Miracle-dz/UniFAR-FTUs huggingface dataset:
Sampling triangulations of manifolds using Monte Carlo methods

We propose a Monte Carlo method to efficiently find, count, and sample abstract triangulations of a given manifold M. The method is based on a biased random walk through all possible triangulations of M (in the Pachner graph), constructed by combining (bi-stellar) moves with suitable chosen accept/reject probabilities (Metropolis-Hastings). Asymptotically, the method guarantees that samples of triangulations are drawn at random from a chosen probability. This enables us not only to sample (rare) triangulations of particular interest but also to estimate the (extremely small) probability of obtaining them when isomorphism types of triangulations are sampled uniformly at random. We implement our general method for surface triangulations and 1-vertex triangulations of 3-manifolds. To showcase its usefulness, we present a number of experiments: (a) we recover asymptotic growth rates for the number of isomorphism types of simplicial triangulations of the 2-dimensional sphere; (b) we experimentally observe that the growth rate for the number of isomorphism types of 1-vertex triangulations of the 3-dimensional sphere appears to be singly exponential in the number of their tetrahedra; and (c) we present experimental evidence that a randomly chosen isomorphism type of 1-vertex n-tetrahedra 3-sphere triangulation, for n tending to infinity, almost surely shows a fixed edge-degree distribution which decays exponentially for large degrees, but shows non-monotonic behaviour for small degrees.
Low-mass Quiescent Galaxies Are Small in Isolated Environments: Environmental Dependence of the Mass–Size Relation of Low-mass Quiescent Galaxies

We study the mass–size relation of quiescent galaxies across various environments, with a particular focus on its environmental dependence at the low-mass part of log(Mstar/M⊙)≲10.0 . Our sample consists of 13,667 quiescent galaxies with log(Mstar/M⊙)≥9.4 and 0.01 < z < 0.04 from the Sloan Digital Sky Survey. We discover that the mass–size relation of low-mass quiescent galaxies (LQGs) with log(Mstar/M⊙)≲10.0 depends on their environment, with LQGs in the highest-density environments exhibiting an average size ∼70% larger than those in isolated environments. Moreover, the slope of the mass–size relation for LQGs in high-density environments is significantly shallower than that of their counterparts in isolated environments. This is in contrast with high-mass quiescent galaxies with log(Mstar/M⊙)≳10.5 that show a nearly identical mass–size relation across all environments. Combined with additional discoveries that the mass–size relation slopes of LQGs and star-forming galaxies are similar to each other in high-density environments, and that LQGs in higher-density environments exhibit more disk-like structures, our results support the idea that LQGs in high-density environments have evolved from star-forming galaxies through environmental effects, which are capable of causing their quenching and transformation into quiescent galaxies. With the aid of an analysis of merger rates for simulated galaxies from a cosmological galaxy formation simulation, we suggest that the steep slope and low normalization of the mass–size relation of LQGs in the lowest-density environments may originate from recent gas-rich mergers, which occur over 10–30 times more frequently in the progenitors of LQGs in the lowest-density environments than in their counterparts in high-density environments at low redshifts.
Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks

Recurrent neural networks (RNNs) trained on compositional tasks can exhibit functional modularity, in which neurons can be clustered by activity similarity and participation in shared computational subtasks. Unlike brains, these RNNs do not exhibit anatomical modularity, in which functional clustering is correlated with strong recurrent coupling and spatial localization of functional clusters. Contrasting with functional modularity, which can be ephemerally dependent on the input, anatomically modular networks form a robust substrate for solving the same subtasks in the future. To examine whether it is possible to grow brain-like anatomical modularity, we apply a recent machine learning method, brain-inspired modular training (BIMT), to a network being trained to solve a set of compositional cognitive tasks. We find that functional and anatomical clustering emerge together, such that functionally similar neurons also become spatially localized and interconnected. Moreover, compared to standard $L_1$ or no regularization settings, the model exhibits superior performance by optimally balancing task performance and network sparsity. In addition to achieving brain-like organization in RNNs, our findings also suggest that BIMT holds promise for applications in neuromorphic computing and enhancing the interpretability of neural network architectures.
Adsorption of Fragrance Capsules onto Cellulose Nano- and Micro-Cellulose Fibers in Presence of Guar Biopolymers

