Nucleon-nucleon scattering process in Lattice Chiral Effective Field Theory approach up to next-to-next-to-next-to-leading order

We carry out a comprehensive analysis of the neutron-proton interaction up to the third order in the scheme of chiral effective field theory on the lattice. The complete two-pion exchange potential is taken into account to allow for a variation of the lattice spacing. We analyze the perturbative as well as the non-perturbative inclusion of the higher-order corrections and present a thorough analysis of the theoretical uncertainties. In addition, a first attempt is made to include chiral contributions at the fourth order as well as the electromagnetic effects relevant for proton-proton scattering. For that, we include all fourth order local four-nucleon interactions and the dominant corrections to the two-pion exchanges. As expected, the higher order chiral corrections give an improved description for the scattering of two nucleons. This work should be extended by performing an uncertainty analysis and investigating the lattice spacing dependence in the future. We further scrutinize nuclei with even and equal numbers of protons and neutrons using nuclear lattice effective field theory, based upon a set of highly improved (smeared) leading order interactions. We present numerical evidence that reveals a first-order transition at zero temperature from a Bose-condensed gas of alpha particles to the nuclear liquid, which is regulated by the strength and locality of the nucleon-nucleon interactions

Neutron-proton scattering at next-to-next-to-leading order in Nuclear Lattice Effective Field Theory

We present a systematic study of neutron-proton scattering in Nuclear Lattice Effective Field Theory (NLEFT), in terms of the computationally efficient radial Hamiltonian method. Our leading-order (LO) interaction consists of smeared, local contact terms and static one-pion exchange. We show results for a fully non-perturbative analysis up to next-to-next-to-leading order (NNLO), followed by a perturbative treatment of contributions beyond LO. The latter analysis anticipates practical Monte Carlo simulations of heavier nuclei. We explore how our results depend on the lattice spacing a, and estimate sources of uncertainty in the determination of the low-energy constants of the next-to-leading-order (NLO) two-nucleon force. We give results for lattice spacings ranging from a = 1.97 fm down to a = 0.98 fm, and discuss the effects of lattice artifacts on the scattering observables. At a = 0.98 fm, lattice artifacts appear small, and our NNLO results agree well with the Nijmegen partial-wave analysis for S-wave and P-wave channels. We expect the peripheral partial waves to be equally well described once the lattice momenta in the pion-nucleon coupling are taken to coincide with the continuum dispersion relation, and higher-order (N3LO) contributions are included. We stress that for center-of-mass momenta below 100 MeV, the physics of the two-nucleon system is independent of the lattice spacing.Comment: 22 pages, 8 figure

Nuclear binding near a quantum phase transition

How do protons and neutrons bind to form nuclei? This is the central question of ab initio nuclear structure theory. While the answer may seem as simple as the fact that nuclear forces are attractive, the full story is more complex and interesting. In this work we present numerical evidence from ab initio lattice simulations showing that nature is near a quantum phase transition, a zero-temperature transition driven by quantum fluctuations. Using lattice effective field theory, we perform Monte Carlo simulations for systems with up to twenty nucleons. For even and equal numbers of protons and neutrons, we discover a first-order transition at zero temperature from a Bose-condensed gas of alpha particles (4He nuclei) to a nuclear liquid. Whether one has an alpha-particle gas or nuclear liquid is determined by the strength of the alpha-alpha interactions, and we show that the alpha-alpha interactions depend on the strength and locality of the nucleon-nucleon interactions. This insight should be useful in improving calculations of nuclear structure and important astrophysical reactions involving alpha capture on nuclei. Our findings also provide a tool to probe the structure of alpha cluster states such as the Hoyle state responsible for the production of carbon in red giant stars and point to a connection between nuclear states and the universal physics of bosons at large scattering length.Comment: Published version to appear in Physical Review Letters. Main: 5 pages, 3 figures. Supplemental material: 13 pages, 6 figure

DAFNet: A dual attention-guided fuzzy network for cardiac MRI segmentation

Background: In clinical diagnostics, magnetic resonance imaging (MRI) technology plays a crucial role in the recognition of cardiac regions, serving as a pivotal tool to assist physicians in diagnosing cardiac diseases. Despite the notable success of convolutional neural networks (CNNs) in cardiac MRI segmentation, it remains a challenge to use existing CNNs-based methods to deal with fuzzy information in cardiac MRI. Therefore, we proposed a novel network architecture named DAFNet to comprehensively address these challenges. Methods: The proposed method was used to design a fuzzy convolutional module, which could improve the feature extraction performance of the network by utilizing fuzzy information that was easily ignored in medical images while retaining the advantage of attention mechanism. Then, a multi-scale feature refinement structure was designed in the decoder portion to solve the problem that the decoder structure of the existing network had poor results in obtaining the final segmentation mask. This structure further improved the performance of the network by aggregating segmentation results from multi-scale feature maps. Additionally, we introduced the dynamic convolution theory, which could further increase the pixel segmentation accuracy of the network. Result: The effectiveness of DAFNet was extensively validated for three datasets. The results demonstrated that the proposed method achieved DSC metrics of 0.942 and 0.885, and HD metricd of 2.50mm and 3.79mm on the first and second dataset, respectively. The recognition accuracy of left ventricular end-diastolic diameter recognition on the third dataset was 98.42%. Conclusion: Compared with the existing CNNs-based methods, the DAFNet achieved state-of-the-art segmentation performance and verified its effectiveness in clinical diagnosis