Seminar

Classification of certain actions of representation categories

June 5 (Fri) 15:00 - 17:00, 2026

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

Last year I showed a classification theorem for certain classes of module categories over the representation category of quantum SU(n). Although its proof is elementary, the classification itself has a natural interpretation based on the concept of quantization.

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

Event Official Language: English

reflection positivity in de Sitter space

June 5 (Fri) 10:30 - 11:30, 2026

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

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

Event Official Language: English

DeepQuark: A Deep-Neural-Network Approach to Multiquark Bound States

June 4 (Thu) 15:00 - 16:00, 2026

Wei-Lin Wu (Ph.D. Student, School of Physics, Peking University, China)

Recent discoveries of multiquark candidates have opened a new frontier in hadron spectroscopy and nonperturbative QCD. Understanding these multiquark states poses a challenging quantum many-body problem governed by SU(3) color interactions. Traditional approaches based on basis expansions often encounter severe bottlenecks as the system size and dynamical complexity increase. In this talk, I will present DeepQuark, a deep-neural-network-based variational Monte Carlo framework for solving multiquark bound states. I will discuss the general methodology behind neural-network quantum states, the challenges of extending existing approaches from electronic and nuclear systems to hadron physics, and the architecture of DeepQuark. By combining physics-informed symmetry constructions with the expressive power of deep neural networks, DeepQuark provides a scalable framework for studying multiquark spectroscopy and exploring confinement dynamics.

Venue: via Zoom

Event Official Language: English

Membrane Geometry Regulates Phase Morphology in Postsynaptic Condensates

June 4 (Thu) 14:00 - 15:00, 2026

Risa Yamada (Ph.D. Student, Division of Biological Sciences, Graduate School of Science, Kyoto University)

Biomolecular condensates are generally regarded as membrane-less organelles formed through liquid–liquid phase separation (LLPS). However, some condensates in living cells emerge in close proximity to biological membranes, where spatial confinement and surface geometry can critically influence their organization and function. In this talk, I will discuss recent advances in understanding how membrane association regulates the phase behavior of postsynaptic density (PSD) condensates. Using mesoscale molecular simulations constrained by experimental interaction data, our study reproduced the distinct condensate architectures observed in solution and on membranes. In three-dimensional solution, AMPA receptor/PSD-95 complexes form the condensate core, whereas NMDA receptor/CaMKII complexes localize to the shell. Strikingly, this organization becomes reversed in membrane-associated two-dimensional systems. The analysis revealed that this transition arises from the competition between CaMKII’s large excluded volume and its highly multivalent interactions. While excluded-volume effects dominate in solution, membrane confinement favors specific multivalent interactions, stabilizing distinct receptor nanodomains. These results provide a physical framework for understanding how spatial dimensionality and molecular architecture regulate biomolecular condensates and synaptic organization.

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

Event Official Language: English

Generative diffusion model with inverse renormalization group flows

June 2 (Tue) 14:00 - 15:00, 2026

Kanta Masuki (Ph.D. Student, Graduate School of Science, The University of Tokyo)

Diffusion models have recently emerged as one of the most powerful frameworks for generative modeling, achieving remarkable success in a wide range of domains, including image generation, audio synthesis, and scientific data generation. However, despite their empirical success, conventional diffusion models often require many denoising steps and do not explicitly exploit the multiscale structure naturally present in various types of data. This limitation motivates us to ask whether ideas from the renormalization group (RG), which is designed to describe scale-dependent effective degrees of freedom, can provide a useful principle for constructing more efficient generative models. In this talk, I will present our recent work on renormalization-group diffusion models (RGDMs) [1], a generative framework that connects diffusion models with RG flows. By establishing a correspondence between diffusion dynamics and exact RG flow equations, we construct a diffusion model whose reverse process generates data in a coarse-to-fine manner, thereby effectively reversing an RG flow. I will first introduce the theoretical formulation of RGDMs and explain how the RG perspective leads to a coarse-to-fine generative process. I will then present numerical results in protein structure prediction and image generation, where RGDMs improve sample quality and/or sampling efficiency compared with conventional diffusion models. Finally, I will discuss possible extensions and open questions, including broader applications of RG-inspired generative modeling.

