BEGIN:VCALENDAR VERSION:2.0 PRODID:-//SoPA UoE//Event Calendar//EN X-WR-CALNAME:Statistical Physics and Complexity Group meeting X-WR-CALDESC:Statistical Physics and Complexity Group meeting X-PUBLISHED-TTL:PT12H CALSCALE:GREGORIAN METHOD:PUBLISH BEGIN:VTIMEZONE TZID:Europe/London X-LIC-LOCATION:Europe/London BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 DTSTART:19810329T010000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU TZNAME:BST END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 DTSTART:19961027T020000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU TZNAME:GMT END:STANDARD END:VTIMEZONE BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-85962@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250812T145136 LAST-MODIFIED:20251007T191927 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251007T150000 DTEND;TZID=Europe/London:20251007T160000 SUMMARY:Dynamically Emergent Correlations DESCRIPTION:The goal of this talk is to show that strong correlations betw een particles may emerge dynamically due to a common stochastically fluctu ating environment\, even when there is no direct built-in interaction betw een particles. These correlations grow with time\, eventually driving the system into a `strongly correlated' nonequilibrium stationary state with   nontrivial properties. I will demonstrate this in an exactly solvable m odel of noninteracting Brownian particles in a harmonic trap whose stiffne ss switches between two values at a constant rate. This model has been rec ently realized experimentally in optically trapped colloidal particle syst ems. Experimental results agree very well with theoretical predictions.\n\ nSpeaker:\n* Satya Majumdar (Université Paris-Saclay) LOCATION:Online - see email for details. URL:https://www.ph.ed.ac.uk/events/2025/85962-dynamically-emergent-correla tions END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86144@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250919T091608 LAST-MODIFIED:20251021T101815 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251014T150000 DTEND;TZID=Europe/London:20251014T160000 SUMMARY:Barrier crossing and rare fluctuations of active particles DESCRIPTION:Peter Sollich\, Institute for Theoretical Physics\, University of Goettingen\n (with Rafael Diaz\, C Karthik\, Leif Peters\, Lars Stutze r\, Diego Tapias)\n \n We study barrier crossing processes for active part icles. Using a low-noise Kramers limit we derive the effective activation barriers for three standard descriptions: active Brownian (ABP)\, active O rnstein-Uhlenbeck (AOUP) and run-and-tumble particles (RTP). We find that\ , because barrier crossing is dominated by rare fluctuations\, there are s ignificant qualitative differences between these\, opening the way to e.g. designing potentials that could sort active particles according to their self-propulsion mechanism. For ABPs one key result is that\, for potential s with a symmetry axis\, activity can generate optimal escape paths that b reak this symmetry.\n\nSpeaker:\n* Professor Peter Sollich (Universität G öttingen\, Institut für Theoretische Physik) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86144-barrier-crossing-and-rare-fl uctuations-of-active-particles END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86015@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250825T182546 LAST-MODIFIED:20251021T171453 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251021T150000 DTEND;TZID=Europe/London:20251021T160000 SUMMARY:Optimal learning protocols via statistical physics and control the ory DESCRIPTION:Learning is a complex dynamical process shaped by many interco nnected decisions. Protocols that govern how to tune hyperparameters in ar tificial networks\, or how to allocate cognitive effort in biological lear ners\, can have dramatic effects on performance. Yet our theoretical under standing of optimal learning strategies remains limited\, due to the nonli near nature of learning dynamics and the high dimensionality of the learni ng space.\n\nIn this talk\, I will present a framework that combines stati stical physics and control theory to identify optimal learning protocols i n prototypical neural network models (see Refs. [1\,2]). In the high-dimen sional limit\, we derive closed-form equations for a small set of order pa rameters that track stochastic gradient descent. This reduction allows to formulate the design of learning protocols—such as curricula\, dropout s chedules\, or noise levels—as an optimal control problem on the dynamics of the order parameters\, with the objective of minimizing the final gene ralization error.\n\nI will discuss applications to both toy models and re al datasets\, showing how the resulting strategies unveil key learning tra de-offs\, for example\, between exploiting informative directions in the d ata and limiting noise sensitivity\, and how these insights may contribute to a principled theory of meta-learning.