Papers

We study cosmological collider signatures in a two-field inflationary system with constant-turn derivative mixing between the canonically normalized curvature fluctuation and a massive isocurvature field. Building on recently derived exact hypergeometric solutions that treat the quadratic mixing nonperturbatively, we construct the mixed propagators constituting the cosmological correlators. A Mellin-Barnes approach helps isolate the pair of nonanalytic late-time branches carried by a heavy field. For a cubic isocurvature self-interaction, these branches contribute towards a squeezed bispectrum with a power-law envelope and logarithmic oscillations. The oscillation frequency encodes the heavy mass, while the amplitude and phase retain the full mixing dependence rather than a perturbative expansion. We perform the squeezed limit integral analytically and compare it with numerical results across representative masses and mixing strengths. At fixed mixing we derive the large-mass JWKB expansion of the squeezed correlator and its phase. We also give integral representations for the isocurvature Wightman function. The research idea was suggested by ARC, the calculation was performed by GPT, and the results were checked by the authors.

Quantum gate design is often represented as pulse optimization, although the physical object that implements a gate is the full controlled evolution generated by the pulse. Here we use physics-informed neural networks to represent single-qubit gate design at this evolution level: the control fields, the Bloch-state trajectories, and the total duration are learned together under the Bloch equation. This changes the optimized object from pulse amplitudes to a differentiable physical process whose structure can be inspected and refined. For rotation gates, the optimized evolutions recover the physical organization expected for bounded single-qubit control, with no prescribed pulse ansatz or duration scan. For a geometric gate, the representation identifies localized bottlenecks in maintaining the geometric condition and turns this diagnosis into feedback, reducing the residual path error while preserving high fidelity. Thus physics-informed learning is used not only to synthesize gates, but also to make optimized quantum controls physically readable, diagnosable, and locally refinable. This process-level view may be especially useful for adapting gates to hardware-specific, task-specific, and locally varying experimental constraints.

Exact fermion to qubit transformations are conventionally regarded as algorithmic tools that translate many-body Hamiltonians into qubit representations for quantum simulation. Here we show that they also define intrinsic geometric representations whose structure encodes physically meaningful information beyond spectral equivalence. We develop a geometric framework based on weighted hypergraphs and coupling space representations constructed from the Bravyi–Kitaev (BK) and Xia–Bian–Kais (XBK) encodings. Within the BK representation, we introduce a geometric observable that compares the algebraic connectivities of the kinetic and interaction hypergraphs, derive its exact analytical dependence on interaction strength, and uncover two geometric universality classes together with an exact spectral organization originating from the binary tree architecture of the encoding. The complementary XBK representation describes the evolution of encoded Hamiltonians through probability measures in coupling space, where optimal transport quantifies interaction-driven reorganization independently of the spectral analysis. Applications to the Hubbard, spinless tV , single impurity Anderson, and Kitaev models demonstrate that these connectivity and transport based geometric descriptions consistently capture the structural evolution of encoded quantum Hamiltonians across distinct classes of many-body systems. Our results establish hypergraph geometry as a new framework for understanding fermion-to-qubit encodings,revealing that they serve not only as computational mappings but also as geometric representations of quantum many-body Hamiltonians.

Building on the multi-determinant Transformer backflow neural quantum state (NQS) ansatz and the associated multi-stage training workflow for the doped two-dimensional Hubbard model, we investigate how the optimization dynamics of the NQS depend on several key optimization and architectural hyperparameters. The workflow consists of neural-network backflow (NNB) initialization, supervised Transformer pre-training, and main energy optimization using the Moment-Adaptive ReConfiguration Heuristic (MARCH) within variational Monte Carlo. Using the doped $4\times4$ periodic Hubbard model at $U=8$ as a baseline, we examine how the update-norm threshold, Transformer width, number of determinant channels, and Monte Carlo batch size affect convergence. We find that a moderate update constraint improves the efficiency of MARCH optimization, larger Transformer width and more determinant channels improve the expressive capacity of the ansatz, and larger Monte Carlo batches reduce sampling noise in the update direction. We further test the same workflow at half filling, weaker interaction strength, open boundary conditions, and on a larger $8\times8$ doped lattice. These results identify practical optimization trends for Transformer backflow NQSs and highlight the balance between ansatz expressivity, MARCH update stability, and Monte Carlo sampling quality.

