Seminar

Quantum Information in Scattering: From Amplitude Poles to Entanglement Features

December 4 (Thu) 14:00 - 16:00, 2025

Chon Man Sou (Postdoctoral Researcher, Department of Physics, Tsinghua University, Beijing, China)

Probing quantum entanglement in high-energy collisions has recently become a rapidly growing direction in particle physics, aiming to measure quantum correlations at the highest energy scales accessible to humans. A key question is how such entanglement relies on the analytic structure of scattering amplitudes. In this talk, I will show that the pole structure, associated with intermediate heavy particles, leads to distinctive entanglement features. When a heavy particle mediates inelastic scatterings with three or more final particles, the entanglement entropy between its decay products and the rest exhibits a universal dip as the energy increases, reflecting the limited information flow through on-shell heavy particles and signaling entanglement suppression in the heavy-particle-dominated regime. This reveals entanglement structures beyond the usual “area-law” behavior of 2-to-2 processes. Finally, I will comment on possible ways to probe these features experimentally through analyses of final-state phase-space distributions. This talk is based on JHEP 10 (2025) 003 [arXiv: 2507.03555].

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

Biological Background of Duplicated Sequence Evolution: A Focus on Gene Conversion

December 4 (Thu) 13:00 - 14:00, 2025

Kenji Okubo (Special Postdoctoral Researcher, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Duplicated sequences—such as gene families, tandem arrays, and segmental duplications—are common in many genomes. Their evolution is shaped by several biological processes, including mutation, recombination, duplication, deletion, and gene conversion. Among these, gene conversion is especially important because it can make nearby copies more similar, while leaving distant copies free to diverge. In this seminar, I will give a broad and accessible overview of the biological background related to duplicated sequences, with a particular focus on what is known about gene conversion. I will summarize well-established patterns such as its dependence on genomic distance, sequence similarity, and recombination context. These biological features are often studied separately, so organizing them in one place can help provide a clearer foundation. The goal of the talk is to outline the biological principles that motivate thinking about duplicated sequences in a more formal or quantitative way in the future. I will not discuss specific model details. Instead, this presentation will serve as background preparation for later theoretical work.

Venue: via Zoom / Seminar Room #359

Event Official Language: English

Quantum Computing Journal Club #1

December 2 (Tue) 10:00 - 12:00, 2025

Bring a recent paper on quantum computing for discussion. No need to prepare slides.

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

From phase reduction to hypergraphs: the higher-order dynamics of coupled phase oscillators

November 27 (Thu) 13:00 - 14:00, 2025

Riccardo Muolo (Special Postdoctoral Researcher, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Networks are powerful tools in the modeling of complex systems, but they do not always capture the right interactions when multiple units are involved simultaneously. Such many-body interactions are encoded by higher-order structures which can be thought as extensions of networks. Over the last years, higher-order networks have been the focus of great excitement, since this novel framework has enormous potential for applications. In this talk, I will give an overview of higher-order interactions and their effects on nonlinear dynamics. I will introduce the basics of dynamics on networks and its extension to the case of higher-order interactions. As examples of the effects on nonlinear dynamics, I will discuss the case of phase reduction for systems with higher-order interactions and show the effects on synchronization dynamics.

Venue: Seminar Room #359 / via Zoom

Event Official Language: English

Introduction to Game Theory #3

November 27 (Thu) 11:00 - 12:00, 2025

Yohsuke Murase (Team Director, Mathematical Social Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

An introductory lecture on game theory to promote potential interdisciplinary collaborations. No prior knowledge is required — the lecture is intended for non-experts. We will cover the fundamental concepts to help you build an intuitive understanding of how game theory analyzes strategic interactions. After briefly reviewing the previous lectures, we will talk about repeated games, where players are engaged in games repeatedly.