\n\n[1] Mignacco\, F. and Mori\, F.\, 2025. A statistical physics framework for optimal learning. arXiv pre print arXiv:2507.07907.\n\n[2] Mori\, F.\, Mannelli\, S.S. and Mignacco\, F.\, Optimal Protocols for Continual Learning via Statistical Physics and Control Theory. In The Thirteenth International Conference on Learning Rep resentations.\n\nSpeaker:\n* Francesca Mignacco (Princeton University) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86015-optimal-learning-protocols-v ia-statistical-physics-and-control-theory END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86025@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250827T100426 LAST-MODIFIED:20251028T181556 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251028T150000 DTEND;TZID=Europe/London:20251028T160000 SUMMARY:The "lifted" TASEP and non-reversible Monte Carlo sampling DESCRIPTION:I discuss non-reversible Markov-chain Monte Carlo algorithms t hat\, for particle systems\, rigorously sample the positional Boltzmann di stribution and have faster than physical dynamics. These algorithms all fe ature a non-thermal velocity distribution. They are exemplified by the "li fted" TASEP\,  which appears as a one-dimensional lattice reduction of ev ent-chain Monte Carlo. It features exceptionally fast out-of-equilibrium m ixing and equilibrium relaxation time scales\, that are faster than for th e (unlifted) TASEP. I finally analyze the lifted TASEP in terms of "true" self-avoiding random walks.\n\nF. H. L. Essler\, W. Krauth PRX 14\, 041035 (2024)\n\nB. Massoulié\, C. Erignoux\, C. Toninelli\, W. Krauth PRL 135\ , 127102 (2025)\n\nSpeaker:\n* Professor Werner Krauth (École Normale Sup érieure\, Paris) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86025-the-lifted-tasep-and-non-rev ersible-monte-carlo-sampling END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-85934@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250725T120234 LAST-MODIFIED:20251106T103255 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251104T150000 DTEND;TZID=Europe/London:20251104T160000 SUMMARY:Collective Response in Biological Groups DESCRIPTION:Response is a defining feature of living collectives. Even mor e than order itself\, it provides a genuine signature of collective behavi our\, reflecting the ability of a group to maintain global coherence when exposed to external stimuli or threats.\n In this talk\, I will explore th e mechanisms of response in flocking systems\, combining empirical observa tions with theoretical insights. I will first summarise experimental findi ngs from natural swarms and flocks\, and then discuss how far minimal mode ls of collective motion can reproduce the behaviour observed in real data. \n\nSpeaker:\n* Professor Irene Giardina (Sapienza University) LOCATION:Zoom - see email. URL:https://www.ph.ed.ac.uk/events/2025/85934-collective-response-in-biolo gical-groups END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86023@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250826T151712 LAST-MODIFIED:20251111T173248 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251111T150000 DTEND;TZID=Europe/London:20251111T160000 SUMMARY:Anomalous heat transport in chains of oscillators. Some results. DESCRIPTION:The description of heat transport from first principles has lo ng challenged researchers. The diffusive behaviour of heat\, as dictated b y Fourier's law of heat conduction\, generally breaks down in low dimensio ns\, yielding anomalous heat transport. We study heat transport in a chain of oscillators perturbed by long-range conservative stochastic noise out of equilibrium. By solving the equations governing the evolution of the co variance matrix in the thermodynamic limit\, we derive expressions for the temperature profile and heat flux\, and show that the evolution is compat ible with a fractional diffusion equation. Then\, we consider the possibil ity of long-range interaction and long-range noise and derive exact expres sions for the heat current-current correlations in the thermodynamic limit . We explore the consequences of our results on the behaviour of anomalous heat transport.\n\nSpeaker:\n* Professor Carlos Mejia-Monasterio (Technic al University of Madrid) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86023-anomalous-heat-transport-in- chains-of-oscillators-some-results END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86019@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250825T183839 LAST-MODIFIED:20251118T173129 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251118T150000 DTEND;TZID=Europe/London:20251118T160000 SUMMARY:Glassy physics - from liquids to living cells DESCRIPTION:The liquid-to-glass transition is a common but extremely compl ex phenomenon that still ranks among the deepest unsolved problems in theo retical condensed matter physics. In this talk I will discuss some recent advances in the theory of glassy matter\, and the (perhaps surprising) lin k with the behavior of living cells in dense cell layers and tissues. Ulti mately\, a better understanding of the physics of the glass transition cou ld even lead to a more accurate prognosis for cancer metastasis.