セミナー

Overview of quantum error correcting codes

2026年7月7日(火) 15:00 - 16:30

松浦 孝弥 (理化学研究所 量子コンピュータ研究センター (RQC) 量子計算理論研究チーム 特別研究員)

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Toward an understanding of microbial circulation in the Mongolian nomadic ecosystem

2026年7月6日(月) 13:00 - 14:00

篠田 あかり (岡山大学 環境生命自然科学学域)

I have been studying microorganisms in the Mongolian nomadic ecosystem from several perspectives. First, I seek to characterize the microbial communities in traditional fermented dairy products—most notably airag (fermented mare's milk)—and their features. Second, I am analyzing the relationship between the traditional Mongolian diet and the gut microbiome. Third, focusing on environmental microorganisms (bioaerosols) in regions undergoing desertification, I aim to trace their origins and atmospheric transport. In the course of these studies, I have come to suspect that microorganisms may circulate among humans, livestock, fermented foods, and the environment. In this research, I aim to understand such microbial circulation by combining approaches from each of these perspectives and by investigating the relationships among these elements. In this talk, I will provide an overview of each topic and discuss the potential of an interdisciplinary approach that connects them.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Thom polynomials relative to prescribed maps around the boundary

2026年7月3日(金) 15:00 - 17:30

田邊 真郷 (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 基礎科学特別研究員)

Thom polynomials are universal cohomological obstructions to the appearance of singularities of given types in differentiable maps. Introduced by R. Thom in the 1950s, they have been extensively studied ever since. In the first half of this talk, I would like to recall their theory with introduction of algebro-topological materials. In the second half, I would also like to talk about applications of Thom polynomials to topology of non-singular maps. Since this century, various invariants of immersions/embeddings have been expressed in terms of singularities of their extensions (a.k.a. singular Seifert surfaces). However, those formulas are obtained in different forms and remain somewhat scattered. As the first step to unify them, I would like to introduce Thom polynomials relative to prescribed maps around the boundary. As a main result, we show a structure theorem of Thom polynomials relative to framable immersions. In fact, most earlier formulas are summarized as the vanishing of "correction terms" appearing in the structure theorem. This is an advanced seminar for mathematical researchers.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Cosmic-ray bath in a past supernova gives birth to Earth-like planets

2026年7月3日(金) 14:00 - 15:15

澤田 涼 (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 基礎科学特別研究員)

A key question in astronomy is how ubiquitous Earth-like rocky planets are. The formation of terrestrial planets in our Solar System was strongly influenced by the radioactive decay heat of short-lived radionuclides (SLRs), particularly 26 Al (aluminum-26), likely delivered from nearby supernovae. However, current models struggle to reproduce the abundance of SLRs inferred from meteorite analysis without destroying the protosolar disk. We propose the "immersion" mechanism, where cosmic-ray nucleosynthesis in a supernova shockwave reproduces estimated SLR abundances at a supernova distance (~1 parsec), preserving the disk. We estimate that solar mass stars in star clusters typically experience at least one such supernova within 1 parsec, supporting the feasibility of this scenario. This suggests that Solar System─like SLR abundances and terrestrial planet formation are more common than previously thought.

会場: 研究本館 424-426号室

イベント公式言語: 英語

Gauge and Homological Structures in Quantum Error Correction

2026年7月2日(木) 16:00 - 17:00

春名 純一 (京都大学 大学院情報学研究科 特定研究員)

