School of Physical Sciences

The Fermi surface is a fundamental concept in condensed matter physics, defining the boundary in reciprocal space between occupied and unoccupied electronic states at zero temperature. Its topology governs essential properties such as electrical conductivity, magnetism, and superconductivity. Experimental techniques for measuring the Fermi surface, such as Angular Correlation of Electron Positron Annihilation Radiation (ACAR), often suffer from poor signal-to-noise ratios, making high-quality data acquisition both costly and time-consuming. Inspired by recent machine learning advances in medical imaging, this work introduces DeepCormack, a hybrid framework that combines the Modified Cormack Method with neural network–based denoising and reconstruction. The approach achieves accurate reconstructions of the Fermi surface from fewer and noisier measurements, reducing reliance on long acquisition times. Moreover, the methodology is adaptable to other techniques for probing the Fermi surface via the electron momentum density, including Compton scattering. By enhancing reconstruction accuracy and efficiency, DeepCormack has the potential to broaden access to Fermi surface studies and accelerate the discovery and characterization of novel material properties. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Georg Francis Barlaup Lovric (University of Cambridge)
• Thursday 11 September 2025, 16:00-16:10
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Statistical mechanics seeks to derive macroscopic thermodynamics from microscopic dynamics, yet its central quantity— entropy— has long lacked a formulation that directly matches the thermodynamic second law. The second law of thermodynamics predicts increasing macroscopic thermal entropy, while the microscopic Gibbs entropy is conserved under Hamiltonian dynamics. To resolve this discrepancy, we introduce the Microscopic Dynamical Entropy (MDE) for a system X coupled to a bath Y , with the composite X + Y evolving under exact Hamiltonian dynamics. The MDE directly encodes the thermodynamic identity T∆S = ∆Q, and coincides with the Gibbs entropy when the bath distribution is taken to be uniform on the energy shell. In this formulation, the thermodynamic entropy increase arises from discarding information into the bath’s degrees of freedom. The MDE preserves dynamics while establishing the second law and resolving the echo paradox. We demonstrate its consistency with both classical and stochastic thermodynamics, and show explicitly that finite baths in the Zwanzig model already yield a monotonic increase of the MDE , demonstrating that irreversibility does not rely on the singular N → ∞ limit. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Mingnan Ding (Shanghai Jiao Tong University)
• Thursday 11 September 2025, 15:50-16:00
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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The physics of Topologically Modified polymers (ToMo polymers) is of interest because of its direct relevance to understand chromosome organization in cells. We have been investigating ToMo ring polymers, which have internal loops along the chain contour, and its emergent organization inside cylindrical confinement. We used these localization properties of suitably “designed” polymer topologies to understand the underlying spatio-temporal dynamics of chromosomes in the bacterial cell E. coli [1,2,3]. In this presentation, I will be focusing on the principles of entropic organization of some segments of the polymer along the long axis of the cylinder. Further investigations show how (i) we can modulate entropic interactions between internal loops to induce alignment of polymers segments along the cylinder long-axis, reminiscent of Ising like interactions of magnetic spin and (ii) how suitably “designed” topological modifications can be used to localize certain sections of a polymers to the regions closer to the surface of a sphere [4].  [1] D. Mitra, Shreerang Pande, A. Chatterji. Phys. Rev.E, 106, 054502 (2022).  [2] D. Mitra, Shreerang Pande, A. Chatterji. Soft Matter, 18, 5615 (2022).  [3] Shreerang Pande, D. Mitra, A. Chatterji. Phys. Rev E, 110, 054401 (2024).  [4] K. Roychoudhury, Shreerang Pande, Indrakanty S.S., D. Mitra, A. Chatterji, arXiv:2501.02276 – Undergoing review in Phys. Rev E 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Shreerang Pande (Indian Institute of Science Education and Research (IISER))
• Thursday 11 September 2025, 15:40-15:50
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Slender structures are ubiquitous in biological and engineered systems, from bacterial flagella to soft robotic arms. The Cosserat rod provides a mathematical framework for slender bodies that can bend, twist, stretch and shear across multiple length scales. In viscous fluid environments at low Reynolds numbers, inertial effects become negligible, and hydrodynamic forces are well approximated by Stokes friction. We demonstrate that the resulting elastohydrodynamic equations of motion, when formulated using Cartan’s method of moving frames, possess the structure of a geometric field theory in which the configuration field takes values in SE(3) , the Lie group of rigid body motions. We present four different representations, namely, vectorial, moving frame, Lie group, and differential form formalisms, of the kinematics, dynamics and constitutive law of the Cosserat rod. Then, a spectral collocation method using Julia is exploited to numerically integrate the coordinatised equations of motion as an Initial-Boundary-Value problem (IBVP), where the local coordinates are specified by 2D translations and rotations. This IBVP is solved as a Differential-Algebraic Equations (DAEs), in which the boundary conditions are imposed as algebraic constraints. Finally, we show that the simulations of a clamped-free Cosserat rod exhibit the expected behaviours. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Mingjia Yan (University of Cambridge)
• Thursday 11 September 2025, 15:30-15:40
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Understanding how environmental conditions shape the evolution of bacteriophages (phages) is critical for designing correct evolutionary experiments that select specific phage traits. This study provides a general mathematical framework that integrates physics-informed neural networks, agent-based statistical simulations, and symbolic regression machine learning techniques to design evolutionary experiments targeting specific phage traits such as high variability in phage phenotypes.  In the study, we used agent-based statistical simulations to generate synthetic time series data for evolutionary scenarios with diverse phenotypic outcomes. Subsequently, we trained Physics-informed neural networks (PINNs) embedded in differential equations on the synthetic time series to reveal possible environments that select given phage traits and uncovered hidden interactions in the system [1].    Reference: [1] Grigorian, G., George, S.V. and Arridge, S., 2024. Learning Governing Equations of Unobserved States in Dynamical Systems. arXiv preprint arXiv:2404.18572. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Hassan Alam (University of Cambridge)
• Thursday 11 September 2025, 15:20-15:30
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Understanding the polarization dynamics of polar solvents is important in advancing research in soft matter, electrochemistry, and biophysics, where accurate prediction of dielectric response plays a key role. In this context, Stochastic Density Functional Theory (SDFT) has emerged as a powerful theoretical framework capable of capturing the collective dynamic behavior of dipolar molecules by incorporating thermal fluctuations into the time-dependent density field. The present work evaluates the reliability of SDFT in predicting the polarization dynamics of polar solvents and provides key insights into integrating these effects into simulations, enabling more accurate and predictive modeling of the solvent polarization effects in soft-matter systems.  Abstract title: Understanding polar solvents through the lens of Stochastic Density Functional Theory  Abstract: Understanding the microscopic behavior and organization of polar solvents has direct implications for a variety of applications, from advanced battery and fuel cell design to the study of charged soft matter systems. Predicting solvent structure and dynamics from first principles remains a significant challenge due to the complex interplay of thermal fluctuations, electrostatic interactions, and molecular orientation. Among the available theoretical approaches, stochastic density functional theory (SDFT) has emerged as a powerful tool for exploring the collective dynamical properties of polar solvents. In this work, we examine the effectiveness of SDFT in describing a polar solvent by comparing its predictions with Brownian dynamics simulations of the Stockmayer fluid-a widely used theoretical model for polar fluids. Our findings indicate that SDFT offers a promising framework for linking molecular-scale interactions to mesoscopic behavior across a broad range of electrochemical and soft-matter systems. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Sleeba Varghere (Sorbonne Université)
• Thursday 11 September 2025, 15:10-15:20
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Dynamic covalent polymer networks are viscoelastic, self-healing materials that have applications in soft robotics, adhesives, 3D printing, and reusable plastics, including coatings. Using poly(dimethyl siloxane)-based dynamic polymer networks, we designed an ultra-thin polymer coating. The PDMS thin film is superhydrophobic, transparent, and adaptable to rough or curved surfaces, making it ideal for multiple applications from the energy sector for solar panels to the commercial sector for cars or as screen protectors. This gel network can be applied to various surfaces (glass, metals, silicon) at heights of 10 nm – 1 micron and still achieve self-healing from pinholes and cuts, prevent delamination of the coating, and promote dropwise condensation for multiple weeks. To unite the dynamic polymer mechanical behavior on the macroscale to the microscale, the relaxation time of the dynamic polymer measured via rheology is compared to the self-healing behavior of a cut in the dynamic thin film using ellipsometry and Atomic Force Microscopy (AFM) as thin film polymer rheology. For non-dynamic glassy thin polymer films, the width of the cut with time follows a power law. This and other models dictating relationships between cut width and self-healing success are investigated for our dynamic polymer network. Factors such as film thickness, cut length and shape, and crosslinking density of the polymer are also used to tune the relaxation response of the material.   