\n\nSpeake r:\n* Professor Liesbeth Janssen (Eindhoven University of Technology) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86019-glassy-physics-from-liquids- to-living-cells END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86017@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250825T183204 LAST-MODIFIED:20251125T195039 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251125T150000 DTEND;TZID=Europe/London:20251125T160000 SUMMARY:Large Deviations in Self-Interacting Processes DESCRIPTION:I will present recent results on large-deviation asymptotics f or self-interacting processes - non-Markovian systems whose dynamics depen d on their own empirical occupation measures. In particular\, I will discu ss a level-2.5 large deviation principle for self-interacting jump process es\, whose rate function can be interpreted as a dynamical extension of th e classical Donsker–Varadhan rate function for Markov processes. I will sketch the main ideas behind the proof and illustrate the framework throug h examples and applications\, including\, time permitting\, kinetic and th ermodynamic bounds.\n\nSpeaker:\n* Francesco Coghi (University of Nottingh am) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86017-large-deviations-in-self-int eracting-processes END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-85923@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250724T093151 LAST-MODIFIED:20251202T165343 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251202T150000 DTEND;TZID=Europe/London:20251202T160000 SUMMARY:Assisting sampling of physical systems with generative models DESCRIPTION:Deep generative models parametrize very flexible families of d istributions able to fit complicated datasets of images or text. These mod els provide independent samples from complex high-distributions at negligi ble costs. On the other hand\, sampling exactly a target distribution\, su ch as the Boltzmann distribution of a physical system\, is typically chall enging: either because of dimensionality\, multi-modality\, ill-conditioni ng or a combination of the previous. In this talk\, I will discuss a recen t line of work using generative models to accelerate sampling. While the a pproach shows promises\, it still struggles as the system size gets large. When a coarse-graining resolving the metastability is known\, I will also discuss how enhanced sampling can be revisited with generative models\, a nd can ease this curse of dimensionality.\n\nSpeaker:\n* Marylou Gabrié ( École Normale Supérieure\, Paris) LOCATION:Zoom - see email invite. URL:https://www.ph.ed.ac.uk/events/2025/85923-assisting-sampling-of-physic al-systems-with-generative-models END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86027@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250827T200505 LAST-MODIFIED:20251209T170416 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20251209T150000 DTEND;TZID=Europe/London:20251209T160000 SUMMARY:The statistical physics of nonequilibria DESCRIPTION:The laws of material equilibria follow a well-known logic: a F irst Law (conservation)\; a Second Law (an entropy tendency principle)\; a nd Legendre Transforms that give: (i) driving forces (T\, p\, μ) from obs ervables (U\, V\,N)\, and give (ii) fluctuation-response and Maxwell Relat ions.  In the past\, there has been no equivalent logic for Non-Equilibri a\, such as forces and flows on networks. I will describe such a logic\, w hich we call Caliber Force Theory (CFT).  It requires maximizing path ent ropies (Maximum Caliber) instead of state entropies.  I will describe som e of the new relationships and insights it gives into dynamics.\n\nSpeaker :\n* Professor Ken A. Dill (Stony Brook University) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2025/86027-the-statistical-physics-of-n onequilibria END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86674@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251127T101055 LAST-MODIFIED:20260113T183522 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260113T150000 DTEND;TZID=Europe/London:20260113T160000 SUMMARY:Avalanches\, Chaos\, and Overlap Locking In Spin Glasses: old prob lems and recent developments DESCRIPTION:Perturbations in disordered systems have dramatic effects both in the structure of low energy states that get completely reshuffled and in the aging dynamics that decorrelates from the unperturbed one.  