Based on a sample of $2.7\times10^{9}$ $\psi(3686)$ events collected by the BESIII detector operating at the BEPCII collider, the decay $\psi(3686)\to\gamma\chi_{cJ}, \chi_{cJ}\to\eta\eta\eta^{\prime}$ is analyzed. The decay modes $\chi_{c1}$ and $\chi_{c2}\to\eta\eta\eta^{\prime}$ are observed for the first time, and their corresponding branching fractions are determined to be ${\cal{B}}(\chi_{c1}\to\eta\eta\eta^{\prime}) = $ $ (1.40\, \pm 0.13\, (\text{stat.}) \pm 0.09\, (\text{sys.})) \times 10^{-4}$ and ${\cal{B}}(\chi_{c2}\to\eta\eta\eta^{\prime}) = (4.18\, \pm 0.84\, (\text{stat.}) \pm 0.48\, (\text{sys.})) \times 10^{-5}$ . An upper limit on the branching fraction of $\chi_{c0}\to\eta\eta\eta^{\prime}$ is set as $2.59 \times 10^{-5}$ at a 90% confidence level (CL). A partial wave analysis (PWA) of the decay $\chi_{c1}\to\eta\eta\eta^{\prime}$ is performed to search for the $1^{-+}$ exotic state $\eta_1(1855)$ . The PWA result indicates that the structure in the $\eta\eta^{\prime}$ mass spectrum is attributed to $f_0(1500)$ , while in the $\eta\eta$ mass spectrum, it is attributed to the $0^{++}$ phase space. The upper limit of ${\cal{B}}(\chi_{c1}\to\eta_{1}(1855)\eta) \cdot {\cal{B}}(\eta_{1}(1855)\to\eta\eta^{\prime}) \lt $ $ 9.79 \times 10^{-5}$ is set based on the PWA at 90% CL.

