IST Austria: PubRep (Institute of Science and Technology)
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Finding periodic orbits in projected quantum many-body dynamics
No full textDescribing general quantum many-body dynamics is a challenging task due to the exponential growth of the Hilbert space with system size. The time-dependent variational principle (TDVP) provides a powerful tool to tackle this task by projecting quantum evolution onto a classical dynamical system within a variational manifold. In classical systems, periodic orbits play a crucial role in understanding the structure of the phase space and the long-term behavior of the system. However, finding periodic orbits is generally difficult, and their existence and properties in generic TDVP dynamics over matrix product states have remained largely unexplored. In this work, we develop an algorithm to systematically identify and characterize periodic orbits in TDVP dynamics. Applying our method to the periodically kicked Ising model, we uncover both stable and unstable periodic orbits. We characterize the Kolmogorov-Arnold-Moser tori in the vicinity of stable periodic orbits and track the change of the periodic orbits as we modify the Hamiltonian parameters. We observe that periodic orbits exist at any value of the coupling constant of the kicked Ising model between prethermal and fully thermalizing regimes, but their relevance to quantum dynamics and imprint on quantum eigenstates diminishes as the system leaves the prethermal regime. Our results demonstrate that periodic orbits provide valuable insights into the TDVP approximation of quantum many-body evolution and establish a closer connection between quantum and classical chaos
LNCS
No full textInformation-flow interfaces is a formalism recently proposed for specifying, composing, and refining system-wide security requirements. In this work, we show how the widely used concept of security lattices provides a natural semantic interpretation for information-flow interfaces
Dynamical probe of the pseudo Jahn-Teller effect in one-dimensional confined fermions
No full textWe investigate the real-time dynamics of a quenched quantum impurity immersed in a one-dimensional ultracold Fermi gas, focusing on the breakdown of the adiabatic Born-Oppenheimer approximation due to nonadiabatic effects. Despite a sizable impurity-bath mass imbalance, increasing interactions induce strong nonadiabatic couplings, disrupting adiabatic motion and enabling population transfer between the adiabatic potential energy curves. These transitions are governed by conical intersections arising from the pseudo Jahn-Teller effect, dynamically shaping the impurity's motion through the bath. Using ab initio simulations via the multilayer multiconfiguration time-dependent Hartree method and a multichannel Born-Oppenheimer framework, we track the impurity's evolution and directly prove the dynamical manifestation of the pseudo Jahn-Teller effect. We analyze two key scenarios: (i) a small initial shift, where a single avoided crossing drives transitions, and (ii) a large shift, where multiple avoided crossings lead to enhanced nonadiabaticity, self-trapping, and energy redistribution. Our findings establish ultracold fermionic few-body systems as tunable platforms for studying nonadiabatic quantum dynamics, opening new avenues for controlled impurity transport in strongly correlated environments
Additive partial matchings for persistent homology
No full textPersistence modules (defined as a sequence of vector spaces and linear maps between them) are a key tool in topological data analysis. They are easy to interpret and fast to compute. However, when considering persistence maps (i.e. maps between persistence modules), these properties are lost. We propose a new invariant for persistence maps consisting of a partial matching such that: it is easy to interpret, it is more discriminative than the image of the persistence map, and can be calculated with cubical complexity
Numerical homogenization of sand from grain-level simulations
No full textThe realistic simulation of sand, soil, powders, rubble piles, and large collections of rigid bodies is a common and important problem in the fields of computer graphics, computational physics, and engineering. Direct simulation of these individual bodies quickly becomes expensive, so we often approximate the entire group as a continuum material that can be more easily computed using tools for solving partial differential equations, like the material point method (MPM). In this paper, we present a method for automatically extracting continuum material properties from a collection of rigid
bodies. We use numerical homogenization with periodic boundary conditions to simulate an effectively infinite number of rigid bodies in contact. We then record the effective stress-strain relationships from these simulations and convert them into elastic properties and yield criteria for the continuum simulations. Our experiments validate existing theoretical models like the Mohr-Coulomb yield surface by extracting material behaviors from a collection of spheres in contact. We further generalize these existing models to more exotic materials derived from diverse and non-convex shapes. We
observe complicated jamming behaviors from non-convex grains, and we introduce a new material model for materials with extremely high levels of internal friction and cohesion. We simulate these new continuum models using MPM with an improved return mapping technique. The end result is a complete system for turning an input rigid body simulation into an efficient continuum simulation with the same effective mechanical properties
BAF-1–VRK-1 mediated release of meiotic chromosomes from the nuclear periphery is important for genome integrity
No full textRapid prophase chromosome movements ensure faithful alignment of the parental homologous chromosomes and successful synapsis formation during meiosis. These movements are driven by cytoplasmic forces transmitted to the nuclear periphery, where chromosome ends are attached through transmembrane proteins. During many developmental stages a specific genome architecture with chromatin nuclear periphery contacts mediates specific gene expression. Whether chromatin is removed from the nuclear periphery as a consequence of chromosome motions or by a specific mechanism is not fully understood. Here, we identify a mechanism to remove chromatin from the nuclear periphery through vaccinia related kinase (VRK-1)–dependent phosphorylation of Barrier to Autointegration Factor 1 (BAF-1) in Caenorhabditis elegans early prophase of meiosis. Interfering with chromatin removal delays chromosome pairing, impairs synapsis, produces oocytes with abnormal chromosomes and elevated apoptosis. Long read sequencing reveals deletions and duplications in offspring lacking VRK-1 underscoring the importance of the BAF-1–VRK-1 module in preserving genome stability in gametes during rapid chromosome movements
Is a 1D perturbative method sufficient for asteroseismic modelling of β Cephei pulsators? Implications for measurements of rotation and internal magnetic fields
No full textContext. Asymmetries in the observed rotational splittings of a multiplet contain information about the star’s rotation profile and internal magnetic field. Moreover, the frequency regularities of multiplets can be used for mode identification. However, to exploit this information, highly accurate theoretical predictions are needed.
