arXiv subjects

Luca Tubiana

Publications and source records attributed to Luca Tubiana.

At least 19 recordsLinked to original sources

arXiv2026

Coarse-grained simulations of dsDNA polycatenanes and network formation in annular nanochannels with topoisomerase II

We numerically investigate the behavior of a system of initially unlinked nicked dsDNA rings confined into an annular square nanochannel in the presence of TopoII. Channel confinement can enhance the catenation likelihood by bringing highly bent regions from different rings in close proximity, while at the same time reducing the emergence of knots. The annular channel topology simplifies the characterization of the system by removing periodic boundary conditions and can lead to the formation of circular catenanes.We characterize the equilibrium and dynamical properties of the steady-state system, including the amount of catenation and the topologies explored by the system, under different parameters of the model and for different levels of confinement. We argue that a similar setup could allow for a direct comparison between experiments and simulations under well characterized and controlled conditions, thus providing a way to select and tune computational models of TopoII, as well as provide a way to obtain dsDNA interlocked materials in a controlled fashion.

cond-mat.soft↗

arXiv2026

Active embracement enables autonomous tweezing in active star polymers

The capacity for autonomous structural reconfiguration is a defining trait of living systems, yet it remains elusive in artificial active matter. Here, we report the discovery of active embracement, a non-equilibrium phenomenon where active star polymers, comprising a central core and self-propelled monomeric arms, transition from open configurations to tightly collapsed, ``hugging'' states. By combining polymer experiments using connected vibrobots with simulations, we demonstrate that internal self-propulsion fundamentally overrides the steric repulsion that keeps passive polymers dispersed. This active drive enables a suite of behaviors unattainable in equilibrium systems: individual star polymers undergo a globular-like self-collapse, multiple star polymers mutually intertwine and mutually embrace, and can spontaneously embrace and capture surrounding passive particles. Our findings reveal that active embracement is a distinct kinetic phase that allows star polymers to function as autonomous tweezers. By bridging the gap between macroscopic robotic collectives and microscopic polymer physics, this work provides a versatile blueprint for the design of smart materials capable of targeted cargo capture and self-directed assembly in complex environments.

cond-mat.soft↗

arXiv2026

On the thermal properties of knotted block copolymer rings

We investigate the thermal and structural properties of knotted diblock copolymer rings using a coarse-grained lattice model in an implicit solvent. The system is studied by means of the Wang--Landau Monte Carlo algorithm, allowing us to analyze thermodynamic and conformational responses over a wide temperature range. Different knot topologies, including the unknot, trefoil, figure-eight, and pentafoil knots, are considered for both symmetric and asymmetric monomer compositions. In the AB model employed here, A-type monomers are self-repulsive, B-type monomers are self-attractive, and A-B interactions are neutral, such that the solvent is effectively good for A-type monomers and poor for B-type monomers at low temperatures. We analyze several key observables, including the heat capacity, the radius of gyration, and its temperature derivative for both the entire copolymer ring and the individual blocks, and the probability that a monomer belongs to the knotted region. Our results show that the interplay between knot topology, monomer composition, and temperature strongly influences polymer conformations. Small variations in the B-block length induce nonmonotonic, reentrant-like conformational behavior as a function of temperature, including transitions between knot localization and delocalization at low temperatures. These effects arise from the competition between energetic and entropic contributions imposed by topological constraints.

cond-mat.soft↗

arXiv2026

NET4EXA: Pioneering the Future of Interconnects for Supercomputing and AI

NET4EXA aims to develop a next-generation high-performance interconnect for HPC and AI systems, addressing the increasing demands of large-scale infrastructures, such as those required for training Large Language Models. Building upon the proven BXI (Bull eXascale Interconnect) European technology used in TOP15 supercomputers, NET4EXA will deliver the new BXI release, BXIv3, a complete hardware and software interconnect solution, including switch and network interface components. The project will integrate a fully functional pilot system at TRL 8, ready for deployment into upcoming exascale and post-exascale systems from 2025 onward. Leveraging prior research from European initiatives like RED-SEA, the previous achievements of consortium partners and over 20 years of expertise from BULL, NET4EXA also lays the groundwork for the future generation of BXI, BXIv4, providing analysis and preliminary design. The project will use a hybrid development and co-design approach, combining commercial switch technology with custom IP and FPGA-based NICs. Performances of NET4EXA BXIv3 interconnect will be evaluated using a broad portfolio of benchmarks, scientific scalable applications, and AI workloads.