The fr agility of the Gibbs states under perturbation and the emergence of a crit ical Long Range Order are two faces of the same coin. In this talk I will consider the effect of very tiny perturbation and study\n\n(1) the emergen ce of universal behaviour in the chaotic dependence of disordered Gibbs st ates in a random field\,\n\n(2) the development of strong correlations in weakly coupled systems\,\n\n(3) the fluctuations leading to size correctio ns in the Sherrington-Kirkpatrick model\,\n\n(4) The stability of spin-gla ss RSB states in Dyson-lattice hierarchical spin glasses.\n\nThese problem s can be addressed in detail at the mean field level through semi-analytic al techniques allowing the efficient generation of random trees describing 'infinite volume spin-glass samples'. We get a coherent picture of fluctu ations that we submit to test in numerical simulations.\n\nSpeaker:\n* Pro fessor Silvio Franz (Università del Salento) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86674-avalanches-chaos-and-overlap -locking-in-spin-glasses-old-problems-and-recent-developments END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86664@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251126T081515 LAST-MODIFIED:20260120T171522 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260120T150000 DTEND;TZID=Europe/London:20260120T160000 SUMMARY:Phenotypic plasticity shapes biofilm’s structure and fluid trans port enhancing resilience to antibiotics DESCRIPTION:Phenotypic heterogeneity is one of the hallmarks of the biofil m lifestyle\, where even isogenic populations give rise to spatially organ ized and phenotypically distinct subpopulations. One such pattern is gener ated by the ability of several biofilm-forming bacteria to switch between a flagellated and a matrix producing state. Here\, using Bacillus subtili s as a model system\, we investigate the role of this switch during biofi lm development on a solid-air interface. \n\nBy comparing the matrix-flag ella spatio-temporal patterns in wild-type biofilms with mixtures of flage lla- and matrix-null mutants biofilms\, we find that pattern formation doe s not require a phenotypic switch that enables individual cells to respond to the local environment\, but can be explained by a completely stochasti c switch coupled to a phenotype-dependent fitness landscape that selects p henotypes at the population level. Integration of experiments and physical models shows that the coexistence between flagellated and matrix-producin g cells provides the population with enhanced resilience to environmental changes\, by enabling cells to manipulate and harness the local morphologi cal and transport properties within the biofilm. Our results not only reve al a new evolutionary advantage of phenotypic plasticity in biofilms\, but also illustrate how the biology and ecology of these populations are intr insically tied to their physical properties.\n\nSpeaker:\n* Associate Prof essor Diana Fusco (University of Cambridge) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86664-phenotypic-plasticity-shapes -biofilms-structure-and-fluid-transport-enhancing-resilience-to END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86666@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251126T082510 LAST-MODIFIED:20260127T174804 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260127T150000 DTEND;TZID=Europe/London:20260127T160000 SUMMARY:How synaptic heavy tails and modularity shape chaotic activity in randomly connected neural networks DESCRIPTION:Understanding how network connectivity shapes neural dynamics is central to both theoretical neuroscience and artificial intelligence. I n this talk\, I will discuss how deviations from classical homogeneous ran dom connectivity alter the emergence and nature of chaotic activity in rec urrent neural networks.\n\nIn the first part\, motivated by growing experi mental evidence that the distribution of cortical synaptic weights exhibit s heavy tails\, I will focus on networks with power-law distributions of w eights. I will show that heavy-tailed connectivity fundamentally reshapes the transition to chaos. In networks of binary neurons\, only networks wit h heavy-tailed weights display a continuous transition to chaos accompanie d by scale-free neuronal avalanches. In networks with heavy-tailed weights and smooth activation functions\, finite-size effects play a crucial role : while infinite-size mean-field theory predicts ubiquitous chaos\, finite networks undergo a slow transition between quiescent and chaotic regimes. As a result\, these networks exhibit critical-like behavior over a wider range of the control parameter compared to their Gaussian counterparts. At the same time\, heavier tails are associated with a lower dimensionality of chaotic activity.\n\nIn the second part\, I will turn to modular and hi erarchical network connectivity structures. Using mean-field theory and si mulations\, I will show that modularity introduces a rich dynamical phase diagram with distinct low- and high-dimensional chaotic regimes\, separate d by a crossover region characterized by low values of the maximal Lyapuno v exponent and participation ratio dimension\, but with high values of the Lyapunov dimension. Surprisingly\, chaos can be attenuated either by addi ng noise to strongly modular networks or by introducing modular structure into otherwise random connectivity. Extending the model to include a multi level\, hierarchical connectivity reveals that a loose balance of activity across levels naturally drives the system toward the edge of chaos.