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Context. Dusty debris discs around main sequence stars are observed to vary widely in terms of their vertical thickness. Their vertical structure may be affected by damping in inelastic collisions. Although kinetic models have often been used to study the collisional evolution of debris discs, these models have not yet been used to study the evolution of their vertical structure. Aims. We extend an existing implementation of a kinetic model of collisional evolution to include the evolution of orbital inclinations and we use this model to study the effects of collisional damping in pre-stirred discs. Methods. We evolved the number of particles of different masses, eccentricities, and inclinations using the kinetic model and used Monte Carlo simulations to calculate collision rates between particles in the disc. We considered all relevant collisional outcomes including fragmentation, cratering, and growth. Results. Collisional damping is inefficient if particles can be destroyed by projectiles that are of much lower mass. If that is the case, catastrophic disruptions shape the distributions of eccentricities and inclinations, and their average values evolve slowly and at the same rate for all particle sizes. Conclusions. The critical projectile-to-target mass ratio (Yc) and the collisional timescale jointly determine the level of collisional damping in debris discs. If Yc is much smaller than unity, a debris disc retains the inclination distribution that it is born with for much longer than the collisional timescale of the largest bodies in the disc. Such a disc should exhibit a vertical thickness that is independent of wavelength even in the absence of other physical processes. Collisional damping is efficient if Yc is of order unity or larger. For millimetre-sized dust grains and common material strength assumptions, this requires collision velocities of lower than ~40 m/s. Abridged, Comment: pre-print of article published in Astronomy & Astrophysics, DOI: https://doi.org/10.1051/0004-6361/202451080; output data DOI: https://doi.org/10.5281/zenodo.14196398

Computationally tractable and reliable, albeit approximate, methods for studying exciton transport in molecular aggregates immersed in structured bosonic environments have been actively developed. Going beyond the lowest-order (Born) approximation for the memory kernel of the generalized quantum master equation typically results in complicated and possibly divergent expressions. Starting from the memory kernel in the Born approximation, and recognizing the quantum master equation as the Dyson equation of the Green's functions theory, we formulate the self-consistent Born approximation to resum the memory-kernel perturbation series in powers of the exciton-environment interaction. Our formulation is in the Liouville space and frequency domain, and handles arbitrary exciton-environment spectral densities. In a molecular dimer coupled to an overdamped oscillator environment, we conclude that the self-consistent cycle significantly improves the Born-approximation energy-transfer dynamics. The dynamics in the self-consistent Born approximation agree well with solutions of hierarchical equations of motion over a wide range of parameters, including the most challenging regimes of strong exciton-environment interactions, slow environments, and low temperatures. This is rationalized by analytical considerations of coherence-dephasing dynamics in the pure-dephasing model. We find that the self-consistent Born approximation is good (poor) at describing energy transfer modulated by an underdamped vibration resonant (off-resonant) with the exciton energy gap. Nevertheless, it reasonably describes exciton dynamics in the seven-site model of the Fenna-Matthews-Olson complex in a realistic environment comprising both an overdamped continuum and underdamped vibrations., Comment: 23 pages, 13 figures

The Lindblad equation is a widely used quantum master equation to model the dynamical evolution of open quantum systems whose states are described by density matrices. These solution matrices are characterized by semi-positiveness and trace preserving properties, which must be guaranteed in any physically meaningful numerical simulation. In this paper, novel full- and low-rank exponential Euler integrators are developed for approximating the Lindblad equation that preserve positivity and trace unconditionally. Theoretical results are presented that provide sharp error estimates for the two classes of exponential integration methods. Results of numerical experiments are discussed that illustrate the effectiveness of the proposed schemes, beyond present state-of-the-art capabilities.

