Tootfinder

Determination of ground states of one-dimensional quantum systems using the cluster iTEBD method
Tao Yang, Rui Wang, Z. Y. Xie, Baigeng Wang
https://arxiv.org/abs/2508.21405 htt…

Determination of ground states of one-dimensional quantum systems using the cluster iTEBD method
Within the framework of imaginary-time evolution for matrix product states, we introduce a cluster version of the infinite time-evolving block decimation algorithm for simulating quantum many-body systems, addressing the computational accuracy challenges in strongly correlated physics. By redefining the wave-function ansatz to incorporate multiple physical degrees of freedom, we enhance the representation of entanglement, thereby improving the accuracy of the ground states. Utilizing the Trotte…

Precision measurement and modelling of the threshold-free 210Pb \beta spectrum
Shuo Zhang, Hao-Ran Liu, Xavier Mougeot, Paul-Antoine Hervieux, Tao Sun, Wen-Tao Wu, Robin Cantor, Jingkai Xia, Zhi Liu, Cheng Liang, Fu-You Fan, Le Zhang, Mingyu Ge, Xiao-Peng Zhou, Adrien Andoche
https://arxiv.org/abs/2509.26390

Precision measurement and modelling of the threshold-free 210Pb βspectrum
Beta decay is a fundamental process that governs nuclear stability and serves as a sensitive probe of the weak interaction and possible physics beyond the Standard Model of particle physics. However, precise measurements of complete βdecay spectra, particularly at low energies, remain experimentally and theoretically challenging. Here we report a high-precision, threshold-free measurement of the full βdecay spectrum of 210Pb to excited states of 210Bi, using a transition-edge sensor (TES)-bas…

Tensor Network Markov Chain Monte Carlo: Efficient Sampling of Three-Dimensional Spin Glasses and Beyond
Tao Chen, Jing Liu, Youjin Deng, Pan Zhang
https://arxiv.org/abs/2509.23945

Tensor Network Markov Chain Monte Carlo: Efficient Sampling of Three-Dimensional Spin Glasses and Beyond
Sampling the three-dimensional (3D) spin glass -- i.e., generating equilibrium configurations of a 3D lattice with quenched random couplings -- is widely regarded as one of the central and long-standing open problems in statistical physics. The rugged energy landscape, pronounced critical slowing down, and intrinsic ergodicity breaking render standard Monte Carlo methods severely inefficient, particularly for large systems at low temperatures. In this work, we introduce the Tensor Network Marko…

On the Viability of Weak Energy Condition Violation in Parity-Violating Electrodynamics
Tao Huang
https://arxiv.org/abs/2509.18188 https://arxiv.org/pdf/25…

Tetratomic states of microwave dressed and associated ultracold 23Na40K molecules
Zhengyu Gu, Xuansheng Zhou, Wei Chen, Wei Han, Fulin Deng, Tao Shi, Pengjun Wang, Jing Zhang
https://arxiv.org/abs/2509.23634

Tetratomic states of microwave dressed and associated ultracold 23Na40K molecules
Ultracold diatomic molecules have achieved significant breakthroughs in recent years, enabling the exploration of quantum chemistry, precision measurements, and strongly correlated many-body physics. Extending ultracold molecular complexity to polyatomic molecules, such as triatomic and tetratomic molecules, has attracted considerable interest. However, the realization of ultracold polyatomic molecules remains technically challenging due to their complex energy-level structures. While only a fe…

Unveiling the landscape of Mottness and its proximity to superconductivity in 4Hb-TaS$_2$
Ping Wu, Zhuying Wang, Yunmei Zhang, Ziyan Chen, Shuikang Yu, Wanru Ma, Min Shan, Zeyu Liang, Xiaoyu Wei, Junzhe Wang, Wanlin Cheng, Zuowei Liang, Xuechen Zhang, Tao Wu, Yoshinari Okada, Kun Jiang, Zhenyu Wang, Xianhui Chen
https://arxiv.org/abs/2508.…

Unveiling the landscape of Mottness and its proximity to superconductivity in 4Hb-TaS$_2$
Mott physics is at the root of a plethora of many-body quantum phenomena in quantum materials. Recently, the stacked or twisted structures of van der Waals (vdW) materials have emerged as a unique platform for realizing exotic correlated states in the vicinity of the Mott transition. However, the definitive feature of Mottness and how it rules the low-energy electronic state remain elusive and experimentally inaccessible in many interesting regimes. Here, we quantitatively describe a filling-co…

HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?
Fangchen Yu, Haiyuan Wan, Qianjia Cheng, Yuchen Zhang, Jiacheng Chen, Fujun Han, Yulun Wu, Junchi Yao, Ruilizhen Hu, Ning Ding, Yu Cheng, Tao Chen, Lei Bai, Dongzhan Zhou, Yun Luo, Ganqu Cui, Peng Ye
https://arxiv.org/abs/2509.07894

HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?
Recently, the physical capabilities of (M)LLMs have garnered increasing attention. However, existing benchmarks for physics suffer from two major gaps: they neither provide systematic and up-to-date coverage of real-world physics competitions such as physics Olympiads, nor enable direct performance comparison with humans. To bridge these gaps, we present HiPhO, the first benchmark dedicated to high school physics Olympiads with human-aligned evaluation. Specifically, HiPhO highlights three key …

Bose-Einstein condensate of ultracold sodium-rubidium molecules with tunable dipolar interactions
Zhaopeng Shi, Zerong Huang, Fulin Deng, Wei-Jian Jin, Su Yi, Tao Shi, Dajun Wang
https://arxiv.org/abs/2508.20518

Bose-Einstein condensate of ultracold sodium-rubidium molecules with tunable dipolar interactions
Realizing Bose-Einstein condensation of polar molecules is a long-standing challenge in ultracold physics and quantum science due to near-universal two-body collisional losses. Here, we report the production of a Bose-Einstein condensate of ground-state sodium-rubidium molecules via high efficiency evaporative cooling, with losses suppressed using the dual microwave shielding technique. The ability to tune the dipolar interaction between these ultracold polar molecules is crucial for producing …

MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
Yuchen Zhu, Wei Guo, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, Molei Tao
https://arxiv.org/abs/2508.10684 h…

MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
We study the problem of learning a neural sampler to generate samples from discrete state spaces where the target probability mass function $π\propto\mathrm{e}^{-U}$ is known up to a normalizing constant, which is an important task in fields such as statistical physics, machine learning, combinatorial optimization, etc. To better address this challenging task when the state space has a large cardinality and the distribution is multi-modal, we propose $\textbf{M}$asked $\textbf{D}$iffusion $\te…

BatchTNMC: Efficient sampling of two-dimensional spin glasses using tensor network Monte Carlo
Tao Chen, Jingtong Zhang, Jing Liu, Youjin Deng, Pan Zhang
https://arxiv.org/abs/2509.19006

BatchTNMC: Efficient sampling of two-dimensional spin glasses using tensor network Monte Carlo
Efficient sampling of two-dimensional statistical physics systems remains a central challenge in computational statistical physics. Traditional Markov chain Monte Carlo (MCMC) methods, including cluster algorithms, provide only partial solutions, as their efficiency collapses for large systems in the presence of frustration and quenched disorder. The recently proposed Tensor Network Monte Carlo (TNMC) method offers a promising alternative, yet its original implementation suffers from inefficien…

Conceptual Design Report of Super Tau-Charm Facility: The Accelerator
Jiancong Bao, Anton Bogomyagkov, Zexin Cao, Mingxuan Chang, Fangzhou Chen, Guanghua Chen, Qi Chen, Qushan Chen, Zhi Chen, Kuanjun Fan, Hailiang Gong, Duan Gu, Hao Guo, Tengjun Guo, Chongchao He, Tianlong He, Kaiwen Hou, Hao Hu, Tongning Hu, Xiaocheng Hu, Dazhang Huang, Pengwei Huang, Ruixuan Huang, Zhicheng Huang, Hangzhou Li, Renkai Li, Sangya Li, Weiwei Li, Xuan Li, Xunfeng Li, Yu Liang, Chao Liu, Tao Liu, Xiaoyu L…

Conceptual Design Report of Super Tau-Charm Facility: The Accelerator
Electron-positron colliders operating in the GeV region of center-of-mass energies or the Tau-Charm energy region, have been proven to enable competitive frontier research, due to its several unique features. With the progress of high energy physics in the last two decades, a new-generation Tau-Charm factory, Super Tau Charm Facility (STCF) has been actively promoting by the particle physics community in China. STCF holds great potential to address fundamental questions such as the essence of c…

SSBE-PINN: A Sobolev Boundary Scheme Boosting Stability and Accuracy in Elliptic/Parabolic PDE Learning
Qixuan Zhou, Chuqi Chen, Tao Luo, Yang Xiang
https://arxiv.org/abs/2508.10322