Venue: via Zoom (Main Venue) / Seminar Room #359

Event Official Language: English

Hamiltonian Learning and Dynamics Prediction via Machine Learning

November 26 (Wed) 15:00 - 16:00, 2025

Li Keren (Assistant Professor, College of Physics and Optoelectronic Engineering, Shenzhen University, China)

Accurate prediction of quantum Hamiltonian dynamics and identification of Hamiltonian parameters are crucial for advancements in quantum simulations, error correction, and control protocols. This talk introduces a machine learning model with dual capabilities: it can deduce time-dependent Hamiltonian parameters from observed changes in local observables within quantum many-body systems, and it can predict the evolution of these observables based on Hamiltonian parameters. The model’s validity was confirmed through theoretical simulations across various scenarios and further validated by two experiments. Initially, the model was applied to a Nuclear Magnetic Resonance quantum computer, where it accurately predicted the dynamics of local observables. The model was then tested on a superconducting quantum computer with initially unknown Hamiltonian parameters, successfully inferring them. We believe that machine learning techniques hold great promise for enhancing a wide range of quantum computing tasks, including parameter estimation, noise characterization, feedback control, and quantum control optimization.

Venue: via Zoom

Event Official Language: English

Adaptive navigation strategies in adversarial predator-prey contexts

November 20 (Thu) 13:00 - 14:00, 2025

Nozomi Nishiumi (Specially Appointed Associate Professor, Academic Assembly Institute of Science and Technology, Niigata University)

Animal navigation has long been a central topic in behavioral biology. In predator-prey systems, both predators and prey must navigate strategically - predators to capture prey and prey to reach safety - each evolving to outsmart the other through coevolution. To uncover the essence of these navigation strategies, I have investigated behavioral mechanisms across taxa. In bats, my collaborators and I found that they integrate multiple sensory and flight tactics to keep erratically flying moths within detection range. In pigeons, we discovered that individuals anticipating drone attacks adjust their positions toward the rear within the flock. I will also introduce an experimental framework that enables controlled interactions between real animals and virtual agents driven by reactive motion control, allowing quantitative tests of navigation efficiency. Through this seminar, I aim to highlight how studies of predator-prey navigation can bridge biology and engineering, providing insights into adaptive decision-making in dynamic environments.

Venue: Seminar Room #359, Seminar Room #359 / via Zoom

Event Official Language: English

Chiral anomaly in Hamiltonian lattice gauge theory

November 18 (Tue) 10:00 - 12:00, 2025

Arata Yamamoto (Senior Research Scientist, Quantum Mathematical Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

The 4th quantum computing gathering organized by Quantum Computing Study Group

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

Contribution of star-forming galaxies to the cosmic gamma-ray background

November 14 (Fri) 14:00 - 15:15, 2025

Junling Chen (Ph.D. Student, Graduate School of Mathematical Sciences, The University of Tokyo)

Fermi Gamma-Ray Space Telescope has measured the diffuse extragalactic gamma-ray background (EGB) radiation in the energy range of 100 MeV to 820 GeV. Several candidate γ -ray sources have been proposed as the candidate components of the unresolved EGB, including active galactic nuclei (AGNs), millisecond pulsars, dark matter annihilation, and star-forming galaxies (SFGs), but their quantitative contribution has not yet been precisely determined. In this talk, I will introduce our latest physical model describing the gamma-ray emission mechanism from SFGs, and our estimate of the contribution of SFGs based on careful calibration with gamma-ray luminosities of nearby galaxies and physical quantities (star formation rate, stellar mass, and size) of galaxies observed by high-redshift galaxy surveys.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

The Uchuu simulations data set: large-scale structures and galaxies - Tomoaki Ishiyama

November 13 (Thu) 14:00 - 15:30, 2025

Tomoaki Ishiyama (Associate Professor, Digital Transformation Enhancement Council, Chiba University)