High-dimensional quantum computing has generated significant interest due to its potential to address scalability and error correction challenges faced by traditional qubit-based systems. This paper investigates the Average Gate Fidelity (AGF) of single qudit systems under Markovian noise in the Lindblad formalism, extending previous work by developing a comprehensive theoretical framework for the calculation of higher-order correction terms. We derive general expressions for the perturbative expansion of the Average Gate Infidelity (AGI) in terms of the environmental coupling coefficient and validate these with extensive numerical simulations, emphasizing the transition from linear to nonlinear behaviour in the strong coupling regime. Our findings highlight the dependence of AGI on qudit dimensionality, quantum gate choice, and noise strength, providing critical insights for optimising quantum gate design and error correction protocols. Additionally, we utilise our framework to identify universal bounds for the AGI in the strong coupling regime and explore the practical implications for enhancing the performance of near-term qudit architectures. This study offers a robust foundation for future research and development in high-dimensional quantum computing, contributing to the advancement of robust, high-fidelity quantum operations.

This paper will present textual corpora for Serbian (and Serbo-Croatian), usable for the training of large language models and publicly available at one of the several notable online repositories. Each corpus will be classified using multiple methods and its characteristics will be detailed. Additionally, the paper will introduce three new corpora: a new umbrella web corpus of Serbo-Croatian, a new high-quality corpus based on the doctoral dissertations stored within National Repository of Doctoral Dissertations from all Universities in Serbia, and a parallel corpus of abstract translation from the same source. The uniqueness of both old and new corpora will be accessed via frequency-based stylometric methods, and the results will be briefly discussed.

We extend to the super Yangian of the special linear Lie superalgebra $\mathfrak{sl}_{m|n}$ and its affine version certain results related to Schur-Weyl duality. We do the same for the deformed double current superalgebra of $\mathfrak{sl}_{m|n}$, which is introduced here for the first time.

The optical-conductivity profile carries information on electronic dynamics in interacting quantum many-body systems. Its computation is a formidable task that is usually approached by invoking the single-particle (bubble) approximation and neglecting the vertex corrections, the importance of which remains elusive even in model Hamiltonian calculations. Here, we combine analytical arguments with our recent breakthroughs in numerically exact and approximate calculations of finite-temperature real-time correlation functions to thoroughly assess the importance of vertex corrections in the one-dimensional Holstein polaron model. We find, both analytically and numerically, vanishing vertex corrections to optical conductivity in the limits of zero electron--phonon interaction, zero electronic bandwidth, and infinite temperature. Furthermore, our numerical results show that vertex corrections to the electron mobility also vanish in many parameter regimes between these limits. In some of these cases, the vertex corrections still introduce important qualitative changes to the optical-conductivity profile in comparison to the bubble approximation even though the self-energy remains approximately local. We trace these changes back to the bubble approximation not fully capturing a time-limited slow-down of the electron on intermediate time scales between ballistic and diffusive transport. We find that the vertex corrections are overall most pronounced for intermediate electron--phonon interaction and may increase or decrease the bubble-approximation mobility depending on the values of model parameters., Comment: Final, published version; main text: 28 pages, 12 figures; supplementary material: 13 pages, 5 figures

A complex interplay between the crystal structure and electron behavior within borophene renders this material an intriguing 2D system with many of its electronic properties still undiscovered. Experimental insight into those properties is additionally hampered by the limited capabilities of the established synthesis methods, which in turn inhibits the realization of potential borophene applications. In this multi-method study, photoemission spectroscopies and scanning probe techniques complemented by theoretical calculations have been used to investigate the electronic characteristics of a high-coverage, single-layer borophene on Ir(111) substrate. Our results show that the binding of borophene to Ir(111) exhibits pronounced one-dimensional modulation and transforms borophene into a nano-grating. The scattering of photoelectrons from this structural grating gives rise to the replication of electronic bands. In addition, the binding modulation is reflected in the chemical reactivity of borophene and gives rise to its inhomogeneous aging effect. Such aging is easily reset by dissolving boron atoms in iridium at high temperature followed by their reassembly into a fresh atomically-thin borophene mesh. Besides proving electron-grating capabilities of the boron monolayer, our data provides a comprehensive insight into the electronic properties of epitaxial borophene which is vital for further examination of other boron systems of reduced dimensionality., Comment: 12 pages, 5 figures, supporting information available

