Loop expansion in polymer field theory: application to phase separation

July 30 (Thu) 16:00 - 17:00, 2026

Kiyoharu Kawana (Research Fellow, Korea Institute for Advanced Study (KIAS), Republic of Korea)

Liquid-liquid phase separation underlies phenomena ranging from protein condensate formation to the phase coexistence of synthetic polymers. In this talk, we develop a field theoretic loop expansion in homopolymer systems by identifying the inverse polymer density ρ^{-1} as the Planck constant ℏ in quantum field theory. The 1-loop approximation is known as the random phase approximation (RPA) and has been extensively applied to many (hetero)polymer systems. We calculate the leading-order (2-loop) and next-to-leading-order (3-loop) corrections to the RPA free energy, denoted as RPA+ and RPA++, respectively. Testing the binodal predicted by the RPA+ against molecular dynamics simulations of bead-spring chains with Gaussian pair interactions, we find that the RPA+ qualitatively improves the dilute-phase coexistence density over the RPA, while the critical point error remains comparable to that of the RPA. Our results establish the loop expansion as a systematic route for refining the RPA-based binodal predictions for polymer phase separation. This talk is based on arXiv: 2605.01261.

Venue: via Zoom

Event Official Language: English

Quantum Reference Frames for Quantum Gravity

July 30 (Thu) 14:00 - 16:00, 2026

Luca Marchetti (Project Researcher, Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU))

This seminar is the first part of a two-part mini-seminar series organized by the Quantum Gravity Gatherings study group. It is intended to have a more lecture-style format, with an extended duration of up to two hours. This will allow the speaker sufficient time to introduce the framework in a clear and pedagogical manner, while also leaving ample room for questions and discussion with the audience. Title: Quantum Reference Frames for Quantum Gravity Abstract: Internal quantum reference frames provide a general framework for handling symmetries in quantum theory, with applications ranging from quantum gravity and gauge theories to quantum information and foundational physics. I will first introduce the formalism in simple mechanical systems, before turning to classical gravity. There, I will motivate the need for internal, dynamical frames in background-independent theories to define relationally local gauge-invariant observables, and show how this framework leads to a relational update of general covariance: frame covariance. I will then move to non-perturbative quantum gravity, showing how quantum reference frames can be used to define a manifestly gauge-invariant relational path integral, which is also invariant under transformations between quantum reference frames. It therefore provides a perspective-neutral description of quantum gravitational physics. I will also discuss the associated relational effective actions. Although effective actions are, in general, not frame-covariant off shell, the on-shell physics they encode is. Finally, I will present several physical consequences of this framework, including the fuzziness of frame-changed local correlators, the non-trivial interplay between quantum-reference-frame transformations and time evolution, and the frame-dependence properties of ground sectors and Hartle-Hawking prescriptions. I will conclude by outlining future directions, with particular emphasis on a relational notion of the renormalization group flow.

Venue: Hybrid Format (3F #359 and Zoom), Main Research Building

Event Official Language: English

Current challenges teaching undergraduate first year physics in Canada

July 30 (Thu) 13:00 - 14:00, 2026

Catherine Beauchemin (Deputy Director, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

I will talk about the challenges of teaching first year physics in 2026 to undergraduate students in computer science and engineering in Canada. Topics will include issues with textbook publishers (online vs physical books), open access textbook/homework systems, teaching, learning and setting evaluations, labs and homework in the era of AI, student attitudes towards learning, academic accommodation for disabilities, etc. This seminar could be interesting to those of you who will face teaching in your future, especially abroad. Although my perspective is based on physics and Canada, a number of issues raised are broadly relevant to other fields and countries.

Venue: Hybrid Format (3F #359 and Zoom), Main Research Building

Event Official Language: English

An optimal transport and information geometric framework for infinite-dimensional Gaussian measures and Gaussian processes (II)

July 28 (Tue) 15:00 - 16:15, 2026

Minh Ha Quang (Senior Research Scientist, Imperfect Information Learning Team, RIKEN Center for Advanced Intelligence Project (AIP))

