イベント検索
671 件
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セミナー
A mathematical formulation of two-dimensional conformal field theory
2022年5月23日(月) 14:00 - 16:30
森脇 湧登 (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
The mathematical construction of non-trivial quantum field theory in four dimensions, known as the "Yang-Mills existence and mass gap problem", is a very important issue in mathematical sciences. There are many examples of rigorous quantum field theories in two dimensions, although the four dimensions have not yet been solved. In particular, two-dimensional conformal field theory, which is a quantum field theory with conformal symmetry, has good properties and can be formulated mathematically using algebraic structures formed by "products of a field and a field" (operator product expansion). In this talk, this algebraic formulation (full vertex algebra) will be explained. Various construction methods and concrete examples (construction using codes, construction from quantum groups, and construction by deformation) will then be discussed. All the talk here is mathematical, but I will try to speak in a way that is motivated by physics as much as possible throughout the talk. I hope to receive various comments from the viewpoints of other fields.
会場: コモンルーム 246-248号室 とZoomのハイブリッド開催
イベント公式言語: 英語
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セミナー
The Hunt for Extraterrestrial Neutrino Counterparts
2022年5月20日(金) 16:00 - 17:00
Yannis Liodakis (Postdoctoral Researcher, University of Turku, Finland)
The origin of high-energy neutrinos is fundamental to our understanding of the Universe. Apart from the technical challenges of operating detectors deep below ice, oceans, and lakes, the phenomenological challenges are even greater. The sources are unknown, unpredictable, and we lack clear signatures. Neutrino astronomy therefore represents the greatest challenge faced by the astronomy and physics communities thus far. The possible neutrino sources range from accretion disks and tidal disruption events, through relativistic jets to galaxy clusters with blazar TXS 0506+056 the most compelling association thus far. Since then, immense effort has been put into associating AGN-jets with high-energy neutrinos, but to no avail. I will discuss our current efforts in understanding the multimessenger processes in the Universe, and once and for all proving or disproving if AGN-jets are neutrino emitters.
会場: via Zoom
イベント公式言語: 英語
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セミナー
More Data, More Problems: Big Data in Correlative Ecology
2022年5月19日(木) 16:00 - 17:00
Dan Warren (沖縄科学技術大学院大学 (OIST) 生物多様性・複雑性研究ユニット 研究員)
The rapidly expanding pool of large data sets on species distributions, community composition, and environmental factors has been accompanied by an increasing number of methodological approaches to analyze this data. If done correctly, this represents an unprecedented opportunity for understanding ecological processes at large scales. However, it also represents an opportunity to be wrong about those same processes at a scale that was previously not possible. In this talk, I will use examples from ecology and other fields to discuss some of the issues that arise when we take big data approaches to ecological questions.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Khovanov homology theory - an introduction to categorification
2022年5月13日(金) 14:00 - 16:30
佐野 岳人 (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
Jones polynomial is a knot invariant discovered by V. F. R. Jones in 1984. Not only that it is a useful mathematical tool, the discovery led to opening up a new research area, quantum topology, which connects quantum mechanics and low-dimensional topology. In 2000, M. Khovanov introduced a “categorification of the Jones polynomial”, which is now called Khovanov homology, and made categorification one of the fundamental concept in knot theory. Now what does categorification mean, and what is it good for? In this talk, assuming that many of the audience are not familiar with abstract category theory, I will start from easy examples of categories and categorifications, for example categorification of natural numbers, and explain why they are something natural to think of. In the latter part, I will briefly explain the construction of Khovanov homology, and introduce several related topics.