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Ellie Porath (Université PSL)
• Thursday 11 September 2025, 15:00-15:10
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Emulsions are mixtures of immiscible fluids, and as such are frequently encountered in everyday life and industrial applications. In this presentation, I will first detail how, based on observations from industrial partners, we have revisited our understanding of emulsion stability and developed emulsions without surfactants. I will then discuss how the physical chemistry of emulsions has contributed to the revolution in single-cell studies in biology.

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Jean Baudry (ESPCI ParisTech)
• Thursday 11 September 2025, 13:35-14:35
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Polymer blends are critical in many commercial products and industrial processes. For instance, in membrane or fibre spinning, composite materials manufacturing, and thermoplastic compounding and moulding. In most circumstances, such products are formulated with samples of high dispersity, which have generally only been studied at the mean-field level. In this talk, I show how field theoretic treatments of concentration fluctuations can be applied to blends of disperse polymers. This requires a careful analysis of both short- and long-range correlations along with thermodynamic analysis in terms of moments of the molecular weight distribution(s). This powerful combination yields analytical results for the inverse susceptibility, i.e. spinodal curve, which is critical in industrial applications. We demonstrate the importance of dispersity on several example systems, including both “toy” models that may be realized in computer simulation and more realistic industrially relevant blends. We find that the effects of long-range fluctuations are particularly prominent in blends where the component dispersities are mismatched, especially when there is a small quantity of the high-dispersity species. This can be understood as a consequence of the shift in the critical concentration(s) from the monodisperse value(s).