cs.NI↗

arXiv2026

Controlling microalgae populations by phototactic memory

Understanding how microorganisms navigate in complex environments is a central question in active matter and biological physics. Phototaxis - the ability to use light as a navigation cue - is a widespread strategy in motile microalgae to optimise photosynthesis and avoid light-induced stress. The microalga Chlamydomonas reinhardtii is a model system for studying this behaviour, where navigation is classically attributed to a photosensitive organelle named eyespot. While this mechanism enables cells to sense the direction of incoming light, their response to light intensity gradients remains less understood. Here we show that structured light landscapes can guide microalgae populations and localise them in defined spatial regions. By analysing single-cell trajectories, we find that cells actively steer relative to the local light gradient, and a comparison with a minimal theoretical model shows that a short-time memory of light exposure acting on the transition between positive and negative phototaxis is necessary to reproduce the observed accumulation. At longer times, we observe a gradual decrease in cell number density within the trapping region, consistent with phototactic adaptation. Beyond controlling population dynamics, our results reveal new aspects of phototactic behaviour, highlighting gradient-aligned steering together with temporal integration as central mechanisms for navigation in structured environments.

cond-mat.soft↗

arXiv2025

The effects of solvent quality and core wetting on the circularization of star polymers

We simulate the formation of cyclical arms in star polymers, focusing on the effects of solvent quality on their resulting linking complexity and gyration radius. We find that polymers circularized in bad solvent present a higher degree of linking among arms with respect to those circularized in good solvent. When both are transported to good solvent, this results in a smaller gyration radius of the former with respect to the latter. This effect is magnified when the polymers present a sufficiently small number of arms (or functionality $f$): in this case, in bad solvent, all arms tend to clump together on one side of the central core, due to circularization, and can hence all interact with each other. Instead, when $f$ is large enough, the whole surface of the core is wetted by the arms, whose distribution becomes radially symmetric. This hinders interactions between faraway arms and reduces the probability of inter-arm linking. Interestingly, we find that both the critical $f_c$ at which the clump transition happens and the minimal arm length $n_c$ for which the transition appears depend on the core size: the grafting density of the arms must be larger than a certain constant $ρ_g^c$, while their length must be sufficient to stretch for, at least, half of the core's circumference.

cond-mat.soft↗

arXiv2025

Effects of knotting on the collapse of active ring polymers

We use numerical simulations to study tangentially active flexible ring polymers with different knot topologies. Simple, unknotted active rings display a transition from an extended phase to a collapsed one upon increasing the degree of polymerization. We find that topology has a significant effect on the polymer size at which the collapse takes place, with twist knots collapsing earlier than torus knots. Increasing knot complexity further accentuates this difference, as the collapse point of torus knots grows linearly with the minimum crossing number of the knot while that of twist knots shrinks, eventually canceling the actively stretched regime altogether. This behavior is a consequence of the ordered configuration of torus knots in their stretched active state, featuring an effective alignment for non-neighboring bonds which increases with the minimal crossing number. Twist knots do not feature ordered configurations or bond alignment, increasing the likelihood of collisions, leading to collapse. These results show that topology yields a degree of control on the properties of active ring polymers, and can be used to tune them. At the same time, they suggest that activity might introduce a bias for torus knots, as complex twist knots cannot be formed in extended active polymers.

cond-mat.soft↗

arXiv2025

Normalized topological indices discriminate between architectures of branched macromolecules