Venue: Seminar Room #359

Event Official Language: English

't Hooft anomaly matching and symmetry enforced gaplessness

June 1 (Mon) 13:00 - 14:00, 2026

Kantaro Ohmori (Senior Research Scientist, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

I will talk about the 't Hooft anomaly matching and its enforcement of gaplessness. I will also briefly touch on my recent work with Takamasa Ando on this topic.

Venue: via Zoom / Seminar Room #359

Event Official Language: English

Closed Seminar on Quantum Topology and Related Topics

May 29 (Fri) 14:00 - 18:00, 2026

Mao Hoshino (Special Postdoctoral Researcher, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
Kan Kitamura (Assistant Professor, Department of Mathematics, College of Science, Rikkyo University)
Yuya Murakami (Research Scientist, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
Vladimir Sosnilo (Research Scientist, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

We will hold a closed seminar on quantum topology and related topics. The talks will be given by the following four speakers. The talks will not be streamed online or recorded. 14:00–14:30 Mao Hoshino 14:30–15:00 Kan Kitamura (15:00–15:30 Coffee break) 15:30–16:00 Yuya Murakami 16:00–16:30 Vladimir Sosnilo (16:30–17:30 Casual reception)

Venue: Seminar Room #359

Event Official Language: English

Bootstrapping Cosmological Correlators

May 28 (Thu) 16:00 - 18:00, 2026

Mang Hei Gordon Lee (Post-Doctoral fellow, Leung Center for Cosmology and Particle Astrophysics, National Taiwan University, Taiwan)

Currently there are hundreds of models describing inflation, a period of accelerated expansion in our universe. Each model lead to different imprints in cosmological observables, and for the purpose of testing the idea of inflation itself, it is essential to understand which predictions are model independent. This lead to the idea of cosmological bootstrap, a set of constraints from physical principles and symmetries alone. In this talk I will give an overview on the cosmological bootstrap program. I will first explain how locality, unitarity and symmetry can constrain the kinematics of cosmological correlators. I will then talk about some recent progress on constructing positivity bounds on cosmology, which places constraints on the interactions of fields in inflation.

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

Event Official Language: English

Introduction to categorification and link homology

May 28 (Thu) 14:00 - 15:30, 2026

Mikhail Khovanov (Professor, Department of Mathematics, Johns Hopkins University, USA)

Quantum link invariants relate topology in 3 dimensions to mathematical physics and representation theory. They admit liftings to 4-dimensional structures, known as link homology. We will explain how the skein relations for quantum invariants turn into homological structures at this higher level and how semisimple representation theory turns into non-semisimple representations and homological algebra upon categorification.

Venue: Okochi Hall (Main Venue) / via Zoom

Event Official Language: English

Towards rock-solid evolutionary genomics

May 28 (Thu) 13:00 - 14:00, 2026

Leo Speidel (RIKEN ECL Research Unit Leader, Mathematical Genomics RIKEN ECL Research Unit, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

I will present an overview of ongoing and future projects in our lab. We aim to understand how human genomes retain information about our evolutionary past; a central goal is to reconstruct a high-resolution history of humans, pushing the limits of what we can learn about our origins, past migrations, and adaptation to changing environments and survival pressures. Our genomes reveal events that would otherwise be lost to history, revealing how evolutionary forces have shaped genetic variation and influence our health today. How can we confidently infer events that occurred tens of thousands of years ago? I will discuss how converging and independent lines of genomic evidence can provide “rock-solid” support for major evolutionary events, including archaic admixture, large-scale migrations across continents, and population bottlenecks, and how we aim to extend these approaches to study the evolutionary history and origins of humans and other species.

Venue: via Zoom / Seminar Room #359

Event Official Language: English

Cooperating on networks: inequality and social structure

May 27 (Wed) 14:00 - 15:00, 2026

Manuel Staab (Lecturer, University of Queensland, Australia)

We analyse how inequality in endowments and social structure jointly affect individuals' ability to cooperate. Individuals repeatedly invest in a local public good ("cooperation'') in an environment that is described by a distribution of endowments and a network of beneficiaries. We measure the cooperativeness of an environment by the minimum discount factor needed to sustain (any) cooperation in equilibrium. We characterise the endowment distribution that maximises cooperativeness for any given network and the corresponding minimum discount factor. The latter is shown to be inversely proportional to the maximal index of the graph describing the network. The corresponding dominant eigenvalue of the adjacency matrix characterises the most cooperative income distribution. Moreover, we show that if an environment maximises cooperativeness (over all income distributions and networks of a certain size), then the network is described by a nested split graph. We further show that this is the same class of graphs that maximise welfare for any given discount factor, and yet, the most cooperative graph need not be equal to the most efficient.