SSBE-PINN: A Sobolev Boundary Scheme Boosting Stability and Accuracy in Elliptic/Parabolic PDE Learning
Physics-Informed Neural Networks (PINNs) have emerged as a powerful framework for solving partial differential equations (PDEs), yet they often fail to achieve accurate convergence in the H1 norm, especially in the presence of boundary approximation errors. In this work, we propose a novel method called Sobolev-Stable Boundary Enforcement (SSBE), which redefines the boundary loss using Sobolev norms to incorporate boundary regularity directly into the training process. We provide rigorous theor…

Modeling Dynamic Gas-Liquid Interfaces in Underwater Explosions Using Interval-Constrained Physics-Informed Neural Networks
Fulin Xing, Junjie Li, Ze Tao, Fujun Liu, Yong Tan
https://arxiv.org/abs/2508.07633

Modeling Dynamic Gas-Liquid Interfaces in Underwater Explosions Using Interval-Constrained Physics-Informed Neural Networks
Underwater explosion modeling faces a critical challenge of simultaneously resolving shock waves and gas-liquid interfaces, as traditional methods struggle to balance accuracy and computational efficiency. To address this, we develop a physics-informed neural network (PINN) framework featuring a dual-network architecture, that one network learns flow-field variables (pressure, density, velocity) from simulation data, while another network tracks the gas-liquid interface despite lacking direct n…

Anomalous narrow-band correlation in a natural superconducting heterostructure
Xiupeng Sun, Zhiyuan Wei, Min Shan, Shuting Peng, Yang Luo, Jianchang Shen, Linwei Huai, Yu Miao, Zhipeng Ou, Mehmet Onbasli, Zhenyu Wang, Tao Wu, Junfeng He, Xianhui Chen
https://arxiv.org/abs/2508.18099

Anomalous narrow-band correlation in a natural superconducting heterostructure
A new frontier in condensed matter physics is to stack atomically thin layered-materials with different properties and create intriguing phenomena which do not exist in any of the constituent layers. Transition metal dichalcogenide 4Hb-TaS$_2$, with an alternating stacking of a spin liquid candidate 1T-TaS$_2$ and a superconductor 1H-TaS$_2$, is a natural heterostructure for such a purpose. Recently, rare phenomena are indeed observed, including chiral superconductivity, two-component nematic s…

Replaced article(s) found for hep-ph. https://arxiv.org/list/hep-ph/new
[2/2]:
- Revisiting the $\Lambda_c^ \to \Lambda \eta \pi^ $ and the roles of intermediate resonances
En Wang, Wen-Tao Lyu, Man-Yu Duan, Chu-Wen Xiao, Dian-Yong Chen, Ju-Jun Xie, Eulogio Oset

Harnessing modal fields retrieved from speckle for multi-dimensional metrology
Qingbo Liu, Zhongyang Xu, Guangkui Tao, Xiuyuan Sun, Min Xue, Weihao Yuan, Shilong Pan
https://arxiv.org/abs/2509.03976

Harnessing modal fields retrieved from speckle for multi-dimensional metrology
Although speckle is a powerful tool for high-precision metrology, large datasets and cumbersome training are always required to learn from the encoded speckle patterns, which is unfavorable for rapid deployment and multi-dimensional metrology. To enable high accuracy and fast training, physics-informed machine learning enforces physical laws to address high-dimensional problems. Here, we harness the modal fields in a few-mode fiber, which follow the law of beam propagation, to enable high-accur…

Quantum criticality and nonequilibrium dynamics on a Lieb lattice of Rydberg atoms
Mark R. Hirsbrunner, Milan Kornja\v{c}a, Rhine Samajdar, Siva Darbha, Majd Hamdan, Jan Balewski, Ermal Rrapaj, Sheng-Tao Wang, Daan Camps, Fangli Liu, Pedro L. S. Lopes, Katherine Klymko
https://arxiv.org/abs/2508.05737

Quantum criticality and nonequilibrium dynamics on a Lieb lattice of Rydberg atoms
Neutral-atom quantum simulators offer a promising approach to the exploration of strongly interacting many-body systems, with applications spanning condensed matter, statistical mechanics, and high-energy physics. Through a combination of quantum experiments, numerical calculations, and analytical methods, we demonstrate a rich set of phenomena accessible on such quantum simulators by studying an array of Rydberg atoms placed on the Lieb lattice. First, we map out the ground states and phase di…