We give the definitive proof that the Dirac Quantum Cellular Automaton (QCA) used for both quantum simulation and algorithmic foundations of Quantum Field Theory (QFT), and especially of Quantum Electrodynamics (QED), as put forward in References https://doi.org/10.1007/s11128-019-2555-4 and https://doi.org/10.22331/q-2023-11-08-1179, does exhibit Fermion Doubling (FD), albeit thrice as less severe as discrete-time standard Lattice Gauge Theories (LGTs) [arXiv:2505.0790], which are naive regarding the spacetime discretization of differential operators acting on fermionic fields. The proof is done for the (1 + 1)D Dirac-QCA model. We show that the (one-time-step) two-point correlation function, also called Green's function (GF), of the Dirac QCA, is of astonishing simplicity, which is in contrast with the GF of the Dirac equation. We also compare, both qualitatively and quantitatively, this Dirac QCA to the continuous-time-LGT spatial discretization of Dirac fermions regarding how well these two lattice models approximate their naive continuum limit$\unicode{x2014}$which is nothing but the Dirac equation$\unicode{x2014}$even when far away from that limit, a situation which must be considered because of experimental limitations in quantum simulation: the Dirac QCA is better for ultrarelativistic regimes, whereas continuous-time LGT is better for non-relativistic regimes. Then, we compute the GF of the FD-fixed model put forward in the last cited reference, called Flavored Dirac QCA (FDQCA)$\unicode{x2014}$which staggers an extra, artificial flavor $only$, on a diamond spacetime lattice, and does not stagger chirality as staggered fermions in usual LGT. The structure of this FDQCA two-point correlation function is of extreme simplicity, and can be expressed in a very simple manner in terms of the four chiral components of the FD-suffering, original-model GF.

In this work, we introduce the One-for-All Adaptive Radiotherapy Planning Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive planning directly from daily cone-beam CT in under two minutes. The agent first autonomously predicts all essential planning components, including synthetic CT generation, multimodal alignment, and tumor/organ segmentation. It then intelligently leverages these outputs to execute the final clinical plan design, providing a comprehensive, automated solution for daily treatment. We also demonstrate that the agent enables clinicians to define planning with intent and intervene at critical decision points, ensuring a "human-in-the-loop" framework that generates acceptable plans before final approval. Evaluated on multiple datasets spanning head-and-neck, lung, abdominal, and prostate cancers with both photon and proton therapy, the proposed framework achieves clinically acceptable accuracy and plan quality comparable to clinically generated treatment plans, with target dose errors (D98) generally within 2.0 Gy of the reference plan. The strong performance of the One-for-All agent highlights the promise of a unified foundation-model approach and opens opportunities for fast, scalable, and fully automated online adaptive radiotherapy across diverse clinical scenarios.

Flexural vibrations dominate the low-energy spectrum of a flat crystalline membrane but do not couple to phonon Hall viscosity. We show that static curvature couples normal motion to in-plane strain, allowing an oscillatory flexural drive to generate elliptical in-plane motion and pump phonon angular momentum along the surface normal. A net angular momentum persists in randomly rippled membranes, with its magnitude and handedness controlled by the drive and ripple spectra. Transfer of the pumped angular momentum to the support produces a steady torque that reverses with the magnetic field and scales with the mean-square curvature. Using the measured bulk Hall viscosity of $\alpha$-RuCl$_3$ to set the scale, we estimate a torque of order $10^{-23}$–$10^{-22}\,\mathrm{N\,m}$ for a few-layer membrane, within reach of demonstrated torsional sensors. The same flexural-to-shear response provides a probe of phonon Hall viscosity in atomically thin crystals.

Bubble-wall friction controls the dynamics of first-order cosmological phase transitions. In Boltzmann-equation approaches, a major uncertainty arises from infrared gauge bosons, whose contribution is artificially enhanced in the massless approximation. We study the impact of thermal masses by including them consistently in both the Liouville operator and the collision integrals. Thermal masses suppress the source term for out-of-equilibrium perturbations while also reducing interaction rates. These effects largely cancel for top quarks, giving only percent-level changes, but they strongly suppress the infrared gauge-boson contribution, shifting the dominant momenta to scales of order the temperature. As a result, gauge bosons become subleading and wall velocities are close to those obtained from top-quark friction alone. We illustrate this in the singlet-extended Standard Model. Our results show that thermal masses reduce the sensitivity of friction calculations to the poorly controlled infrared sector of the plasma.