Debris discs are our best means to probe the outer regions of planetary systems. Many studies assume that planets lie at the inner edges of debris discs, akin to Neptune and the Kuiper Belt, and use the disc morphologies to constrain those otherwise-undetectable planets. However, this produces a degeneracy in planet mass and semimajor axis. We investigate the effect of a sculpting planet on the radial surface-density profile at the disc inner edge, and show that this degeneracy can be broken by considering the steepness of the edge profile. Like previous studies, we show that a planet on a circular orbit ejects unstable debris and excites surviving material through mean-motion resonances. For a non-migrating, circular-orbit planet, in the case where collisions are negligible, the steepness of the disc inner edge depends on the planet-to-star mass ratio and the initial-disc excitation level. We provide a simple analytic model to infer planet properties from the steepness of ALMA-resolved disc edges. We also perform a collisional analysis, showing that a purely planet-sculpted disc would be distinguishable from a purely collisional disc and that, whilst collisions flatten planet-sculpted edges, they are unlikely to fully erase a planet's signature. Finally, we apply our results to ALMA-resolved debris discs and show that, whilst many inner edges are too steep to be explained by collisions alone, they are too flat to arise through completed sculpting by non-migrating, circular-orbit planets. We discuss implications of this for the architectures, histories and dynamics in the outer regions of planetary systems., Comment: 24 pages, 18 figures, accepted for publication in MNRAS

Catastrophically evaporating rocky planets provide a unique opportunity to study the composition of small planets. The surface composition of these planets can be constrained via modelling their comet-like tails of dust. In this work, we present a new self-consistent model of the dusty tails: we physically model the trajectory of the dust grains after they have left the gaseous outflow, including an on-the-fly calculation of the dust cloud's optical depth. We model two catastrophically evaporating planets: KIC 1255b and K2-22b. For both planets, we find the dust is likely composed of magnesium-iron silicates (olivine and pyroxene), consistent with an Earth-like composition. We constrain the initial dust grain sizes to be $\sim$ 1.25-1.75 $\mu$m and the average (dusty) planetary mass-loss rate to be $\sim$ 3$M_\oplus \mathrm{Gyr^{-1}}$. Our model shows the origin of the leading tail of dust of K2-22b is likely a combination of the geometry of the outflow and a low radiation pressure force to stellar gravitational force ratio. We find the optical depth of the dust cloud to be a factor of a few in the vicinity of the planet. Our composition constraint supports the recently suggested idea that the dusty outflows of these planets go through a greenhouse effect-nuclear winter cycle, which gives origin to the observed transit depth time variability. Magnesium-iron silicates have the necessary visible-to-infrared opacity ratio to give origin to this cycle in the high mass-loss state., Comment: Accepted for publication in MNRAS

The performance of automated algorithm selection (AAS) strongly depends on the portfolio of algorithms to choose from. Selecting the portfolio is a non-trivial task that requires balancing the trade-off between the higher flexibility of large portfolios with the increased complexity of the AAS task. In practice, probably the most common way to choose the algorithms for the portfolio is a greedy selection of the algorithms that perform well in some reference tasks of interest. We set out in this work to investigate alternative, data-driven portfolio selection techniques. Our proposed method creates algorithm behavior meta-representations, constructs a graph from a set of algorithms based on their meta-representation similarity, and applies a graph algorithm to select a final portfolio of diverse, representative, and non-redundant algorithms. We evaluate two distinct meta-representation techniques (SHAP and performance2vec) for selecting complementary portfolios from a total of 324 different variants of CMA-ES for the task of optimizing the BBOB single-objective problems in dimensionalities 5 and 30 with different cut-off budgets. We test two types of portfolios: one related to overall algorithm behavior and the `personalized' one (related to algorithm behavior per each problem separately). We observe that the approach built on the performance2vec-based representations favors small portfolios with negligible error in the AAS task relative to the virtual best solver from the selected portfolio, whereas the portfolios built from the SHAP-based representations gain from higher flexibility at the cost of decreased performance of the AAS. Across most considered scenarios, personalized portfolios yield comparable or slightly better performance than the classical greedy approach. They outperform the full portfolio in all scenarios., Comment: Proc. of International Conference on Automated Machine Learning (AutoML 2023)