Fabric softeners are formulated to enhance textile softness and impart a pleasant scent. One of the most efficient technologies for controlled fragrance delivery onto fabrics involves encapsulating scent molecules in polymer capsules. Here, we investigate the adsorption of anionic fragrance capsules on cotton fabrics with the goal of reducing the reliance on palm-oil-derived surfactants. First, we employ 200 nm cellulose nanocrystals (CNC) as a reliable model for cotton fibers. CNC enables us to explore interactions among various softener components, including surfactants, guar biopolymers, and fragrances, using physical chemistry techniques applied to bulk dispersions. The primary objective is to elucidate the role of surfactant vesicles, the primary ingredient in textile conditioners, in the association between fragrance capsules and cotton. Secondly, we examine the influence of biopolymers present in a newly developed environmentally friendly softener on this association. Our findings demonstrate that anionic fragrance capsules are deposited onto cotton microfibers in the presence of either cationic surfactants or guar biopolymers, driven by electrostatic interactions. Scanning electron microscopy confirms capsule adsorption on textile fibers when these cationic ingredients are present. Understanding the interaction mechanisms between fragrance capsules and cotton fabrics, as well as the roles played by other softener components, can facilitate the design of more efficient and sustainable formulations.
Systematic simulation of age-period-cohort analysis: Demonstrating bias of Bayesian regularization

Age-period-cohort (APC) analysis is one of the fundamental time-series analyses used in the social sciences. This paper evaluates APC analysis via systematic simulation in term of how well the artificial parameters are recovered. We consider three models of Bayesian regularization using normal prior distributions: the random effects model with reference to multilevel analysis, the ridge regression model equivalent to the intrinsic estimator, and the random walk model referred to as the Bayesian cohort model. The proposed simulation generates artificial data through combinations of the linear components, focusing on the fact that the identification problem affects the linear components of the three effects. Among the 13 cases of artificial data, the random walk model recovered the artificial parameters well in 10 cases, while the random effects model and the ridge regression model did so in 4 cases. The cases in which the models failed to recover the artificial parameters show the estimated linear component of the cohort effects as close to zero. In conclusion, the models of Bayesian regularization in APC analysis have a bias: the index weights have a large influence on the cohort effects and these constraints drive the linear component of the cohort effects close to zero. However, the random walk model mitigates underestimating the linear component of the cohort effects.
Shock-driven periodic variability in a low-mass-ratio supermassive black hole binary

We investigate the time-varying electromagnetic emission of a low-mass-ratio supermassive black hole binary (SMBHB) embedded in a circumprimary disk, with a particular interest in variability of shocks driven by the binary. We perform a 2D, locally isothermal hydrodynamics simulation of a SMBHB with mass ratio q = 0.01 and separation a = 100 Rg, using a physically self-consistent steady disk model. We estimate the electromagnetic variability from the system by monitoring accretion onto the secondary and using an artificial viscosity scheme to capture shocks and monitor the energy dissipated. The SMBHB produces a wide, eccentric gap in the disk, previously only observed for larger mass ratios, which we attribute to our disk model being much thinner (H/R ≈ 0.01 near the secondary) than is typical of previous works. The eccentric gap drives periodic accretion onto the secondary SMBH on a timescale matching the orbital period of the binary, $t_{\rm {bin}}\approx 0.1\,\,\rm {yr}$, implying that the variable accretion regime of the SMBHB parameter space extends to lower mass ratios than previously established. Shocks driven by the binary are periodic, with a period matching the orbital period, and the shocks are correlated with the accretion rate, with peaks in the shock luminosity lagging peaks in the accretion rate by 0.43 tbin. We propose that the correlation of these quantities represents a useful identifier of SMBHB candidates, via observations of correlated variability in X-ray and UV monitoring of AGN, rather than single-waveband periodicity alone.
Is time-optimal speed planning under jerk constraints a convex problem?