We establish operational limits on the broadcasting of genuine multipartite entanglement (GME) in quantum networks. Using a distributed protocol in which each of N parties locally implements optimal 1 $\to$ 2 cloning via beam-splitter interactions, we derive exact expressions for the broadcast fidelity of Greenberger-Horne-Zeilinger (GHZ), W states, and Cluster states in a limited setting. We show that the fidelity decays exponentially with system size as [c(R)]$^N$, providing a quantitative expression of multipartite entanglement monogamy in the broadcasting setting, and that both state families share a universal normalisation factor arising from independent post-selection probabilities. Most significantly, we prove a no-go result for simultaneous GME certification: for all reflectivities and all system sizes, the two broadcast copies cannot be simultaneously certified as genuinely multipartite entangled within the standard framework of fidelity-based witnesses. We further check this behaviour for three- and four-party cluster states, finding consistent results that support the generality of the no-go beyond the GHZ and W families. This obstruction arises from the redistribution of multipartite coherence, which both reduces the achievable fidelity and increases the corresponding certification threshold. Our results reveal a fundamental trade-off between the broadcastability of multipartite entanglement and its operational certifiability, and delineate intrinsic limits on entanglement distribution in quantum networks.

In this work, we investigate the violation of the chaos bound for spinning test particles in Gauss-Bonnet anti-de Sitter spacetime, focusing on the regulatory roles of the Gauss-Bonnet parameter and spacetime dimensionality. In five-dimensional space time, the Lyapunov exponent grows monotonically with particle spin. In contrast, in eight- and nine-dimensional spacetimes, it exhibits non-monotonic behavior-first decreasing and then increasing-reflecting the nonlinear nature of higher-dimensional tensor couplings. The Gauss-Bonnet parameter significantly modulates the violation by reshaping the near-horizon geometry: in five dimensions, the deviation of the Lyapunov exponent from the surface gravity first increases and then decreases with the Gauss-Bonnet parameter, whereas in the higher dimensions the bound is more easily violated. Increasing the total angular momentum of the particle also enhances chaos; however, when the Gauss-Bonnet parameter and black hole charge are small, the spacetime dimensionality, rather than the angular momentum, dominates. These results establish the spacetime dimensionality and the Gauss-Bonnet parameter as important factors governing the validity of the chaos bound in modified gravity theories.

Gauge theories and quantum error-correcting codes share the same underlying structure: both use constraints to identify a specific subspace of the full Hilbert space. In quantum error correction, these constraints are known as stabilizers, while in gauge theories they correspond to Gauss law. In this work, we consider a family of discrete Abelian lattice gauge theories described by a $\mathbb{Z}_{N}$ gauge group with $N$ an arbitrary power of two. In this setting, we find a set of stabilizers for the gauge-invariant subspace which is an alternative to the Gauss operators, and we call them binary Gauss stabilizers. We use this alternative stabilizer group to build practical error-correcting codes exploiting the gauge symmetries of the system without the addition of extra qubits. The applications of our finding are not limited to error correction though. We also provide a new strategy of gauge fixing to remove the redundancies based on our alternative stabilizer, which might provide advantages with respect to already-existing approaches such as the axial gauge. Our results provide new tools to study lattice gauge theories and their quantum simulation, and opens directions for future work at the interface of lattice gauge theory and quantum information.

Upcoming cosmic microwave background (CMB) and large-scale-structure surveys require theoretical power spectra with numerical errors well below their observational uncertainties over the scales that carry most of the constraining power. We describe a substantial update to CAMB designed to provide fast, high-precision predictions for two key outputs: the lensed CMB and matter power spectra. The central development is a new treatment of the hyperspherical Bessel functions used for line-of-sight integration in non-flat cosmologies. A leading-order Olver construction maps the curved radial equation onto the flat spherical Bessel equation by matching their actions through the turning point. The resulting approximation is exact in the flat limit, remains smooth through the turning point, and reduces near flatness to a simple rescaling of the flat Bessel argument and amplitude. We also describe updated integrators, a recalibrated fast recombination model, stabilized parameterized post-Friedmann dark-energy evolution, and improvements to CMB lensing accuracy. Numerical convergence is assessed by comparing unboosted default results against more converged calculations. The defaults meet conservative $10^{-3}$ pointwise convergence targets over the main lensed-CMB and quasi-linear matter-power ranges relevant for future surveys. Errors measured in typical runs are substantially smaller than this. We also describe the convention dependence of the nominally linear matter power spectrum when a homogeneous calculation attempts to represent the effects of reionization heating. Essentially all of the new algorithms and code were developed with LLMs or AI agents under human supervision.

