Birational rigidity of singular Fano threefolds

October 23 (Fri) 14:00 - 16:00, 2026

Chi-Kang Chang (Special Postdoctoral Researcher, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

Birationally rigid varieties form an important class of Fano varieties. A Fano variety is called birationally rigid if it is not birationally equivalent to any other Mori fibre space. Many well-known examples of birationally rigid smooth Fano threefolds have been known for a long time. However, the first example of a birationally rigid singular Fano threefold was found only recently by Krylov, Okada, Paemurru, and Park. Their example is a sextic double solid with only cA1 singularities. On the other hand, Paemurru proved that sextic double solids with cAn singularities are not birationally rigid when n is at least four. In our work, we generalized the method of Krylov, Okada, Paemurru, and Park to more general cDV singularities and found the first example of a birationally rigid Fano threefold with cD-type singularities. This is joint work with Jheng-Jie Chen and Takuzo Okada.

Venue: via Zoom / #359, Main Research Building

Event Official Language: English

An Origin Story for Money

October 22 (Thu) 15:00 - 16:00, 2026

Stephen Marsland (Professor, Victoria University of Wellington, New Zealand)

In indirect reciprocity a reputation is used to enable donors to choose whether or not to provide costly help to potential recipients. Often this reputation is binary — good or bad — and is maintained by a third party who oversees all interactions. I will introduce extensions to this system that enables money to be viewed as a reputation and investigate how this helps us identify how systems of money may have first been invented.

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

Event Official Language: English

Observability-based causal inference in linear stochastic systems with hidden inputs

October 22 (Thu) 13:00 - 14:00, 2026

Daiki Sekizawa (Special Postdoctoral Researcher, Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science (CBS))

Causal inference from neural time series is confounded by correlations induced by hidden common inputs, a problem that is especially acute because the full set of variables shaping neural activity is rarely accessible. Prediction based measures such as Granger causality can therefore falsely attribute such dependencies to causal influence. Delay coordinate reconstruction, which is also closely connected to observability in control theory, provides a complementary route: in deterministic systems, downstream delays can reconstruct upstream causes, whereas the reverse does not generally hold. This asymmetry provides a signature of causal direction, as exploited by convergent cross mapping. In stochastic dynamics, however, dynamical and observation noise enter delay coordinates and prevent exact trajectory reconstruction. Here, we develop data driven criteria that extend this observability principle to partially observed stochastic systems. First, we show that observability can be tested by regression of time lagged covariance matrices, which removes direct noise contributions while preserving the observability relation. Second, we show that causal direction can be tested through inclusion of stochastic Koopman eigenvalues estimated from upstream and downstream delay coordinates, because downstream observations generically contain the dynamical components observable upstream. Numerical examples show that the proposed criteria recover causal direction and reject spurious dependencies induced by unobserved common inputs, including cases in which Granger causality and convergent cross mapping fail to distinguish common input from causal influence. Although motivated by neural recordings, the framework applies broadly to partially observed stochastic dynamical systems beyond neuroscience.

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

Event Official Language: English

Data assimilation with the full covariance on a fault-tolerant quantum computer

October 21 (Wed) 15:00 - 16:30, 2026

Takemasa Miyoshi (Team Principal, Data Assimilation Research Team, RIKEN Center for Computational Science (R-CCS))

Data assimilation (DA) is the core of numerical weather prediction, estimating an accurate state of the weather model by combining forecast and observations. DA provides a general approach and is being applied to various problems beyond weather. The state estimation is a linear solve where the background error covariance B is essential. Since B is an N × N matrix with N ~ 10^8 to 10^9 for the weather model, the full B has never been used. For decades the community has approximated B by parameterized covariance models or by low-rank ensembles with localization and thereby discards genuine structures that we know exist from large-ensemble experiments. Fault-tolerant quantum computing (FTQC) could remove this constraint, since quantum linear system solvers scale polylogarithmically in N. However, the DA equations cannot be applied naively: the observation-space form squares the block-encoding normalization factor for observations with wide footprints, and the state-space form contains B^{-1}, whose condition number ~10^8. This talk presents a combined state-observation formulation that avoids both difficulties: it contains no B^{-1}, and its condition number is governed by the observation error covariance R rather than by B. Numerical experiments with the Lorenz-96 model reproduce the exact solution with the full B and outperform localized ensemble Kalman filters. The formulation assumes that B and the observation operator are provided as block-encoded oracles, and how to construct such oracles without ever storing the matrices is the open problem. A first concrete target is an end-to-end demonstration with Lorenz-96 on a quantum simulator with only seven data qubits, which I would like to discuss with the iTHEMS community.