We consider the speed planning problem for a vehicle moving along an assigned trajectory, under maximum speed, tangential and lateral acceleration, and jerk constraints. The problem is a nonconvex one, where nonconvexity is due to jerk constraints. We propose a convex relaxation, and we present various theoretical properties. In particular, we show that the relaxation is exact under some assumptions. Also, we rewrite the relaxation as a Second Order Cone Programming (SOCP) problem. This has a relevant practical impact, since solvers for SOCP problems are quite efficient and allows solving large instances within tenths of a second. We performed many numerical tests, and in all of them the relaxation turned out to be exact. For this reason, we conjecture that the convex relaxation is always exact, although we could not give a formal proof of this fact.
Palaeoclimate record in the Late Pleistocene loess-paleosol sequence at Miseluk (Vojvodina, Serbia)

Trois unites loessiques entrecoupees par deux complexes de sols sont decrites dans une coupe de loess d'environ 8 m localisee a Miseluk (Vojvodine, Serbie). Les donnees geochronologiques issues des mesures de racemisation des acides amines des coquilles de mollusques permettent de proposer des correlations entre les unites loessiques Ll et L2 de Miseluk et les loess des deux derniers cycles glaciaires (B et C) des autres sequences d'Europe centrale. Les resultats des analyses sedimentologiques et des mesures de susceptibilite magnetique debouchent sur la mise en evidence de plusieurs episodes froids et secs alternant avec des periodes plus chaudes et plus humides au cours des derniers 150 000 ans. L'etude malacologique montre par ailleurs des similitudes importantes entre les faunes de Miseluk et celles du sud de la Transdanubie en Hongrie ("Paleopreilynan fauna"), suggerant que la region de Miseluk constituait une zone refuge au cours des periodes de sedimentation loessique.
Global upper mantle tomography of seismic velocities and anisotropies

A data set of 2600 paths for Rayleigh waves and 2170 paths for Love waves enabled us to retrieve three-dimensional distributions of different seismic parameters. Shallow layer corrections have been carefully performed on phase velocity data before regionalization and inversion at depth. The different seismic parameters include the five parameters of a radially anisotropic medium and the eight azimuthal anisotropic parameters as defined by Montagner and Nataf. It is found that the lateral heterogeneities of velocities and anisotropies in the upper mantle are dominated down to 250–30 km by plate tectonics with slow velocities below ridges, high velocities below continents and a velocity increasing with the age of the seafloor. Anisotropy is present in this whole depth range and the directions of maximum velocities are in good agreement with absolute plate velocities. Below 300 km, there is a sharp decreasing of the amplitude of lateral heterogeneities of seismic velocities and anisotropies. Below 450 km, lateral heterogeneities display a degree 2 and to a less extent a degree 6 pattern. Therefore, between 250 km and 450 km, there is a transition region where vertical circulation of matter is possible as shown by subducted slabs and “plumes” of slow velocities but which probably separates two types of convection. The first one is closely related to plate tectonics and to the distribution of continents. The second one dominates below 450 km and is characterized by two downgoing and two upgoing flows.
Entanglement asymmetry and quantum Mpemba effect in the XY spin chain

Entanglement asymmetry is a quantity recently introduced to measure how much a symmetry is broken in a part of an extended quantum system. It has been employed to analyze the non-equilibrium dynamics of a broken symmetry after a global quantum quench with a Hamiltonian that preserves it. In this work, we carry out a comprehensive analysis of the entanglement asymmetry at equilibrium taking the ground state of the XY spin chain, which breaks the U(1) particle number symmetry, and provide a physical interpretation of it in terms of superconducting Cooper pairs. We also consider quenches from this ground state to the XX spin chain, which preserves the U(1) symmetry. In this case, the entanglement asymmetry reveals that the more the symmetry is initially broken, the faster it may be restored in a subsystem, a surprising and counter-intuitive phenomenon that is a type of a quantum Mpemba effect. We obtain a quasi-particle picture for the entanglement asymmetry in terms of Cooper pairs, from which we derive the microscopic conditions to observe the quantum Mpemba effect in this system, giving further support to the criteria recently proposed for arbitrary integrable quantum systems. In addition, we find that the power law governing symmetry restoration depends discontinuously on whether the initial state is critical or not, leading to new forms of strong and weak Mpemba effects.
The tectonic significance of Italian magmatism: an alternative view to the popular interpretation

