iTHEMS Biology Seminar
259 events
We are holding regular seminars and other activities on topics related to biology. Our aim is to lower the boundaries between biology and mathematics/physics, to identify common grounds between biology and mathematics/physics, and to develop ideas for new research topics at the intersection of biology and mathematics or physics.
For further details see iTHEMS Biology Seminar Study Group page.
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Seminar
Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocation
November 26 (Thu) 13:00 - 14:00, 2026
Yuichi Shiraishi (Chief, Division of Genome Analysis Platform Development, National Cancer Center Japan)
Centromeres are highly variable and rapidly evolving regions of the human genome, and are frequently implicated in various cancers. Human centromeres consist of highly repetitive DNA sequences known as α-satellite higher-order repeats (HORs), which makes their analysis using conventional genome sequencing approaches extremely challenging. Although long-read sequencing technologies now enable near-complete sequencing of centromeres, applying these methods to large numbers of samples remains difficult. As a result, our understanding of centromere diversity across populations and its role in chromosomal rearrangements in cancer has remained limited. In this study, by focusing on rare k-mer markers, we demonstrate that α-satellite HOR haplotypes cluster into genetically related haplogroups. We further developed a software tool, ascairn, to accurately infer these haplogroups from common short-read whole-genome sequencing (WGS) data. Applying our approach to a dataset of more than 3,300 human samples revealed extensive centromere diversity and geographic variation. We also applied the rare k-mer–based approach to centromere sequences from 104 Japanese individuals generated as part of the Japanese Pangenome Project. This analysis revealed characteristic patterns of centromere evolution in the Japanese population and provided new insights into Japanese-specific centromere variation. In addition, we used this method to investigate class-defining chromosomal translocations, specifically der(1;19), also known as 1p/19q co-deletion, in oligodendrogliomas. By analyzing 142 samples from TCGA, we hypothesized that the breakpoints occurred on the p-arm side of D1Z7 and the q-arm side of D19Z3. This hypothesis was subsequently validated through extensive long-read sequencing in two cases, indicating that der(1;19) results in a dicentric chromosome containing two functional centromeres. We also observed that chromosomal rearrangements preferentially occurred in haplotypes with longer repetitive arrays on either the q-arm or p-arm side of the centromere. Furthermore, we identified specific centromere haplogroups associated with either increased or decreased likelihoods of der(1;19) translocations. Our findings show that rare k-mer analysis is a powerful approach for investigating centromere complexity and clarifying the mechanisms underlying centromere-associated abnormalities in cancer.
Venue: via Zoom / Seminar Room #359
Event Official Language: English
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SeminarTopological properties of empirical fitness landscapes from merge trees
November 9 (Mon) 13:00 - 14:00, 2026
Igors Dubanevics (Ph.D. Student, Okinawa Institute of Science and Technology Graduate University (OIST))
How evolution navigates sequence space depends on the shape of the fitness landscape. Viewed as a scalar field over a discrete genotype graph, theoretical landscapes range from single-peaked to rugged and fragmented, with very different mutational accessibility. Which shapes real biological sequences occupy remains an open empirical question. Deep mutational scanning now measures sequence–function maps across complete combinatorial regions of sequence space, but the resulting landscapes are large, noisy, and hard to compare across studies. Existing analyses typically reduce each dataset to a few summary statistics, discarding which peaks connect to which, and through which saddles. We are developing a two-layer toolkit for empirical sequence–function landscapes. A statistical layer models overdispersed sequencing counts directly to separate genuine phenotypic differences from measurement noise, pruning spurious topological features before analysis. A topological layer then summarises the landscape as a merge tree of peaks, saddles, and the high-fitness ridges that link them, using persistence as a natural scale to distinguish global structure from minor ruggedness. I will first illustrate this approach on the largest published combinatorially complete protein-coding landscape, spanning over 260,000 sequences. Filtering by measurement uncertainty and persistence simplifies an apparently rugged surface, revealing that major peaks remain connected through high-fitness saddles rather than isolated by deep valleys. I will then present preliminary findings from a comparative atlas of more than 150 combinatorially complete sequence–function landscapes spanning DNA, RNA, and protein. By comparing merge-tree structure across this collection, we ask whether high-fitness ridges that bypass rugged regions recur across unrelated sequences, and whether landscapes group by the biological function they encode.