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

Event Official Language: English

Bubble wall dynamics from non-equilibrium quantum field theory

October 21 (Wed) 13:30 - 15:00, 2026

Matthias Carosi (Postdoctoral Researcher, International Centre for Theoretical Physics Asia-Pacific (ICTP-AP), University of Chinese Academy of Sciences, China)

First-order phase transitions in the early universe are a unique probe of physics beyond the Standard Model, with potential implications for electroweak baryogenesis, the formation of primordial black holes, magnetogenesis and the production of dark matter. Upcoming gravitational wave detectors may capture the imprint of such transitions, but to extract theoretical insights from these signals requires a precise understanding of the underlying dynamics. In this talk, I show how the language of non-equilibrium quantum field theory, combined with the two-particle-irreducible effective action, provides a natural framework for describing the dynamics of a bubble after nucleation. After a brief introduction to the closed-time-path formalism, I derive the dynamical equations governing the bubble and the plasma and identify all sources of friction for the bubble expansion. This framework unifies the pre-existing approaches within a single, consistent description. In the ultrarelativistic regime, I demonstrate how to compute the friction induced by the pair production of heavy scalar particles.

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

Event Official Language: English

Quantum Simulations of Entanglement in Jet Production and Structure Functions at the EIC

October 20 (Tue) 15:30 - 17:00, 2026

Dima Kharzeev (Professor, Department of Physics, University of Connecticut, USA)

The Electron–Ion Collider (EIC) offers an opportunity to explore the quantum structure of hadronic matter and the role of entanglement in high-energy scattering. I will present our results on quantum simulations of entanglement in jet production and structure functions, highlighting how quantum computing can help investigate correlations in partonic dynamics. I will discuss the physical insights emerging from these simulations and their implications for connecting quantum information concepts with observables at the EIC.

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

Event Official Language: English

Mini-Workshop: Quantum Frontiers — From Molecules to Quarks and the EIC

October 20 (Tue) 9:45 - 17:00, 2026

== Mini-workshop Program == 9:45 - 10:15 Erik Loetstedt (RIKEN) Rovibrational energy levels of molecules by quantum computing 10:15 - 10:45 Ryusuke Hamazaki (RIKEN) Quantum many-body Mpemba effect through resonances 10:45 - 11:15 Yang-yang Tan (U. Tokyo) Generative Modeling of Stochastic Dynamics for Long-Time Evolution 11:15 - 11:45 Yan Lyu (RIKEN) Charmonia scattering from lattice QCD 11:45 - 13:00 Lunch 13:00 - 13:30 Arata Yamamoto (RIKEN) Quantum anomaly for benchmarking quantum computing 13:30 - 14:00 Tianyin Li (RIKEN) Efficient Quantum Simulations of Yang-Mills theory with Maximal-tree Gauge 14:00 - 14:30 Yahui Chai (RIKEN) Probing Resonances through Real-Time Particle Scattering 14:30 - 15:00 Ermal Rrapaj (LBL) Quantum Simulations of Two-Dimensional Non-Abelian Adjoint String Breaking 15:00 - 15:30 Coffee Break 15:30 - 17:00 Dima Kharzeev (U. Connecticut) Quantum Simulations of Entanglement in Jet Production and Structure Functions at the EIC

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

Event Official Language: English

AI and Scientific Discovery

October 19 (Mon) 13:00 - 14:00, 2026

Joseph Ledsam (Google Health Lead, Japan, Google Japan)

Artificial intelligence is having a transformative impact on health and scientific discovery. This presentation will trace the evolution from foundational breakthroughs to the sophisticated capabilities of today's large-scale AI models. It will explore how these advanced systems are creating new possibilities across the healthcare landscape, from accelerating therapeutic development to enhancing diagnostic processes and interpreting complex medical data. The session will also take a deeper look at the future possibilities for AI in health and explore the emerging role of agentic AI in scientific discovery. The core theme is the responsible development of AI to create tools that assist scientists, support healthcare professionals, and empower users. Bio: Dr Joseph Ledsam leads Google Health in Japan, where he works across AI research, digital health and health in Google products. He has led research in medical AI, genomics and drug discovery published in journals including Nature, Nature Medicine and Nature Methods. Before moving to Japan he worked as a medical doctor in the UK, and founded the Health Research and Genomics teams in Google DeepMind. He obtained his medical degree from The University of Leeds, UK, and was a research fellow at University College London during his clinical residency.