This article presents results from an experiment in which 44 human subjects interact with a dynamic system to perform 40 trials of a command-following task. The reference command is unpredictable and different on each trial, but all subjects have the same sequence of reference commands for the 40 trials. The subjects are divided into 4 groups of 11 subjects. One group performs the command-following task without preview of the reference command, and the other 3 groups are given preview of the reference command for different time lengths into the future (0.5 s, 1 s, 1.5 s). A subsystem identification algorithm is used to obtain best-fit models of each subject's control behavior on each trial. The time- and frequency-domain performance, as well as the identified models of the control behavior for the 4 groups are examined to investigate the effects of reference-command preview. The results suggest that preview tends to improve performance by allowing the subjects to compensate for sensory time delay and approximate the inverse dynamics in feedforward. However, too much preview may decrease performance by degrading the ability to use the correct phase lead in feedforward., Comment: Preprint submitted to IEEE Transactions on Cybernetics

Due to the global water crisis there is a strong need for real-time water quality monitoring with high temporal and spatial resolution. This paper presents an economical multiparameter water quality monitoring system for continuous monitoring of fresh waters. It is based on a sensor node that integrates turbidity, temperature, and conductivity sensors, a miniature eighteen-channel spectrophotometer, and a sensor for the detection of thermotolerant coliforms, which is a major novelty of the system. Due to the influence of water impurities on the measurement of thermotolerant coliforms, a heuristic method has been developed to mitigate this effect. Moreover, the sensor is low power and with an integrated Long Range Wide Area Network module, it comprises a system that is wireless sensor network ready and can send data to a dedicated server. In addition, the system is submersible, capable of long-term field operation, and significantly cheaper in comparison to existing solutions. The purpose of the system is to give early warning of incidental pollution situations, thus enabling authorities to take action regarding further prevention of such occasions.

Performance complementarity of solvers available to tackle black-box optimization problems gives rise to the important task of algorithm selection (AS). Automated AS approaches can help replace tedious and labor-intensive manual selection, and have already shown promising performance in various optimization domains. Automated AS relies on machine learning (ML) techniques to recommend the best algorithm given the information about the problem instance. Unfortunately, there are no clear guidelines for choosing the most appropriate one from a variety of ML techniques. Tree-based models such as Random Forest or XGBoost have consistently demonstrated outstanding performance for automated AS. Transformers and other tabular deep learning models have also been increasingly applied in this context. We investigate in this work the impact of the choice of the ML technique on AS performance. We compare four ML models on the task of predicting the best solver for the BBOB problems for 7 different runtime budgets in 2 dimensions. While our results confirm that a per-instance AS has indeed impressive potential, we also show that the particular choice of the ML technique is of much minor importance., Comment: To appear in the Companion Proceedings of GECCO 2023 as poster paper

Numerically "exact" methods addressing the dynamics of coupled electron--phonon systems have been intensively developed. Nevertheless, the corresponding results for the electron mobility $\mu_\mathrm{dc}$ are scarce, even for the one-dimensional (1d) Holstein model. Building on our recent progress on single-particle properties, here, we develop the momentum-space hierarchical equations of motion (HEOM) method to evaluate real-time two-particle correlation functions of the 1d Holstein model at finite temperature. We compute numerically "exact" dynamics of the current--current correlation function up to real times sufficiently long to capture the electron's diffusive motion and provide reliable results for $\mu_\mathrm{dc}$ in a wide range of model parameters. In contrast to the smooth ballistic-to-diffusive crossover in the weak-coupling regime, we observe a temporally limited slow-down of the electron on intermediate time scales already in the intermediate-coupling regime, which translates to a finite-frequency peak in the optical response. Our momentum-space formulation lowers the numerical effort with respect to existing HEOM-method implementations, while we remove the numerical instabilities inherent to the undamped-mode HEOM by devising an appropriate hierarchy closing scheme. Still, our HEOM remains unstable at too low temperatures, for too strong electron--phonon coupling, and for too fast phonons., Comment: final, published version; main text: 23 pages, 8 figures; supplementary material contains detailed information on the dataset available at https://doi.org/10.5281/zenodo.8068546