\n\nSp eaker:\n* Łukasz Kuśmierz (Allen Institute\, Seattle\, Washington\, USA) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86666-how-synaptic-heavy-tails-and -modularity-shape-chaotic-activity-in-randomly-connected-neural-networks END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86651@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251120T085059 LAST-MODIFIED:20260203T183521 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260203T150000 DTEND;TZID=Europe/London:20260203T160000 SUMMARY:Can Neural networks generate new data? DESCRIPTION:This talk will describe the present status of theoretical stud ies on generative diffusion  based on statistical physics\, focusing on the important question of memorization versus generalization.\n\nSpeaker:\ n* Professor Marc Mézard (Bocconi University) LOCATION:Online - see email invite. URL:https://www.ph.ed.ac.uk/events/2026/86651-can-neural-networks-generate -new-data END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86155@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20250923T083635 LAST-MODIFIED:20260219T115426 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260210T150000 DTEND;TZID=Europe/London:20260210T160000 SUMMARY:Proxitaxis: an adaptive search strategy based on proximity and sto chastic resetting DESCRIPTION:We introduce proxitaxis\, a simple search strategy where the s earcher has only information about the distance from the target but not th e direction. The strategy consists of three crucial components: (i) local adaptive moves with a distance-dependent diffusion coefficient\, (ii) inte rmittent long-range returns via stochastic resetting to a certain location $\\vec{R}_0$\, and (iii) an inspection move where the searcher dynamicall y updates the resetting position $\\vec{R}_0$. We compute analytically the capture probability of the target within this strategy and show that it c an be maximized by an optimal choice of the control parameters of this str ategy. Moreover\, the optimal strategy undergoes multiple phase transition s as a function of the control parameters. These phase transitions are gen eric and occur in all dimensions.\n\nSpeaker:\n* Manas Kulkarni (Tata Inst itute of Fundamental Research (TIFR) Bangalore) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86155-proxitaxis-an-adaptive-searc h-strategy-based-on-proximity-and-stochastic-resetting END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86662@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251125T093250 LAST-MODIFIED:20260224T175325 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260224T150000 DTEND;TZID=Europe/London:20260224T160000 SUMMARY:How can neural networks compute with few resources? A lesson from mice. DESCRIPTION:Despite the unsustainable growth in energy consumption by arti ficial intelligence models and the recognition of the major role played by metabolic constraints in brain evolution\, the relationship between compu tation and energy remains insufficiently studied and understood. Recently\ , Padamsey et al. experimentally investigated this relationship in the con text of visual information processing in food-deprived mice. Combining ana lysis of their activity data and modeling inspired by statistical physics\ , in particular some variants of the Hopfield model\, I will propose some mechanism by which neural circuits can spare considerable energy with litt le impact on their performance.\n\nSpeaker:\n* Professor Remi Monasson (Ec ole Normale Supérieure\, Paris) URL:https://www.ph.ed.ac.uk/events/2026/86662-how-can-neural-networks-comp ute-with-few-resources-a-lesson-from-mice END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86269@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251021T102905 LAST-MODIFIED:20260303T185522 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260303T150000 DTEND;TZID=Europe/London:20260303T160000 SUMMARY:Life on a Noisy Seascape: Extinction\, Growth\, and Diversity DESCRIPTION:Populations and communities rarely evolve in static environmen ts\; their fitness landscapes fluctuate across space and time\, forming wh at may be called a noisy seascape. This talk examines how such variability modifies classical models of population dynamics and community stability. Beginning from the logistic equation\, I will show how spatiotemporal flu ctuations in fitness lead naturally to power-law population statistics and \, under certain conditions\, to the empirical (fractional) Richards growt h law. Extending these ideas to interacting species reveals that the combi ned effects of dispersal and environmental noise can stabilize large\, div erse communities despite strong competitive interactions. The resulting fr amework connects extinction\, growth\, and coexistence within a unified vi ew of life on a noisy seascape.