セミナー

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

Which Cosmological EFTs Survive the UV? A first step from quantum consistency to late-time cosmology

2026年6月15日(月) 10:00 - 11:30

Carlos Pastor-Marcos (Ph.D. Student, ITP, Heidelberg University, Germany)

EFTs for cosmology are one of our best tools to describe possible departures from GR in the Universe we observe. However, not every low-energy theory can arise from a consistent quantum theory at high energies. In this talk, I will discuss how this question can be addressed using asymptotic safety (AS), and how UV consistency can constrain the space of viable modified-gravity EFTs. Instead of treating all EFT parameters as equally possible, we can ask which regions of theory space are connected to a well-defined fixed point in the UV. This provides the first ingredients of a UV-to-IR strategy, restricting the allowed low-energy theories and indicating how quantum-gravity information may reach cosmology. I will first give a pedagogical introduction to AS and the functional RG, focusing on the physical picture rather than technical details. I will then apply the framework to generalized Proca theories, a class of vector–tensor modified-gravity EFTs with relevant cosmological applications, to illustrate how this analysis is performed in practice and how it can constrain viable IR theories. I will close by discussing how UV completion can become a practical guide for cosmology, translating quantum-consistency conditions into phenomenological signatures, from late-time modified gravity to early-universe observables, strong-gravity tests and GW probes.

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

Noncritical Conformal Gravity and 4D Liouville Theory

2026年6月12日(金) 15:00 - 16:30

太田 信義 (大阪公立大学 南部陽一郎物理学研究所 客員教授)

We study the quantum aspects of the conformal gravity in four dimensions, specifically addressing a known discrepancy in beta functions between general quadratic curvature theories and conformal gravity, which corresponds to two scalar degrees of freedom. We demonstrate that this mismatch is resolved by carefully introducing gauge-fixing and ghost terms via the BRST symmetry, which effectively adds the two scalar modes. Drawing lessons from two-dimensional quantum gravity and Liouville theory, we proceed to integrate the four-dimensional trace anomaly to derive a consistent Liouville action, which is given by a free-field action for the conformal mode with a consistent conformal anomaly. We give the condition that the BRST transformation is anomaly free. Finally I would like to talk about some application of this theory.

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

Testing quantum gravity

2026年6月12日(金) 10:30 - 12:00

Daniel Carney (Scientist, Lawrence Berkeley National Laboratory (LBNL), USA)

I will give an overview of proposals to test the quantization of the gravitational field using terrestrial experiments. This will include gravitational entanglement experiments, "single-graviton detection" experiments, and searches for anomalous gravitational noise and decoherence.

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

Quantum Improved Black Holes in Asymptotically Safe Gravity

2026年6月11日(木) 15:00 - 16:30

Chiang-Mei Chen (Professor, Department of Physics, National Central University, Taiwan)

In this talk, I will explore quantum-improved black hole solutions within the framework of asymptotic safety. In this approach, the Newton coupling becomes scale-dependent, necessitating a meaningful identification between the energy scale and a corresponding physical (length) scale to derive observable consequences for black hole spacetimes. I will argue that the requirement of consistency with the first law of black hole thermodynamics provides a physically motivated criterion for this scale-setting, particularly near the event horizon. Applying this principle, we propose a specific identification scheme that leads to a regularized geometry capable of resolving the ring singularity of Kerr black holes.

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

Mode Estimation in the Space of Phylogenetic Trees with Applications to Species Tree Reconstruction

2026年6月11日(木) 13:00 - 14:00

髙澤 祐槻 (東京大学 大学院情報理工学系研究科 特任助教)

Analyzing samples of phylogenetic trees arises in many settings, including bootstrap tree sets, Bayesian posterior samples, and collections of gene trees. The Billera–Holmes–Vogtmann (BHV) tree space provides a geometric framework in which such samples can be viewed as point clouds in a common metric space. A fundamental summary in this space is the Fréchet mean, but it has a property known as stickiness: mean trees tend to lie on lower-dimensional boundaries of the space, corresponding to unresolved, non-binary trees. This behavior can be undesirable, as the mean may then fail to represent the center of interest. In this talk, I will introduce the BHV tree space framework and discuss mode estimation as an alternative way to summarize distributions of phylogenetic trees. After motivating the use of the mode, I will present simple approaches to mode estimation and discuss their consistency and robustness properties. I will then discuss how these ideas can be applied to species tree reconstruction from conflicting gene trees. To handle larger taxon sets, I will use quartet-based aggregation, in which local modal summaries are constructed from trees restricted to sets of four taxa and then combined to reconstruct a species tree. This approach provides a scalable way to apply mode estimation to trees with many taxa and helps reduce the influence of contamination in gene tree collections, as illustrated in simulation studies.

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

Disorder and Defects in Critical Systems

2026年6月8日(月) 13:30 - 15:00

Baishali Roy (Postdoctoral Fellow, Indian Institute of Technology Kanpur, India)

Real critical systems are often constrained by boundaries and affected by impurities. In 3d, the effect of disordered impurities on the boundary can be modeled by a random magnetic field on a two-dimensional defect. In this talk, I will discuss how such disorder affects the Wilson-Fisher fixed point in d=4−\epsilon dimensions. By analyzing the one-loop RG flow of the defect couplings using the replica formalism, we find a non-trivial "dirty" fixed point which represents a new boundary universality class, stabilized by the bulk \phi^4 interaction. Disordered systems at critical points are known to exhibit logarithmic behavior — I will also discuss how operator mixing in the replica limit gives rise to a logarithmic defect CFT in our setup.

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

Classification of certain actions of representation categories

2026年6月5日(金) 15:00 - 17:00

星野 真生 (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)

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.

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

reflection positivity in de Sitter space

2026年6月5日(金) 10:30 - 11:30

鈴木 優樹 (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)

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

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

2026年6月4日(木) 15:00 - 16:00

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.

会場: via Zoom

イベント公式言語: 英語

Membrane Geometry Regulates Phase Morphology in Postsynaptic Condensates

2026年6月4日(木) 14:00 - 15:00

山田 莉彩 (京都大学 大学院理学研究科 生物科学専攻 博士課程)

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.

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

Generative diffusion model with inverse renormalization group flows

2026年6月2日(火) 14:00 - 15:00

増木 貫太 (東京大学 大学院理学系研究科 博士課程)

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.

会場: セミナー室 (359号室)

イベント公式言語: 英語

't Hooft anomaly matching and symmetry enforced gaplessness

2026年6月1日(月) 13:00 - 14:00

大森 寛太郎 (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 上級研究員)

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.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語