China

M. Ablikim

Russia

M.N. Achasov

Sweden

P. Adlarson

X.C. Ai

Germany

R. Aliberti

Italy

A. Amoroso

Q. An

Y. Bai

O. Bakina

Y. Ban

H.R. Bao

Poland

V. Batozskaya

Mongolia

K. Begzsuren

N. Berger

M. Berlowski

M. Bertani

D. Bettoni

F. Bianchi

E. Bianco

A. Bortone

I. Boyko

United States

R.A. Briere

A. Brueggemann

H. Cai

M.H. Cai

X. Cai

A. Calcaterra

G.F. Cao

N. Cao

Türkiye

S.A. Cetin

X.Y. Chai

J.F. Chang

G.R. Che

Y.Z. Che

C.H. Chen

Chao Chen

G. Chen

H.S. Chen

H.Y. Chen

M.L. Chen

S.J. Chen

S.L. Chen

S.M. Chen

T. Chen

X.R. Chen

X.T. Chen

X.Y. Chen

Y.B. Chen

Y.Q. Chen

Z. Chen

Z.J. Chen

Z.K. Chen

S.K. Choi

X. Chu

G. Cibinetto

F. Cossio

United Kingdom

J. Cottee-Meldrum

J.J. Cui

H.L. Dai

J.P. Dai

A. Dbeyssi

R.E. de Boer

D. Dedovich

C.Q. Deng

Z.Y. Deng

A. Denig

I. Denysenko

M. Destefanis

F. De Mori

B. Ding

X.X. Ding

Y. Ding

Y.X. Ding

J. Dong

L.Y. Dong

M.Y. Dong

X. Dong

M.C. Du

S.X. Du

Y.Y. Duan

P. Egorov

G.F. Fan

J.J. Fan

Y.H. Fan

J. Fang

S.S. Fang

W.X. Fang

Y.Q. Fang

R. Farinelli

L. Fava

F. Feldbauer

G. Felici

C.Q. Feng

J.H. Feng

L. Feng

Q.X. Feng

Search for $\textit{η}$ $_{1}$(1855) in $\textit{χ}$ $\textit{cJ}$ → $\textit{ηηη}$′ decays * Supported in part by National Key R&D Program of China (2023YFA1606000, 2023YFA1606704); National Natural Science Foundation of China (NSFC) (11635010, 11935015, 11935016, 11935018, 12025502, 12035009, 12035013, 12061131003, 12192260, 12192261, 12192262, 12192263, 12192264, 12192265, 12221005, 12225509, 12235017, 12361141819); the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; CAS (YSBR-101); 100 Talents Program of CAS; The Institute of Nuclear and Particle Physics (INPAC) and Shanghai Key Laboratory for Particle Physics and Cosmology; Agencia Nacional de Investigación y Desarrollo de Chile (ANID), Chile (ANID PIA/APOYO AFB230003); German Research Foundation DFG (FOR5327); Istituto Nazionale di Fisica Nucleare, Italy; Knut and Alice Wallenberg Foundation (2021.0174, 2021.0299); Ministry of Development of Turkey (DPT2006K-120470); National Research Foundation of Korea ( NRF-2022R1A2C1092335); National Science and Technology fund of Mongolia; National Science Research and Innovation Fund (NSRF) via the Program Management Unit for Human Resources Institutional Development, Research and Innovation of Thailand ( B50G670107); Polish National Science Centre (2024/53/B/ST2/00975); Swedish Research Council (2019.04595); U. S. Department of Energy (DE-FG02-05ER41374)

Based on available experimental results on $ \chi _{cJ}(J=0,1,2) $ decays, we investigated the $ \chi_{cJ}\to PP $ , $ VV $ , $ PV $ , and $ PT $ decays using the $\textit{SU}$(3) flavor symmetry/breaking approach, where $\textit{P}$, $\textit{V}$, and $\textit{T}$ denote light pseudoscalar, vector, and tensor mesons, respectively. With the decay amplitude relations determined by $\textit{SU}$(3) flavor symmetry/breaking, we present the branching ratios for all $ \chi_{cJ}\to PP $ and $ \chi_{cJ}\to VV $ modes, including those without experimental data. While theoretical considerations strongly suppress or even forbid most $ \chi_{cJ}\to PV $ and $ PT $ decays, we also provide quantitative predictions constrained by existing experimental data. Our results are expected to be accessible in future experiments at BESIII and the planned Super Tau-Charm Facility.

Bo Lan

Qin-Ze Song

Jin-Huan Sheng

Yi Qiao

Ru-Min Wang

Study of χ$_{cJ}$ ($\textit{J}$ = 0,1,2) decays to light meson pairs based on $\textit{SU}$(3) flavor symmetry/breaking analysis * Supported by the National Natural Science Foundation of China (12175088, 12305100, 12365014) and Graduate Innovation Fund Project of Jiangxi Provincial Department of Education (YJS2024091)

By capturing the characteristics of the Bethe-Salpeter amplitude for the pion excitation state, we construct an algebraic model to provide the overall features of the pion’s first excitation state parton distribution amplitude and distribution function. We find that, at the hadronic scale, the distribution amplitude of the excited state exhibits nodes, while the distribution function is unimodal, with a peak at $x=1/2 $ and distinct concave and convex fluctuations in the valence region. These findings provide new insights into the partonic structure of excited mesons and contribute significantly to our understanding of hadronic excitations.

Xiaobin Wang

Lei Chang

Unveiling the inner structure of the Pion’s first excited state * This work is financially supported by the National Natural Science Foundation of China (12135007)

The study of extra charged gauge bosons beyond the Standard Model has always been of great interest. Future muon colliders will have a significant advantage in discovering exotic particles. In this paper, by studying the $ \mu^+ \mu^- \to W^{\prime +} W^{\prime -} \to e^+ e^- n_e \bar{n}_e $ process, we explore the properties of $ W^\prime $ in the alternative left-right model. The cross section and angular distribution of the final electron are investigated in a scenario of different $ W^\prime $ masses and right-handed coupling constants. The forward-backward asymmetry is also an important observable to reflect the properties of $ W^\prime $ . We provide a method to effectively suppress the background processes by imposing constraints on the transverse momentum $ P_T $ and azimuthal angle of the final-state electrons $\textit{α}$. With cuts of $ 600 \lt P_T \lt 3500 $ GeV and $ 0.5 \lt \alpha \lt 3 $ , the significance exceeds 5$\textit{σ}$ for 4.8 TeV $ W^\prime $ at a collision energy of 10 TeV.