I will introduce the Uchuu suite of large high-resolution cosmological N-body simulations. The largest simulation, named Uchuu, consists of 2.1 trillion dark matter particles in a box of side-length 2.0 Gpc/h, with particle mass of 3.27e8 Msun/h. The highest resolution simulation, Shin-Uchuu, consists of 262 billion particles in a box of side-length 140 Mpc/h, with particle mass of 8.97e5 Msun/h. Combining these simulations, we can follow the evolution of dark matter haloes and subhaloes spanning those hosting dwarf galaxies to massive galaxy clusters across an unprecedented volume from very high-z. We release N-body data (halo/subhalo catalogs and merger trees) and mock galaxy/AGN catalogs constructed using various models, which cover objects from z=0 to very high-z. These catalogs open a new window on understanding the large-scale structures and galaxy formation. In this presentation, I will also introduce results of cosmological simulations adopting a time-varying dark energy, conducted on the supercomputer Fugaku.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

DA Seminar: Machine learning for precipitation estimation and forecasting / Analysis of a Long-Lived Supercell: Life Cycle and Severe Weather Patterns in Northern Buenos Aires Province

November 13 (Thu) 10:30 - 12:00, 2025

Juan Ruiz (Visiting Scientist, Prediction Science Research Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
Luciano Vidal (Visiting Scientist, Prediction Science Research Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Title: Machine learning for precipitation estimation and forecasting Speaker: Dr. Juan Ruiz (University of Buenos Aires – CONICET) Abstract: Estimating and forecasting precipitation is essential for a wide range of human activities as well as for disaster prevention. In this talk we will discuss the application of deep neural networks to the estimation of precipitation with high time and spatial resolution, combining remote sensors and numerical weather predictions. The proposed models show that these information sources can be effectively combined to improve the accuracy of real-time precipitation estimates. Additionally, we will present the application of deep neural networks as a postprocessing tool for short-range deterministic and ensemble-based numerical weather predictions and for the quantification of their uncertainty. The performance of the machine-learning models in the quantification of the uncertainty is close to that achieved by the dynamical ensembles and can be even better in the presence of a model. Title: Analysis of a Long-Lived Supercell: Life Cycle and Severe Weather Patterns in Northern Buenos Aires Province Speaker: Dr. Luciano Vidal (National Meteorological Service, Argentina) Abstract: This work presents a detailed analysis of a long-lived convective supercell that affected the northern Buenos Aires province, Argentina, on March 19, 2024. The primary objective is to characterize its life cycle and associated severe weather patterns using an integrated multi-sensor approach. This methodology combines data from satellite imagery with documentation of surface damage caused by large hail and intense winds. The storm exhibited a remarkable longevity, traveling approximately 400 km over 5.5 hours and impacting a total of 11 municipalities before its dissipation. Throughout its trajectory, the supercell generated significant damage due to large hail and severe wind gusts that, in some areas, exceeded 150 km/h. Furthermore, the storm ultimately affected the Sarandí-Santo Domingo basin (the pilot basin of the Argentine-Japanese SATREPS/PREVENIR project) by generating flash floods. The results of this analysis provide crucial information for the improvement of forecasting and early warning systems for severe weather events in the region.

Venue: Hybrid Format (RIKEN R-CCS room 107 and Zoom)

Event Official Language: English

Topological physics and its interdisciplinary influence

November 12 (Wed) 13:00 - 14:00, 2025

Tomoki Ozawa (Professor, Advanced Institute for Materials Research (AIMR), Tohoku University)

Topological insulators are materials which do not conduct current inside but do conduct at the surface or the edge. The name "topological" comes from the fact that the "shape" of the wavefunction of electrons in topological insulators show non-trivial twist, which can be mathematically characterized by the language of topology. Alongside the development of the study of topological insulators in solids, analogous phenomena were found to exist also in other systems such as photonics, mechanics, geophysics, and active matter. In this seminar, I discuss how the underlying concept of "topology of states" can have a broad impact applicable to various areas in physics, with some emphasis on my own contribution to the field. I aim to structure the first half of my seminar to be accessible to those outside physics, and latter half to be more specialized, covering cutting-edge results.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

A genealogy-based framework to infer the demographic history, genetic structure, and phenotype association

November 11 (Tue) 14:00 - 15:00, 2025

Charleston Chiang (Associate Professor, University of Southern California, USA)