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

Event Official Language: English

Harnessing inequality for cooperation

May 26 (Tue) 14:00 - 15:00, 2026

Maria Kleshnina (Senior Lecturer, School of Mathematical Sciences, Queensland University of Technology, Australia)

Inequality in resources is widely thought to undermine cooperation in social dilemmas. Yet cooperation among unequals is ubiquitous: between senior and junior colleagues, firms of different sizes, nations with asymmetric stakes. Here, we offer a resolution to this puzzle and derive a novel prediction: if the returns from cooperation are shared in accordance with the individuals' strategic incentives, inequality enables and strengthens cooperation. We develop a strategic framework to systematically explore cooperation when the returns of a joint project can be shared unevenly. We characterise the optimal sharing rule, which we call resilient sharing, that can sustain cooperation in repeated interactions when no other rule can. Resilient sharing equalises incentives to defect across players, but is neither egalitarian nor proportional. Surprisingly, it typically rewards weaker partners beyond their relative contributions. We show that cooperation can be sustained through direct reciprocity in any environment whenever individual contributions are sufficiently unequal. Evolutionary simulations and a behavioural experiment confirm the central prediction: under resilient sharing, cooperation succeeds among unequal partners where it fails among equals. This suggests that cooperation is more likely to evolve and thrive when individuals can vary contributions and divide returns flexibly, pointing to the role of institutions and norms in harnessing inequality to stabilize cooperation.

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

Event Official Language: English

Singularities of differentiable maps and Thom polynomials

May 22 (Fri) 15:00 - 17:30, 2026

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

Singularities are locations where something is exceptional. In particular, singularities of differentiable maps are mathematical concepts corresponding to stationary points of functions and apparent contours of surfaces under projection onto the retina. These are unavoidable in general, but important to study the shape of spaces and behavior of maps. The theory for them was initiated by R. Thom in 1950's, and have been deeply studied by many researchers.

Venue: Room 359, RIKEN Wako Campus (Main Venue) / via Zoom

Event Official Language: English

Entanglement entropy and conformal bounds for five-dimensional CFTs

May 21 (Thu) 15:00 - 16:00, 2026

Javier Moreno (Project Assistant Professor, Yukawa Institute for Theoretical Physics, Kyoto University)

Abstract: The entanglement entropy of spatial regions in odd-dimensional conformal field theories contains a universal constant contribution that encodes important information about the theory. This quantity can be defined in a robust way using mutual information between slightly deformed versions of a given region. In three-dimensional conformal field theories, it is known that this quantity is always positive and bounded from below by the value corresponding to a spherical region. There is also strong evidence that, for any region, its normalized value is maximized by the free scalar theory. In this work, we show that the situation changes significantly in five dimensions. Although the spherical region remains a local minimum under small shape deformations, more general regions can lead to values that become arbitrarily large in magnitude, with either sign. This implies that, in five-dimensional conformal field theories, the quantity is not bounded from above or below. We also demonstrate that the analogous maximization property observed in three dimensions does not hold in five dimensions when considering general regions. Despite this, we find that existing evidence is consistent with a weaker statement: for small deformations of a spherical region, the normalized quantity remains bounded above by the free scalar result across all five-dimensional conformal field theories. This leads to a new conjectured universal bound relating two key physical quantities—the coefficient governing stress-tensor correlations and the sphere free energy—which appears to hold for all currently known examples.

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

Event Official Language: English

Stochastic Thermodynamics: noise and energetics of nanoscale systems

May 21 (Thu) 13:00 - 14:00, 2026

Jean-Charles Delvenne (Professor, Applied Mathematics, Université Catholique de Louvain, Belgium)

Stochastic thermodynamics, initiated three decades ago, aims at quantifying the fluctuations of physical observables in relation with thermodynamic quantities (such as heat or entropy production). A typical result is the Thermodynamic Uncertainty Relation, which states that a high entropy production is required to obtain a favorable noise-to-signal ratio for some observables (such as displacement of a molecular motor) in stationary out-of-equilibrium systems. It is especially relevant for nanoscale systems, where the fluctuations cannot be neglected. This includes biological systems (e.g. biological motors such as kinesin along a microtubule), electronic systems (transistor-based memories), chemical reactions, etc. The talk will be both a tutorial on some basic results or applications, and a presentation of some recent results and perspectives.

