9:30-10:30: Toky Andriamanalina

Title: Untangling 3-periodic entanglements of filaments and nets

Abstract: Entanglements of curves and nets can used to describe various biological and chemical structures, such as coordination polymers, liquid crystals, or DNA origami crystals. We recently developed new diagrammatic descriptions of 3-periodic entanglements. These new diagrams are drawn out of a projection along one axis of a unit cell of a 3-periodic structure. By using these diagrams, we define the notion of untangling number for 3-periodic structures, which is a measure of complexity of the entanglement.
Thanks to this, it is now possible to characterise the least tangled structures that we call ground states, and in particular we show that the rod packings are the generic ground states of entanglements of curves.

10:30-11:00: coffee break

11:00 - 12:00: Stephen Hyde

Title: Tangles... and untangles

Abstract: Knots, braids, links, self-entangled nets, multiple catenated infinite nets... are examples of what we call, simply, “tangles”. They are relevant to molecular-scale (bio)materials, from duplexed ssRNA to metal-organic frameworks.

We are interested in understanding:
1.Which tangles are “simple”?
2.How tangled is a tangle!?

Our tangle toolkit is a simple one: we assemble helices into networks, allowing a broad spectrum of tangles to be built, from knots to tangled nets. Interesting “simple” tangles are entanglements of the edges of Platonic polyhedra [1] and entangled 2-periodic nets [2].
A proposed answer to point 2. above will be discussed. if there is time.
The ideas are at present largely unpublished, and being working into a book to be published, we hope, in late 2025 [3].

13:00 - 14:00: Myfanwy Evans

Title: Can solvents tie knots? Helical folds of biopolymers in liquid environments.

Abstract: Using a simulation technique based on the morphometric approach to solvation, we performed computer experiments which fold a short open flexible tube, modelling a biopolymer in aqueous environments, according to the interaction of the tube with the solvent alone. We find an array of helical geometries that self-assemble depending on the solvent conditions, including symmetric double helices where the strand folds back on itself and overhand knot motifs. Interestingly these shapes—in all their variety—are energetically favoured over the optimal helix. By differentiating the role of solvation in self–assembly our study helps illuminate the energetic background scenery in which all soluble biomolecules live.

This event is organized with the Interdisciplinary Math Study Group.

The equation of state and the internal composition of a neutron star are still unanswered questions in astrophysics. To constrain the different composition scenarios inside neutron stars, we rely on pulsars observations and gravitational waves detections. This seminar shows different applications of supervised/unsupervised machine learning models in neutron stars physics, such as: i) extract the equation of state; ii) infer the proton fraction; iii) detect the possible existence of a second branch in the mass-radius diagram; and iv) detect the presence of hyperons.

Márcio Ferreira is a researcher at the Center for Physics at the University of Coimbra, Portugal, focusing on the application of machine learning to astrophysics and materials science. His work utilizes generative and descriptive models to address key questions in these fields. With a PhD in high energy physics and a Master’s in quantitative methods for finance, Márcio also merges his expertise in physics with an interest in financial market dynamics.​

Nuclear clustering is one of the unique phenomena in the nucleon many-body system. Historically, alpha formation has been known since the very early years of the nuclear physics, in the light and heavy mass regions. The former is known as the alpha clustering and its threshold rule, which was introduced by the Ikeda diagram in 1968. The latter has been known since the beginning of the nuclear physics as the alpha decay phenomena; the formation of alpha particles and their tunneling through the Coulomb barrier.
Recently, the alpha clustering has been experimentally confirmed in the medium mass nuclei, 112-124Sn (Tin isotopes), using the alpha knockout reaction. Triggered by the experimental observation, the alpha knockout reaction is used as a reaction probe for the alpha clustering phenomena. In this talk, I will give an overview of the clustering phenomena and its reaction observables, in particular I will introduce the idea that the alpha knockout reaction can be a probe for the alpha formation on the alpha decay nuclei. In general, this idea can be applied to probe the particle trapped in the potential resonance.