Venue: #435-437, Main Research Building (Main Venue) / via Zoom

Event Official Language: English

Multi-Agent Scientific Discovery in Theoretical Quantum Physics

October 14 (Wed) 15:30 - 16:30, 2026

Sirui Lu (Ph.D. Candidate, Max Planck Institute of Quantum Optics and TU Munich, Germany)

This is a joint seminar co-hosted by Institute for Physics of Intelligence (iπ), UTokyo. Large language model agents have excelled on mathematical and coding benchmarks, but can they accelerate scientific discovery in quantum physics? In this talk, I will present a multi-agent framework that couples LLM reasoning with computational backends at increasing levels of rigor and demonstrate it through two applications: (i) co-design of quantum error-correcting codes with transversal diagonal gates via multi-agent numerical search, and (ii) formal verification of tensor network theory and MIP*=RE in Lean 4. The underlying system, TeXRA, orchestrates specialized agents and builds research and verification frameworks that connect informal physical reasoning to numerical computation and machine-checked proof.

Venue: via Zoom

Event Official Language: English

Finding your rhythm in a complex acoustic environment

October 14 (Wed) 13:00 - 14:00, 2026

Kim Hoke (Professor, Department of Biology, Colorado State University, USA)

My lab integrates genetic, transcriptomic, morphological, and physiological mechanisms to understand the striking diversity of behavior. This talk will focus on recent work on frog acoustic communication. Although the basic acoustic features of frog calls differ reliably among species, individual males of the same species differ in some acoustic properties and female frogs use those male-male differences in mate choice. And for many species, this communication is occurring in very dense choruses which can reach hundreds of males! Our current work assesses which features of calls are characteristic of individuals and how males adjust their calling based on their social environments. We hope to trace how overall chorus dynamics emerge from individual call strategies playing out in time and space, and link those individual strategies to neurobiological mechanisms. We also address the complementary question of female preferences: how do females integrate over a series of signals in this cacophony to make mate choice decisions? Together these lines of research adopt a systems approach to understand how the robust genetic and developmental processes that produce species-specific behaviors have evolved to generate the striking diversity of communication strategies frogs employ.

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

Event Official Language: English

Majorana Modes: Fundamentals, Status & Directions

October 13 (Tue) - 16 (Fri) 2026

Workshop Overview Majorana modes lie at the heart of contemporary condensed-matter physics, exhibiting non-Abelian exchange statistics; when protected by topology, they are robust against environmental perturbations. Here, “Majorana mode” is used broadly to include a localized zero-energy Majorana state (a Majorana zero mode) and chiral Majorana edge states with gapless dispersion crossing zero energy. This three-day in-person workshop returns to fundamentals and open questions. It opens with a tutorial session on the afternoon of October 13 for non-experts and adjacent fields, and emphasizes rigorous theory–experiment dialogue, robust methodology, and concrete benchmarks for realizing and testing Majorana modes. Participants Experimentalists and theorists working on Majorana modes Researchers in adjacent fields (quantum materials, superconductivity, mesoscopic physics) Graduate students and postdocs interested in entering the field Topics include (non-exhaustive) Majorana zero modes in a variety of nanostructures Chiral Majorana edge states in quantum spin liquids and other platforms Disorder, interactions, and realistic device modeling Experimental diagnostics and “smoking gun” signatures Topological Quantum Spin Systems

Venue: Okochi Hall

Event Official Language: English

From data to cohomologies of digraphs, to representations of categories

October 13 (Tue) 10:30 - 12:00, 2026

Luigi Caputi (Research Fellow, Department of Mathematics, University of Bologna, Italy)

Motivated by applications to topological data analysis, in the last years we have been witnessing a growing interest in new (topological, homological, categorical) features associated to graphs. The aim of the talk is to describe a recently developed (co)homology theory of directed graphs, called multipath cohomology, whose definition is inspired by Khovanov homology of knots. We will show its relations with more established invariants, such as chromatic homology of graphs, Hochschild homology of algebras, and matching complexes. If time allows it, we will show that the ranks of multipath cohomology, when restricted to graphs with bounded genus, grow at most polynomially in the number of edges, and that the order of its torsion is bounded. This will depend upon structural properties of (the representation category of) graphs, such as its Noetherianity properties.