会場: コモンルーム 246-248号室 とZoomのハイブリッド開催
イベント公式言語: 英語
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セミナー
Classical and Quantum Chaos
2022年5月12日(木) 16:00 - 17:00
首藤 啓 (東京都立大学 大学院理学研究科 物理学専攻 教授)
Classical and quantum mechanics in multi-dimensions are qualitatively different from those in one-dimension since they are no more integrable in general and chaos appears in the dynamics. This brings a great deal of complexity or even richness both in classical and quantum dynamics. Especially in generic nonintegrable systems which are neither completely integrable nor fully chaotic, phase space becomes a mixture of regular and chaotic components. Such an aspect is a source of inexhaustible questions not only in the past but in the future. We here overview classical and quantum chaos in Hamiltonian systems.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Diversity of Asgardarchaota and Theoretical verification of the endosymbiotic theory
2022年4月28日(木) 10:00 - 11:00
熊倉 大騎 (北海道大学 大学院生命科学院 生命科学専攻 博士課程)
How did intracellular symbiosis occur and give rise to eukaryotic ancestor? This question has been considered to the two theories as three-domain theory and eocyte theory. Here I present asgard archaea, the archaeon closest to eukaryotes. Asgard archaea is an archaeon found at a deep-sea sampling site called Loki's castle at between Greenland and Norway. So all the closely related species are named after Norse mythology (Loki-, Thor-, Odin-, Heimdall-, etc.). Unlike other archaea, asgard archaea has many eukaryotic-specific proteins and is considered to be the closest to eukaryotes. In 2020, one of the asgard archaea species was finally successfully cultured. This archaeon was cultured and found to take on a branch-like structure. It is then hypothesized that intracellular symbiosis between this archaeon and the ancestor of mitochondria resulted in the ancestor of today's eukaryotic cells. In this talk, I would like to discuss with you the explanation of how we arrived at this hypothesis and how to construct a mathematical model.
会場: via Zoom
イベント公式言語: 英語
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特別講演会
iTHEMS × academist オンラインイベント「数理で読み解く科学の世界 2022」
2022年4月24日(日) 10:00 - 16:30
谷口 正樹 (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
田屋 英俊 (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
原田 了 (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
許 インイン (理化学研究所 数理創造プログラム (iTHEMS) 基礎科学特別研究員)
矢﨑 裕規 (理化学研究所 数理創造プログラム (iTHEMS) 特別研究員)「数理で読み解く科学の世界」は、2020年より毎年4月に開催しているオンラインイベントです。iTHEMS所属の若手研究者5名が最先端の研究について中学生や高校生にもわかるように30分の講演を行います。また、一般参加者からの質問やコメントを受け付ける時間も設けています。 詳細、参加お申し込みは、関連リンクをご覧ください。 日時：2022年4月24日（日）10:00〜16:30（開場 9:45） 場所：Web会議サービス「Zoom」（申込者に事前に招待URLをお伝えいたします） 参加費：無料 対象者：中学生・高校生、社会人（どなたでもご参加いただけます） 主催：iTHEMS 共催（企画・運営・宣伝）：アカデミスト 講演者および発表タイトル： 谷口 正樹 博士「結び目から4次元空間を見る」 田屋 英俊 博士「「無」から「有」をつくる」 原田 了 博士「元素のルーツは宇宙の花火」 許 インイン 博士「情報学の船に乗って科学の大航海の旅へ」 矢崎 裕規 博士「（系統的に）迷子の生物を助けたい！〜分子系統学者になったライフセーバー〜」 ※ 昼休み企画として「iTHEMS研究者の日常に迫る！」の配信も予定しています。
会場: via Zoom
イベント公式言語: 日本語
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セミナー
Recurrence theorems for topological Markov chains
2022年4月22日(金) 17:00 - 19:00
Cédric Ho Thanh (理化学研究所 開拓研究本部 (CPR) 三好予測科学研究室 特別研究員)
Recurrence theorems place conditions under which probabilistic systems, specifically Markov chains, are expected to visit certain states infinitely often. For example, a printer with its many moving parts and the random requests it receives, may be described as a probabilistic system, and recurrence of the "ready to print" state is desirable. Recurrence theorems in the case of finite Markov chains are widely known. In this talk, we are interested in generalization to the infinitary setting. As it turns out, some care has to be put in the definition of infinite Markov chains. Rather than simply infinite, the introduct topological Markov chains, and show how standard constructions can be naturally extended to thisframework: path spaces, cylinder sets, as well as the semantic of LTL and PCTL. With all these tools in hand, we finally state our recurrence theorems. This is work in progress in collaboration with Natsuki Urabe and Ichiro Hasuo. This seminar is hold in a hybrid style. If you want attend the seminar onsite, please contact to Keita Mikami.