Gauge theory, quantum error correction, and homology theory share a common mathematical backbone that, when made explicit, becomes a practical toolkit for fault-tolerant quantum computation. A CSS code is naturally a length-2 chain complex in which the X-stabilizers act as Gauss-law generators and the code space is the gauge-invariant subspace, the toric code being the prototypical realization of a Z_2 lattice gauge theory. Building on this correspondence, I present two results. First, I introduce a gauge-field formalism in which logical gates are written as exponentials of polynomials of operator-valued cochains—the lattice gauge fields—on the underlying chain complex. Requiring no special structure on the code, the construction applies to general CSS codes and yields explicit physical-gate decompositions of logical S, H, CZ, and T gates whose action depends only on the cohomology class of the logical qubits. Second, I show that the transversal implementability of logical Pauli-Z rotations has a purely homological origin: their logical action is classified by a Z_{2^m}-module extending logical Pauli operators to higher levels of the Clifford hierarchy, and transversality is governed by compatibility and lifting obstructions on homology classes beyond the usual Z_2 coefficient. From a high-energy-physics viewpoint, a level-m transversal gate is a gauge-invariant "2^{m-1}-th root of a Wilson loop." Together these results offer a unifying language for designing logical gates and point toward fault-tolerance from lattice gauge theory and algebraic topology. This talk is based on arXiv:2511.15224 and arXiv:2602.14499.

会場: セミナー室 (359号室) 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語

Cosmology with Galaxy Shapes: Intrinsic Alignments as a Probe of Fundamental Physics

2026年7月2日(木) 14:00 - 16:00

奥村 哲平 (Research Fellow, ASIAA, Academia Sinica, Taiwan)

Galaxies in the Universe are not oriented randomly. Their shapes exhibit coherent alignments across cosmological scales due to the surrounding tidal gravitational field. For many years, these intrinsic alignments were regarded mainly as a contaminating effect in weak gravitational lensing observations. In recent years, however, they have emerged as a new cosmological probe, complementary to conventional galaxy-clustering analyses.  In this talk, I will review recent theoretical and observational developments that establish galaxy shapes as a tool for studying the growth of cosmic structure and testing gravity on cosmological scales. I will present the first measurements demonstrating that intrinsic galaxy alignments can constrain cosmological parameters directly from observational data. The results are consistent with general relativity and provide information complementary to traditional galaxy-clustering analyses. I will also discuss future prospects for using galaxy alignments to probe dark energy, modified gravity, gravitational waves, and the physics of the early Universe with next-generation galaxy surveys.

会場: セミナー室 (359号室) 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語

120th Data Assimilation and Prediction Science Seminar

2026年7月2日(木) 14:00 - 16:00

Upmanu Lall (Professor, Columbia University, USA)
Mengqian Lu (Professor, Hong Kong University of Science and Technology, Hong Kong)
Hyun-Han Kwon (Professor, University of Seoul, Republic of Korea)