Venue: #359, 3F, Main Research Building (Main Venue) / via Zoom

Event Official Language: English

Quantum Computing for Nuclear Physics (QC-NP 2026)

October 13 (Tue) - 16 (Fri) 2026

Join us for a comprehensive workshop on the application of quantum computing to nuclear physics, bringing together experts from around the world to share the latest developments and advancements in this rapidly evolving field. The workshop will cover a broad range of topics, including quantum algorithms, quantum computing hardware, and their applications to lattice field theories, gauge field theories, scattering, nuclear structure, and nuclear astrophysics. The workshop will provide ample opportunities for participants to exchange ideas, share their research, and initiate new collaborations. Through a combination of presentations and interactive discussion sessions, we aim to foster a collaborative environment that drives innovation and advances our understanding of the intersection of quantum computing and nuclear physics. [Workshop Schedule] The workshop will start from the morning of October 13 The banquet will be held on the evening of October 15 [Important Dates] Registration deadline with oral presentation: August 31, 2026 Recommended to register by: August 31, 2026 [Invited Speakers] A. Baha Balantekin (University of Wisconsin Madison) Raul Briceño (University of California Berkeley/Lawrence Berkeley National Laboratory) Philipp Höhn (Okinawa Institute of Science and Technology Etsuko Itou (Kyoto University) Dima Kharzeev (Brookhaven National Laboratory/Stony Brook University) Yuta Kikuchi (Quantinuum) Denis Lacroix (IJCLab) Dean Lee (Michigan State University) Mario Motta (IBM Quantum) Takeshi Sato (University of Tokyo) Ionel Stetcu (Los Alamos National Laboratory) Paul Stevenson (University of Surrey) Nathan Wiebe (University of Toronto) Seiji Yunoki (RIKEN) [Organizers] Ermal Rrapaj (Lawrence Berkeley National Laboratory/RIKEN, Chair) Carlo Barbieri (University of Milan) Tetsuo Hatsuda (RIKEN) Masaaki Kimura (RIKEN/University of Tokyo) Haozhao Liang (University of Tokyo) Tomoya Naito (University of Tokyo/RIKEN) Enrico Prati (University of Milan) Alessandro Roggero (University of Trento) Takeshi Sato (University of Tokyo)

Venue: Faculty of Science Bldg.1, School of Science, The University of Tokyo, Hongo Campus

Event Official Language: English

Adaptive Regulation through Model-Observation Mismatch: From Process Control to Cognitive Neurorobotics

October 8 (Thu) 13:00 - 14:00, 2026

Henrique Oyama (Postdoctoral Researcher, Cognitive Neurorobotics Research Unit, Okinawa Institute of Science and Technology Graduate University (OIST))

Adaptive behavior requires biological and artificial systems to respond when their internal models no longer match what they observe. How can such discrepancies be used not only to correct predictions, but also to regulate how a system interacts with its environment? In this talk, I will explore this question across two research directions spanning process control and cognitive neurorobotics. First, I will introduce a model predictive control framework in which a controller actively guides a nonlinear process toward informative conditions to distinguish among competing models while maintaining safe operation. I will then move to cognitive neurorobotics, where brain-inspired computational principles are used to investigate perception, prediction, and action in embodied artificial agents. In physical human-robot interaction, I will show how a predictive-coding-inspired recurrent neural network enables a humanoid robot to regulate the balance between its learned expectations and sensory information arising from human-guided movements. In particular, recent mismatches between sensory observations and the robot's internal model are used to regulate how strongly it relies on its learned dynamics or accommodates ongoing interaction. Together, these studies illustrate how model-observation mismatch can provide a general signal for adaptive regulation, connecting ideas from control engineering, artificial intelligence, neuroscience, and embodied cognition.

