446494 research outputs found
Sort by
The Advanced Plunger-Particle detector Array - APPA
No full textThe Advanced Plunger-Particle detector Array (APP
Handling the Cornell potential within the Lagrange-mesh method in momentum space
No full textThis work presents an alternative methodology for computing potentials matrix elements within the Lagrange-mesh method in momentum space. The proposed approach extends the range of treatable potentials to include previously inaccessible cases, such as the Coulomb and linear interactions. It enables, in particular, an efficient and accurate treatment of the Cornell potential, which plays an important role in potential models for hadronic physics. The method is validated across a variety of systems, with special attention given to the representation of both momentum and position probability densities
A practical guide to unbinned unfolding
No full textUnfolding, in the context of high-energy particle physics, refers to the process of removing detector distortions in experimental data. The resulting unfolded measurements are straightforward to use for direct comparisons between experiments and a wide variety of theoretical predictions. For decades, popular unfolding strategies were designed to operate on data formatted as one or more binned histograms. In recent years, new strategies have emerged that use machine learning to unfold datasets in an unbinned manner, allowing for higher-dimensional analyses and more flexibility for current and future users of the unfolded data. This guide comprises recommendations and practical considerations from researchers across a number of major particle physics experiments who have recently put these techniques into practice on real data
The 3D time evolution of the dust size distribution in protostellar envelopes
No full textDust plays a fundamental role during protostellar collapse and disk and planet formation. Recent observations suggest that efficient dust growth can begin early in the protostellar envelopes, potentially even before the formation of the disk. Three-dimensional models of protostellar evolution that address multi-size dust growth, gas and dust dynamics, and magnetohydrodynamics (MHD) are required to characterize the dust evolution in the embedded stages of star formation.
We aim to establish a new framework for dust evolution models that follow in 3D the dust size distribution in both time and space, i.e., MHD models that describe the formation and evolution of star-disk systems at low numerical cost.
We coupled the dust evolution module that uses the Smoluchowski equations to numerical computations, performing the first 3D MHD simulation of protostellar collapse that simultaneously includes polydisperse dust growth modeled by the Smoluchowski equation and dust dynamics in the terminal velocity approximation. COALA RAMSES
We note that, locally in the protostellar collapse, the dust size distribution deviates significantly from the Mathis--Rumpl--Nordsieck (MRN) distribution due to dust growth. Ice-coated micron-sized grains can rapidly grow in the envelope and survive by not entering the fragmentation regime. The evolution of the dust size distribution is highly inhomogeneous due to the turbulent nature of the collapse and the development of favorable locations, such as outflow cavity walls, which locally enhance the dust-to-gas ratio.
We analyzed the first 3D non-ideal MHD simulations that self-consistently account for dust dynamics and growth during the protostellar stage. Very early in the lifetime of a young embedded protostar, micron-sized grains can grow, and locally the dust size distribution deviates from the initial MRN shape. This new numerical method opens the possibility of treating gas and dust dynamics with dust growth simultaneously in 3D simulations at a low numerical cost for several astrophysical environments
Physicochemical characteristic of corn starch nanoparticles obtained by acid hydrolysis method
No full textNative corn starch often lacks the stability and functionality needed for modern formulations. Here, commercial corn starch was acid-hydrolyzed using 2.2 N HCl at 35 °C for 120 h to generate nano-enabled starch (CSNPs) and to probe how selective chain removal alters structure–property relationships. Relative to the untreated control (CS-Control), the hydrolyzed material showed consistently lower in amylose (14.78 → 13.61%), swelling power (17.86 → 16.58%), solubility (19.95 → 14.69%), moisture (10.95 → 8.91%), and protein/fat contents. These shifts indicate preferential cleavage of amorphous, less ordered regions, enabling residual chains to repack via stronger hydrogen bonding. FTIR spectra retained the characteristic starch bands without evidence of new chemistry; a slightly more bonded O–H region and a sharper 1150– 900 cm-1 fingerprint supported increased order and reduced amorphous content. Morphology evolved from smooth granules to etched, rounded particles with surface debris (SEM), while TEM revealed tens-to- hundreds-of-nanometers fragments that readily aggregate—consistent with DLS detecting sub-micron to micron-scale populations. Overall, acid hydrolysis yielded a more ordered, nano-enabled starch while highlighting an important practical point: nanoparticles are created, but without an added dispersion step they remain partially aggregated. These insights can guide post-processing (when discrete nanoscale behavior is required
Foreland neotectonic contractional structures in the Cenozoic carbonate succession of the Malta Horst, Central Mediterranean
