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Zhenghao Fu

Publications and source records attributed to Zhenghao Fu.

4 recordsLinked to original sources

Early Preconfiguration Failure: A Novel Predictor of the Repetitive Subconcussion

Early diagnosis and assessment of repetitive subconcussive (rSC) brain injuries are crucial for early clinical intervention. Conventional methods, largely relying on slow fMRI, fail to capture millisecond-level early cortical dynamics, particularly spatiotemporal features associated with pre-configuration dynamics. This study introduces a novel approach integrating dynamic hierarchical spatial features and cortical early behavioral time-domain sensitivity, utilizing EEG and visual attention tasks. We analyzed cortical early behaviors in 24 healthy controls (HC), 21 rSC patients,and a validation cohort of 25 cTBI patients from public datasets. Results reveal distinct temporal patterns in HC: elevated integration at 0-100 ms, rebound dynamics at 100-200ms, and visual perception integration peaks at 200-600 ms. In contrast, rSC patients exhibited significantly impaired dynamic features, with reduced integration levels indicating a decline in pre-configuration dynamics. Signed center distance (SCD) analysis of separation-integration trajectories showed significantly lower early SCD values in rSC patients compared to HC, while cTBI patients displayed negative SCD values, reflecting irreversible damage. Machine learning classification achieved optimal performance in distinguishing between HC, rSC, and cTBI groups using early cortical features, highlighting the critical role of millisecond-level cortical dynamics in rSC diagnosis.

q-bio.NC

TIDMAD: Time Series Dataset for Discovering Dark Matter with AI Denoising

Dark matter makes up approximately 85% of total matter in our universe, yet it has never been directly observed in any laboratory on Earth. The origin of dark matter is one of the most important questions in contemporary physics, and a convincing detection of dark matter would be a Nobel-Prize-level breakthrough in fundamental science. The ABRACADABRA experiment was specifically designed to search for dark matter. Although it has not yet made a discovery, ABRACADABRA has produced several dark matter search results widely endorsed by the physics community. The experiment generates ultra-long time-series data at a rate of 10 million samples per second, where the dark matter signal would manifest itself as a sinusoidal oscillation mode within the ultra-long time series. In this paper, we present the TIDMAD -- a comprehensive data release from the ABRACADABRA experiment including three key components: an ultra-long time series dataset divided into training, validation, and science subsets; a carefully-designed denoising score for direct model benchmarking; and a complete analysis framework which produces a community-standard dark matter search result suitable for publication as a physics paper. This data release enables core AI algorithms to extract the dark matter signal and produce real physics results thereby advancing fundamental science. The data downloading and associated analysis scripts are available at https://github.com/jessicafry/TIDMAD

cs.LG

Combined Pre-Supernova Alert System with Kamland and Super-Kamiokande

Preceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande, both located in the Kamioka mine in Japan, have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance.

hep-ex

Long-Distance Nuclear Matrix Elements for Neutrinoless Double-Beta Decay from Lattice QCD

Neutrinoless double-beta ($0\nu\beta\beta$) decay is a heretofore unobserved process which, if observed, would imply that neutrinos are Majorana particles. Interpretations of the stringent experimental constraints on $0\nu\beta\beta$-decay half-lives require calculations of nuclear matrix elements. This work presents the first lattice quantum-chromodynamics (LQCD) calculation of the matrix element for $0\nu\beta\beta$ decay in a multi-nucleon system, specifically the $nn \rightarrow pp ee$ transition, mediated by a light left-handed Majorana neutrino propagating over nuclear-scale distances. This calculation is performed with quark masses corresponding to a pion mass of $m_\pi = 806$ MeV at a single lattice spacing and volume. The statistically cleaner $\Sigma^- \rightarrow \Sigma^+ ee$ transition is also computed in order to investigate various systematic uncertainties. The prospects for matching the results of LQCD calculations onto a nuclear effective field theory to determine a leading-order low-energy constant relevant for $0\nu\beta\beta$ decay with a light Majorana neutrino are investigated. This work, therefore, sets the stage for future calculations at physical values of the quark masses that, combined with effective field theory and nuclear many-body studies, will provide controlled theoretical inputs to experimental searches of $0\nu\beta\beta$ decay.

hep-lat