The total dust mass of protoplanetary disks is a key property that determines the potential for planet formation. Upper Scorpius (USco), with an age of ~5-12Myr, provides an important laboratory for investigating the evolution of dust reservoirs on timescales comparable to those of planet formation. In this work, we analyze the dust mass distribution of 136 full and transitional disks in USco using the largest ALMA 0.88mm continuum sample currently available for the region. To improve the accuracy of dust mass estimates, we construct a grid of 918 self-consistent radiative transfer models that account for stellar-mass-dependent disk sizes, accretion rates, and porous dust properties. The models yield a new calibration between dust temperature and stellar luminosity, predicting systematically higher dust temperatures for low-mass stars than commonly adopted prescriptions. Using these revised dust temperatures together with porous dust opacities, we derive dust masses for the USco disks and compare them with those of a younger sample in the Chamaeleon~I star-forming region. We find a median dust mass of 0.95M_E for the USco disks, approximately six times lower than that of the Chamaeleon I disks (5.69M_E), providing strong evidence for substantial depletion of millimeter-sized dust grains over the first several Myr of disk evolution. We confirm the previous finding of a highly significant correlation between stellar mass and dust mass, with a slightly steeper relation in USco than in Chamaeleon I. The low dust masses observed in USco, together with their comparison to mature exoplanetary systems, suggest that a large fraction of the primordial solid reservoir has already been incorporated into larger bodies, removed by radial drift, or hidden from millimeter observations by ages of 5-12 Myr.

Reproducibility remains a major challenge in materials synthesis, particularly for nanomaterials whose properties are highly sensitive to experimental conditions. Here, we present a systematic review and meta-analysis evaluating the reproducibility of two widely used synthesis routes: the Turkevich method for gold nanoparticles (AuNPs) and the chemical vapor deposition (CVD) growth of MoS2. An adapted PRISMA-based protocol combined with a modified SPIDER framework was applied to assess methodological transparency, parameter reporting, and experimental consistency across the literature. More than 1,300 articles for each case study were retrieved from Scopus and Web of Science and systematically screened using structured checklists and a Python-based text classification algorithm validated against independent human reviewers. Despite the extensive literature and the widespread perception of these methods as reproducible, only a small fraction of studies rigorously addressed synthesis reproducibility. Critical experimental parameters were frequently underreported, and statistical analyses were rarely included, limiting inter-laboratory comparability and reproducibility. These findings demonstrate the value of systematic reviews and meta-analyses as tools for identifying reproducibility gaps and guiding the development of more transparent and reliable synthesis protocols in materials science.

This paper presents the design and implementation of a flexible data acquisition system13 developed for the Timepix4 ASIC. The system is based on a modular14 FPGA-centric architecture combining high-speed serial readout, Ethernet-based data transport,15 and deterministic multi-board synchronization. The hardware platform includes a scalable stack16 composed of commercial FPGA carrier boards, FMC-based interface electronics, detector-specific17 chipboards, and a dedicated Trigger Logic Unit for synchronized operation.18 The firmware architecture separates control and data paths, enabling independent configuration19 and high-throughput acquisition through UDP over 10 GbE links. The design supports zero-back-20 pressure operation toward the ASIC and allows adaptation of the readout bandwidth to different21 experimental conditions. Synchronization between multiple DAQ systems is achieved through22 a common clock and trigger distribution network, experimentally demonstrated with sub-100 ps23 precision.24 The system has been developed to support detector characterization, laboratory measurements,25 and beam-test campaigns for the 4DPHOTON detector concept. Hardware organization, firmware26 architecture, synchronization strategy, and performance measurements are presented.