\n\nSpeaker:\n* Professor Mehran Kardar (Ma ssachusetts Institute of Technology) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86269-life-on-a-noisy-seascape-ext inction-growth-and-diversity END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86620@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251111T102913 LAST-MODIFIED:20260310T165540 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260310T150000 DTEND;TZID=Europe/London:20260310T160000 SUMMARY:Subordination processes for non-Gaussian diffusion: modelling and first passage phenomena DESCRIPTION:The motion of diffusive tracers in complex and disordered envi ronments often deviates from classical Gaussian statistics associated with standard Brownian motion\, instead exhibiting robust non-Gaussian behavio ur\, even when the mean squared displacement remains diffusive. Experiment al\, analytical and computational studies have linked such deviations to s ample-to-sample variability and/or spatio-temporal heterogeneity intrinsic to these systems. I will present a general theoretical framework based on the concept of subordination that captures the emergence of non-Gaussian diffusion across a broad class of complex systems. Within this framework\, two dynamical regimes\, characterised by distinct scaling properties of t he subordinator’s probability density function\, naturally arise. Buildi ng on this formalism\, I will show that\, in the context of first-passage phenomena\, Gaussian search strategies remain more effective in terms of t he mean first-passage time. However\, non-Gaussian dynamics can become mar kedly more efficient when only a small fraction of tracers is required to reach the target\, leading to substantial deviations from Gaussian predict ions. Finally\, I will outline ongoing work and discuss future perspective s.\n\nSpeaker:\n* Vittoria Sposini (University of Padova) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86620-subordination-processes-for- non-gaussian-diffusion-modelling-and-first-passage-phenomena END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86700@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251202T163807 LAST-MODIFIED:20260317T171607 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260317T150000 DTEND;TZID=Europe/London:20260317T160000 SUMMARY:Position-Momenta Uncertainties in Classical Systems DESCRIPTION:We demonstrate that classical particles coupled to thermal bat hs that conserve angular momentum\, or allow it to fluctuate about a nonz ero mean\, obey a position–momentum uncertainty relation formally anal ogous to the Heisenberg bound. For motion in an arbitrary central potentia l\, this relation universally reduces to  $\\Delta x  \\Delta p_x   >  L /2 $   where  $L$  is the mean angular momentum (or the conserved initial value). We establish the physical realizability of such baths by constructing Langevin dynamics that preserve a Boltzmann energy distributi on in steady state for both conserved and non-conserved angular momentum  ensembles. We also outline experimental routes for observing this emerge nt classical uncertainty bound.\n\nRef: Dipesh K. Singh\, P. K. Mohanty\,  Phys. Rev. E 112\, 054129 (2025)\n\nSpeaker:\n* Professor P K Mohanty (I ISER Kolkata) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86700-position-momenta-uncertainti es-in-classical-systems END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86744@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251208T150648 LAST-MODIFIED:20260325T064130 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260324T150000 DTEND;TZID=Europe/London:20260324T160000 SUMMARY:Molecular Kinetics with Koopman Generators and Random Fourier Feat ures DESCRIPTION:In this talk\, I will present recent work on estimating kineti c properties of molecular systems - such as transition rates and correlati on functions - using models for the Koopman generator. I will show that ra ndom Fourier features - a low-rank approximation technique for kernel meth ods - provide a versatile and efficient framework to estimate these models from data. I will present three use cases: first\, a benchmark study on e stimating slow transition timescales. Second\, interpolation of kinetic pr operties across temperatures using generative models. Third\, learning of coarse grained models which preserve transition timescales.