No full textThe Malta Horst is a NW-SE trending, 30 km-wide structural high situated on the southern Hyblean-Malta Plateau, which is an African continental indenter in collision with Eurasia. Sediments consist of a shallow marine carbonate platform succession (Mesozoic to Oligocene) capped by Miocene pelagic carbonates and marl. Utilizing seismic profiles, well data, and outcrop observations, this study provides the first description of kilometre-scale contractional structures within the horst and analyses the reactivation of normal faults by transcurrent movement under NW compression. The tectonic evolution of this foreland region is defined by five distinct phases (A through E), alternating between extension and compression. This cyclicity reflects the interplay between the migrating Calabrian Arc and the converging African craton. Initial NE-SW trending faults (Phases A and B) developed during the Late Oligocene to Early Miocene, coinciding with platform drowning. Following Tortonian uplift (Phase C), accelerated migration of the Calabrian Arc during Phase D triggered N-S extension, establishing the NW-SE and NE-SW normal faults that bound the Malta Horst. The neotectonic regime (Phase E) marks a return to dominance of the NW-directed compression by the African craton as the Calabrian Arc migration decelerated. This regional stress field has reactivated the NW-SE marginal normal faults through strike-slip motion. The combination of transcurrent drag and regional compression has inverted Phase A NE-SW normal faults into oblique reverse faults. These thrusts sole along a weak top Eocene evaporite décollement, producing a series of folds and inverted basins within 10 km of the horst's northeast margin. Onshore, these structures are manifest as en echelon, non-cylindrical, and doubly plunging folds that define the topography of Malta's northeast coast. These shear zone structures are thin-skinned deformations in Oligo-Miocene sediments controlled by thick-skinned, W-E transcurrent movement in the crust and Mesozoic sediments. Ongoing compression suggests an increase in seismic risk proximal to the Maltese Islands, with significant implications for local geohazard frequency and magnitude
Selective semi-saturation measurement of spin-1
No full textTensor polarization in spin-1 systems is essential for accessing unique observables in nuclear and hadronic structure studies, particularly in experiments probing gluon and quark distributions. Accurate measurement of tensor polarization enhances sensitivity to tensor-polarized observables, which are critical for isolating partonic degrees of freedom in nuclei and exploring nucleon structure in bound states. This work presents an overview of limitations in direct measurements of tensor polarization from the NMR absorption line and a proposal for improved measurement instrumentation and techniques. These methods attempt to avoid biased assumptions to improve precision while helping to quantify measurement error, especially under the application of frequency-selective radiofrequency techniques that locally manipulate spin populations. Non-equilibrium spin dynamics, spin diffusion, and rate equation modeling are helpful to characterize the response of the spin system in these circumstances. The impact of instrumental constraints, including fitting error, binning resolution, sweep rate, data acquisition system bandwidth, and evolution of the spin system during NMR measurements, is discussed. Mitigation strategies are proposed using real-time signal processing and edge computing. These developments can support accurate, adaptive control of tensor polarization and improve the figure of merit in scattering experiments that rely on spin-1 polarized targets
Enhanced robustness of non-maximal multipartite entanglement under Hawking radiation
No full textIt is commonly expected that maximally multipartite entangled states provide the richest quantum correlations and thus represent optimal quantum resources in the Schwarzschild black hole background. Here, by analyzing the genuine N-partite entanglement of fermionic modes near the event horizon, quantified via concurrence, we identify a counterintuitive phenomenon: in this curved spacetime, the genuine multipartite entanglement of a maximally entangled state can be lower than that of a suitably chosen non-maximally entangled state. This observation implies that, from the perspective of quantum resource efficiency, non-maximally entangled multipartite states may outperform their maximal counterparts for quantum information tasks under gravitational effects. Therefore, preparing appropriately engineered non-maximally entangled multipartite states as initial resources provides a more practical and effective approach to quantum information processing in Schwarzschild spacetime
Feedback stabilization for a spatial-dependent Sterile Insect Technique model with Allee Effect p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 17.2px Helvetica; color: #000000}
No full textThis work focuses on feedback control strategies for applying the sterile insect technique (SIT)
to eliminate pest populations. The presentation is centered on the case of mosquito populations,
but most of the results can be extended to other species by adapting the model and selecting
appropriate parameter values to describe the reproduction and movement dynamics of the species
under consideration.
In our study, we address the spatial distribution of the population in a two dimensional
bounded domain by extending the temporal SIT model analyzed in [2], thereby obtaining a
reaction-diffusion SIT model. After the analysis of the existence and the uniqueness of the solution
of this problem, we construct a feedback law that globally asymptotically stabilizes the extinction
equilibrium thus yielding a robust strategy to keep the pest population at very low levels in the
long term.
p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Helvetica; color: #000000
Advanced control strategies for stochastic systems using PDF optimisation
No full textThis paper presents an innovative probabilistic control framework for continuous-time stochastic systems. Unlike traditional control approaches that optimise deterministic control strategies, our framework directly optimises the probability density function (PDF) of the control signal, allowing for a more adaptable and robust response to stochastic variations. By integrating stochastic differential equations with the Hamilton–Jacobi–Bellman equation and utilising the Fokker–Planck dynamics, our method offers a precise and dynamic approach to managing uncertainty. The framework minimises the Kullback–Leibler divergence to align the system’s joint state and control distribution with a desired joint target distribution, ensuring effective control even in unpredictable environments. A novel algorithm iteratively refines the control PDF based on real-time feedback, further enhancing the system’s alignment with the target behaviour. The proposed method is demonstrated on an Ornstein–Uhlenbeck process, showcasing its effectiveness in steering the system’s state distribution toward desired outcomes and underscoring its broad applicability to stochastic systems