Branching architecture characterizes numerous systems, ranging from synthetic (hyper)branched polymers and biomolecules such as lignin, amylopectin, and nucleic acids to tracheal and neuronal networks. Its ubiquity reflects the many favourable properties that arise because of it. For instance, branched macromolecules are spatially compact and have a high surface functionality, which impacts their phase characteristics and self-assembly behaviour, among others. The relationship between branching and physical properties has been studied by mapping macromolecules to mathematical trees whose architecture can be characterized using topological indices. These indices, however, do not allow for a comparison of macromolecules that map to trees of different size, be it due to different mapping procedures or differences in their molecular weight. To alleviate this, we introduce a novel normalization of topological indices using estimates of their probability density functions. We determine two optimal normalized topological indices and construct a phase space that enables a robust discrimination between different architectures of branched macromolecules. We demonstrate the necessity of such a phase space on two practical applications, one being ribonucleic acid (RNA) molecules with various branching topologies and the other different methods of coarse-graining branched macromolecules. Our approach can be applied to any type of branched molecules and extended as needed to other topological indices, making it useful across a wide range of fields where branched molecules play an important role, including polymer physics, green chemistry, bioengineering, biotechnology, and medicine.

cond-mat.soft↗

arXiv2025

Organisation and dynamics of individual DNA segments in topologically complex genomes

Capturing the physical organisation and dynamics of genomic regions is one of the major open challenges in biology. The kinetoplast DNA (kDNA) is a topologically complex genome, made by thousands of DNA (mini and maxi) circles interlinked into a two-dimensional Olympic network. The organisation and dynamics of these DNA circles are poorly understood. In this paper, we show that dCas9 linked to Quantum Dots can efficiently label different classes of DNA minicircles in kDNA. We use this method to study the distribution and dynamics of different classes of DNA minicircles within the network. We discover that maxicircles display a preference to localise at the periphery of the network and that they undergo subdiffusive dynamics. From the latter, we can also quantify the effective network stiffness, confirming previous indirect estimations via AFM. Our method could be used more generally, to quantify the location, dynamics and material properties of genomic regions in other complex genomes, such as that of bacteria, and to study their behaviour in the presence of DNA-binding proteins.

cond-mat.soft↗

arXiv2024

Meta-plasticity and memory in multi-level recurrent feed-forward networks

Network systems can exhibit memory effects in which the interactions between different pairs of nodes adapt in time, leading to the emergence of preferred connections, patterns, and sub-networks. To a first approximation, this memory can be modelled through a ``plastic'' Hebbian or homophily mechanism, in which edges get reinforced proportionally to the amount of information flowing through them. However, recent studies on glia-neuron networks have highlighted how memory can evolve due to more complex dynamics, including multi-level network structures and ``meta-plastic'' effects that modulate reinforcement. Inspired by those systems, here we develop a simple and general model for the dynamics of an adaptive network with an additional meta-plastic mechanism that varies the rate of Hebbian strengthening of its edge connections. The meta-plastic term acts on a second network level in which edges are grouped together, simulating local, longer time-scale effects. Specifically, we consider a biased random walk on a cyclic feed-forward network. The random walk chooses its steps according to the weights of the network edges. The weights evolve through a Hebbian mechanism modulated by a meta-plastic reinforcement, biasing the walker to prefer edges that have been already explored. We study the dynamical emergence (memorisation) of preferred paths and their retrieval and identify three regimes: one dominated by the Hebbian term, one in which the meta-reinforcement drives memory formation, and a balanced one. We show that, in the latter two regimes, meta-reinforcement allows the retrieval of a previously stored path even after the weights have been reset to zero to erase Hebbian memory.

cond-mat.dis-nn↗

arXiv2024

Conformation and topology of cyclical star polymers

We study the conformation and topological properties of cyclical star polymers with $f$ ring arms, each made of $n$ beads. We find that the conformational properties of unlinked cyclical star polymers are compatible to those of linear star polymers with $2f$ arms made of $n/2$ beads each. This compatibility vanishes when the topology of the star, measured as the degree of linking between arms, changes. In fact, when links are allowed we notice that the gyration radius decreases as a function of the absolute linking number $\vert Lk \vert$ of the arms, regardless of the protocol that is employed to introduce said links. Furthermore, the internal structure of the macromolecules, as highlighted by the radial density function, changes qualitatively for large values of $\vert Lk \vert$.

cond-mat.soft↗

arXiv2024

Molecular dynamics characterization of the free and encapsidated RNA2 of CCMV with the oxRNA model