Speaker: Professor Lall (Columbia University) Title: "Taming the Storm: Can We Predict, Engineer, and Reduce Losses from Climate and Weather Extremes?" Abstract: Climate and weather extremes — storms, heat waves, floods, droughts, and compound events — have become the defining natural hazard challenge of the 21st century. Their growing frequency and intensity are overwhelming engineered infrastructure, disrupting global supply chains, and propagating risks across societies through teleconnections that no single country can insulate itself against. While climate change mitigation through decarbonization remains an urgent priority, even optimistic emissions trajectories leave us facing decades of increasing exposure. Climate adaptation efforts — improved infrastructure design, financial instruments, early warning systems — are essential but are constrained by limited data, deep uncertainty in future projections, and the diffuse question of who bears responsibility for action. This talk argues that a third pillar is emerging and demands serious scientific and institutional attention: Climate Stabilization, or the deliberate modification of developing weather and climate extremes to reduce their societal impact. Rather than waiting for disasters to unfold and recovering afterward, this paradigm asks whether the physical dynamics of the atmosphere offer leverage points — windows in time and space — where strategically placed, small perturbations could redirect the trajectory of an extreme event. This is the core idea of Weather Jiu-Jitsu: exploiting the inherent instabilities and nonlinear sensitivities of atmospheric circulation to achieve large-scale redirection of an extreme using energy borrowed from the circulation itself, not brute-force external forcing. J The talk will address the foundational questions this agenda raises for a forecasting and Earth science community: What physical mechanisms enable or constrain atmospheric steering? How can ensemble prediction systems, adjoint methods, and emerging AI tools be harnessed to identify intervention points and compute impact outcomes with spatial specificity? What are the data and modeling gaps? How do we frame the ethical and governance dimensions as this moves from laboratory curiosity to potential operational deployment and commercial application?  I will sketch a research roadmap integrating chaos-informed perturbation theory to AI-enabled adaptive control optimization that builds on AI-accelerated impact forecasting to provide the foundation for Climate Stabilization as a rigorous scientific enterprise and, within a decade, a viable business with measurable returns to investors and societies alike. We hope that this will stimulate discussion with RIken's Moonshot Goal 8 program, which is exploring similar scientific and technological frontiers. Speaker: Professor Mengqian Lu (Hong Kong University of Science and Technology) Title: Bridging Climate Data to Actionable Decision-Making Across Industries Abstract: Extreme weather is escalating—impacting infrastructure, supply chains, and profitability across the world. At the same time, sustainability targets demand that businesses go green without sacrificing growth. The question is no longer if climate risk matters, but how to act on it—quickly and smartly. This talk presents climate solutions that combine advanced climate modeling with AI to deliver industry-specific, actionable insights. Developed at HKUST through the Center for Climate Resilience and Sustainability (CCRS) and the World Sustainable Development Institute (WSDI), this AI–dynamical hybrid system is already being applied across key sectors, including renewable energy, Arctic logistics, and disaster risk management. These tools enable organizations to make faster, more informed decisions under uncertainty. Backed by UNESCO and the WMO, this Research-to-Operation (R2O) framework turns complex climate data into operational tools that drive resilience, reduce losses, and uncover new opportunities. Real-world case studies will be shared to spark cross-sector collaboration between science, business, and policy. Speaker: Professor Hyun-Han Kwon (University of Seoul) Title: Bayesian Mixture Extreme-Value Modeling of Nonstationary Extreme Precipitation Across U.S. Regions Abstract Extreme precipitation is a major driver of flood risk, infrastructure stress, and climate-related disaster losses. However, annual maximum rainfall often reflects multiple physical mechanisms, including frontal or convective systems, tropical-cyclone-related rainfall, and transitional atmospheric regimes. Treating these extremes as samples from a single homogeneous process can obscure how regional rainfall risks are changing. This talk presents an ongoing study of nonstationary extreme precipitation using a Bayesian mixture extreme-value model. The model represents annual maximum daily precipitation as a combination of latent low- and high-intensity rainfall regimes, with time-varying component behavior and regime probabilities. This allows changes in return levels to be separated into contributions from baseline rainfall intensity, high-intensity event magnitude, and the probability of entering an extreme-producing regime. The framework is applied to long-term U.S. station records across the Southeast/Gulf, Mid-Atlantic, Northeast, and inland-control regions. Tropical-cyclone proximity and ERA5-based atmospheric diagnostics are used as external physical evidence, rather than as imposed predictors in the likelihood, to interpret the latent high-intensity regime and its regional variability. The broader goal is to move extreme-value analysis beyond stationary design estimation toward mechanism-aware and decision-relevant understanding of climate risk. By linking Bayesian uncertainty quantification, hydrometeorological interpretation, and regional comparison, this work provides a basis for improved infrastructure planning, impact-based forecasting, and future AI-enabled climate risk services.

会場: Hybrid Format (RIKEN R-CCS room C107 and Zoom)

イベント公式言語: 英語

Genome Structural Variation and the Evolutionary Potential of Sex in the Unicellular Green Alga Closterium

2026年7月2日(木) 13:00 - 14:00

川口 也和子 (国立遺伝学研究所 分子生命史研究室 博士研究員)

Genome size varies widely among eukaryotes, even between closely related species and within species. However, we still know relatively little about where such variation originates, how organisms tolerate its potential negative effects, and whether it can contribute to adaptation. In this seminar, I will present our studies on the unicellular green alga Closterium peracerosum–strigosum–littorale complex. I will first show that genome size variation in this alga is largely explained by extensive genome-wide copy number variation, and that gene expression can be buffered against changes in gene copy number. I will then show that a single episode of sexual reproduction can generate substantial variation in population growth rates under dual environmental stressors, with some F1 populations growing even when both parental strains decline. Finally, I will discuss how sexual reproduction may drive rapid evolutionary change not only by reshuffling alleles, but also by rearranging genome structure.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Phase Transitions as the Breakdown of Statistical Indistinguishability