Bayesian Optimization (BO) is a class of surrogate-based, sample-efficient algorithms for optimizing black-box problems with small evaluation budgets. The BO pipeline itself is highly configurable with many different design choices regarding the initial design, surrogate model, and acquisition function (AF). Unfortunately, our understanding of how to select suitable components for a problem at hand is very limited. In this work, we focus on the definition of the AF, whose main purpose is to balance the trade-off between exploring regions with high uncertainty and those with high promise for good solutions. We propose Self-Adjusting Weighted Expected Improvement (SAWEI), where we let the exploration-exploitation trade-off self-adjust in a data-driven manner, based on a convergence criterion for BO. On the noise-free black-box BBOB functions of the COCO benchmarking platform, our method exhibits a favorable any-time performance compared to handcrafted baselines and serves as a robust default choice for any problem structure. The suitability of our method also transfers to HPOBench. With SAWEI, we are a step closer to on-the-fly, data-driven, and robust BO designs that automatically adjust their sampling behavior to the problem at hand., Comment: AutoML Conference 2023

We study pressure acoustic propagation in asymmetric spoof-fluid-spoof acoustic waveguides and its potential application in acoustic gas sensors. First, a stable and efficient analytical method is established for fast calculation of the dispersion curves based on spectral expansion and enforcement of continuity between segments at suitable collocation points. The analysis is validated by a commercial finite element software. The geometric design of the waveguide is then optimized for the emergence of a nearly-flat dispersion curve associated with vertical geometric asymmetry. The waveguide is fabricated using 3D printing technology and the measurement results corroborate the numerical simulations. Based on the nearly-flat dispersion curve supported by this waveguide, a CO$_2$ sensor is proposed allowing to relate the phase difference measured between two points in the waveguide to the composition of the gas in the waveguide. The proposed sensor is experimentally validated in a controlled environment and the measurement results match the computational predictions well. The sensor is robust with respect to noise and signal-recording duration due to fast phase measurements and shows high sensitivity to gas concentration due to reliance on the second, nearly-flat, dispersion curve. In addition, the sensor is label-free and low-cost, while exhibiting rapid response, low-maintenance requirements and potential for measurements in a wide range of CO$_2$ concentrations without saturation issues., Comment: 21 pages, 12 figures

In recent years, transmission system operators have started requesting converter-interfaced generators (CIGs) to participate in grid services such as power oscillation damping (POD). As power systems are prone to topology changes because of connection and disconnection of generators and electrical lines, one of the most important requirements in the POD controller design is to account for these changes and to deal with them by using either adaptive or robust approaches. The robust approach is usually preferred by system operators because of the fixed structure of the controller. In this paper, a procedure to design POD controllers for CIG-based power plants that takes into consideration all possible network configurations is presented. This procedure is based on frequency-response techniques, so it is suitable for the commissioning in newly installed power plants, even in those cases when a detailed small-signal model of the system is not available. This procedure can be used to damp critical system modes by using active power, reactive power, or both power components simultaneously. The proposed procedure is applied to the design of the POD controller for a CIG-based power plant connected to the IEEE 39 Bus system. Simulations performed in Matlab and SimPowerSystems are used to validate the proposed design procedure.

Low-frequency oscillations are an inherent phenomena in transmission networks and renewable energy plants should be configured to damp them. Commonly, a centralised controller is used in PV plants to coordinate PV generators via communication channels. However, the communication systems of PV plants introduce delays of a stochastic nature that degrade the performance of centralised control algorithms. Therefore, controllers for oscillation damping may not operate correctly unless the communication channel characteristics are not considered and compensated. In this paper, a centralised controller is proposed for the oscillation damping that uses a PV plant with all the realistic effects of communication channels taken into consideration. The communication channels are modelled based on measurements taken in a laboratory environment. The controller is designed to damp several modes of oscillation by using the open-loop phase shift compensation. Theoretical developments were validated in a laboratory using four converters acting as two PV inverters, a battery and a STATCOM. A real-time processing platform was used to implement the centralised controller and to deploy the communication infrastructure. Experimental results show the communication channels impose severe restrictions on the performance of centralised POD controllers, highlighting the importance of their accurate modelling and consideration during the controller design stage.