Divergences between probability distributions play a crucial role in many areas of probability theory, statistics, machine learning, and their applications. While a large part of the literature is focused on divergences between finite-dimensional distributions, there is a growing body of work on infinite-dimensional distances/divergences, which are motivated by applications in functional data analysis, Bayesian inverse problems, and functional Bayesian neural networks, among others. In this lecture, we present an overview of recent results on some of the most important divergences being studied, including the Kullback-Leibler, Renyi, and Geometric Jensen-Shannon divergences. We discuss the many challenges that arise in the infinite-dimensional setting, e.g. the lack of a natural reference measure such as the Lebesgue measure and the fact that many functions such as determinants and logarithm are only well-defined in specific settings. In particular, in the setting of Gaussian measures on infinite-dimensional Hilbert spaces, the closed form expressions for the above divergences are only generalizable to equivalent Gaussian measures. We present the resolution to the above challenges via the geometrical framework of positive definite unitized (or regularized) trace class and Hilbert-Schmidt operators, including the Alpha and Alpha-Beta Log-Determinant divergences. Using this framework and the methodology of reproducing kernel Hilbert spaces (RKHS), we furthermore obtain consistent finite-dimensional  approximations of the above divergences in the Gaussian process setting, with dimensional-independent sample complexities. The resulting numerical algorithms can be readily employed in practical applications. We shall also discuss the generalization of the above classical divergences above to the quantum setting, namely the Quantum Jensen-Shannon divergence between quantum states, defined in terms of the von Neumann and Tsallis entropies, from finite to infinite-dimensional settings.

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

Event Official Language: English

An optimal transport and information geometric framework for infinite-dimensional Gaussian measures and Gaussian processes (I)

July 28 (Tue) 13:30 - 14:45, 2026

Minh Ha Quang (Senior Research Scientist, Imperfect Information Learning Team, RIKEN Center for Advanced Intelligence Project (AIP))

Optimal transport (OT) and information geometry (IG) have been attracting much research attention in various fields, in particular machine learning and statistics. In this lecture, we present results on the generalization of IG and OT distances for finite-dimensional Gaussian measures to the setting of infinite-dimensional Gaussian measures and Gaussian processes. Our focus is on the Entropic Regularization of the 2-Wasserstein distance and the generalization of the Fisher-Rao Riemannian metric and related quantities. In both settings, regularization leads to many desirable theoretical properties, including in particular dimension-independent convergence and sample complexity. The mathematical formulation involves the interplay of IG and OT with Gaussian processes and the methodology of reproducing kernel Hilbert spaces (RKHS). All of the presented formulations admit closed form expressions that can be efficiently computed and applied practically. The mathematical formulations will be illustrated with numerical experiments on Gaussian processes.

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

Event Official Language: English

Center-vortex condensation and monopole condensation in 4d gapped phases

July 27 (Mon) 14:00 - 15:30, 2026

Yui Hayashi (JSPS Postdoctoral Research Fellow, Yukawa Institute for Theoretical Physics, Kyoto University)

Two well-known scenarios for quark confinement are center-vortex proliferation and monopole condensation. We consider gauge-invariant criteria for center-vortex condensation and monopole condensation in terms of Z(N) 1-form symmetry. The condensation of a soliton can be characterized by the non-suppression of the partition function with a proper twisted boundary condition, and we utilize this idea for these criteria. With these definitions, we show that gapped phases with the center-vortex condensation necessarily exhibit the monopole condensation.

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

Event Official Language: English

Some instances where topological illustration induced new mathematics

July 24 (Fri) 16:30 - 18:00, 2026

Sofia Lambropoulou (Professor, School of Applied Mathematical and Physical Sciences, National Technical University of Athens, Greece)

We shall present instances from generalized knot theory, braid theory and their interactions, where illustration promoted understanding and inspired new mathematics. The first instance addresses a question of V.F.R. Jones whether one can make analogous constructions to the (2-variable) Jones polynomial using other braid groups and other types of Hecke algebras. The second instance addresses the question of formulating braid equivalences, analogous to the Markov theorem for classical braids, in settings where we may not even have available algebraic structures for the related braids. The third instance is about the theory of bonded knots and bonded knotoids used for modelling proteins.

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

Event Official Language: English

Unraveling the very early universe with black holes, boson stars, and cannibal stars

July 24 (Fri) 14:00 - 16:00, 2026

Takeshi Kobayashi (Associate Professor, International School for Advanced Studies (SISSA), Italy)

According to the standard picture of cosmology, the rich structure of our universe began to form roughly 50,000 years after the big bang. In this talk I will explore the possibility that cosmic structures could also have formed in the extremely early universe, within a fraction of a second after inflation. I will show how this early structure formation can give rise to compact objects, including exotic stars and primordial black holes. These relics provide powerful probes of the first instants of cosmic history, especially the reheating epoch, and may even act as seeds for cosmological phase transitions. Note: This seminar is jointly organized by the iTHEMS-phys Study Group and the iTHEMS-ABBL Joint Astro Study Group.