2026年6月29日(月) 15:00 - 16:00

宮原 英之 (北海道大学 大学院情報科学研究院 准教授)

We introduce a novel characterization of phase transitions based on hypothesis testing. In our formulation, a phase transition is defined as the breakdown of statistical indistinguishability under vanishing parameter perturbations in the thermodynamic limit. This perspective provides a general, order-parameter-free framework that does not rely on model-specific insights or learning procedures. We show that conventional approaches, such as those based on the Binder parameter, can be reinterpreted as special cases within this framework. As a concrete realization, we employ a distribution-free two-sample run test and demonstrate that the critical point of the two-dimensional Ising model is accurately identified without prior knowledge of the order parameter.

会場: セミナー室 (359号室) 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語

Primitive Ideals and Hilbert Space Representations of Quantized Coordinate Algebras of Complex Semisimple Lie Groups

2026年6月26日(金) 16:30 - 18:00

Heon Lee (Postdoc Researcher, Institute for Advanced Study in Mathematics, Harbin Institute of Technology, Republic of Korea)

The primitive ideals of the coordinate algebra $ \mathcal{O} ( G ) $ of a complex semisimple Lie group $ G $ are in bijection with the points of $ G $, via the correspondence assigning to each point of $ G $ the kernel of the associated evaluation homomorphism on $ \mathcal{O} ( G ) $. This establishes a direct link between the algebraic structure of $ \mathcal{O} ( G ) $ and the geometry of $ G $. In this talk, we investigate the quantum analogue of this classical relationship for the $ q $-deformation $ G_q $. Specifically, we establish a sharp dichotomy: primitive ideals in homogeneous Joseph strata arise as kernels of irreducible representations of $ \mathcal{O} ( G_q ) $ by bounded operators on Hilbert spaces, which provide a quantum analogue of evaluation homomorphisms at points of $ G $, whereas those in inhomogeneous Joseph strata do not. This clarifies the extent to which the primitive spectrum of $ \mathcal{O} ( G_q ) $ can be accessed through operator-theoretic methods. We also analyze the semiclassical consequences of this result in light of the fact that the primitive ideals of $ \mathcal{O} ( G_q ) $ are parametrized by the symplectic leaves of the natural Poisson structure on $ G $. This talk is based on joint work with Christian Voigt.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語

Symmetry origin of the quantum-classical transition, hydrodynamics, and decodability.

2026年6月26日(金) 14:00 - 16:00

Cenke Xu (Professor, University of California, Santa Barbara, USA)

We discuss the following question: when a quantum system evolves into classical one, is there a sharp transition? We will show that the “strong-to-weak” spontaneous symmetry breaking (SW-SSB) provides a sharp onset of classical physics. We present the theoretical framework and summarize recent experimental progress toward observing SW-SSB. We will also discuss the consequence of the SW-SSB, including the emergence of hydrodynamics, and also its information aspect, such as the transition of decodability and distinguishability. Much of the theoretical analysis maps to a problem of defect in the Euclidean spacetime.