Venue: via Zoom / Hybrid Format (3F #359 and Zoom), Seminar Room #359
Event Official Language: English
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Seminar TomorrowTowards the Geometric Beauty of Bonsai
October 29 (Thu) 13:00 - 14:00, 2026
Shinobu Utsumi (JSPS PD Researcher, Mathematical Social Science Team, Division of Applied Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
I will present an overview of my ongoing and future research projects. Art has been a central element of human culture and society across regions and throughout history. However, the inherent subjectivity of aesthetic evaluation has long made it challenging to study art quantitatively and systematically within the mathematical sciences. My research tackles this challenge through bonsai—the art of recreating the grandeur of natural landscapes and majestic trees within a small pot. Often described as a “living art” and a “crystallization of Japanese aesthetics,” bonsai provides a unique opportunity to explore a fundamental question: How can we quantify something as seemingly subjective as beauty? The key methodology of this research involves the 3D digitization of actual bonsai using photogrammetry, followed by the extraction of their skeletal structures and their representation as 3D non-looped tree graphs. I then apply morphological and network analyses to investigate commonalities and differences in branching structures across bonsai of different styles and grades. Looking ahead, I will discuss future research directions, including how these analyses and mathematical models could be extended to quantitatively characterize traditional Japanese aesthetic principles (e.g., the beauty of subtraction and negative space), as well as what distinguishes the structures of artistically cultivated bonsai from those of naturally growing trees.
Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359 / via Zoom
Event Official Language: English
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Seminar
Observability-based causal inference in linear stochastic systems with hidden inputs
October 22 (Thu) 13:00 - 14:00, 2026
Daiki Sekizawa (Special Postdoctoral Researcher, Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science (CBS))
Causal inference from neural time series is confounded by correlations induced by hidden common inputs, a problem that is especially acute because the full set of variables shaping neural activity is rarely accessible. Prediction based measures such as Granger causality can therefore falsely attribute such dependencies to causal influence. Delay coordinate reconstruction, which is also closely connected to observability in control theory, provides a complementary route: in deterministic systems, downstream delays can reconstruct upstream causes, whereas the reverse does not generally hold. This asymmetry provides a signature of causal direction, as exploited by convergent cross mapping. In stochastic dynamics, however, dynamical and observation noise enter delay coordinates and prevent exact trajectory reconstruction. Here, we develop data driven criteria that extend this observability principle to partially observed stochastic systems. First, we show that observability can be tested by regression of time lagged covariance matrices, which removes direct noise contributions while preserving the observability relation. Second, we show that causal direction can be tested through inclusion of stochastic Koopman eigenvalues estimated from upstream and downstream delay coordinates, because downstream observations generically contain the dynamical components observable upstream. Numerical examples show that the proposed criteria recover causal direction and reject spurious dependencies induced by unobserved common inputs, including cases in which Granger causality and convergent cross mapping fail to distinguish common input from causal influence. Although motivated by neural recordings, the framework applies broadly to partially observed stochastic dynamical systems beyond neuroscience.
Venue: Hybrid Format (3F #359 and Zoom), Main Research Building / via Zoom
Event Official Language: English
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Seminar
Finding your rhythm in a complex acoustic environment
October 14 (Wed) 13:00 - 14:00, 2026
Kim Hoke (Professor, Department of Biology, Colorado State University, USA)
My lab integrates genetic, transcriptomic, morphological, and physiological mechanisms to understand the striking diversity of behavior. This talk will focus on recent work on frog acoustic communication. Although the basic acoustic features of frog calls differ reliably among species, individual males of the same species differ in some acoustic properties and female frogs use those male-male differences in mate choice. And for many species, this communication is occurring in very dense choruses which can reach hundreds of males! Our current work assesses which features of calls are characteristic of individuals and how males adjust their calling based on their social environments. We hope to trace how overall chorus dynamics emerge from individual call strategies playing out in time and space, and link those individual strategies to neurobiological mechanisms. We also address the complementary question of female preferences: how do females integrate over a series of signals in this cacophony to make mate choice decisions? Together these lines of research adopt a systems approach to understand how the robust genetic and developmental processes that produce species-specific behaviors have evolved to generate the striking diversity of communication strategies frogs employ.