Venue: Seminar Room #359 / via Zoom

Event Official Language: English

The decision intelligence of humans and machines

July 24 (Fri) 10:30 - 11:30, 2026

Petter Holme (Professor, Department of Computer Science, Aalto University, Finland)

The event has been rescheduled from July 22 to July 24. To understand our near-future of artificial intelligence firmly integrated into many levels of social life, a challenge is to understand the differences and similarities between human and AI decision-making. In controlled laboratory settings assessing risk and uncertainty, LLMs demonstrate superhuman efficiency but fundamentally diverge from human behavior through a rigid hyper-rationality and an inability to disengage from obsolete strategies. However, when applied to messy, real-world dilemmas "in the wild," these models pivot to function as highly effective "satisficers". Human subjects consistently prefer this artificial counsel over human peer advice, noting its ability to carefully balance emotional context with logical constraints while actively reducing anxiety and regret. Ultimately, this synthesis shows that while AI can offer near-optimal laboratory performance and therapeutic impact in daily life, they also have a distinct lack of behavioral plasticity that we need to account for in models of the future.

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

Event Official Language: English

When Is Collective Intelligence a Lottery? Toward a Physics of Bounded Agent Societies

July 22 (Wed) 16:00 - 17:30, 2026

Hidenori Tanaka (Group Leader, CBS-NTT Physics of Intelligence Program, Center for Brain Science, Harvard University, USA)

Multi-agent LLM systems can reach agreement quickly, but agreement alone does not reveal whether a group has integrated evidence, amplified a bias, or merely locked in the luck of early samples. In this talk, I will develop a physics-style approach to this problem through two synthetic games. In reward-free naming games, populations form conventions through mutual in-context learning: agents treat one another's sampled outputs as evidence, so early fluctuations compound into consensus. A minimal model, Quantized Simplex Gossip (QSG), identifies this regime as memetic drift and predicts scaling laws and a crossover from lottery-like drift to bias-driven selection. I will then introduce the Flag Game, in which a hidden country flag provides verifiable ground truth but each agent sees only a private crop of it. Here, bounded agents must balance private evidence against social input. We find rich phenomenologies, where adding agents can help or hurt, large groups can polarize, and social-awareness prompting, model diversity, and organizational structure all reshape collective performance. Extending QSG with grounded evidence and model-specific update rules explains these effects. More broadly, these studies frame an LLM society as a network of networks, neural networks coupled through social interaction, and outline a route toward a multiscale physics of interacting AI agents, linking model-internal representations, agent-level decision mechanisms, and population-level social dynamics.

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

Event Official Language: English

Workshop on Discrete & Continuous Aspects of Reaction-Diffusion in Pattern Formation (DiCoRD2026)

July 22 (Wed) - 24 (Fri) 2026

Ryoko Oishi-Tomiyasu (Professor, Institute of Mathematics for Industry, Kyushu University)
Makoto Sato (Professor, Kanazawa University)
Nobuhiko Suematsu (Professor, School of Interdisciplinary Mathematical Sciences, Meiji University)
Yasumasa Nishiura (Professor Emeritus, Hokkaido University)
Riccardo Muolo (Special Postdoctoral Researcher, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
Jonathan Dawes (Professor, University of Bath, UK)
Henrik Weyer (Postdoctoral Scholar, University of California, Santa Barbara, USA)
Yuzuru Kato (Associate Professor, Department of Complex and Intelligent Systems, School of Systems Information Science, Future University-Hakodate)
Ayumi Ozawa (Young Research Fellow, Japan Agency for Marine-Earth Science and Technology (JAMSTEC))
Takanori Sugimoto (Associate Professor, Faculty of Engineering Science, Kansai University)
Natsuhiko Yoshinaga (Professor, School of Systems Information Science, Future University-Hakodate)
Jens Rademacher (Professor, University of Hamburg, Germany)
Takeshi Fukao (Professor, Faculty of Advanced Science and Technology, Ryukoku University)
Yoshitaro Tanaka (Associate Professor, School of Systems Information Science, Future University-Hakodate)
Shuji Ishihara (Project Associate Professor, The University of Tokyo)
Hiroshi Ishii (Assistant Professor, Research Institute for Electronic Science, Hokkaido University)
Takeshi Watanabe (Associate Professor, Nagano University)
Antoine Diez (Research Scientist, Mathematical Application Research Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Venue: via Zoom / Research Seminar Room 3, 6F, High-Rise Building, Meiji University (Nakano Campus)