The Tyrrhenian rift zone has been the site of widespread magmatism since late Tortonian times. A pronounced asymmetrical distribution, reflecting the tectonic structure, characterizes Italian magmatism. Sodic basalts occur on the western Tyrrhenian flank and transitional-MORB basalts occur in the Tyrhenian Sea. The eastern flank, however, is characterized by K-alkaline and HK- to ultra-alkaline (e.g. carbonatites and melilitites) rocks. Major trace elements and isotopic compositions allow two major magmatic lineages to be identified: one relating to a non-radiogenic basaltic end-member and the other to a mantle end-member enriched in Ca, with high LILE/HFSE ratio and high Sr isotopic ratios. Their mantle sources are located within the lithosphere thermal boundary layer (TBL) and the metasomatized phlogopite-carbonate asthenosphere at the base of the TBL, respectively. The composition and spatial distribution of volcanism and relative mantle sources tend to map the geometry of the lithospheric mantle and to define a pronounced increase in depth from less than 60 km to about 100 km across the boundary between the thinned Tyrrhenian lithosphere and the Adriatic lithosphere. A mechanism of intra-continental passive rifting, which drives mantle upwelling, is sufficient to satisfy the petrological and geochemical constraints and the observed tectonic environment without requiring a subduction plane.
Gaussian deconvolution and the lace expansion for spread-out models

We present a new proof of $|x|^{-(d-2)}$ decay of critical two-point functions for spread-out statistical mechanical models on $\mathbb{Z}^d$ above the upper critical dimension, based on the lace expansion and assuming appropriate diagrammatic estimates. Applications include spread-out models of the Ising model and self-avoiding walk in dimensions $d>4$, and spread-out percolation for $d>6$. The proof is based on an extension of the new Gaussian deconvolution theorem we obtained in a recent paper. It provides a technically simpler and conceptually more transparent approach than the method of Hara, van der Hofstad and Slade (2003).
Vector dark matter production during inflation and reheating

Gravitational particle production of spectator fields due to the expansion universe during the inflationary and reheating phases of the early universe is of particular interest in the context of dark matter, since it allows to constrain the properties of the dark candidate by comparing the density of particles produced with the observed dark matter abundance. In such processes, tachyonic instabilities arise as a consequence of the coupling to the curvature, greatly enhancing mode production. In this work, we consider a massive vector field that is coupled to the curvature scalar and the Ricci tensor only, and study its gravitational production through inflation and reheating. We show how the mechanism is more efficient than in the case of a non-minimally coupled scalar field, giving rise to larger abundances. Moreover, we analyze the importance of the coupling to the Ricci tensor, which increases tachyonic instabilities in the system, and constrain the mass of the dark particle and the values of the coupling constants by comparing the corresponding abundance with observations.
Analyzing students’ assumptions to varying degree of prompting during problem solving

Reports on pedagogical transformations have called for promoting authentic knowledge-building practices in science classrooms. Making assumptions is one such practice that is integral to “doing” physics. In this study, we analyze the nature and characteristics of students’ assumptions when they are (i) not prompted, (ii) prompted explicitly at the beginning, and (iii) prompted at the end of physics problems. Preliminary observations indicate that students seldom generate assumptions unless prompted. When explicitly asked at the beginning of problem solving, students perceive making assumptions as a separate task dissociated from the problem-solving process. However, when asked to reflect on the validity of their solutions in light of their assumptions, not only do students make assumptions that are closely “tied" to their solutions, but go an extra mile by articulating the implications of the violations of their assumptions. Implications of these findings for instruction and assessment design are discussed.
A Fifty-Year Record of Historical Sedimentation at Deer Lake, North Carolina

