相关论文: Two-step nuclear reactions: The Surrogate Method, …

Bayesian inverse modeling is important for a better understanding of hydrological processes. However, this approach can be computationally demanding, as it usually requires a large number of model evaluations. To address this issue, one can…

We present new results based on an improved version of the Glauber model, used to describe the nuclear absorption of J/psi in reactions between nuclei at high energy. The excitation of the colour degrees of freedom of nucleons, due to…

The nuclear deformation and neutron-transfer process have been identified as playing a major role in the magnitude of the sub-barrier fusion (capture) cross sections. There are a several experimental evidences which confirm the importance…

Coulomb dissociation is an especially simple and important reaction mechanism. Since the perturbation due to the electric field of the (target) nucleus is exactly known, firm conclusions can be drawn from such measurements. Electromagnetic…

The LIT method has allowed ab initio calculations of electroweak cross sections in light nuclear systems. This review presents a description of the method from both a general and a more technical point of view, as well as a summary of the…

We discuss the building blocks for a consistent inclusion of chiral three-nucleon (3N) interactions into ab initio nuclear structure calculations beyond the lower p-shell. We highlight important technical developments, such as the…

Hadronic cross sections are important ingredients in many of the ongoing research methods in high-energy nuclear physics, and it is always important to measure and/or calculate the probabilities of different types of reactions. In heavy-ion…

The neutron capture cross section of the unstable nucleus $^{186}$Re is studied by investigating the inverse photodisintegration reaction $^{187}$Re($\gamma$,n). The special interest of the {\it s}-process branching point $^{186}$Re is…

Continuous Time Echo State Networks (CTESNs) are a promising yet under-explored surrogate modeling technique for dynamical systems, particularly those governed by stiff Ordinary Differential Equations (ODEs). A key determinant of the…

Neural networks are powerful surrogates for numerous forward processes. The inversion of such surrogates is extremely valuable in science and engineering. The most important property of a successful neural inverse method is the performance…

Leveraging the kernel trick in both the input and output spaces, surrogate kernel methods are a flexible and theoretically grounded solution to structured output prediction. If they provide state-of-the-art performance on complex data sets…

Time-dependent Hartree-Fock (TDHF) theory has achieved a remarkable success in describing and understanding nuclear many-body dynamics from nucleons' degrees of freedom. We here report our investigation of multinucleon transfer (MNT)…

Markov chain Monte Carlo methods for exponential family models with intractable normalizing constant, such as the exchange algorithm, require simulations of the sufficient statistics at every iteration of the Markov chain, which often…

Heterogeneity and uncertainty in a composite microstructure lead to either computational bottlenecks if modeled rigorously or to solution inaccuracies in the stress field and failure predictions if approximated. Although methods suitable…

Transfer reactions have provided exciting opportunities to study the structure of exotic nuclei and are often used to inform studies relating to nucleosynthesis and applications. In order to benefit from these reactions and their…

Optimization plays an important role in chemical engineering, impacting cost-effectiveness, resource utilization, product quality, and process sustainability metrics. This chapter broadly focuses on data-driven optimization, particularly,…

The photon spectrum in macrocoherent atomic de-excitation via radiative emission of neutrino pairs (RENP) has been proposed as a sensitive probe of the neutrino mass spectrum, capable of competing with conventional neutrino experiments. In…

For stochastic process models, parameter inference is often severely bottlenecked by computationally expensive likelihood functions. Simulation-based inference (SBI) bypasses this restriction by constructing amortized surrogate likelihoods,…

An important ingredient for applications of nuclear physics to e.g. astrophysics or nuclear energy are the cross sections for reactions of neutrons with rare isotopes. Since direct measurements are often not possible, indirect methods like…

Theoretical models of the (d,p) reaction are exploited for both nuclear astrophysics and spectroscopic studies in nuclear physics. Usually, these reaction models use local optical model potentials to describe the nucleon- and…