Seminar

A one-world interpretation of quantum mechanics

January 16 (Fri) 14:00 - 16:00, 2026

Isaac Layton (Postdoctoral Researcher, Department of Physics, Graduate School of Science, The University of Tokyo)

The measurement problem arises in trying to explain how the objective classical world emerges from a quantum one. In this talk I’ll advocate for an alternative approach, in which the existence of a classical system is assumed a priori. By asking that the standard rules of probability theory apply to it when it interacts with a system linearly evolving in Hilbert space, I’ll show that with a few additional assumptions one can recover the unitary dynamics, collapse and Born rule postulates from quantum theory. This gives an interpretation of quantum mechanics in which classically definite outcomes are always assigned probabilities, rather than superpositions, giving one-world instead of many. The main technical tool used is a change of measure on the space of classical paths, the functional form of which characterises the quantum dynamics and Born rules of a class of quantum-like theories. Time allowing, I will also discuss how these results clarify which additional assumptions must be accepted if one wishes to seriously consider classical alternatives to quantum gravity.

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

Event Official Language: English

Median-based estimators for randomized quasi-Monte Carlo integration

January 9 (Fri) 15:00 - 17:00, 2026

Kosuke Suzuki (Associate Professor, Yamagata University)

High-dimensional numerical integration is a ubiquitous challenge across various fields, from mathematical finance to computational physics and Bayesian statistics. While standard Monte Carlo (MC) methods are robust, their probabilistic error convergence rate of $O(N^{-1/2})$ is often insufficient for demanding applications. In this talk, I will introduce Quasi-Monte Carlo (QMC) and Randomized QMC (RQMC) methods, which offer a powerful framework for accelerating integration using low-discrepancy point sets. A key advantage of this deterministic approach is its ability to achieve a convergence rate of $O(N^{-1+\epsilon})$, significantly outperforming the standard MC rate. The second part of the talk will focus on the construction of point sets, specifically lattice rules and digital nets. I will explain how these methods achieve higher-order convergence rates, faster than $O(N^{-1})$, for sufficiently smooth integrands. I will also discuss their randomized variants and demonstrate how RQMC with mean-based estimators provides practical error estimation while maintaining high-order convergence. Finally, I will discuss recent progress in RQMC involving median-based estimators. I will highlight how these estimators achieve almost optimal convergence rates for various function spaces without requiring prior knowledge of the integrand.

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

Event Official Language: English

Higher Gauge Structures and Invariant Action Principles

January 6 (Tue) 15:15 - 16:15, 2026

Sebastián Salgado (External Researcher, Instituto de Alta Investigacion, Universidad de Tarapaca, Chile)

I present the systematic construction of gauge theories based on free differential and L-infinity algebras. This provides a consistent algebraic framework for constructing gauge-invariant theories whose field content is extended by higher-degree differential forms as gauge potentials. I derive explicit expressions for the corresponding extended Chern-Simons actions and the generalized anomaly terms that emerge from them. Possible applications to gravity and supergravity will also be discussed.

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

Event Official Language: English

Invitation to Random Tensor Models: from random geometry, enumeration of tensor invariants, to characteristic polynomials

January 6 (Tue) 13:30 - 14:30, 2026

Reiko Toriumi (Associate Professor, Okinawa Institute of Science and Technology Graduate University (OIST))

I will introduce random tensor models by first reviewing their motivation coming from random geometric approach to quantum gravity. Then, I will selectively present some of the interesting research results, by highlighting recent results on enumeration of graphs representing tensor invariants, and reporting our recent work on a new notion of characteristic polynomials for tensors via Grassmann integrals and distributions of roots of random tensors. The latter two are based on arXiv:2404.16404[hep-th] and arXiv:2510.04068[math-ph]

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

Event Official Language: English

Topological Image Analysis

December 25 (Thu) 12:00 - 13:00, 2025

Shizuo Kaji (Professor, Institute of Mathematics for Industry, Kyushu University)

Topological Data Analysis (TDA) applies algebraic topology to the study of data such as point clouds. When applied to image and volumetric data, TDA provides a way to capture the topological features that characterise shapes and spatial structures. In this talk, I will outline the strengths and limitations of TDA for image analysis, and compare its capabilities with those of deep neural networks. I will also present hands-on examples using our open-source software Cubical Ripser. Finally, I will highlight a new direction in the use of TDA for image processing.