The cowpea chlorotic mottle virus (CCMV) has emerged as an exemplary model system to assess the balance between electrostatic and topological features of ssRNA viruses, specifically in the context of the viral self-assembly process. Yet, in spite of its biophysical significance, little structural data of the RNA content of the CCMV virion is currently available. Here, the conformational dynamics of the RNA2 fragment of CCMV was assessed via coarse-grained molecular dynamics simulations, employing the oxRNA2 model. The behavior of RNA2 has been characterized both as a freely-folding molecule and within a mean-field depiction of a CCMV-like capsid. For the latter, a multi-scale approach was employed, to derive a radial potential profile of the viral cavity, from atomistic structures of the CCMV capsid in solution. The conformational ensembles of the encapsidated RNA2 were significantly altered with respect to the freely-folding counterparts, as shown by the emergence of long-range motifs and pseudoknots in the former case. Finally, the role of the N-terminal tails of the CCMV subunits (and ionic shells thereof) is highlighted as a critical feature in the construction of a proper electrostatic model of the CCMV capsid.

cond-mat.soft↗

arXiv2024

EXCOGITO, an extensible coarse-graining toolbox for the investigation of biomolecules by means of low-resolution representation

Bottom-up coarse-grained (CG) models proved to be essential to complement and sometimes even replace all-atom representations of soft matter systems and biological macromolecules. The development of low-resolution models takes the moves from the reduction of the degrees of freedom employed, that is, the definition of a mapping between a system's high-resolution description and its simplified counterpart. Even in the absence of an explicit parametrisation and simulation of a CG model, the observation of the atomistic system in simpler terms can be informative: this idea is leveraged by the mapping entropy, a measure of the information loss inherent to the process of coarsening. Mapping entropy lies at the heart of the extensible coarse-graining toolbox, or EXCOGITO, developed to perform a number of operations and analyses on molecular systems pivoting around the properties of mappings. EXCOGITO can process an all-atom trajectory to compute the mapping entropy, identify the mapping that minimizes it, and establish quantitative relations between a low-resolution representation and the geometrical, structural, and energetic features of the system. Here, the software, which is available free of charge under an open-source licence, is presented and showcased to introduce potential users to its capabilities and usage. Published on the J. Chem. Inf. Model. on June 11, 2024. DOI: https://doi.org/10.1021/acs.jcim.4c00490

cond-mat.soft↗

arXiv2024

A contact map method to capture the features of knot conformations

Inspired by recent advances in the chromosome capture techniques, a method is proposed to study the structural organization of systems of polymers rings with topological constraints.To this purpose, the system is divided into compartments and a simple condition is provided in order to determine if two compartments are in contact or not. Next, a set of contact matrices $\bar T_{ab}$ is defined that count how many times during a simulation a compartment $a$ was found in contact with a non-contiguous compartment $b$ in conformations with a given energy or temperature. Similar strategies based on correlation maps have been applied to the study of knotted polymers in the recent past. The advantage of the present approach is that is coupled with the Wang-Landau algorithm. Once the density of states is computed, it is possible to generate the contact matrices at any temperature. This gives an immediate overview over the changes of phases that polymer systems undergo. The information on the structure of knotted polymers and links stored in the contact matrices is the result of averaging hundred of billions of conformations and visualized by means of colormaps. The obtained color patterns allow to identify the main properties of the structure of the system under investigation at any temperature. The method is applied to detect the structural rearrangements following the phase transitions of a knotted polymer ring and a circular polycatenane composed by four rings in a solution. It is shown that the colormaps have a finite number of patterns that can be clearly associated with the different phases of these systems. Colormaps also bring new knowledge, for instance predicting the average number of tails appearing in the conformations of the considered polymers at a given temperature.