Liuxin Zhao

Honglei Li

Zhi-Long Han

Fei Huang

Xinyi Yan

Extra charged gauge boson $\textit{W}$′ in Alternative Left-Right Model at future muon collider * This work is supported by the Natural Science Foundation of Shandong Province (ZR2022MA065, ZR2024QA138), and University of Jinan Disciplinary Cross-Convergence Construction Project 2024 (XKJC-202404)

High-precision regression of physical parameters from black hole images generated by General Relativistic Ray Tracing (GRRT) is essential for investigating spacetime curvature and advancing black hole astrophysics. However, owing to limitations in observational resolution, high observational costs, and imbalanced distributions of positive and negative samples, black hole images often suffer from data scarcity, sparse parameter spaces, and complex structural characteristics. These factors pose significant challenges to conventional regression methods based on simplified physical models. To overcome these challenges, this study introduces the Multiscale Adaptive Network (MANet), a novel regression framework grounded in deep learning. MANet integrates an Adaptive Channel Attention (ACA) module to selectively enhance features in physically informative regions. Meanwhile, a Multiscale Enhancement Feature Pyramid (MEFP) is employed to capture fine-grained spatial structures, such as photon rings and accretion disks, while alleviating information loss due to downsampling. Experimental evaluations on GRRT-simulated datasets demonstrate that MANet substantially improves parameter estimation accuracy and generalization capability in high-dimensional parameter spaces, outperforming existing baseline approaches. This framework presents a promising avenue for high-precision parameter regression in Event Horizon Telescope (EHT) data analysis and broader astrophysical imaging applications characterized by sparse and noisy data.

Jialei Wei

Ao Liu

Dejiang Li

Cuihong Wen

Physical parameter regression from black hole images using a multiscale adaptive neural network * Supported by the Natural Science Foundation of Hunan Province under grant No. 2023JJ30384; the National Natural Science Foundation of China under Grants No. 12374408; the University Students' Innovation and Entrepreneurship Training Program Project

We present a Physics-Informed Neural Network (PINN) framework for reconstructing the redshift-dependent Hubble parameter $$H(z)$$ within the Tsallis Holographic Dark Energy (THDE) model extended by massive neutrinos. In this approach, the modified Friedmann equation is incorporated into the neural network loss function, enabling training on Cosmic Chronometers data up to $$z \le 2$$ . The framework allows for the simultaneous estimation of the Hubble constant $$H_0$$ , the neutrino density parameter $$\Omega _\nu $$ , and the Tsallis non-extensivity index $$\delta $$ . Uncertainty quantification is performed through dropout simulations, resulting in statistically consistent $$1\sigma $$ confidence bands. Our results show that the THDE+ $$\nu $$ model, reconstructed via PINN, alleviates the statistical Hubble tension from the canonical $$\sim 5\sigma $$ level down to a range of $$0.5\sigma \le T \le 2.2\sigma $$ , depending on the redshift sampling. Additionally, we constrain the total neutrino mass to $$\Sigma m_\nu < 0.11\,\text {eV}$$ . A detailed comparison with the traditional Markov Chain Monte Carlo (MCMC) analysis demonstrates the consistency of both methods, while highlighting the competitiveness of the PINN-based THDE framework as a robust, data-driven approach for non-parametric cosmological inference within generalized thermodynamics.

Iran

Muhammad Yarahmadi

Amin Salehi

Towards a machine learning solution for hubble tension: Physics-Informed Neural Network (PINN) analysis of Tsallis Holographic Dark Energy in presence of neutrinos