Photochemical haze, a common aerosol type expected to form in the atmospheres of hot-Jupiters, can become concentrated to different extents between the morning and evening limbs depending on the balance between advection, gravitational settling, and radiation pressure. We present a analytical framework incorporating the effect of gravity, planetary radius, and stellar flux, alongside the particle size of the haze on its resulting relative distribution between the two limbs. Using this framework and further comparing with 3D climate simulations, our framework provides a reasonable first-order estimate of the maximum radius of haze particles which would reach the morning limb and subsequently be trapped by the nightside gyres, resulting in a higher or comparable concentration of haze over the morning limb compared to the evening limb for a given hot-Jupiter atmosphere. We find that the framework performs best for higher-gravity planets, where the transport of haze particles is more strongly controlled by gravitational settling and therefore less sensitive to the approximations made in describing the atmospheric circulation. We further show that for low-gravity hot-Jupiters, even large haze particles can be readily transported to the morning limb before being removed by gravitational settling, whereas for high-gravity hot-Jupiters only small particles can survive transport to the morning limb. Our novel framework provides a rapid way to understand the transport of haze and plan limb asymmetry observations with JWST, constraining the parameter space exploration for full-scale computationally expensive 3D simulations.

Globular clusters are systems which are known to be particularly well described by two-body relaxation. In recent decades many studies have shown that Chandrasekhar's orbit-averaged theory is able to reproduce many features of numerical simulations. However, it has been claimed that differences between the theory and simulation remain, such as an amplitude mismatch of the rate of change of the distribution function. In this paper we compare the theoretical predictions of Chandrasekhar's theory for anisotropic clusters to precise $N$-body data. We show that more careful $N$-body measurements are able to reduce the claimed mismatch. Nevertheless, we observe a dependency of the remaining mismatch on both position and anisotropy. While the dependence on anisotropy may be understood qualitatively on theoretical grounds, the radial dependence implies that spatial inhomogeneities, and therefore collective effects, may become unavoidable to resolve the residual mismatch between theory and simulations.

Multiple cosmological observables, such as the galaxy overdensity or cosmic shear, consist of fields sampled at the discrete positions of astrophysical sources. Recent work has presented methods to estimate the angular power spectra of such fields, avoiding the construction of pixelated sky maps and the finite-resolution effects associated with them. In this work, we present a method to estimate the disconnected (also known as "Gaussian") covariance of these angular power spectra, addressing subtle effects such as the effective area overlap between different catalogue-based fields and the additional Poisson-like variance arising from the discrete nature of the catalogues. The method relies on the so-called Narrow-Kernel Approximation to account for the contribution of distinct source pairs to the estimator, while including the noise-like contributions from self-pairs exactly. We explicitly compare this approach with a brute-force method that can produce the exact covariance for sparse samples, and validate it against simulations. We show that the method is accurate in realistic scenarios, spanning both dense and noise-dominated datasets (e.g., cosmic shear) and sparse, noise-dominated observables (e.g., fast radio bursts). The method is implemented in the public code NaMaster.

We present a set of ultra-compact spectrographs fabricated using two-photon polymerisation, each under 1 mm in length and printed directly onto an optical fiber. This fully integrated, alignment-free architecture enables extremely low-mass instrumentation with broad potential across astrophotonics, space systems, drone-based sensing, and quantum optics. Two transmissive configurations are presented; they combine beam-expansion optics, dispersive elements, and stray-light suppression within monolithic printed structures optimised for J- and H-band operation. Coarse gratings provide resolving powers of approximately R = 30. Experimental characterisation confirms the feasibility of fiber-coupled, fully printed spectrographs and demonstrates their promise as deployable components for next-generation integrated photonic instrumentation.