\n\nSpeaker:\n* Dr Feliks Nüske (Max Planck Institute\, Magdeburg) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86744-molecular-kinetics-with-koop man-generators-and-random-fourier-features END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86611@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251107T080844 LAST-MODIFIED:20260331T172055 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260331T150000 DTEND;TZID=Europe/London:20260331T160000 SUMMARY:Random Multiplicative Growth\, Redistribution and Inequalities DESCRIPTION:Random multiplicative growth processes provide a simple yet re markably powerful framework to understand a wide range of “scale‑free ’’ phenomena\, from city and firm sizes to wealth distributions. I wil l review how multiplicative noise generically generates Pareto (power‑la w) tails. In the absence of redistribution (/migrations)\, the model revea ls a genuine condensation transition: wealth/populations concentrates on a vanishing fraction of entities.\n\nI will then introduce a generic stocha stic model in which multiplicative growth is coupled to redistribution or diffusion on a network—motivated by migration between cities\, wealth ta xes and transfers\, portfolio rebalancing\, or species flow between habita ts. This framework allows one to discuss (i) the asymptotic global growth rate\, (ii) the tail exponent of the stationary distribution of “abundan ces”\, and (iii) the conditions under which redistribution prevents cond ensation.\n\nI will discuss the role of network topology\, heterogeneity o f local growth rates and their time-persistence\, and show how these ingre dients lead to non‑trivial “exploration–exploitation’’ trade‑o ffs and to an optimal tax or transfer rate. Connections with directed poly mers\, KPZ‑type growth\, the Random Energy Model will be discussed\, as well as recent applications in economics and ecology.\n\nSpeaker:\n* Profe ssor Jean-Philippe Bouchaud (École Normale Supérieure and Capital Fund M anagement) LOCATION:Online - see email invite. URL:https://www.ph.ed.ac.uk/events/2026/86611-random-multiplicative-growth -redistribution-and-inequalities END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86790@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20260107T093942 LAST-MODIFIED:20260428T191902 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260428T150000 DTEND;TZID=Europe/London:20260428T160000 SUMMARY:Self-organized hyperuniformity in a minimal model of population dy namics DESCRIPTION:In this talk\, I will present our recent work [1]\, in which w e uncover self-organized hyperuniformity in a generic model of population dynamics. The model generalizes a class of models recently introduced to a ccount for protracted transients in biological systems. In these models\, competition among individuals for a shared resource generates an effectiv e feedback mechanism that asymptotically guides the population towards a critical steady state with divergent individual lifetimes. \n\nRemarkably \, we find that in its spatially extended form\, the model exhibits hyperu niform density correlations. Through explicit coarse-graining\, we derive a hydrodynamic theory that clarifies the underlying mechanism for this str iking statistical behaviour. Unlike previous models for non-equilibrium hy peruniform states\, our model does not exhibit conservation laws\, even in the asymptotic regime. Instead\, hyperuniformity arises from the asymptot ic divergence of the interaction range.\n\nThese results suggest potential applications to cellular population dynamics and ecological systems. More broadly\, our framework highlights how resource-mediated interactions can regulate collective behaviour in living systems\, and opens new direction s for exploring self-organization in non-equilibrium biological contexts.\ n\n[1] TA\, N. Wiegenfeld\, O. Karin\, and B. D. Simons\, arXiv:2509.08077 (2026).\n\nSpeaker:\n* Tal Agranov (University of Cambridge) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86790-self-organized-hyperuniformi ty-in-a-minimal-model-of-population-dynamics END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86791@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20260107T171225 LAST-MODIFIED:20260505T182443 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260505T150000 DTEND;TZID=Europe/London:20260505T160000 SUMMARY:Many unstable fixed points\, and chaotic dynamics: an high-dimensi onal example DESCRIPTION:Complex systems tend to exhibit out-of-equilibrium dynamics ov er a broad range of timescales. A key theory challenge is to understand th e features of this out-of-equilibrium behavior from the properties of the attractors of the system’s dynamical equations. Mean-field theories of s pin glass dynamics offer elegant examples\, linking phenomena such as agin g to the properties of special families of stationary points of the underl ying free-energy landscape\, that attract the dynamics at large times. How ever\, these insights apply mainly to systems to which one can associate s uch landscapes. It is an open question how to extend these ideas to high-d imensional non-conservative systems (such as biological neural networks\, large ecosystems) whose dynamics is not landscape optimization. I will pre sent a simple model of a high-dimensional system with non-reciprocal inter actions whose out-of-equilibrium\, chaotic dynamics can be characterized a nalytically at long times. I will discuss its dynamical phase diagram and compare it to the statistical distribution of the many\, unstable fixed points of the dynamical equations. This comparison challenges the idea tha t chaotic dynamics in non-conservative settings can be understood from fix ed points alone\, at least from the typical ones.