Tidal disruption events occur when a star is disrupted by a supermassive black hole, resulting in an elongated stream of gas that partly falls back to the pericenter. Due to apsidal precession, the returning stream may collide with itself, leading to a self-crossing shock that launches an outflow. If the black hole spins, this collision may additionally be affected by Lense-Thirring precession that can cause an offset between the two stream components. We study the impact of this effect on the outflow properties by carrying out local simulations of collisions between offset streams. As the offset increases, we find that the geometry of the outflow becomes less spherical and more collimated along the directions of the incoming streams, with less gas getting unbound by the interaction. However, even the most grazing collisions we consider significantly affect the trajectories of the colliding gas, likely promoting subsequent strong interactions near the black hole and rapid disc formation. We analytically compute the dependence of the offset to stream width ratio, finding that even slowly spinning black holes can cause both strong and grazing collisions. We estimate that the self-crossing shock luminosity is lower for an offset collision than an aligned one since radiation energy injected by the shock is significantly lower for more offset collisions. We find that the deviation from outflow sphericity may cause significant variations in the efficiency at which X-ray radiation from the disc is reprocessed to the optical band, depending on the viewing angle, and increase the degree of the observed polarization. These potentially observable features hold the promise of constraining the black hole spin from tidal disruption events., Comment: 15 pages, 12 figures, published in MNRAS. Movies from the simulations are available at https://www.youtube.com/playlist?list=PLH8qhWjKWQ91adY0ae1lD2vRVbaerSWmb

Today, multiple new platforms are implementing qudits, $d$-level quantum bases of information, for Quantum Information Processing (QIP). It is therefore crucial to study their efficiencies for QIP compared to more traditional qubit platforms. We present a comparative study of the infidelity scalings of a qudit and $n$-qubit systems, both with identical Hilbert space dimensions and noisy environments. The first-order response of the Average Gate Infidelity (AGI) to the noise in the Lindblad formalism, which was found to be gate-independent, was calculated analytically in the two systems being compared. This yielded a critical curve $O(d^2/\log_2(d))$ of the ratio of their respective gate times in units of decoherence time. This quantity indicates how time-efficient operations on these systems are. The curve delineates regions where each system has a higher rate of increase of the AGI than the other. This condition on gate efficiency was applied to different existing platforms. It was found that specific qudit platforms possess gate efficiencies competitive with state-of-the-art qubit platforms. Numerical simulations complemented this work and allowed for discussion of the applicability and limits of the linear response formalism.

Highly energetic stellar tidal disruption events (TDEs) provide a way to study black hole characteristics and their environment. We simulate TDEs with the PHANTOM code in a general relativistic and Newtonian description of a supermassive black hole's gravity. Stars, which are placed on parabolic orbits with different parameters $\beta$, are constructed with the stellar evolution code MESA and therefore have realistic stellar density profiles. We study the mass fallback rate of the debris $\dot{M}$ and its dependence on the $\beta$, stellar mass and age as well as the black hole's spin and the choice of the gravity's description. We calculate peak value $\dot{M}_\mathrm{peak}$, time to the peak $t_\mathrm{peak}$, duration of the super-Eddington phase $t_\mathrm{Edd}$, time $t_{>0.5\dot{M}_\mathrm{peak}}$ during which $\dot{M}>0.5\dot{M}_\mathrm{peak}$, early rise-time $\tau_\mathrm{rise}$ and late-time slope $n_\infty$. We recover the trends of $\dot{M}_\mathrm{peak}$, $t_\mathrm{peak}$, $\tau_\mathrm{rise}$ and $n_\infty$ with $\beta$, stellar mass and age, which were obtained in previous studies. We find that $t_\mathrm{Edd}$, at a fixed $\beta$, scales primarily with the stellar mass, while $t_{>0.5\dot{M}_\mathrm{peak}}$ scales with the compactness of stars. The effect of SMBH's rotation depends on the orientation of its rotational axis relative to the direction of the stellar motion on the initial orbit. Encounters on prograde orbits result in narrower $\dot{M}$ curves with higher $\dot{M}_\mathrm{peak}$, while the opposite occurs for retrograde orbits. We find that disruptions, at the same pericenter distance, are stronger in a relativistic tidal field than in a Newtonian. Therefore, relativistic $\dot{M}$ curves have higher $\dot{M}_\mathrm{peak}$, and shorter $t_\mathrm{peak}$ and $t_\mathrm{Edd}$., Comment: 18 pages, 11 figures, accepted for publication in ApJ