Reentrant coil-globule-coil transitions, in which a polymer collapses and then reexpands as a single parameter is varied, have been observed across diverse soft matter systems, yet the minimal ingredients required to produce them remain unclear. Using molecular dynamics simulations of coarse-grained polymers interacting with a single species of attractive crowder, we show that crowder volume fraction $\phi_c$ alone is sufficient to drive a complete reentrant transition. At low $\phi_c$, crowders bridge distant monomers and drive cooperative collapse; at high $\phi_c$, saturation of monomer binding sites suppresses bridging connectivity and produces reentrant expansion. This density-driven transition is absent with purely repulsive crowders, which produce only monotonic compaction while preserving self-avoiding walk (SAW) chain statistics. In contrast, bridging breaks SAW universality: the rescaled size distributions no longer collapse onto a universal curve, and the conformational distributions trace the full coil-globule-coil trajectory as $\phi_c$ is varied. For charged polymers with explicit counterions, electrostatics amplifies rather than suppresses reentrance: bridging crowders displace counterions from the chain, and upon saturation the unscreened backbone charges drive expansion well beyond the original chain size. Saturable geometric bridging thus emerges as a minimal mechanism linking reentrant phenomena across neutral and charged polymers in crowded environments.

Gravitational instabilities are among the most widespread natural hazards and are expected to become increasingly significant under ongoing environmental change. Despite substantial advances in process understanding, monitoring, and modeling, predicting the timing of failure remains a fundamental challenge because instability emerges from complex interactions operating across multiple spatial and temporal scales. Existing approaches often focus on specific processes, forcing mechanisms, or observational signatures, resulting in a fragmented view of how systems evolve toward failure. This article propose a unified conceptual framework in which gravitational instabilities are interpreted as the progressive evolution of a latent system state controlled by damage accumulation, stress redistribution and external forcing to catastrophic failure. Within this perspective, failure emerges from the continuous interplay between internal system dynamics and external forcing, while predictability depends on our ability to infer the evolving state of the system from incomplete and indirect observations. The framework provides a common structure linking physical processes, observable manifestations, monitoring strategies, modeling approaches, and forecasting methods across a wide range of gravitational hazards. By integrating concepts from geomechanics, fracture mechanics, statistical physics, and data-driven sciences, the proposed framework shifts the focus from the search for universal precursors toward the reconstruction of evolving system states and their proximity to instability. It offers a unifying perspective for understanding failure processes and developing more robust approaches to hazard assessment and early warning.

The interplay between topology and magnetism in Weyl semimetals has recently emerged as a fertile ground for novel quantum phases. While monopole harmonic order parameters have been established for superconductivity and charge density waves in these systems, their spin density wave counterparts remain unexplored. Here we introduce monopole spin density wave (SDW) states arising from particle-hole pairing between nested Fermi surfaces enclosing Weyl nodes of the same chirality. We demonstrate that the SDW order parameter inherits a nontrivial pairing Berry phase and is described by monopole harmonic functions that exhibit topologically protected nodal structures in the gap function. Through a concrete lattice model, we show that helical and cycloidal SDW orders produce distinct signatures in band structures, Fermi arc distributions, and surface spin polarization patterns, which can be directly resolved by spin- and angle-resolved photoemission spectroscopy. Remarkably, we find that the quantum geometric tensor of the monopole pairing realizes ideal quantum geometry in the weak-coupling limit, where quantum distance fluctuations are entirely governed by Berry curvature. Our results not only unify the understanding of monopole ordered states across pairing channels but also provide experimental avenues for distinguishing competing magnetic orders in ReAlX (Re=rare earth elements, X=Si, Ge) materials and suggest potential applications in topological spintronics.

We review the current status of compact object simulations that are based on the Smoothed Particle Hydrodynamics (SPH) method. The first section of this review is dedicated to SPH as a numerical method for Newtonian, ideal gas dynamics and it should be fairly self-contained. It begins with the basics of the method, but also describes recent advances including various meshless derivatives or methods for treating shocks. A separate chapter summarizes general relativistic SPH, including its special relativistic limit, and it explains in some detail the recent development of full numerical relativity in SPH where matter is evolved together with a dynamical spacetime. The remainder of the review has an astrophysical focus, here we discuss the status of the simulations of white dwarf–white dwarf, neutron star–neutron star and neutron star–black hole systems. For each type of system the emphasis is on gravitational-wave-driven mergers, but we also briefly summarize dynamical collisions that can occur in locations with large stellar densities.