Neural networks have emerged as a powerful paradigm for tasks in high energy physics, yet their opaque training process renders them as a black box. In contrast, the traditional cut flow method offers simplicity and interpretability but requires extensive manual tuning to identify optimal cut boundaries. To merge the strengths of both approaches, we propose the $\textit{Learnable Cut Flow}$ (LCF), a neural network that transforms the traditional cut selection into a fully differentiable, data-driven process. LCF implements two cut strategies — parallel, where observable distributions are treated independently, and sequential, where prior cuts shape subsequent ones — to flexibly determine optimal boundaries. Building on this strategy, we introduce the $\textit{Learnable Importance}$, a metric that quantifies feature importance and adjusts their contributions to the loss accordingly, offering model-driven insights unlike ad-hoc metrics. To ensure differentiability, a modified loss function replaces hard cuts with mask operations, preserving data shape throughout the training process. LCF is tested on six varied mock datasets and a realistic diboson vs. QCD dataset. Results demonstrate that LCF (1) accurately learns cut boundaries across typical feature distributions in both parallel and sequential strategies, (2) assigns higher importance to discriminative features with minimal overlap, (3) handles redundant or correlated features robustly, and (4) performs effectively in real-world scenarios. In the diboson dataset, LCF initially underperforms boosted decision trees and multilayer perceptrons when using all observables. LCF bridges the gap between traditional cut flow method and modern black-box neural networks, delivering actionable insights into the training process and feature importance. Source code and experimental data are available at .

Jing Li

Hao Sun

Learnable cut flow for high energy physics

<p>We use the physics-informed renormalization group (PIRG) for the construction of gauge invariant renormalization group flows. The respective effective action is a sum of a gauge invariant quantum part and the classical gauge fixing part which arranges for invertibility of the gauge field two-point function. Thus, the BRST transformations simply accommodate the gauge consistency of the gauge fixing sector, while the quantum part of the effective action is gauge and BRST invariant. We apply this physics-informed approach to Yang-Mills theory and gravity and show how the flowing gauge fields arrange for full gauge invariance. We also embed the background field approximation to the functional renormalization group (fRG) in an exact gauge invariant PIRG flow. This allows us to discuss the dynamics of the correction terms, and the nontrivial ultraviolet or infrared relevant terms are elucidated within a one-loop approximation. The background field approximation of the latter is known for violating one-loop universality for specific regulators, and we show how the present setup reinstates universality in a constructive way. Finally, we discuss the landscape of fRG flows in gauge theories through the lens of the novel PIRG approach as well as potential applications.</p>

Friederike Ihssen

Jan M. Pawlowski

Physics-informed gauge theories

Recent results on the Coherent Elastic Neutrino-Nucleus Scattering (CE$\textit{ν}$NS) on germanium present significant discrepancies among experiments. We perform a combined analysis of the Dresden-II, CONUS+ and COHERENT data, quantifying the impact of quenching factor uncertainties on their CE$\textit{ν}$NS cross section measurement. No choice of quenching factor can bring these three data sets into mutual agreement, whereas the combination of COHERENT with either Dresden-II or CONUS+ agrees well albeit for very different quenching factors. We further study the quenching factor dependence on the sensitivity of these experiments to a large neutrino magnetic moment, finding that the constraints can vary by up to an order of magnitude. Our work highlights the importance of reducing this uncertainty on quenching factors in order to probe new physics from neutrinos at the low-energy frontier.

Yulun Li

Gonzalo Herrera

Patrick Huber

New physics versus quenching factors in Coherent Neutrino Scattering

We consider a disordered system of interacting fermions, for which we demonstrate, that depending on the relationship between the degree of disorder and real physical dimensionality <italic>d</italic>, this system undergoes a delocalization (e.g. a metal-insulator) phase transition. The effect of the disorder is accounted for by replacing the ordinary single-particle kinetic energy operator by that with a fractional spectrum. These fractional spectra represent the microscopic equivalent of the well-known non-trivial power-law decay of the low-energy density of states of non-interacting disordered systems. We develop a powerful approach to analyze the density of states in interacting disordered system, combining both the saddle-point and renormalization group methods. These two methods complement each other effectively. Through this approach, we identify a fixed point in the renormalization group flow of the model&#8217;s parameters, which dictates the behavior of the system in the conducting phase. Additionally, we extend our analysis to include static conductivity. Our examination of the system&#8217;s conductivity allows us to establish several strict conditions regarding the stability of the metallic state across different spatial dimensions <italic>d</italic>. Notably, we emphasize the unique significance of the two-dimensional case <math altimg='si13.svg'><mrow><mi>d</mi><mo linebreak='goodbreak'>=</mo><mn>2</mn></mrow></math>. We also compare our findings with salient experimental features observed in paradigmatic physical systems.

A. Sinner

V.A. Stephanovich

B. Pytel

A. Wójcik

Fractional spectrum due to disorder and its effect on the ground state in the ensembles of interacting fermions