Abstract Although many once-deforested areas of the eastern United States are now revegetated, impacts of this disturbance on watershed processes may persist. In this study, lake sediment stratigraphy and magnetism were used to assess the recovery of a small watershed in the southern Blue Ridge Mountains following abrupt reduction of human impacts. Average sediment yields were found to be higher than those of less disturbed basins nearby, and lower than those reported from the early twentieth-century Piedmont Province. Temporal trends in sediment yield appear to reflect both meteorological and land-use histories. Although most of the lake sediment is magnetically similar to bottomland sources, two instances of local upland sediment input, possibly related to human activities, are evident in the record. Interpreting relationships between sediment yield and changing environmental influences is impeded by poor temporal control in the methodology as well as by the intrinsic dynamics of the fluvial system. *I thank Henry McNabb and the U.S. Forest Service at Bent Creek Experimental Forest for resources, useful discussion, historical information, and other means of facilitating this research. I am also indebted to I. L. Larsen, Oak Ridge National Laboratory, Environmental Sciences Division, for crucial assistance with Cs-137 counting.
Phydi: Initializing Parameterized Hypercomplex Neural Networks As Identity Functions

Neural models based on hypercomplex algebra systems are growing and prolificating for a plethora of applications, ranging from computer vision to natural language processing. Hand in hand with their adoption, parameterized hypercomplex neural networks (PHNNs) are growing in size and no techniques have been adopted so far to control their convergence at a large scale. In this paper, we study PHNNs convergence and propose parameterized hypercomplex identity initialization (PHYDI), a method to improve their convergence at different scales, leading to more robust performance when the number of layers scales up, while also reaching the same performance with fewer iterations. We show the effectiveness of this approach in different benchmarks and with common PHNNs with ResNets- and Transformer-based architecture. The code is available at https://github.com/ispamm/PHYDI.
The classical field approximation of ultra light dark matter: quantum breaktimes, corrections, and decoherence

The classical field approximation is widely used to better understand the predictions of ultra-light dark matter. Here, we use the truncated Wigner approximation method to test the classical field approximation of ultra-light dark matter. This method approximates a quantum state as an ensemble of independently evolving realizations drawn from its Wigner function. The method is highly parallelizable and allows the direct simulation of quantum corrections and decoherence times in systems many times larger than have been previously studied in reference to ultra-light dark matter. Our study involves simulation of systems in 1, 2, and 3 spatial dimensions. We simulate three systems, the condensation of a Gaussian random field in three spatial dimensions, a stable collapsed object in three spatial dimensions, and the merging of two stable objects in two spatial dimensions. We study the quantum corrections to the classical field theory in each case. We find that quantum corrections grow exponentially during nonlinear growth with the timescale being approximately equal to the system dynamical time. In stable systems the corrections grow quadratically. We also find that the primary effect of quantum corrections is to reduce the amplitude of fluctuations on the deBroglie scale in the spatial density. Finally, we find that the timescale associated with decoherence due to gravitational coupling to Baryonic matter is at least as fast as the quantum corrections due to gravitational interactions. These results strongly imply that quantum corrections do not impact the predictions of the classical field theory.
A Positive Quasilocal Mass for Causal Variational Principles

A new inequality for a nonlinear surface layer integral is proved for minimizers of causal variational principles. This inequality is applied to obtain a new proof of the positive mass theorem with volume constraint. Next, a positive mass theorem without volume constraint is stated and proved by introducing and using the concept of asymptotic alignment. Moreover, a positive quasi-local mass and a synthetic definition of scalar curvature are introduced in the setting of causal variational principles. Our notions and results are illustrated by the explicit examples of causal fermion systems constructed in ultrastatic spacetimes and the Schwarzschild spacetime. In these examples, the correspondence to the ADM mass and similarities to the Brown-York mass are worked out.