Event Official Language: English

Entanglement suppression for ΩΩ scattering

July 17 (Fri) 15:00 - 16:30, 2026

Katsuyoshi Sone (Ph.D. Student, Graduate School of Science, Tokyo Metropolitan University)

The S-matrix describing the scattering process can be expressed in terms of projection operators onto the allowed spin–flavor channels and the corresponding phase shifts. Using the entanglement entropy in the spin space of the two-particle state, one can define the entanglement power, which quantifies the ability of the S-matrix to generate entanglement in the system. By investigating the conditions under which the entanglement power of the S-matrix is minimized, namely, the conditions for entanglement suppression, one can derive relations among the phase shifts in different spin–flavor channels. Furthermore, by comparing these relations with the interaction Lagrangian, one can identify the underlying symmetries [1,2]. In this work, we apply the entanglement suppression framework to two-baryon scattering involving spin-3/2 baryons in the flavor decuplet [3]. Lattice QCD calculations have shown that the spin-0 ΩΩ system exhibits scattering close to the unitary limit. Combining this result with the relation between the phase shifts obtained from entanglement suppression, we discuss the scattering behavior of the spin-2 ΩΩchannel.

Venue: #445-447, 4F, Main Research Building (Main Venue) / via Zoom

Event Official Language: English

The 33th MACS Colloquium

July 17 (Fri) 14:45 - 18:00, 2026

Hajime Naruse (Professor, Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University)
Yohsuke Murase (Team Director, Mathematical Social Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

14:45-15:00 Teatime Discussion 15:00-16:00 Hajime Naruse (Professor, Department of Geophysics, Graduate School of Science, Kyoto University) "What Do Sedimentary Layers Remember? Exploring Past Earth Environments through Machine Learning" 16:15-17:15 Yosuke Murase (Team Director, Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), RIKEN) "Mathematics of Cooperation in Society: The Evolution of Cooperation through Direct and Indirect Reciprocity" 17:15-18:00 Discussion

Venue: Science Seminar House (Map 9), Kyoto University

Event Official Language: Japanese

A first step towards Non-Archimedean Geometric Quantization

July 17 (Fri) 14:00 - 15:30, 2026

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

Calabi--Yau manifolds have long attracted interest from both mathematics and physics, particularly in the context of mirror symmetry, and form an important class of compact Kähler manifolds. A compact Kähler manifold is Calabi--Yau if and only if it admits a Ricci-flat Kähler metric, which we shall call a CY metric. Such a metric is highly analytic in nature, as it is given as the solution to a second-order PDE on the manifold, namely the complex Monge--Ampère equation. When the Calabi--Yau manifold is a complex projective variety, one algebraic approach to understanding this analytically defined CY metric is to approximate it by algebraically defined metrics called balanced metrics. This framework was initiated by Donaldson and is now known as geometric quantization. In this talk, following the spirit of this theory, we consider a non-Archimedean analogue of this approximation theory. More precisely, for a non-Archimedean analytic space associated with a maximally degenerating family of Calabi--Yau manifolds, we study the approximation of the NACY metric, a non-Archimedean analogue of the CY metric, by algebraically defined metrics. In particular, we introduce NA balanced metrics, which are expected to provide such an approximation, and explain that, for totally degenerating families of abelian varieties, NA balanced metrics indeed approximate the NACY metric.

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

Event Official Language: English

Mathematical Application Research Team Meeting #17

July 17 (Fri) 10:30 - 11:45, 2026

Hugo Koubbi (Ph.D. Student, CEREMADE, Université Paris Dauphine, France)

Mathematical Application Research Team is delighted to welcome Hugo Koubbi from CEREMADE, Université Paris Dauphine, for an upcoming team meeting. We warmly invite everyone to join us to hear his talk: Title: Mean-field Transformers Abstract: Since their introduction, Transformers have achieved unprecedented success across a wide range of deep-learning tasks. In this talk, we present a recent line of work that interprets Transformer architectures as interacting particle systems and studies their continuum, or mean-field, limits. By considering idealized attention dynamics on the sphere, we establish connections between Transformers, Wasserstein gradient flows, and synchronization models such as the Kuramoto model. We describe a global clustering phenomenon in which tokens eventually synchronize, following long-lived metastable regimes characterized by the coexistence of several clusters. Finally, we explain how recent work extends these ideas beyond idealized models and reveals analogous phenomena in more realistic Transformer architectures at initialization.