Venue: via Zoom / Seminar Room #359

Event Official Language: English

On Mean-Field Games

May 21 (Thu) 10:30 - 11:30, 2026

Antoine Diez (Research Scientist, Mathematical Application Research Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Stochastic differential games with a large number of players are notoriously challenging, both theoretically and numerically, typically when it comes to computing Nash equilibria. Yet, when many players interact somehow symmetrically by responding only to the average behavior of the others, the game can surprisingly become more tractable by taking the limit of an infinite number of players. This is in direct analogy with the so-called « mean-field theory » which simplifies the analysis of large systems of interacting particles in statistical physics. Introduced independently about two decades ago by Lasry and Lions (mathematics) and Caines, Huang and Malahamé (engineering), the theory of Mean-Field Games has since been greatly developed with various applications in engineering, economical, social and biological sciences. The goal of this short lecture is to introduce the key concepts, particularly the deep connections between game theory, Partial Differential Equations and stochastic analysis, and to showcase a few striking recent applications.

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

Event Official Language: English

Positivity constraints for the gravitational path integral

May 21 (Thu) 10:00 - 11:50, 2026

Gabriele Di Ubaldo (Postdoctoral Researcher, RIKEN-Berkeley Center, Division of Global Collaborations and Research Talent Development, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

For a quantum theory of gravity to have a well-defined Hilbert space, the inner product between different states of open and closed universes must be positive semi-definite. Positivity however is not manifest in the low-energy effective theory and in fact imposes nontrivial constraints on the theory. Working in the Gravitational Path Integral (GPI) approach, we derive the general set of positivity constraints on the closed and open universe Hilbert spaces. In the case of AdS gravity, open universe positivity in principle follows from CFT unitarity, however the holographic description of closed universes remains unclear. Strikingly, we exhibit positivity of closed universes across many theories and prove that open positivity implies closed positivity, showing that the CFT 'knows' about the closed universe hilbert space. We then analyze positivity constraints on gravitational theories coupled to axions. We present a method to compute off-shell axion wormholes in AdS and flat space which we use to show that positivity is violated if the axion shift symmetry is exact. In low-energy EFTs where these wormholes are perturbatively stable, to restore positivity the wormhole must have a non-perturbative instability due to instantons that breaks the shift symmetry. Positivity then leads to a proof of a sharp version of the Axion Weak Gravity Conjecture A-WGC, including precise numerical constants. For the QCD axion this provides a bound on the axion decay constant which has phenomenological and experimental consequences for axion searches. In string theory, positivity gives a bound on the coupling between the axion and the dilaton in the low energy effective action.

Venue: via Zoom

Event Official Language: English

Realizing two-dimensional discrete time crystals on a digital quantum computer

May 19 (Tue) 15:00 - 16:30, 2026

Kazuya Shinjo (Research Scientist, Computational Quantum Matter Research Team, RIKEN Center for Emergent Matter Science (CEMS))

This work was featured in a RIKEN press release. For details, please see the related link.

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

Event Official Language: English

Synthetic Data from Domain Knowledge: Pretraining Medical Deep Networks under Data Scarcity

May 18 (Mon) 14:00 - 15:00, 2026

Naoki Nonaka (Senior Research Scientist, Medical Science Deep Learning Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Training deep learning models typically requires large-scale data, yet in the medical domain such data are often difficult to obtain due to privacy constraints, the rarity of certain diseases, and the high cost of acquisition. In this talk, I present one approach to this challenge: pretraining with synthetic data generated from domain knowledge. As concrete examples, I introduce the synthesis of electrocardiograms (ECG) and phonocardiograms (PCG). For ECG, each waveform component (P, Q, R, S, and T) is modeled with Gaussian functions; for PCG, synthetic signals are generated by combining S1 and S2 heart sounds with modulated noise. I show that pretraining a model on such synthetic data and then fine-tuning on a small amount of real data substantially improves classification performance compared to training on real data alone, and that this improvement becomes more pronounced as the size of the real dataset decreases. I will also touch on extensions such as self-supervised learning with synthetic data and a comparison between knowledge-driven simulators and learned generative models, and discuss the broader potential of domain knowledge as a data source for medical applications where real data are limited.

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

Event Official Language: English