Inverse problems are widely studied in various scientific fields, including mathematics, physics, and medical imaging (such as CT and MRI reconstructions). In this talk, I will present a novel method for solving inverse problems using the diffusion model, with an application to CT reconstruction. The diffusion model, which is a core component of recent image-generative AI, such as Stable Diffusion and DALL-E3, is capable of producing high-quality images with rich diversity. The imaging process in CT (i.e., CT reconstruction) is mathematically an inverse problem. When the radiation dose is reduced to minimize a patient's exposure, image quality deteriorates due to information loss, making the CT reconstruction problem highly ill-posed. In the proposed method, the diffusion model, trained with a large dataset of high-quality images, serves as a regularization technique to address the ill-posedness. Consequently, the proposed method reconstructs high-quality images from sparse (low-dose) CT data while preserving the patient's anatomical structures. We also compare the performance of the proposed method with those of other existing methods, and find that the proposed method outperforms the existing methods in terms of quantitative indices.

14:45-15:00 Teatime discussion
15:00-16:00 Talk by Dr. Ryusuke Hamazaki (RIKEN Hakubi Team Leader, Nonequilibrium Quantum Statistical Mechanics RIKEN Hakubi Research Team)
16:15-17:15 Talk by Dr. Teruaki Enoto (Associate Professor, Department of Physics, Division of Physics and Astronomy, Graduate School of Science, Kyoto University)
17:15-18:00 Discussion

The Standard Model of Particle Physics, encapsulating the vast majority of our understanding of the fundamental nature of our Universe, is at its core a gauge theory. Much of the richness of its phenomenology can be traced back to the complicated interplay of its various gauged interactions. While massive theoretical and algorithmic developments in classical computing have allowed us to probe many of these aspects, there remain a plethora of open questions that do not seem amenable to these methods. With a fundamentally different computational strategy, quantum computers hold the potential to address these open questions. However, a long road lies ahead of us before this potential may be realized. In this talk, I discuss a key step on this journey: constructing lattice gauge Hamiltonians that can be efficiently simulated on digital quantum devices. In particular, I focus on recent work that develops a fully gauge fixed Hamiltonian for SU(2) without fermions. Not only is this formulation well-suited for "close to continuum" simulations, it is also significantly less non-local than might be initially expected.

When simulating fermionic quantum systems, non-perturbative Monte Carlo techniques are often the most efficient approach known to date. However, beyond half filling they suffer from the so-called sign problem, i.e. negative "probabilities", so that stochastic sampling becomes infeasible. Recently, considerable progress has been made in alleviating the sign problem by deforming the integration contour of the path integral into the complex plane and applying machine learning to find near-optimal alternative contours. In this talk, I am going to present a particularly successful architecture, based on complex-valued affine coupling layers. Furthermore, I will demonstrate how insight gained from the trained network can be used for simpler analytic approaches.

The quantisation of gravity is widely believed to result in gravitons - particles of discrete energy that form gravitational waves. But their detection has so far been considered impossible. Here we show that signatures of single gravitons can be observed in laboratory experiments. We show that stimulated and spontaneous single graviton processes can become relevant for massive quantum acoustic resonators and that stimulated absorption can be resolved through optomechanical read-out of single phonons of a multi-mode bar resonator. We analyse the feasibility of observing a signal from the inspiral, merger and post-merger phase of a compact binary inspiral. Our results show that single graviton signatures are within reach of experiments. In analogy to the discovery of the photoelectric effect for photons, such signatures can provide the first experimental evidence of the quantisation of gravity.

[1] G. Tobar, S. K. Manikandan, T. Beitel, and I. Pikovski, Nature Communications 15, 7229.
[2] G. Tobar, Igor Pikovski ,Michael E. Tobar, arXiv:2406.16898 (2024).

Emergence of space-time is a key concept in matrix models as a nonperturbative formulation of string theory. In this lecture, starting with a brief introduction to nonperturbative effects in string theory, I will review various aspects of emergence of space-time in matrix models. The topics I discuss include dynamical triangulation, double scaling limit, eigenvalue instanton, large-N reduction, T-duality for D-brane effective theories (orbifolding), noncommutative geometry and covariant derivative interpretation. Finally, I will introduce the type IIB matrix model.