We propose a conceptual analogy in population genetics to the central dogma of molecular biology. While the central dogma describes the flow of information from DNA to RNA to protein, we posit that under neutrality, a population's demography shapes its underlying genealogy, which in turn determines patterns of genetic variation that give rise to phenotypic variation. At the center of this analogous dogma is the genetic genealogies. Recent advances in inferring the Ancestral Recombination Graph (ARG), a complete record of a population's genealogies, have enabled us to develop a suite of methods that interrogates each stage these fundamental and connected components:

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

On the Role of Hidden States of Modern Hopfield Network in Transformer

November 10 (Mon) 14:00 - 15:00, 2025

Masato Taki (Associate Professor, Graduate School of Artificial Intelligence and Science, Rikkyo University)

Large language models such as ChatGPT are based on deep learning architectures known as Transformers. Owing to their remarkable performance and broad applicability, Transformers have become indispensable in modern AI development. However, it still remains an open question why Transformers perform so well and what the essential meaning of their unique structure is. One possible clue lies in the mathematical correspondence between Hopfield Networks and Transformers. In this talk, I will first introduce the major developments over the past decade that have significantly increased the storage capacity of Hopfield Networks. I will then review the theoretical correspondence between Hopfield Networks and Transformers. Building on this background, I will present our recent findings: by extending this correspondence to include the hidden-state dynamics of Hopfield Networks, we discovered a new class of Transformers that can recursively propagate attention-score information across layers. Furthermore, we found, both theoretically and experimentally, that this new Transformer architecture resolves the “rank collapse” problem often observed in conventional multi-layer attention. As a result, when applied to language generation and image recognition tasks, it achieves performance surpassing that of existing Transformer-based models.

Venue: Seminar Room #359, Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

Towards the prediction of clusters of primordial black holes

November 7 (Fri) 16:00 - 17:30, 2025

Danilo Artigas (JSPS Postdoctoral Research Fellow, Department of Physics Ⅱ, Division of Physics and Astronomy, Graduate School of Science, Kyoto University)

Primordial black holes (PBHs) are a major candidate for dark matter, expected to form from the collapse of large density fluctuations generated during inflation. Their abundance is highly sensitive to non-linear effects, some of which can be described through the δN formalism. This approach models the universe as a set of locally homogeneous patches evolving independently throughout inflation. However, accounting for the spatial correlations between these patches is crucial to predicting the spatial distribution of PBHs and the formation of clusters. In this talk, after reviewing the δN formalism, I will show how to include spatial correlations within this framework. As an illustration, I will discuss the ultra-slow-roll model and compute the curvature perturbation ζ — necessary to determine PBH formation — and its spatial correlations at the end of inflation. In the future, this could enable the prediction of PBH binaries and clusters, which may leave observable imprints such as gravitational waves.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

Rational function semifields of dimension one

November 7 (Fri) 13:30 - 15:30, 2025

JuAe Song (Assistant Professor, Faculty of Mathematics, Kyushu University)

Recently some researchers gave many studies toward algebro-geometric foundation for tropical geometry. I focused on rational function semifields of tropical curves and characterized them. With this characterization, in this talk, I suggest a definition of ``rational function semifield of dimension one". This definition can write out weight in the term of $\boldsymbol{T}$-algebra homomorphism, and can write balancing condition together with harmonic functions, where both weight and balancing condition are fundamental concepts for tropical varieties and $\boldsymbol{T}$ is the tropical semifield $(\boldsymbol{R} \cup \{-\infty\}, \operatorname{max}, +)$.

Venue: Seminar Room #359 / via Zoom

Event Official Language: Japanese

Pairing in Bose-Fermi and Fermi-Fermi systems

November 6 (Thu) 15:00 - 16:30, 2025

Pierbiagio Pieri (Associate Professor, Dipartimento di Fisica e Astronomia “Augusto Righi”, Università di Bologna, Italy)