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

Event Official Language: English

Strong Corks: Applications and Construction

October 2 (Fri) 14:00 - 15:30, 2026

Tateaki Mukohara (Master's Student, Graduate School of Information Science, The University of Osaka)

Four-dimensional topology exhibits remarkable phenomena that are quite different from those in other dimensions. Understanding exotic phenomena in dimension four is one of the central problems in the field, but much remains mysterious. Corks are fundamental objects closely related to various exotic phenomena in dimension four. In recent years, developments in Floer theory have led to increasing interest in the study of strong corks. In this talk, I will first explain why strong corks are important, focusing on their applications to knot theory. I will then explain Floer-theoretic methods for detecting strong corks. Finally, I will present new infinite families of strong corks constructed in my work (arXiv:2601.02230) using equivariant Kirby calculus.

Venue: via Zoom / #359, 3F, Seminar Room #359

Event Official Language: English

Evolutionary Dynamics and Information Theory

October 1 (Thu) 15:00 - 16:00, 2026

Marc Harper (Data Scientist, Google Inc., USA)

We'll discuss some of the history of connections among information theory, evolutionary dynamics, and statistical inference, drawing analogies between concepts and results in these fields, for example between the replicator equation (a model of natural selection) and Bayesian inference. Time permitting, we'll continue with generalizations to finite populations with mutation and/or variations including an analogy between epigenetics from biological evolution and momentum from machine learning.

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

Event Official Language: English

Coexistence and hybridization in plant communities - lessons from mediterranean shrublands

October 1 (Thu) 13:00 - 14:00, 2026

Carmelo Gómez Martínez (Postdoctoral Researcher, Global Change Research Institute, Universidad Rey Juan Carlos, Spain)

This talk explores how two closely related Mediterranean shrubs, the rockroses Cistus ladanifer and Cistus laurifolius, share the same habitat despite being direct competitors for soil, light and pollinators. Hybridization – the natural interbreeding of two related species – often produces offspring that blend both parents' traits, and is surprisingly common in plants, including the Cistus genus. Fieldwork across Spain's Iberian Central System combining genomics, flowering timing and soil experiments shows that no single factor by itself – not genetics, climate or soil – fully explains these dynamics. The next step is to study how pollination shapes hybridization, and for that, we are developing and agent-based model that simulates bee foraging across realistic landscapes to predict new hybrid outcomes under environmental change.

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

Event Official Language: English

Mathematical Application Research Team Meeting #19

September 28 (Mon) 14:00 - 15:15, 2026

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

In this meeting, Antoine Diez will give a talk on his work in progress regarding "Scaling limits for active Laguerre tessellations."

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

Event Official Language: English

121st Data Assimilation and Prediction Science Seminar

September 28 (Mon) 14:00 - 16:00, 2026

Shunji Kotsuki

Title: "Exploring Live Cameras for Actionable Weather Prediction: Recent Studies with Chiba University’s BAECAST Network" Abstract: Numerical weather prediction has advanced substantially through improvements in observing technologies, data assimilation methods, and numerical weather prediction (NWP) models. More recently, artificial intelligence (AI) has increasingly been used to develop surrogates for NWP models and to advance nonlinear and non-Gaussian data assimilation. These developments are expected to enable more effective use of large volumes of observational data, including satellite observations. To further improve weather forecast accuracy, it is important not only to refine data assimilation methods and NWP models but also to explore new sources of observations. Our research focuses on the vast amounts of data generated by live-streaming cameras already deployed in everyday settings. Many of these cameras capture aspects of weather conditions, and harnessing this information could contribute to further improvements in weather prediction. This talk will present several studies on weather forecasting and diagnostics using live-streaming cameras installed at Chiba University. I will introduce BAECAST, an approach to visual weather forecasting, and discuss which meteorological variables can be retrieved from live-camera imagery. I will also present our efforts to transform the nature of weather forecasts using live-camera data using a conditional diffusion model.

Venue: Hybrid Format (RIKEN R-CCS room C107 and Zoom) / via Zoom

Event Official Language: English

Foundations of Quantum Programming Mini-Workshop & Contributed Talks

September 28 (Mon) - October 2 (Fri) 2026

Mingsheng Ying (Professor, University of Technology Sydney, Australia)
Hiroyuki Ochiai (Professor, Institute of Mathematics for Industry, Kyushu University)
Jianjun Zhao (Professor, Kyushu University)
Minh Canh Do (Instructor, Japan Advanced Institute of Science and Technology)

Venue: Room C502, West Zone 1 Building D, Ito Campus, Kyushu University, SUURI-COOL (Kyushu) (Main Venue) / via Zoom

Event Official Language: English