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Phillip Rauscher (Syensqo)
• Thursday 11 September 2025, 11:35-12:35
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Natural and synthetic multi-component gels display emergent properties, which implies that they are more than just the sum of their components. The space between and within human cells, for example, is permeated by multi-component self-assembled gel networks, the extra-cellular matrix and the cytoskeleton, whose self- organization and heterogeneity is central to biological functions. I will discuss how in self-assembled double networks inter-species lateral association can drastically modify the composite architecture, leading to significant changes in plasticity, toughness, and resilience to environmental changes. The architecture, therefore, could be used as a design principle for double networks which are made to emphasize either stability to perturbations or responsiveness to stimuli. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Emanuela Del Gado (Georgetown University)
• Thursday 11 September 2025, 10:35-11:15
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Active solids consume energy to allow for actuation and shape change not possible in equilibrium. We discover a striking anomaly in the continuum description of non-reciprocal active solids, a ubiquitous class of active materials. We find that as microscopic activity increases, macroscale active response can vanish: more is less. Our results unveil a counterintuitive facet of active matter, offering new principles for engineering materials far from equilibrium. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Anton Souslov (University of Cambridge)
• Thursday 11 September 2025, 09:55-10:35
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Generative AI represents a groundbreaking development within the broader “Machine Learning Revolution,” significantly influencing technology, science, and society. In this talk, I will focus on the state-of-the-art “diffusion models,” which are currently used to generate images, videos, and sounds. They are fascinating algorithms for physicists, as they are very much connected to concepts from stochastic thermodynamics, particularly time-reversed Langevin dynamics. Diffusion models initiate from a simple white noise input and evolve it through a Langevin process to generate complex outputs such as images, videos, and sounds. I will show that statistical physics provides guiding principles and methods to characterise this generation process. Specifically, I will discuss how phenomena such as the transition from memorization to generalization and the emergence of data-structure can be understood through the lens of symmetry breaking, phase transitions, and disordered systems.  

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Giulio Biroli (CNRS - Ecole Normale Superieure Paris)
• Wednesday 10 September 2025, 16:50-17:30
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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The ability to concisely describe the dynamical behavior of soft materials through closed form constitutive relations holds the key to accelerated and informed design of materials and processes. The conventional approach is to construct constitutive relations through simplifying assumptions and approximating the time- and rate-dependent stress response of a complex fluid to an imposed deformation. Once the constitutive model is available, it’s usually solved numerically for other flow geometries and kinematics. While traditional frameworks have been foundational to our current understanding of soft materials, they often face a two-fold existential limitation: (i) constructed on ideal and generalized assumptions, precise recovery of material-specific details is usually serendipitous, if possible, and (ii) inherent biases that are involved by making those assumptions commonly come at the cost of new physical insight. I will present a wide spectrum of data-driven frameworks that can help both develop and solve the new generation of constitutive models for soft materials. These are generally methods that involve combination of statistical inference formalisms, with the addition of physical intuition. These physical intuitions can come in form of low fidelity data or model predictions; but the overall result is the same: combination of data-driven predictions and physical intuition clearly opens new horizons for constitutive model detection, discovery, and simulation. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Safa Jamali (Northeastern University)
• Wednesday 10 September 2025, 13:50-14:30
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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Flows used to process complex soft materials almost always involve complex deformations that cannot be captured in a rheometer but may profoundly influence the final microstructure and performance of the material.  Furthermore, accurate first-principles models to relate flow, microstructure, and stress are unavailable for most complex fluids, especially when undergoing complex deformations. We describe a framework that uses machine learning and data assimilation to circumvent these limitations, exploiting a new experimental approach from the research group of Matt Helgeson that yields microstructural information in complex flows of complex fluids. The framework is constructed to automatically satisfy the key symmetry of microstructural evolution, material frame indifference, and enables data-driven determination of microstructural evolution equations for complex fluids in very general flows. 

TGM150 - 9th Edwards Symposium – Frontiers in Statistical Physics and Soft Matter

• Speaker: Michael Graham (University of Wisconsin-Madison)
• Wednesday 10 September 2025, 13:10-13:50
• Venue: External.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 18:00-19:00
• Venue: Seminar Room 2, Newton Institute.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 12:30-13:30
• Venue: Churchill College.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 10:30-11:00
• Venue: Foyer.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 09:00-10:30
• Venue: Seminar Room 1, Newton Institute.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 09:00-10:30
• Venue: Discussion Room, Newton Institute.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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TGM151 - UK Graduate Modelling Camp 2025

• Speaker:
• Thursday 25 September 2025, 09:00-10:30
• Venue: Seminar Room 2, Newton Institute.
• Series: Isaac Newton Institute Seminar Series; organiser: nobody.

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