会場: コモンルーム 246-248号室 とZoomのハイブリッド開催 (メイン会場)
イベント公式言語: 英語
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コロキウム
How is turbulence born: Statistical mechanics and ecological collapse in transitional fluids
2022年4月22日(金) 15:00 - 16:30
Hong-Yan Shih (Assistant Research Fellow, Institute of Physics, Academia Sinica, Taiwan)
The onset of turbulence is ubiquitous in daily life and is important in various industrial applications, yet how fluids become turbulent has remained unsolved for more than a century. Recent experiments in pipe flow finally quantified this transition, showing that non-trivial statistics and spatiotemporal complexity develop as the flow velocity is increased. Combining numerical simulations of the hydrodynamics equations and an effective theory from statistical mechanics, we discovered the surprising fact that fluid behavior at the transition is governed by the emergent predator-prey dynamics, leading to the mathematical prediction that the laminar-turbulent transition is analogous to an ecosystem on the edge of extinction. This prediction demonstrates that the laminar-turbulent transition is a non-equilibrium phase transition in the directed percolation universality class, and provides a unified picture of transition to turbulence in various systems. I will also show our recent progresses on transitional turbulence, including how an extended ecological model with energy balance successfully recapitulates the spatiotemporal patterns beyond the critical point, and the determination of the critical behavior and an emergent novel phase under interactions in the experimental collaboration.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Coherent emission from 3D relativistic shocks
2022年4月22日(金) 14:00 - 15:00
岩本 昌倫 (九州大学)
The origin of fast radio bursts (FRBs; Lorimer et al. 2007) is one of the unsolved problems in astrophysics. Many observations of FRBs indicate that FRBs must be coherent emission in the sense that coherently moving electrons radiate electromagnetic waves. In relativistic shocks, it is well known that coherent electromagnetic waves are excited by synchrotron maser instability (SMI) in the shock transition (Hoshino & Arons 1991). The SMI is also known as the emission mechanism of coherent radio sources such as auroral kilometric radiation at Earth and Jovian decametric radiation. Recently, some models of fast radio burst based on the coherent emission from relativistic shock via the SMI have been proposed (e.g., Lyubarsky 2014; Beloborodov 2017; Plotnikov & Sironi 2019; Metzger et al. 2019) and the SMI in the context of relativistic shocks attracts more attention from astrophysics. In this study, by performing the world’s first three-dimensional (3D) particle-in-cell (PIC) simulation of relativistic shocks, we will demonstrate that large-amplitude electromagnetic waves are indeed excited by the SMI even in 3D and that the wave amplitude is significantly amplified and comparable to that in pair plasmas due to a positive feedback process associated with ion-electron coupling. Based on the simulation results, we will discuss the applicability of the SMI for FRBs in this talk.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Neurons are potential statisticians
2022年4月21日(木) 10:00 - 11:00
磯村 拓哉 (理化学研究所 脳神経科学研究センター (CBS) 脳型知能理論研究ユニット ユニットリーダー)
Humans and animals can predict what will happen in the future and act appropriately by inferring how the sensory inputs were generated from underlying hidden causes. The free-energy principle is a theory of the brain that can explain how these processes occur in a unified way. However, how the fundamental units of the brain, such as the neurons and synapses, implement this principle has yet to be fully established. Here, we have mathematically shown that neural networks that minimise a cost function implicitly follow the free-energy principle and actively perform statistical inference. We have reconstructed a biologically plausible cost function for neural networks based on the equation of neural activity and shown that the reconstructed cost function is identical to variational free energy, which is the cost function of the free-energy principle. This equivalence speaks to the free-energy principle as a universal characterisation of neural networks, implying that even at the level of the neurons and synapses, the neural networks can autonomously infer the underlying causes from the observed data, just as a statistician would. The proposed theory will advance our understanding of the neuronal basis of the free-energy principle, leading to future applications in the early diagnosis and treatment of psychiatric disorders, and in the development of brain-inspired artificial intelligence that can learn like humans.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Journal Club: Phase separation in a many-component system with random interactions