Aims. We aim to quantify the difference in the predicted mode asymmetries between a 1D perturbative method and a 2D method that includes a 2D stellar structure model, which takes rotation into account. We then place these differences between 1D and 2D methods in the context of asteroseismic measurements of internal magnetic fields. We only focus on the asymmetries and not on possible additional frequency peaks that can arise when the magnetic and rotation axis are misaligned.
Methods. We coupled the 1D pulsation codes GYRE and StORM to the 2D stellar structure code ESTER and compared the oscillation predictions with the results from the 2D TOP pulsation code. We focused on zero-age main-sequence models representative of rotating β Cephei pulsators spinning at up to 20 per cent of the critical Keplerian rotation rate. Specifically, we investigated low-radial-order gravity and pressure modes.
Results. We find a generally good agreement between the oscillation frequencies resulting from the 1D and 2D pulsation codes. We report differences in predicted mode multiplet asymmetries of mostly below 0.06 d−1. Since the magnetic asymmetries are small compared to the differences in the rotational asymmetries resulting from the 1D and 2D predictions, accurate measurements of the magnetic field are in most cases challenging.
Conclusions. Differences in the predicted mode asymmetries of a rotating star between 1D perturbative methods and 2D non-perturbative methods can greatly hinder accurate measurements of internal magnetic fields in main-sequence pulsators with low-order modes. Nevertheless, reasonably accurate measurements could be possible with npg ≥ 2 modes if the internal rotation is roughly below 10 per cent of the Keplerian critical rotation frequency for (aligned) magnetic fields of the order of a few hundred kilogauss. While the differences between the 1D and 2D frequency predictions are mostly too large for internal magnetic field detections, the rotational asymmetries predicted by StORM are in general accurate enough for asteroseismic modelling of the stellar rotation in main-sequence stars with identified low-order modes
Mode dispersion with magnetic field in a cavity-magnonics system
No full textThese are the raw data files that supplement our study of mode dispersion with magnetic field of a cavity-magnonics system containing chromium trichloride on coplanar waveguide resonator
JWST provides a new view of cosmic dawn: Latest developments in studies of early galaxies
No full textStudies of the distant Universe are providing key insights into our understanding of the formation of galaxies. The advent of the James Webb Space Telescope (JWST) has significantly enhanced our observational capabilities, leading to an expanded redshift frontier, providing unprecedented detail in the characterisation of early galaxies and enabling the discovery of new populations of accreting black holes. This review aims to provide an introduction to the basic processes and components that shape the observed spectra of galaxies, with a focus on their relevance to techniques with which high-redshift galaxies are selected. The review further introduces specific topics that have attracted significant attention in recent literature, including the discovery of highly efficient galaxy formation in the early Universe, the relation between galaxies and the process of reionization, new insights into the formation of the first stars and the enrichment of interstellar gas with heavy elements, and breakthroughs in our understanding of the origins of supermassive black holes
High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating
No full textBiological memory is known to be flexible—memory formation and recall depend on factors such as the behavioral context of the organism. However, this property is often ignored in associative memory models, leaving it unclear how memories can be organized and recalled when subject to contextual control. Because of the lack of a rigorous analytical framework, it is also unknown how contextual control affects memory stability, storage capacity, and information content. Here, we bring the dynamic nature of memory to the fore by introducing a novel model of associative memory, which we refer to as the context-modular memory network. In our model, stored memory patterns are associated to one of several background network states, or contexts. Memories are accessible when their corresponding context is active, and are otherwise inaccessible. Context modulates the effective network connectivity by imposing a specific
configuration of neuronal and synaptic gating—gated neurons (synapses) have their activity (weights) momentarily silenced, thereby reducing interference from memories belonging to other contexts. Memory patterns are randomly and independently chosen, while neuronal and synaptic gates may be selected randomly or optimized through a process of contextual synaptic refinement. Through analytic and numerical results, we show that context-modular memory networks can exhibit both improved memory capacity and differential control of memory stability with random gating (especially for neuronal gating). For contextual synaptic refinement, we devise a method in which synapses are gated off for a given context if they destabilize the memory patterns in that context, drastically improving memory capacity and enabling even more precise control over memory stability. Notably, synaptic refinement allows for patterns to be
accessible in multiple contexts, stabilizing memory patterns even for weight matrices that alone do not contain any information about the memory patterns, such as Gaussian random matrices. Overall, our model integrates recent ideas about context-dependent memory organization with classic associative memory models and proposes a rigorous theory which can act as a framework for future work. Furthermore, our work carries important implications for the understanding of biological memory storage and recall in the brain, such as highlighting an intriguing trade-off between memory capacity and accessibility