Venue: Room C501, West Zone 1 Building D, Ito Campus, Kyushu University, SUURI-COOL (Kyushu) (Main Venue) / via Zoom

Event Official Language: English

Origin and evolutionary history of an urban underground mosquito

December 18 (Thu) 13:00 - 14:00, 2025

Yuki Haba (Postdoc, Zuckerman Institute, Columbia University, USA)

Urbanization is rapidly reshaping landscapes around the world, which poses questions about whether and how quickly animals and plants can adapt. Culex pipiens form molestus, more commonly known as the "London Underground mosquito," has been held up as a benchmark for the potential speed and complexity of urban adaptation. This intraspecific lineage within Cx. pipiens, a major West Nile virus vector, is purported to have evolved human biting and a suite of other human-adaptive behaviors in the subways and cellars of northern Europe within the past 200 years. Form molestus features prominently in textbooks as well as scholarly reviews of urban adaptation. Yet, the hypothesis of in situ urban evolution has never been rigorously tested. I will talk our recent efforts to understand the contentious origin and evolutionary history of the urban, human-biting mosquito. Our synthesis and meta-analysis of rich yet confusing literature show that its London Underground origin is unlikely (Haba and McBride 2022 Current Biology). Whole genome resequencing and population genomics of 800+ mosquitoes across ~50 countries again debunk the in situ evolution hypothesis and instead support that molestus first adapted to human environments >1000 years ago in the Mediterranean or Middle East, most likely in ancient Egypt or another early agricultural society (Haba et al. 2025 Science). I will outline implications of our results in urban evolutionary biology as well as in public health. Speaker Bio Yuki Haba, Ph.D., is an evolutionary biologist passionate about understanding how and why diverse behaviors evolve in nature. He is currently a Leon Levy Scholar in Neuroscience at Columbia University's Zuckerman Mind Brain Behavior Institute. He aims to take multi-desciplinary approaches, combining genomics, neuroscience, and field-based behavioral ecology to comprehensively understand the evolution of behavior. Yuki completed his PhD at Princeton, MA at Columbia, and undergraduate degree at the University of Tokyo. Personal webpage: https://yukihaba.github.io/

Venue: Seminar Room #359

Event Official Language: English

A bi-fidelity Asymptotic-Preserving Neural Network approach for multiscale kinetic problems

December 17 (Wed) 11:00 - 12:00, 2025

Liu Liu (Assistant Professor, Department of Mathematics, The Institute of Mathematical Sciences, The Chinese University of Hong Kong, Hong Kong)

In this talk, we will introduce a bi-fidelity Asymptotic-Preserving Neural Network (BI-APNNs) framework, designed to efficiently solve forward and inverse problems for the linear Boltzmann equation. Our approach builds upon the previously studied Asymptotic-Preserving Neural Network (APNNs), which employs a micro-macro decomposition to handle the model’s multiscale nature. We specifically address a bottleneck in the original APNNs: the slow convergence of the macroscopic density in the near fluid-dynamic regime. This strategy significantly accelerates the training convergence as well as improves the accuracy of the forward problem solution, particularly in the fluid-dynamic limit. We show several numerical experiments on both linear Boltzmann and the Boltzmann-Poisson system that this new BI-APNN method produces more accurate and robust results for forward and inverse problems compared to the standard APNNs. This is a joint work with Zhenyi Zhu and Xueyu Zhu.

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

Event Official Language: English

Phase transition in parametrized quantum circuits

December 16 (Tue) 10:00 - 12:00, 2025

Xiaoyang Wang (Postdoctoral Researcher, Quantum Mathematical Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))

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

Event Official Language: English

RIKEN Quantum hands-on seminar on IBM and QEDMA software for quantum computing beginners