2022年3月31日(木) 10:00 - 11:00
足立 景亮 (理化学研究所 生命機能科学研究センター (BDR) 生体非平衡物理学理研白眉研究チーム 基礎科学特別研究員)
Several kinds of protein condensates have been observed in living cells, and the liquid-liquid phase separation is regarded as a basic mechanism of the condensate formation. However, given that there are thousands of protein species in a cell, it is not clear how the number and the composition of distinct condensates are controlled. One of the physics approaches to this problem is considering a model of many components with random interactions. In this Journal Club, I will introduce a recent paper [1] that applies random-matrix theory to the phase separation dynamics.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Explore the possibility to control hurricanes
2022年3月18日(金) 16:00 - 18:00
Lin Li (理化学研究所 開拓研究本部 (CPR) 三好予測科学研究室 特別研究員)
Hurricanes, also known as tropical cyclones and typhoons, are the biggest and the most devastating storms on Earth. In this seminar, I will talk about the possibility to control hurricanes with existing human capability. Energetically speaking, controlling hurricanes is a very challenging task due to a large gap: hurricanes are gigantic heat engines with a power of around 1014 Watt, while the most powerful manmade engines have the power of only 108 Watt. This six-order-magnitude gap is the major obstacle toward using existing engines to control hurricanes. To fill in this gap, we propose to utilize the chaotic nature of hurricanes, namely, the sensitivity of a chaotic system to its initial condition, to control hurricanes. In this presentation, I will first review the basics of hurricanes and existing chaos control methods, and then present my thoughts on hurricane control and preliminary results I acquired since joining Prediction Science Laboratory. Future directions on using reinforcement learning to control hurricanes will also be discussed. Since it is a very challenging task, I welcome any discussions, questions, and comments. I hope we can make the hurricane-risk-free future come earlier.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Phylogenomics revealed one of the problems for phylogeny –The monophyly of Archaeplastida including land plant-
2022年3月17日(木) 10:00 - 11:00
矢﨑 裕規 (理化学研究所 数理創造プログラム (iTHEMS) 特別研究員)
There are many problems between large eukaryotic lineages. One of these is the monophyly of Archaeplastida to which land plants and other photosynthetic organisms belong. Although it has been believed that the Archaeplastida are monophyletic because they share common chloroplast structures, several large-scale molecular phylogenetic analyses have failed to reproduce this phylogenetic relationship. In this study, by enhancing the taxon sampling of the data set, the monophyly of Archaeplastida was successfully reconstructed, showing that the taxa critical for the reconstruction are present. Through detailed molecular phylogenetic and statistical analyses, it was estimated that the lack of monophyly ofArchaeplastida is due to the specific evolutionary signals of certain taxa.
会場: via Zoom
イベント公式言語: 英語
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特別講演会
【森重文×坂上貴之 特別対談】数学は社会でどういきている？ - 数学研究の本質を探る
2022年3月12日(土) 13:00 - 14:30
初田 哲男 (理化学研究所 数理創造プログラム (iTHEMS) プログラムディレクター)
坂上 貴之 (京都大学 大学院理学研究科 数学・数理解析専攻 教授)
森 重文 (京都大学 高等研究院 (KUIAS) 院長)古くはナイル川の氾濫を防ぐための幾何学や、商売を円滑に行うための代数学など、数学は人間社会と共に長い年月をかけて発展してきました。現在でも私たちの生活や社会の至るところに数学がいきていますが、日常的に意識することは少ないかもしれません。今回のイベントでは、数学者として多くの実績を残されてきた2名をお招きし、講演・対談を通じて数学の本質を考え、社会との接点について考えていきます。 2022年3月12日（土）13:00〜14:30 会場：ZOOM（URLはイベント参加お申込み後にお知らせいたします。） 定員：500名 参加費：無料（途中参加・退室可） 対象者：どなたでもご参加いただけます 主催：理化学研究所 数理創造プログラム（iTHEMS） 【タイムスケジュール】 13:00-13:05 趣旨説明・Zoomの使い方等 13:05-13:10 開会の挨拶 理化学研究所 数理創造プログラム（iTHEMS）プログラムディレクター 初田哲男 13:10-13:25 講演1「数学から社会課題の解決へ」京都⼤学 ⼤学院理学研究科 数学教室 教授 坂上貴之 13:25-13:40 講演2「数学の楽しさ・美しさ」京都大学 高等研究院 (KUIAS) 院長 森重文 13:40-14:10 パネルディスカッション「数学と社会はどうつながっているのか？」 登壇者：森重文、坂上貴之 進行：柴藤亮介（アカデミスト株式会社 代表取締役CEO） 14:10-14:25 質疑応答・まとめ 14:25-14:30 閉会の挨拶 理化学研究所 数理創造プログラム（iTHEMS）プログラムディレクター 初田哲男
会場: via Zoom
イベント公式言語: 日本語
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セミナー