Venue: Seminar Room #359, Seminar Room #359 / via Zoom
Event Official Language: English
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Seminar
Adaptive Regulation through Model-Observation Mismatch: From Process Control to Cognitive Neurorobotics
October 8 (Thu) 13:00 - 14:00, 2026
Henrique Oyama (Postdoctoral Researcher, Cognitive Neurorobotics Research Unit, Okinawa Institute of Science and Technology Graduate University (OIST))
Adaptive behavior requires biological and artificial systems to respond when their internal models no longer match what they observe. How can such discrepancies be used not only to correct predictions, but also to regulate how a system interacts with its environment? In this talk, I will explore this question across two research directions spanning process control and cognitive neurorobotics. First, I will introduce a model predictive control framework in which a controller actively guides a nonlinear process toward informative conditions to distinguish among competing models while maintaining safe operation. I will then move to cognitive neurorobotics, where brain-inspired computational principles are used to investigate perception, prediction, and action in embodied artificial agents. In physical human-robot interaction, I will show how a predictive-coding-inspired recurrent neural network enables a humanoid robot to regulate the balance between its learned expectations and sensory information arising from human-guided movements. In particular, recent mismatches between sensory observations and the robot's internal model are used to regulate how strongly it relies on its learned dynamics or accommodates ongoing interaction. Together, these studies illustrate how model-observation mismatch can provide a general signal for adaptive regulation, connecting ideas from control engineering, artificial intelligence, neuroscience, and embodied cognition.
Venue: Hybrid Format (3F #359 and Zoom), Main Research Building / via Zoom
Event Official Language: English
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Seminar
Coexistence and hybridization in plant communities - lessons from mediterranean shrublands
October 1 (Thu) 13:00 - 14:00, 2026
Carmelo Gómez Martínez (Postdoctoral Researcher, Global Change Research Institute, Universidad Rey Juan Carlos, Spain)
This talk explores how two closely related Mediterranean shrubs, the rockroses Cistus ladanifer and Cistus laurifolius, share the same habitat despite being direct competitors for soil, light and pollinators. Hybridization – the natural interbreeding of two related species – often produces offspring that blend both parents' traits, and is surprisingly common in plants, including the Cistus genus. Fieldwork across Spain's Iberian Central System combining genomics, flowering timing and soil experiments shows that no single factor by itself – not genetics, climate or soil – fully explains these dynamics. The next step is to study how pollination shapes hybridization, and for that, we are developing and agent-based model that simulates bee foraging across realistic landscapes to predict new hybrid outcomes under environmental change.
Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359 / via Zoom
Event Official Language: English
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Seminar
How fungi generate one of the highest pressures in biology: the cell wall as a living nanoporous material
September 7 (Mon) 14:00 - 15:00, 2026
Naoyoshi Kumakura (Senior Research Scientist, RIKEN Center for Sustainable Resource Science (CSRS))
Many devastating crop diseases, including anthracnose and rice blast, begin when a fungal pathogen builds a single infection cell called an appressorium. This single cell generates up to ~8 megapascals of turgor pressure (roughly 40 times a car tire’s air pressure), among the highest documented in any living organism, to physically rupture the plant's tough surface. This pressure arises because the cell wall acts as a semipermeable membrane, retaining internal osmolytes such as glycerol while allowing water to pass. What confers this selective permeability had remained unknown for decades: melanin was long assumed responsible, but turgor still forms in melanin-deficient mutants. Using genome editing and direct biochemical analysis of these fungi, we identified two enzymes, PKS2 and PBG13, that synthesize a novel polymer from dihydroxyhexanoic acid (DHHA), which narrows cell-wall pore size at the nanometer scale and is required for turgor generation (Kumakura* et al., Science, 2026). I will frame this system as a living adaptive porous material and discuss questions open to mathematical and physical modeling, including how pore geometry sets the limits of selective permeability.
Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359
Event Official Language: English
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Seminar
Computational demands shape seizure susceptibility in recurrent neural networks
September 3 (Thu) 13:00 - 14:00, 2026
Sebastian Eydam (Research Scientist, Neural Circuits and Computations Unit, RIKEN Center for Brain Science (CBS))
Why do some brain areas slip into seizures more readily than others? Anatomy and physiology are part of the story, but in this talk we argue that the computation a network performs is itself a determinant of its vulnerability. Working in the language of recurrent neural networks and attractor dynamics, we contrast two computational regimes: networks that represent continuous variables (e.g. tracking a continuous position in space) establish barrier-free state manifolds, whereas networks that store discrete memories have to separate different states by establishing deep wells. A simple energy-landscape picture suggests that continuous networks can amplify perturbations into runaway activity more easily while discrete networks contain them. We test this idea across three systems: handcrafted spiking attractor networks, recurrent networks trained on continuous or discrete computational tasks, and in vivo Neuropixels recordings comparing medial entorhinal cortex (continuous, grid-cell dynamics) with hippocampal CA3 (discrete memory). Under a shared disinhibitory "seizure perturbation," the continuous systems destabilize sooner and drive stronger epileptiform activity, and causal silencing shows this depends on intact entorhinal output. Together, these results establish a direct link between the computation a network is built to perform and its susceptibility to seizures, showing that the very features that enable a network to process information also shape its vulnerability to pathological transitions.
Venue: via Zoom / #359, 3F, Seminar Room #359
Event Official Language: English
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Seminar
Multistability in Biochemical Reaction Systems: Structural Approach
August 27 (Thu) 16:00 - 17:00, 2026
Takashi Okada (Associate Professor, Program of Mathematical and Life Sciences, Graduate School of Integrated Sciences for Life, Hiroshima University)
In living cells, biochemical reactions form intricate networks that can exhibit multistability, allowing a single system to maintain multiple stable states under identical conditions. However, determining theoretically whether a given reaction system can exhibit multistability is challenging because detailed kinetic parameters are often unknown. In this presentation, we introduce a structural framework that decomposes biochemical networks into subnetworks based solely on network topology. For each subnetwork, we define a scalar quantity, and an index-theoretic argument shows that the sign of this quantity determines whether the subnetwork can contribute to multistability. Our method identifies indicator species whose concentrations distinguish all steady states without detailed kinetic information, thereby enabling efficient measurement design in large networks.
Venue: via Zoom
Event Official Language: English
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Seminar
Theoretical Approaches for Cell Deaths
August 6 (Thu) 13:00 - 14:00, 2026
Yusuke Himeoka (Assistant Professor, Universal Biology Institute, The University of Tokyo)
Understanding the boundary between cell life and death is a fundamental challenge and a highly important theme in biology. In this talk, focusing on microbial cell death, I would like to discuss how "cell death" can be understood from the perspective of mathematical sciences. Research on microbial cell death has progressed by identifying the molecular mechanisms that drive relevant biochemical processes, which are identified based on empirically known cell death markers. However, there has been little discussion on what death actually is in the first place, or how it can be "defined." Furthermore, recent reports have shown that commonly used live/dead assays—such as dead-cell staining and metabolic activity measurements—can yield conflicting results regarding cell viability, highlighting the growing need to discuss what criteria we should use to define "death." In this study, we propose a definition: a cell is "dead" if it cannot return to a predetermined "representative point of the living state," no matter how gene expression levels or external nutrient concentrations are controlled. Plant seeds may appear "dead" at first glance due to their lack of apparent biochemical activity, yet they germinate when watered. Our proposal in this study is to determine the life or death of a cell based on whether an operation equivalent to "watering" exists [1]. Of course, it is experimentally impossible to prove that a cell cannot regain activity under any operation; however, it is theoretically possible using mathematical models. We developed a method called "Stoichiometric Rays" to calculate the controllability of metabolic reaction systems. Using this, we calculated states that cannot be controlled back to the "representative point of the living state" regardless of how enzyme levels and external nutrient concentrations are manipulated. Consequently, we succeeded in quantifying the separating hyperplane between the "living state" and the "dead state" in a mathematical model of metabolism [2], which we call the Separating Alive and Non-life Zone (SANZ) Hypersurface. In this talk, I will outline the theory, the quantification of the SANZ hypersurface, and its biological interpretation. In addition, through our research [3], we have partially identified a class of models that do not exhibit "death" in the sense described above. I would also like to discuss the relationship between the absence of "death" in these models and the autonomy of life.
