+0.0063}_{-0.014}$. The constraints on $r$ are further tightened compared to the result of BICEP/Keck collaborations. Though there might be still systematic uncertainties in B-mode measurements due to the foreground contamination, our work is to not say what the value of $r$ is, but present the state-of-the-art constraints on $r$ and emphasize that the detection for $r$ depends potentially on our insight into the dark universe, highlighting the important role of cosmological surveys in comprehending our very early universe.

astro-ph.CO↗

arXiv2025

Influence of supermassive primordial black holes on ultraviolet luminosity of high-redshift galaxies

Recently James Webb Space Telescope (JWST) have observed an excess of luminous galaxies at high redshifts ($z \gtrsim 10$). In this work, we investigate whether supermassive primordial black holes (SMPBHs) can explain it by their influence on the ultraviolet luminosity function (UV LF) of high-redshift galaxies. Through Markov Chain Monte Carlo analysis, we constrain the parameters relevant with SMPBHs against current JWST observational data. The results reveal that SMPBHs with masses $M_{\rm PBH} \sim 10^{6.3\text{-}8.3} M_\odot$, abundances $f_{\rm PBH} \sim 10^{-7}\text{-}10^{-5}$, and sub-Eddington ratios $λ_E \ll 1$ can effectively enhance the bright end of the UV LF, consistent with JWST observations.

astro-ph.GA↗

arXiv2025

Tightening constraints on primordial oscillations with latest ACT and SPT data

The oscillation feature in primordial power spectrum (PPS), a fingerprint of not only a wide class of models of inflation but new physics, is of significant theoretical interest, and can be imprinted on the cosmic microwave background (CMB). In this work, we present constraints on periodic oscillations in the PPS using the latest ACT DR6 and SPT-3G D1 CMB data with the precise measurements at high multipoles beyond the Planck angular resolution and sensitivity. It is found that the combination of SPT and ACT with Planck CMB dataset significantly tightens the upper bound to $A_\mathrm{log,lin}\lesssim 0.029$ at $95\%$ C.L., showing no hint for primordial oscillations, where $A_\mathrm{log,lin}$ are the amplitudes of logarithmic and linear oscillation in the PPS, respectively. Our work presents state-of-the-art CMB constraints on primordial oscillations, highlighting the power of the ground-based CMB experiments in constraining physics beyond the simplest slow-roll models.

astro-ph.CO↗