(This is the 7th Intensive Lectures by Quantum Gravity Gatherings in iTHEMS. )

Program
December 17
10.15~10.30 Registration and Coffee
10.30~12.00 Lecture 1
12.00~13.30 Lunch
13.30~15.00 Lecture 2
15.00~16.00 Coffee break
16.00~17.00 Lecture 3
17.30~19.30 Banquet

December 18
10.15~11.45 Lecture 4
11.45~13.30 Lunch
13.30~15.00 Lecture 5
15.00~16.00 Coffee break
16.00~17.00 Lecture 6

December 19
10.15~11.45 Lecture 7
11.45~13.30 Lunch
13.30~15.00 Lecture 8
15.00~16.00 Coffee break
16.00~17.00 Lecture 9

Normalizing Flows (NFs) are a class of deep generative models that have recently been proposed as efficient samplers for Lattice Field Theory. Although NFs have demonstrated impressive performance in toy models, their scalability to larger lattice volumes remains a significant challenge, limiting their application to state-of-the-art problems. A promising approach to overcoming these scaling limitations involves combining NFs with non-equilibrium Markov Chain Monte Carlo (NEMCMC) algorithms, resulting in Stochastic Normalizing Flows (SNFs). SNFs harness the scalability of MCMC samplers while preserving the expressiveness of NFs. In this seminar, I will introduce the concepts of NEMCMC and NFs, demonstrate their combination into SNFs, and outline their connections with non-equilibrium thermodynamics. I will conclude by discussing key aspects of SNFs through their application to Effective String Theory, SU(3) gauge theory, and conformal field theory.

Neutron stars - the densest stars in the Universe - cool down mainly by loss of neutrinos, emitted from the stars' interior due to particle reactions. By comparing cooling models with observed surface temperature or luminosity, one can probe the properties of high-density matter, such as what kind of particles and states exist inside neutron stars. In this presentation, I will first review cooling theory, focusing on the neutrino cooling processes. In particular, we focus on the equation of state (EOS) uncertainties, which significantly affect cooling curves. We discuss aspects such as the effect of including hyperons in our EOS. Using the updated cooling code, C-HERES, we calculate cooling curves with different EOS. Finally, we present the future prospects for this study.

Research on planet formation involves various approaches, including explorations of small solar system bodies, observations of protoplanetary disks, dust experiments, simulations, and theoretical studies. One of the primary objectives in this field is to develop a comprehensive theory that explains how kilometer-sized planetesimals form from micrometer-sized dust grains, drawing upon findings from these diverse research methods.

This workshop will focus on the concept of pebbles, which play a crucial role in the planet formation process. Pebbles — typically defined as solids ranging from millimeter to centimeter in size — are intermediate building blocks in planet formation, though their definition varies depending on the context. Assuming pebbles has led to theoretical advances in mechanisms such as streaming instability and pebble accretion, which promote the formation and growth of planetesimals. Additionally, pebbles have been linked to barriers against dust growth, such as the bouncing barrier. Furthermore, observations of protoplanetary disks have revealed the size distribution and porosity of solids, while the strength and thermal conductivity of comets obtained by the Rosetta mission suggest the accumulation of pebbles due to disk instabilities. However, inconsistencies have been pointed out between pebble formation and theories of dust growth.

This workshop aims to revisit and refine our understanding of solid materials implicated in planet formation, particularly in light of findings from solar system explorations and protoplanetary disk observations. We aim to reevaluate the definition and role of pebbles in the broader context of planet formation, with a special focus on the current challenges and open questions in the field. The workshop will include discussions of experiments and simulations of dust growth and collisions, and planetesimal formation mechanisms such as streaming instability. The workshop features keynote talks from the perspectives of explorations, observations, experiments, simulations, and theories, and we also call for presentations on related topics.

The density functional theory (DFT) is one of the powerful methods to solve quantum many-body problems, which, in principle, gives the exact energy and density of the ground state. The accuracy of DFT is, in practice, determined by the accuracy of an energy density functional (EDF) since the exact EDF is still unknown. Currently, DFT has been used in many communities, including nuclear physics, quantum chemistry, and condensed matter physics, while the fundamental study of DFT, such as the first principle derivations of an accurate EDF and methods to calculate many observables from obtained densities and excited states, is still ongoing. However, there has been little opportunity to have interdisciplinary communication.

On December 2022, we had the first workshop on this series (DFT2022) at Yukawa Institute for Theoretical Physics, Kyoto University, and several interdisciplinary discussions and collaborations were started. On February 2024, we had the second workshop on this series (DFT2024) at RIKEN Kobe Campus, and more stimulated discussion occured. To keep and extend collaborations, we organize the third workshop. Since the third workshop, we extend the scope of the workshop to the development and application of DFT as well. In this workshop, the current status and issues of each discipline will be shared towards solving these problems by meeting together among researchers in mathematics, nuclear physics, quantum chemistry, and condensed matter physics.

This workshop mainly comprises lectures/seminars on cutting-edge topics and discussion, while sessions composed of contributed talks are also planned.