cond-mat.soft↗

arXiv2023

Single-Molecule Morphology of Topologically Digested Olympic Networks

The kinetoplast DNA (kDNA) is the archetype of a two-dimensional Olympic network, composed of thousands of DNA minicircles and found in the mitochondrion of certain parasites. The evolution, replication and self-assembly of this structure are fascinating open questions in biology that can also inform us how to realise synthetic Olympic networks in vitro. To obtain a deeper understanding of the structure and assembly of kDNA networks, we sequenced the Crithidia fasciculata kDNA genome and performed high-resolution Atomic Force Microscopy (AFM) and analysis of kDNA networks that had been partially digested by selected restriction enzymes. We discovered that these topological perturbations lead to networks with significantly different geometrical features and morphologies with respect to the unperturbed kDNA, and that these changes are strongly dependent on the class of DNA circles targeted by the restriction enzymes. Specifically, cleaving maxicircles leads to a dramatic reduction in network size once adsorbed onto the surface, whilst cleaving both maxicircles and a minor class of minicircles yields non-circular and deformed structures. We argue that our results are a consequence of a precise positioning of the maxicircles at the boundary of the network, and we discuss our findings in the context of kDNA biogenesis, design of artificial Olympic networks and detection of in vivo perturbations.

cond-mat.soft↗

arXiv2023

Emergent circulation patterns from anonymized mobility data: Clustering Italy in the time of Covid

Using anonymized mobility data from Facebook users and publicly available information on the Italian population, we model the circulation of people in Italy before and during the early phase of the SARS-CoV-2 pandemic (COVID-19). We perform a spatial and temporal clustering of the movement network at the level of fluxes across provinces on a daily basis. The resulting partition in time successfully identifies the first two lockdowns without any prior information. Similarly, the spatial clustering returns 11 to 23 clusters depending on the period ("standard" mobility vs. lockdown) using the greedy modularity communities clustering method, and 16 to 30 clusters using the critical variable selection method. Fascinatingly, the spatial clusters obtained with both methods are strongly reminiscent of the 11 regions into which emperor Augustus had divided Italy according to Pliny the Elder. This work introduces and validates a data analysis pipeline that enables us: i) to assess the reliability of data obtained from a partial and potentially biased sample of the population in performing estimates of population mobility nationwide; ii) to identify areas of a Country with well-defined mobility patterns, and iii) to distinguish different patterns from one another, resolve them in time and find their optimal spatial extent. The proposed method is generic and can be applied to other countries, with different geographical scales, and also to similar networks (e.g. biological networks). The results can thus represent a relevant step forward in the development of methods and strategies for the containment of future epidemic phenomena.

physics.soc-ph↗

arXiv2023

Scaling properties of RNA as a randomly branching polymer

Formation of base pairs between the nucleotides of an RNA sequence gives rise to a complex and often highly branched RNA structure. While numerous studies have demonstrated the functional importance of the high degree of RNA branching -- for instance, for its spatial compactness or interaction with other biological macromolecules -- RNA branching topology remains largely unexplored. Here, we use the theory of randomly branching polymers to explore the scaling properties of RNAs by mapping their secondary structures onto planar tree graphs. Focusing on random RNA sequences of varying lengths, we determine the two scaling exponents related to their topology of branching. Our results indicate that ensembles of RNA secondary structures are characterized by annealed random branching and scale similarly to self-avoiding trees in three dimensions. We further show that the obtained scaling exponents are robust upon changes in nucleotide composition, tree topology, and folding energy parameters. Finally, in order to apply the theory of branching polymers to biological RNAs, whose length cannot be arbitrarily varied, we demonstrate how both scaling exponents can be obtained from the distributions of the related topological quantities of individual RNA molecules with fixed length. In this way, we establish a framework to study the branching properties of RNA and compare them to other known classes of branched polymers. By understanding the scaling properties of RNA related to its branching structure we aim to improve our understanding of the underlying principles and open up the possibility to design RNA sequences with desired topological properties.

physics.bio-ph↗

arXiv2023

Viral RNA as a branched polymer

Myriad viruses use positive-strand RNA molecules as their genomes. Far from being only a repository of genetic material, viral RNA performs numerous other functions mediated by its physical structure and chemical properties. In this chapter, we focus on its structure and discuss how long RNA molecules can be treated as branched polymers through planar graphs. We describe the major results that can be obtained by this approach, in particular the observation that viral RNA genomes have a characteristic compactness that sets them aside from similar random RNAs. We also discuss how different parameters used in the current RNA folding software influence the resulting structures and how they can be related to experimentally observable quantities. Finally, we show how the connection to branched polymers can be extended to take advantage of known results from polymer physics and can be further moulded to include additional interactions, such as excluded volume or electrostatics.

physics.bio-ph↗