会場: セミナー室 (359号室) 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語

Classical and quantum computing of Nash equilibria of two-player games

2026年6月25日(木) 10:30 - 11:30

エリック・ローツステット (理化学研究所 数理創造研究センター (iTHEMS) 数理展開部門 量子数理科学チーム 上級研究員)

Nash equilibrium is an important concept in game theory. However, finding mixed-strategy Nash equilibria is computationally hard even for relatively small games. I will review some aspects of the numerical computation of Nash equilibria of two-player games including the Lemke-Howson algorithm. I will also discuss preliminary attempts at solving the Nash equilibrium problem on a quantum computer by the quantum approximate optimization algorithm.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Fermionic modes of D-instanton wormholes from broken local supersymmetry

2026年6月24日(水) 15:30 - 17:00

糸山 浩司 (大阪公立大学 南部陽一郎物理学研究所 特任教授)

In low-energy supergravity treatment of type IIB superstring on general D-instanton wormhole profiles in the bulk, we obtain non-vanishing scalar two-point functions in addition to the vanishing　〈τ＊τ＊〉 that corresponds to the BPS amplitude detected by two D-instantons at their respective boundaries. This is exploited to show that the modes of broken local supersymmetry in the bulk deliver the fermionic (diagonal) modes on the boundaries through the deformation by the form of current-current two point functions propagating on the tree level cylinder geometry. Our treatment is generalizable to multi D-instanton cases and general Euclidean branes.

会場: 研究本館 3階 359号室 (メイン会場) / via Zoom

イベント公式言語: 英語

Machine-learned fixed-point actions and observables for SU(3) lattice gauge theory

2026年6月24日(水) 10:30 - 11:30

Müller David (Postdoctoral Researcher, Institute for Theoretical Physics, TU Wien, Austria)

Lattice regularization is the established approach for studying non-perturbative phenomena in quantum chromodynamics, but accurate predictions for the continuum theory remain challenging because standard actions exhibit large lattice artifacts. The renormalization group on the lattice provides a way of suppressing these artifacts: classically perfect fixed-point (FP) actions. In this talk, I show how gauge-equivariant neural networks yield accurate parametrizations of FP actions. Using these machine-learned actions, we perform Monte Carlo simulations to measure gradient-flow scales with highly suppressed artifacts compared to unimproved actions. I will also present preliminary results for machine-learned FP observables to improve the extraction of the topological susceptibility in four-dimensional SU(3) gauge theory.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Gravitational Properties of the Monopole Bag

2026年6月23日(火) 13:30 - 15:30

Yu Komiya (京都大学 基礎物理学研究所 博士課程)

Processes such as phase transitions and symmetry breaking in the early universe are well-studied and thought to be instrumental in giving rise to the nature and composition that we observe. In particular, axionic cosmologies constitute a class of phenomenologically rich models with symmetry breaking, UV relevance, and potentially detectable consequences. In the case where monopoles are also present in such a background, the axion profile may be deformed; it is possible to construct a "monopole bag" state composed of a central monopole within a closed axion domain wall. We consider the gravitational properties of this hybrid defect, and find a both horizon-less and a black hole-like final state can result as remnants of the monopole-domain wall system after gravitational collapse for different input parameters

会場: セミナー室 (359号室) 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語

iTHEMS Cosmology Forum n°6 - Cosmological Collider Physics

2026年6月22日(月) 9:15 - 17:00

Yi Wang (Professor, Department of Physics, Hong Kong University of Science and Technology, Hong Kong)
山口 昌英 (Director, Center for Theoretical Physics of the Universe, Institute for Basic Science, Republic of Korea)
向田 享平 (高エネルギー加速器研究機構 (KEK) 理論センター 助教)
秋津 一之 (R&D, Proxima Technology)

This sixth workshop will bring together researchers exploring the physics of the early universe through cosmological collider signatures. Primordial non-Gaussianities generated during inflation provide a unique opportunity to probe heavy particles and high-energy interactions in the early universe, potentially accessing energies much larger than that probed by terrestrial experiments. In recent years, the subject has developed rapidly, incorporating ideas from inflationary cosmology, quantum field theory in curved spacetime, effective field theory, and scattering amplitudes.