\n\nThe results are prese nted in arXiv:2503.20908\n\nSpeaker:\n* Valentina Ros Dr (CNRS - Universit é Paris Saclay\, Orsay) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86791-many-unstable-fixed-points-a nd-chaotic-dynamics-an-high-dimensional-example END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86831@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20260113T080212 LAST-MODIFIED:20260512T180959 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260512T150000 DTEND;TZID=Europe/London:20260512T160000 SUMMARY:Emergent polar order in nonpolar mixtures with nonreciprocal inter actions DESCRIPTION:Self-organization in living and active systems emerges from mi croscopic interactions\, which are governed by symmetries and intrinsic pr operties of individual constituents. It is possible\, however\, that spont aneously formed composite units lead to the emergence of large-scale behav ior that is completely different from what is expected for the single part icles. An example of such occurrences is non-reciprocal active matter\, wh ere asymmetric interactions can induce polarity in nonpolar mixtures.\n\nT o study this phenomenon\, I will present a generic class of active matter models with two scalar fields that represent the concentration of molecula r species interacting nonreciprocally. We study the stability of the emerg ent ordered state\, showing the existence of true long-range polar order i n two dimensions and above\, both at the linear level and by including all relevant nonlinearities in the Renormalization Group sense. We achieve th is by uncovering a mapping to the Kardar-Parisi-Zhang universality class f or the dynamics of fluctuations. This classification allows us to prove a conclusive violation of the Mermin-Wagner theorem and to predict the large -scale behavior of systems with non-reciprocal interactions at any dimensi on.\n\nMoreover\, natural systems are often three dimensional\, leading to momentum conservation in the bulk. To address this scenario\, I will exte nd this dry system to a wet case\, incorporating hydrodynamic interactions in a momentum-conserving fluid. The dynamics of the polar order parameter reveal a fluid-mediated linear instability of the ordered state\, which i s ultimately stabilized by nonlinear effects in the regime of strong non-r eciprocity. This result confirms that the emergent non-equilibrium polar p attern is robust also to hydrodynamic couplings.\n\nREFERENCES.\n [1] G. P isegna\, S. Saha\, R. Golestanian\, Emergent polar order in nonpolar mixtu res with nonreciprocal interactions\, Proceedings of the National Academy of Sciences 121 (51) (2024).\n [2] G. Pisegna\, N.Rana\, R. Golestanian\, S. Saha\, Non-reciprocal mixtures in suspension: the role of hydrodynamic interactions\, Physical Review Letters 135 (10)\, 108301 (2025).\n\nSpeake r:\n* Giulia Pisegna (Department of Living Matter Physics\, Max Planck Ins titute for Dynamics and Self-Organization\, Göttingen) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86831-emergent-polar-order-in-nonp olar-mixtures-with-nonreciprocal-interactions END:VEVENT BEGIN:VEVENT CLASS:PUBLIC UID:EVENT-86742@www.ph.ed.ac.uk DTSTAMP:20260606T120819 CREATED:20251208T082929 LAST-MODIFIED:20260520T110348 STATUS:CONFIRMED DTSTART;TZID=Europe/London:20260519T150000 DTEND;TZID=Europe/London:20260519T160000 SUMMARY:Non-equilibrium physics of the epigenome DESCRIPTION:The self-organization of cells into complex organism is a stri king example of a non-equilibrium system. Epigenetic modifications of the DNA play key roles and experimental breakthroughs in biology now allow u s to profile such molecular states of cells with unprecedented detail. Dr awing on these experiments\, I will show how field theory methods from non -equilibrium statistical physics can unveil the biophysical principles tha t govern the time evolution of the epigenome. In the first part of my talk \, I will show how non-equilibrium field theory and renormalisation group theory can make sense of an unexpected observation of self-similar scalin g in the embryonic epigenome. I will then discuss how the interplay betwee n geometric and chemical changes of the DNA constitutes a clock that deter mines the time scale of ageing.\n\nSpeaker:\n* Professor Steffen Rulands ( Ludwig-Maximilians-Universität\, Munich) LOCATION:Online - see email. URL:https://www.ph.ed.ac.uk/events/2026/86742-non-equilibrium-physics-of-t he-epigenome END:VEVENT END:VCALENDAR