Lectures on Quantum Measurement Theory: I

2026年6月2日(火) 15:30 - 17:00

小澤 正直 (名古屋大学 名誉教授)

Lecture I: Conventional approach: Repeatability, Heisenberg’s original uncertainty principle, and the SQL for gravitational-wave detection The conventional approach to quantum measurement theory taken by von Neumann (1932), Dirac (1958), and Schrödinger (1935) assumes the "repeatability hypothesis" stating that if a physical quantity is measured twice in succession, then the same value is obtained each time, which is often quantitatively generalized to the "approximately repeatable hypothesis" stating that after a measurement of a physical quantity with error ε, the post-measurement deviation around the measured value is no larger than ε; this is equivalent to saying that the state after obtaining a measurement result with error ε becomes an ε-approximate eigenstate corresponding to that measurement result. From the approximate repeatability hypothesis, one can derive "Heisenberg’s original formulation of the uncertainty principle," namely, that when position and momentum are approximately measured simultaneously, the product of their respective errors is at least ℏ/2 (Heisenberg 1927, Kennard 1927, Ozawa 2015), as well as the "standard quantum limit (SQL) for monitoring the free-mass position", which states that when the position of a free mass m is measured at a time interval τ, the result of the second measurement cannot be predicted with uncertainty smaller than (ℏτ/ m)^{1/2} (Caves 1985). The last result leads to a sensitivity limit for interferometric gravitational-wave detectors, and in the early 1980s it was therefore argued that gravitational waves of the expected strength could not be observed using interferometric detectors (Braginsky et al. 1980, Caves et al. 1980).

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

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

Closed Seminar on Quantum Topology and Related Topics

2026年5月29日(金) 14:00 - 18:00

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)
北村 侃 (立教大学 理学部 数学科 助教)
村上 友哉 (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 研究員)
ウアジーミャ・ソスニロ (理化学研究所 数理創造研究センター (iTHEMS) 数理基礎部門 研究員)

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)

会場: セミナー室 (359号室)

イベント公式言語: 英語

Bootstrapping Cosmological Correlators

2026年5月28日(木) 16:00 - 18:00

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.

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

Introduction to categorification and link homology

2026年5月28日(木) 14:00 - 15:30

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.

会場: 大河内記念ホール (メイン会場) / via Zoom

イベント公式言語: 英語

Towards rock-solid evolutionary genomics

2026年5月28日(木) 13:00 - 14:00

シュパイデル 玲雄 (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 理研ECL研究ユニットリーダー)

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.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語

Cooperating on networks: inequality and social structure

2026年5月27日(水) 14:00 - 15:00

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.

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

Harnessing inequality for cooperation

2026年5月26日(火) 14:00 - 15:00

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.

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

The First RIKEN Quantum International Workshop on Frontiers of Quantum Computing Applications and Quantum-HPC Integration

2026年5月25日(月) - 26日(火)

This two-day workshop will bring together leading experts from academia, industry, and national laboratories to explore the rapidly evolving frontiers of quantum computing applications and their integration with high-performance computing (HPC) platforms. Hosted by RIKEN Quantum, the event will provide a forum for discussing recent advances, practical challenges, and future directions toward achieving utility-scale quantum computations and robust quantum–HPC hybrid workflows. The workshop is primarily an in-person event, but a special session on quantum computing in chemistry and life sciences will also be accessible via Zoom.

会場: 理化学研究所和光キャンパス 本部棟2階大会議室

イベント公式言語: 英語

Singularities of differentiable maps and Thom polynomials

2026年5月22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)

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.

会場: 理化学研究所 和光キャンパス (メイン会場) / via Zoom

イベント公式言語: 英語

Mathematical Application Research Team Meeting #15

2026年5月22日(金) 10:30 - 12:00

Pietro De Lellis (Associate Professor, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Italy)

Mathematical Application Research Team is delighted to welcome Dr. Pietro De Lellis from University of Naples Federico II, for an upcoming team meeting. We warmly invite everyone to join us for this opportunity to hear about his latest research. Title: Synchronization and Control in Higher-Order Network Dynamics Abstract Understanding how network structure shapes coordinated behavior in coupled dynamical systems is a central question in network science. Although pairwise interactions among identical nodes are well understood, much less is known about the effects of directed higher-order interactions, especially in systems with heterogeneous nodes. In this seminar, I will discuss recent results on the emergence and control of collective behavior in such systems. I will first present an extension of the standard pairwise framework to higher-order directed interactions and derive conditions for synchronization in the identical-node setting. I will then introduce a mathematically grounded heuristic for steering the system toward a prescribed trajectory. Moving to heterogeneous dynamics, I will present a new notion of network synchronizability that quantifies how hypergraph topology can promote trajectory alignment even when node parameters differ. The resulting metric is analytically derived, agrees closely with numerical observations, and scales efficiently to large networks. This makes it possible to compare higher-order and pairwise interactions systematically, and to identify when multi-body interactions favor or obstruct synchronization. I will conclude with an application to opinion dynamics, where the framework highlights which hyperedges are most conducive to consensus formation.

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

Entanglement entropy and conformal bounds for five-dimensional CFTs

2026年5月21日(木) 15:00 - 16:00

Javier Moreno (京都大学 基礎物理学研究所 基研特任助教)

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.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語

Stochastic Thermodynamics: noise and energetics of nanoscale systems

2026年5月21日(木) 13:00 - 14:00

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.

会場: via Zoom / セミナー室 (359号室)

イベント公式言語: 英語

On Mean-Field Games

2026年5月21日(木) 10:30 - 11:30

アントワーヌ・ディエズ (理化学研究所 数理創造研究センター (iTHEMS) 数理展開部門 数学応用研究チーム 研究員)

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.

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

Positivity constraints for the gravitational path integral

2026年5月21日(木) 10:00 - 11:50

ガブリエル・ディウバルド (理化学研究所 数理創造研究センター (iTHEMS) 国内外連携・人材育成部門 理研バークレーセンター 特別研究員)

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.

会場: via Zoom

イベント公式言語: 英語

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

2026年5月19日(火) 15:00 - 16:30

新城 一矢 (理化学研究所 創発物性科学研究センター (CEMS) 計算物性物理研究室 研究員)

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

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

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

2026年5月18日(月) 14:00 - 15:00

野中 尚輝 (理化学研究所 数理創造研究センター (iTHEMS) 数理展開部門 医科学深層学習チーム 上級研究員)

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.

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

Basics of chiral lattice fermion

2026年5月18日(月) 13:00 - 14:00

山本 新 (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)

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