会場: 大河内記念ホール

イベント公式言語: 英語

The Virasoro TQFT approach to 3D gravity and the sum over topologies (QuIG Seminar)

2026年6月19日(金) 13:30 - 16:00

Mengyang Zhang (東京大学 カブリ数物連携宇宙研究機構 (Kavli IPMU) 特任研究員)

In the first part of this talk, I will review the construction of Virasoro TQFT from the Chern–Simons formulation of pure AdS_3 gravity and its application to the statistics of two-dimensional holographic CFT data. I will then discuss its extension to three-dimensional de Sitter gravity and its relation to the double-scaled SYK model. In the second part, I will address the issue of topological invariance in Virasoro TQFT. Despite being “topological,” its partition function is not well-defined on arbitrary three-manifolds, distinguishing it from conventional Reshetikhin–Turaev–Witten TQFTs. I will explain how far the standard proofs of topological invariance can be generalized to this framework. Finally, I will comment on the role of the sum over topologies in the 3D gravitational path integral.

会場: via Zoom / 研究本館

イベント公式言語: 英語

Improving data analysis in biology and in general with Tensor Decomposition

2026年6月18日(木) 13:00 - 14:30

リュカ・ソール (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 数理遺伝学理研ECL研究ユニット 特別研究員)

This talk will provide an introduction to the basic principles of tensor decomposition methods, especially CANDECOMP/PARAFAC (CP) decomposition. I will explain how such methods can be used to extract meaningful and interpretable patterns from high-dimensional tensor-structured data, which commonly arises in biology, as well as in a broad range of other scientific domains. These patterns can then be used to gain a better understanding of the phenomena under study. I will also briefly discuss how tensor decomposition methods can be extended for various types of data, focusing in particular on how I have been trying to better model longitudinal data.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語

Prediction of viral evolution and exploration of next-pandemic viruses

2026年6月15日(月) 15:00 - 16:00

伊東 潤平 (大阪大学 微生物病研究所 附属バイオインフォマティクスセンター 教授)

One of the major challenges in controlling viral infectious diseases is that viruses continuously alter their properties through evolution. During the COVID-19 pandemic, for example, variants with enhanced immune escape and increased fitness emerged successively, thereby making epidemic control substantially more difficult. In this seminor, I will introduce our research on understanding and predicting viral evolution and epidemic dynamics by integrating protein language models, massive viral genome sequence data, and large-scale experimental datasets to model the relationships among viral genotypes, antigenicity, and fitness. Another major factor complicating the control of viral infectious diseases is the cross-species transmission of viruses harbored by wild animals to humans and livestock, leading to the emergence of novel infectious diseases. The COVID-19 pandemic, for instance, is thought to have originated from a coronavirus carried by horseshoe bats that subsequently spilled over into humans. To prepare for future pandemics, it is essential to comprehensively identify and systematically catalog viruses circulating in wildlife populations. In this seminar, I will also present our research on efficiently discovering novel viruses from massive public RNA-seq datasets by predicting viral infection based on host immune responses.

会場: セミナー室 (359号室) (メイン会場) / via Zoom

イベント公式言語: 英語

Patient-adaptive medical AI: Similarity-based fine-tuning for cross-patient generalization

2026年6月15日(月) 14:00 - 15:00

趙 旭陽 (大阪大学 大学院医学系研究科・医学部 助教)

Medical AI models often face performance degradation when applied to new patients due to inter-patient variability in physiological characteristics, disease manifestations, and clinical histories. This challenge, commonly referred to as the cross-patient problem, limits the generalizability and clinical applicability of machine learning systems. We introduce a similarity-driven framework for patient-adaptive learning that improves model performance on previously unseen patients. The proposed approach first trains a base model using conventional supervised learning and subsequently estimates the similarity between a target patient and the training population using intermediate model representations. The similarity information is then incorporated into a fine-tuning procedure through patient-dependent weighting, enabling the model to adapt its decision boundaries toward the characteristics of each individual patient. We demonstrate the effectiveness of this strategy in two medical AI applications, including seizure onset zone classification in epilepsy and medical image classification tasks. Experimental results show consistent improvements over standard cross-patient learning approaches, highlighting the potential of similarity-based adaptation as a practical solution for personalized and generalizable medical AI systems.

会場: 研究本館 3階 359号室とZoomのハイブリッド開催

イベント公式言語: 英語