This seminar is co-hosted by GWX-EOS Working Group and iTHEMS-ABBL Joint Astro Study Group. Abstract: In the first part of my talk, I will review recent work on Bose-Fermi mixtures with an attractive interaction inducing pairing between bosons and fermions. After discussing a recent experiment on this system [1], which has confirmed predictions obtained by us some time ago within a many-body diagrammatic approach [2], I will present novel results for the compressibility [3] that suggest a metastable nature for the many-body phase observed in [1]. Then, I will discuss the extension of our calculations to two-dimensional Bose-Fermi mixtures [4,5]. The results obtained in 2D challenge previous beliefs formulated for 3D systems. In the second part, I will discuss attractive polarized Fermi systems, for which the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) phase was proposed many years ago as a possible superfluid phase. I will discuss how significant precursor FFLO fluctuation effects appear already in the normal phase of polarized Fermi gases at finite temperature [6], and how they could be experimentally detected with ultracold gases. At zero temperature [7], I will discuss how the quasi-particle parameters of the normal Fermi gas change when approaching an FFLO quantum critical point, with a complete breakdown of the quasi-particle picture analogous to what found in heavy-fermion materials at an antiferromagnetic quantum critical point. Finally, I will discuss a recent joint experimental-theoretical work on the motion of a vortex orbiting a pinned anti-vortex in a strongly interacting Fermi gas [8], highlighting the interplay between Andreev bound states in the vortex core and delocalized thermal excitations in shaping the vortex dynamics.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

Semiotic Rupture and the Emergence of Writing: Toward a Multimodal Model of Representational Innovation

November 6 (Thu) 13:00 - 14:00, 2025

Joshua Englehardt (Professor, Center of Archeologist Studies, El Colegio de Michoacán, Mexico)
Michael D. Carrasco (Associate Dean for Research / Associate Professor, College of Fine Arts, Florida State University, USA)

Writing is a unique—and distinctively human—creation, one which arose independently in only six locations worldwide. From these primary sites of innovation, this relatively recent technology spread across the world. Its development is routinely lauded as one of humanity’s most important inventions, among its “greatest intellectual and cultural achievements,” and a key to human evolution. The scholar Florian Coulmas labels it “the single most important sign system ever invented on our planet. This presentation presents a theoretical framework for modeling the emergence, development, and structure of writing and other visual representational systems through a formal, processual lens. Building on Noam Chomsky’s distinction between internal language (I-language) and its externalization as E-language, we model writing as the mediated product of E-language and propose a set of visual analogues: I-image and E-image, understood as structurally similar generative systems. We offer a formal, cross- and multimodal model of writing and its development that treats it not as a codified extension of speech, but as a recursive reorganization of visual and linguistic generative systems. Rather than asking what writing is, we ask how it and other semiotic systems emerge. What tensions, pressures, and interactions catalyze their formation, transformation, and typological diversity? We contend that the semiotic dynamics that give rise to writing are not isolated or unique events, but are grounded in deeper processes, such as those underlying the emergence of image-making, that are already established in the cognitive evolution of Homo sapiens and plausibly present in ancestral hominins. That is, we see writing not as a spontaneous invention but as an emergent semiotic modality grounded in cognitive evolution and cultural externalization.

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

Introduction to Game Theory #2

November 6 (Thu) 11:00 - 12:00, 2025

Yohsuke Murase (Team Director, Mathematical Social Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

An introductory lecture on game theory to promote potential interdisciplinary collaborations. No prior knowledge is required — the lecture is intended for non-experts. We will cover the fundamental concepts to help you build an intuitive understanding of how game theory analyzes strategic interactions. After briefly reviewing the previous lecture, we will discuss mixed-strategy Nash equilibria and their computational complexity.

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English

Quantum multi-body problems using unsupervised machine learning

November 5 (Wed) 15:00 - 16:00, 2025

Tomoya Naito (Project Assistant Professor, Department of Nuclear Engineering and Management, Graduate School of Engineering, The University of Tokyo)

I will introduce the recent development of a method to calculate the (anti)symmetrized wave functions and energies of the ground and low-lying excited states using the unsupervised machine learning technique. I will also introduce the recent attempts to consider the spin-isospin degrees of freedom and extend them to the Dirac equation.

Venue: Seminar Room #359 (Main Venue) / via Zoom

Event Official Language: English