Venue: #359, Seminar Room #359 (Main Venue) / via Zoom
Event Official Language: English
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Seminar
Visual system and (social) behavior in zebrafish
July 16 (Thu) 13:00 - 14:00, 2026
Fumi Kubo (Team Director, Laboratory for Sensorimotor Integration, RIKEN Center for Brain Science (CBS))
Animals make decisions about their actions using sensory information from the external world. Our lab investigates how the brain processes visual information and generates appropriate behavior using the vertebrate model organism, zebrafish. Our research has uncovered the neural circuits required for processing optic flow, a visual cue that animals use to estimate their own motion. We employ a diverse range of techniques, including behavioral tracking, live imaging of neural activity, and molecular and genetic characterization of neuronal cell types. More recently, our research has focused on social behavior, in which groups of animals collectively generate behavioral decisions. In this seminar, I will present our recent work investigating behavioral contagion in zebrafish.
Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359
Event Official Language: English
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Seminar
Toward an understanding of microbial circulation in the Mongolian nomadic ecosystem
July 6 (Mon) 13:00 - 14:00, 2026
Akari Shinoda (Assistant Professor, Faculty of Environmental, Life, Natural Science and Technology, Okayama University)
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.
Venue: Seminar Room #359 (Main Venue) / via Zoom
Event Official Language: English
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Seminar
Genome Structural Variation and the Evolutionary Potential of Sex in the Unicellular Green Alga Closterium
July 2 (Thu) 13:00 - 14:00, 2026
Yawako W. Kawaguchi (Postdoctoral Researcher, Molecular Life History Laboratory, National Institute of Genetics)
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.
Venue: Seminar Room #359 (Main Venue) / via Zoom
Event Official Language: English
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Seminar
Improving data analysis in biology and in general with Tensor Decomposition
June 18 (Thu) 13:00 - 14:30, 2026
Lucas Sort (Postdoctoral Researcher, Mathematical Genomics RIKEN ECL Research Unit, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
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.
Venue: via Zoom / Seminar Room #359
Event Official Language: English
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Seminar
Mode Estimation in the Space of Phylogenetic Trees with Applications to Species Tree Reconstruction
June 11 (Thu) 13:00 - 14:00, 2026
Yuki Takazawa (Project Research Associate, Graduate School of Information Science and Technology, The University of Tokyo)
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.
Venue: Seminar Room #359 (Main Venue) / via Zoom
Event Official Language: English
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Seminar
Membrane Geometry Regulates Phase Morphology in Postsynaptic Condensates
June 4 (Thu) 14:00 - 15:00, 2026
Risa Yamada (Ph.D. Student, Division of Biological Sciences, Graduate School of Science, Kyoto University)
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.
Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359
Event Official Language: English
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Seminar
Towards rock-solid evolutionary genomics
May 28 (Thu) 13:00 - 14:00, 2026
Leo Speidel (RIKEN ECL Unit Leader, Mathematical Genomics RIKEN ECL Research Unit, Division of Fundamental Mathematical Science, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
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.
Venue: via Zoom / Seminar Room #359
Event Official Language: English
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Seminar
Stochastic Thermodynamics: noise and energetics of nanoscale systems
May 21 (Thu) 13:00 - 14:00, 2026
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.
Venue: via Zoom / Seminar Room #359
Event Official Language: English
259 events