December 15 (Mon) 9:30 - 12:20, 2025

This seminar will be conducted in a hybrid format, both in-person and via Zoom. Since it includes hands-on sessions, we kindly ask you to consider attending in person whenever possible to ensure more effective learning. The overview of the seminar is as follows: Program: 9:30 - 10:50 Yuri Kobayashi (IBM Quantum) "Introduction to IBM Quantum and Qiskit" 10:50 - 11:00 Break 11:00 - 12:20 Ori Alberton (QEDMA) "Introduction to QESEM error mitigation software: Theory,  use-case demonstrations and usage tutorial" Abstract of Yuri Kobayashi's tutorial: This talk introduces HPC researchers to the IBM Quantum platform and the Qiskit SDK, providing a practical orientation to quantum programming without assuming prior quantum-computing knowledge. Attendees will learn how to construct and execute quantum circuits using Qiskit, explore available simulators, and real quantum backends and submit jobs to IBM’s cloud-based quantum processors. The session will also showcase how to map your problem to quantum circuits through specific use-case applications. Abstract of Ori Alberton's tutorial: This talk introduces QESEM, Qedma’s characterization-based software tool for reliable, high-accuracy quasi-probabilistic error mitigation. We will begin by explaining why error mitigation methods are expected to be the first to unlock quantum advantage, and why they will continue to play a central role even as error correction becomes feasible. We will highlight some of the key innovations underlying QESEM’s operation and present recent results on IBM Heron r2 devices demonstrating its capabilities in the largest utility-scale unbiased error mitigation experiment to date. In addition different use-cases and demonstrations ran by QESEM users will be presented. Finally, we will provide guidance on how to start using QESEM to obtain error-mitigated results in experiments on IBM quantum systems.

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

Event Official Language: English

Fracture squares and separable algebras

December 12 (Fri) 16:00 - 17:30, 2025

Luca Pol (Postdoctoral Researcher, Max Planck Institute for Mathematics in Bonn, Germany)

In this talk I will present a way to reconstruct a category from its subcategories of complete and local objects while retaining the symmetric monoidal structure. As an application of this machinery I will discuss how to calculate separable algebras in equivariant homotopy theory.

Venue: via Zoom / 3F 345-347 Seminar Room, Main Research Building

Event Official Language: English

Widespread conservation of genetic effect sizes between human groups across traits

December 12 (Fri) 13:30 - 15:00, 2025

Simon Robert Myers (Professor, University of Oxford, UK)

Understanding genetic differences between populations is essential for avoiding confounding in genome-wide association studies and improving polygenic score (PGS) portability. We developed a statistical pipeline to infer fine-scale Ancestry Components and applied it to UK Biobank data. Ancestry Components identify population structure not captured by widely used principal components, improving stratification correction for geographically correlated traits. To estimate the similarity of genetic effect sizes between groups, we developed ANCHOR, which estimates changes in the predictive power of an existing PGS in distinct local ancestry segments. ANCHOR infers highly similar (estimated correlation 0.98 ± 0.07) effect sizes between UK Biobank participants of African and European ancestry for 47 of 53 quantitative phenotypes, suggesting that gene–environment and gene–gene interactions do not play major roles in poor cross-ancestry PGS transferability for these traits in the United Kingdom, and providing optimism that shared causal mutations operate similarly in different populations.

Venue: via Zoom / Seminar Room #359

Event Official Language: English

From perturbations of operators to noncommutative condensers

December 11 (Thu) 16:00 - 17:00, 2025

Dan Voiculescu (Professor, Department of Mathematics, University of California, Berkeley, USA)

A numerical invariant, the quasicentral modulus underlies the multivariable generalizations of the classical Weyl-von Neumann-Kuroda and Kato-Rosenblum theorems. There are also connections to the Kolmogorov-Sinai dynamical entropy. I will also point out some of the open problems. Recently a noncommutative analogy with condenser capacity in nonlinear potential theory is emerging, that provides a new perspective on the subject.

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

Event Official Language: English

Self-organized mechano-chemical instabilities drive the emergence of tissue morphogenesis in digit organoids

December 11 (Thu) 13:00 - 14:00, 2025

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

Tissue morphogenesis is an emergent phenomenon: macroscopic structures cannot be predicted from a mere list of genes and cells. We examine here how digits arise from a spherical limb bud and present a framework linking microscopic cellular behavior to morphogenesis. To extract digit morphogenesis in vitro, we created a limb-mesenchyme organoid that breaks symmetry and forms digit-like cartilage. Analyzing cell behavior, iterating between experimental evidence and cellular-based models, shows that microscopic mechanisms like differential adhesion between distal and proximal autopod cells, chemotaxis toward Fgf8b, and biased traction can drive tissue-wide deformations by convergent extension that eventually lead to the formation of digit structures. Taking the continuum limit of these microscopic rules yields a modified Cahn–Hilliard equation, that is well known to describe fluid interfaces and so-called fingering instabilities, but that is shown here to recapitulate well organoid morphogenesis. Taken together, this work suggests that the emergence of “fingers” can be explained in a theoretical framework as a type of fingering instability.

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

Event Official Language: English