Extracting rules from trained machine learning models with applications in Bioinformatics
2022年3月11日(金) 16:00 - 18:00
Pengyu Liu (理化学研究所 情報統合本部 (R-IH) 医療データ数理推論チーム 特別研究員)
Recently, Machine learning methods have achieved great success in various areas. However, some machine learning-based models are not explainable (e.g., Artificial Neural Networks), which may affect the massive applications in medical fields. In this talk, we first introduce two approaches that extract rules from trained neural networks. The first one leads to an algorithm that extracts rules in the form of Boolean functions. The second one extracts probabilistic rules representing relations between inputs and the output. We demonstrate the effectiveness of these two approaches by computational experiments. Then we consider applying an explainable machine learning model to predict human Dicer cleavage sites. Human Dicer is an enzyme that cleaves pre-miRNAs into miRNAs. We develop an accurate and explainable predictor for the human Dicer cleavage site -- ReCGBM. Computational experiments show that ReCGBM achieves the best performance compared with several existing methods. Further, we find that features close to the center of pre-miRNA are more important for the prediction.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Toward modeling complete supernova neutrino emissions
2022年3月11日(金) 16:00 - 17:00
諏訪 雄大 (東京大学 大学院総合文化研究科 宇宙地球部会 准教授 / 京都大学 基礎物理学研究所 基研特任准教授)
Neutrinos are guaranteed observable from the next Galactic supernova (SN). Optical lights and gravitational waves are also observable but can be difficult to observe if SN location in the galaxy and the explosion details are unsuitable. The key to the next coming SN observation will be understanding various physical quantities using neutrinos first and then connecting them to other signals. In particular, understanding neutrinos in the late time (> 1 sec after the onset of explosion) is essential, since physics in this time scale has much smaller uncertainties than that of the early time. We should construct a simple and understandable neutrino model based on the late-time emissions. It allows us to tackle the physics in the early phase like the explosion mechanism. In this talk, I will discuss the following topics: 1) how to model the complete neutrino emissions from the very early phase up to the last observable event. 2) what physical quantities (e.g., mass and radius of neutron stars) can be extracted from observations using large statistical neutrinos as physics probes. 3) how to use these extracted physical quantities to link with the explosion mechanism of SN and multi-messenger observations.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Independent regulation of multiple checkpoints in cell-cycle network system -Biological function originated in the law of localization-
2022年3月10日(木) 10:00 - 11:00
望月 敦史 (京都大学 ウイルス･再⽣医学研究所 教授)
In cell cycle, G1-S and G2-M checkpoints are regulated by different protein complexes, Cdc2-Cdc13 and Cdc2-Cig2, respectively. For a normal mitosis, activity of two complexes should rise specifically at different timing. However, the complex formations share common species of proteins and activation reactions conform a complicated network. We study how independent regulation of two checkpoints is realized in the network system by “structural sensitivity analysis”, which was previously established by us. The analyses clarified that activities of two complexes are regulated by disjoint sets of reaction parameters in the system. A series of non-trivial behaviors are generated by “buffering structures with an intersection”, which can generally appear in chemical reaction network including complex formation.
会場: via Zoom
イベント公式言語: 英語
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セミナー
Introduction to stability conditions 2
2022年3月9日(水) 16:00 - 17:30
小関 直記 (Postdoctoral Research Associate, School of Mathematics, University of Edinburgh, UK)
In 2002, Bridgeland defined the notion of stability conditions on a triangulated category, motivated by string theory and mirror symmetry. Since then, Bridgeland stability conditions have been found very useful not only in Mathematical Physics, but also in various areas of Pure Mathematics. In the first part, I will review basic background and open problems in the theory of Bridgeland stability conditions. In the second part, I will explain recent developments of the theory, especially its applications to algebraic geometry.
会場: via Zoom
イベント公式言語: 英語