- A. Ekström (Nuclear interaction)
Title: Recent advances in chiral forces and uncertainty quantification for nuclear structure
Abstract: Describing nuclear phenomena across a wide range of energy scales from hundreds of MeV in binding energies to fractions of an MeV for low-lying excitations remains a long-standing challenge in nuclear physics. The ab initio method is a systematically improvable approach for quantitatively describing nuclei using the finest resolution scale possible while maximizing its predictive capabilities. In this talk, I will highlight recent advances in ab initio nuclear structure calculations, focusing on developments in chiral nuclear forces and methods for estimating uncertainties in theoretical predictions.
- K. Bennaceur (Nuclear Interaction)
Title: On the use of charge distributions to constrain effective interactions
Abstract: The key ingredient for mean-field calculations in nuclear structure is the effective interaction which models the strong force in the nuclear medium. Such interactions usually depend on a set of parameters fitted to properties nuclei and infinite nuclear matter. These interactions can suffer several limitations and problems. For example, since they are usually adjusted on properties of observed nuclei close to the valley of stability, their predictive power for exotic and super-heavy nuclei may be questionable. Furthermore, unphysical finite-size instabilities can sometimes appear when these interactions are used to calculate properties of nuclei which have not been considered to constrain their parameters. These instabilities can appear in various channels and therefore have scalar, vector, isoscalar or isovector characters. It was shown that the formalism of the linear response in infinite-nuclear matter can be used to avoid such instabilities for the construction of zero-range interaction (of Skyrme type). Although such a formalism was also developed for finite-range interactions (Gogny type), the calculations for the linear response are much more time-consuming and can hardly be incorporated in the procedure used to fit their parameters. I will discuss how the scalar-isovector instabilities are related to the distributions of protons and neutrons in nuclei and how, in turn, information on charge density distributions can be used to prevent these instabilities. Beside the avoidance of instabilities, information about the charge distribution may lead to a better balance between the different contributions to the binding energy of nuclei and their evolution with mass and asymmetry. I will show that the use of constraints on charge distributions from a set of chosen nuclei can be used to avoid the appearance of scalar-isovector instabilities and discuss how this could improve the predictive power of the mean-field calculations.
- T. Duguet (Nuclear structure)
Title: Review of ab initio calculations of atomic nuclei
Abstract: coming soon
- G. Potel (Nuclear reactions)
Title: Some recent trends in nuclear reaction theory for basic science and applications
Abstract: In recent times, it has become commonplace to mention the unification of structure and reaction nuclear theory as one of the hot topics in low-energy nuclear physics. This interest is, of course, not new, but some present circumstances might have made it more acute. First, the experimental access to very weakly bound or unbound nuclei has blurred the limits between structure and reaction theory. Second, the fast development of computational tools and resources has rendered scattering problems tractable with bound states techniques. We will also address some ideas in the path to another important unification: the theory of direct and compound nucleus reactions. This line of research is important in order to address important processes, such as capture reactions, involving nuclei away from the stability valley, where an unusually low level density calls for the description of a transition between the statistical and direct reaction regimes.
- D. Lacroix (Quantum computing)
Title: Quantum computing applied to nuclear physics
Abstract: Atomic nuclei are complex many-body systems with a number of constituents ranging from very few to several hundreds. Among the difficult aspects, nuclei are self-bound systems that require the treatment of a continuum of wave functions in the Hilbert space. The nuclear strong interaction is scarcely known and highly non-perturbative, with the onset of multi-body interaction beyond the usual interaction of particles two-by-two. Nuclear physics also belongs to problems that face the exponential growth of the Hilbert space when the number of constituents increases. For these reasons, the exact treatment of these systems on classical computers, starting from the interaction, is still restricted to a few percent of the nuclear chart. Quantum technologies and associated quantum algorithms appear in this context as disruptive technologies that might surpass the current limitations in the coming years. I have recently initiated a long-term project to explore using quantum computers and quantum information for nuclear physics and related many-body problems. Inspired by strategies used in classical computing, several novel approaches have been proposed to obtain the ground or low-lying states in many-body systems. A significant effort has been made to use the symmetry breaking/symmetry restoration method. Based on the use of projectors through phase estimation, quantum oracles, or classical shadow, the Quantum Variation After Variation was formulated. Several methods were proposed to access excited states, including the Quantum Krylov, Quantum equation of motion, or Quantum Generator Coordinate Method. After reviewing and illustrating these methods, the current status and future challenges in using quantum computers for atomic nuclei will be discussed.
- D. Regnier (Artificial Intelligence)
Title: Artificial intelligence for nuclear physics
Abstract: The last decade has put artificial intelligence in the spotlight both in science and in our daily life. This boom takes its origin from the wealth of recently designed machine learning algorithms such as generative adversarial networks (2014) or transformers (2017). An other important key to its success is its large accessibility through open source libraries such as TensorFlow and PyTorch steamed by the increasing power and availability of GPUs. A natural question in such a context is: Can we import techniques or ideas from the field of artificial intelligence to nuclear physics or the other way around ?In this talk I will survey the main applications of machine learning to nuclear experiments and theory. I will try to emphasize which of these techniques are mature for applications, proof of principle, or ideas for future explorations.
- S. Giuliani (Astrophysics and nuclear data)
Title: Nuclear properties for astrophysics: an overview
Abstract: Nuclear astrophysics aims at describing the nuclear properties occurring in and powering astrophysical objects, as well as the cosmic origin of chemical elements found in the Universe. During this talk, I will present some recent progress and future challenges in the field of nuclear data for astrophysics, with a particular focus on the nucleosynthesis of heavy elements.
- N. Schunck (Nuclear fission)
Title: Microscopic Theory of Nuclear Fission
Abstract: coming soon
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