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

Event Official Language: English

Artificial Intelligence in New Physics Electroweak Phase Transition Studies

July 16 (Thu) 15:00 - 16:00, 2026

Yang Zhang (Professor, Henan Normal University, China)

The study of electroweak phase transitions in BSM involves complex numerical calculations, large parameter spaces, and the integration of multiple computational tools. In this talk, I will review recent developments in applying artificial intelligence to new physics phase transition studies. First, I will discuss how machine learning methods can accelerate electroweak phase transition studies, including efficient evaluations of phase transition dynamics, such as bounce action calculations, and the exploration of detectable parameter regions for gravitational-wave searches. Then, I will introduce the emerging role of AI agents in scientific workflows, including automated model construction, effective potential generation, and parameter scans. These developments illustrate how AI can transform traditional computational pipelines and provide new possibilities for future high-energy physics research.

Venue: via Zoom

Event Official Language: English

Visual system and (social) behavior in zebrafish

July 16 (Thu) 13:00 - 14:00, 2026

Fumi Kubo (Team Director, Laboratory for Sensorimotor Integration, RIKEN Center for Brain Science (CBS))

Animals make decisions about their actions using sensory information from the external world. Our lab investigates how the brain processes visual information and generates appropriate behavior using the vertebrate model organism, zebrafish. Our research has uncovered the neural circuits required for processing optic flow, a visual cue that animals use to estimate their own motion. We employ a diverse range of techniques, including behavioral tracking, live imaging of neural activity, and molecular and genetic characterization of neuronal cell types. More recently, our research has focused on social behavior, in which groups of animals collectively generate behavioral decisions. In this seminar, I will present our recent work investigating behavioral contagion in zebrafish.

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

Event Official Language: English

Joint Seminar on Cosmology

July 13 (Mon) 13:30 - 18:00, 2026

Yukihiro Kanda (Project Researcher, Institute for Cosmic Ray Research (ICRR), The University of Tokyo)
Fumiya Okamatsu (Research Assistant, Department of Physics, College of Humanities and Sciences, Nihon University)
Fumiya Sano (JSPS Postdoctoral Research Fellow, Graduate School of Arts and Sciences, The University of Tokyo)

The Joint Seminar is a collaborative seminar series organized by universities and research institutes in and around Tokyo. It is held once every one or two months, with the venue rotating among the participating institutions. At each meeting, we have around three talks and open, informal discussions. After the seminar, participants are also welcome to join an informal social gathering.

Venue: Okochi Hall

Event Official Language: English

How did we come to be? — Particle Physics for the Next Decades —

July 10 (Fri) 15:30 - 17:00, 2026

Hitoshi Murayama (Professor, Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU), The University of Tokyo / Professor, Department of Physics, University of California, Berkeley, USA)

Particle Physics is a study of the smallest and the biggest to uncover the fundamental laws that govern the universe. In recent years, both the United States and Europe have been through long-range planning processes. The future plans worldwide include the studies of (1) neutrinos that may have saved us from a complete annihilation, (2) the Higgs boson that keeps us in one piece, (3) dark matter that assembled us from the primordial soup, (4) inflation that created the macroscopic universe, and (5) the exploration of unknown particles and forces. It requires development of mind-boggling technologies.

Venue: Okochi Hall (Main Venue) / via Zoom

Event Official Language: English

What determines accuracy in matrix projection models?

July 10 (Fri) 14:30 - 15:30, 2026

Richard Shefferson (Professor, Graduate School of Arts and Sciences, The University of Tokyo)

Matrix projection models (MPMs) have grown in complexity as ecologists have sought to include more factors that may influence population size and structure. However, some studies suggest that MPMs may lead to predictions inaccurate enough as to question their overall utility. I used long-term (21-36 year) demographic datasets on 6 herbaceous perennial species to examine and compare the ability of MPMs with different structural characteristics to predict future population size and structure. In absolute terms, almost all models performed poorly. In relative terms, density-dependent, ahistorical stage-based models with simple life histories and fewer stages were most successful in predicting population size. My results indicate that MPMs and IPMs are typically poor predictors of absolute population size and structure, but, when constructed properly, can still be used as useful qualitative predictors of population change.

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

Event Official Language: English