Accurate prediction of the Born effective charge (BEC) tensor is crucial for modeling materials under electric fields but remains computationally expensive. To bridge this gap, we present SevenNet-Polar, an equivariant graph neural network framework based on the SevenNet architecture for fast and accurate BEC predictions. Our BEC-only predictors can achieve an RMSE as low as 0.0043 e on ZrO$_2$, Li$_3$PO$_4$, and perovskites, despite the presence of high-temperature (up to 2,000 K) and defect-laden training data. Our all-in-one multitask models for predicting energy, forces, stress, and BEC in ZrO$_2$ and Li$_3$PO$_4$ achieve high accuracy with an RMSE of 1.0 meV/atom for energy, 12 meV/angstrom for forces, 0.05 GPa for stress, and 0.0029 e for BEC. BEC accuracy is not degraded by multitask training. Scaling analysis reveals distinct exponents for diagonal and off-diagonal BEC components, both of which exhibit less favorable scaling than energy, force and stress errors. SevenNet-Polar generalizes robustly when tested on scenarios containing structural environments absent from the training set, such as along nudged elastic band (NEB) trajectories or grain boundaries in ZrO$_2$. Accelerated by FlashTP, SevenNet-Polar enables simulations containing up to 1.5 million atoms on multi-GPU supercomputers and up to approximately 15,000 atoms on a single consumer-grade GPU. This makes charge-aware molecular dynamics simulations under electric fields more accessible.

Recent studies have shown that the accretion of kinematically misaligned gas fuels the central reservoir of galaxies, triggering nuclear activity and star formation. In this work, we show that this specific accretion channel can only sustain main-sequence levels of star formation in galaxies with $M_* \lesssim 10^{10} {\rm M_\odot}$. Using a sample of 201 kinematically misaligned galaxies, and a comparison sample of 3689 aligned galaxies, from the Mapping Nearby Galaxies at Apache Point Observatory survey, we investigate the impact of kinematically misaligned gas on star formation across stellar mass. We characterise the global specific star formation rate, central concentration and mass of ionized gas of our samples, and derive radial profiles of specific star formation rate and ionized gas mass surface density. We find that misaligned galaxies exhibit more centrally concentrated ionized gas than their aligned counterparts, with the strongest enhancement occurring at intermediate masses ($10^{10}$-$10^{10.6} {\rm M_\odot}$), where the central ionized gas density peaks. In galaxies less massive than $10^{10} {\rm M_\odot}$, misaligned gas fuels nuclear star formation at rates typical of star-forming systems. At higher masses, however, the impact of this newly accreted gas is diluted by the larger pre-existing stellar mass in the central regions, limiting its ability to rejuvenate the star formation activity in these galaxies. Our results also show that misaligned galaxies with or without nuclear activity exhibit similar central concentrations of ionized gas, suggesting that most have a reservoir capable of fuelling their supermassive black holes over timescales longer than typical nuclear activity episodes.

Quantum remote control, also known as quantum remote implementation of an operator (QRIO), enables the remote manipulation of an arbitrary quantum state by implementing a desired quantum operation at a distant location. Significant progress has recently been made in developing QRIO protocols and their variants. Most existing schemes employ hyperentangled states where entanglement is shared across multiple degrees of freedom (DOFs). However, these protocols typically exploit only one degree of freedom at a time. In this work, we propose a QRIO protocol that simultaneously utilizes the polarization and spatial DOFs of a two-qubit hyperentangled state to remotely implement an arbitrary hybrid operator on an unknown single-photon two-qubit hyperstate. The shared hyperentangled resource is realized using the polarization and spatial modes of photons, while the protocol is constructed using linear optical elements and cross-Kerr nonlinear interactions to facilitate effective photon-photon coupling. Furthermore, the effects of measurement errors arising from finite coherent state distinguishability and coherent state dissipation are analyzed and the corresponding success probability of the protocol is evaluated. The results demonstrate that an appropriate choice of the cross-Kerr phase shift and coherent state amplitude significantly enhances the protocol performance, making the proposed scheme a promising candidate for hybrid quantum communication and distributed quantum information processing.

This paper traces the evolution of Red Ambiental Ciudadana de Monitoreo (RACiMo), a citizen-science and environmental-education initiative developed by Universidad Industrial de Santander in Colombia. RACiMo has evolved through successive editions from a school-based open-hardware programme into a regional environmental monitoring network that integrates meteorological and air-quality data, open-data practices, and student-centred research. The project's central objective is to train citizens, especially secondary-school students, teachers, and university mentors, to record, curate, analyse, interpret, and communicate climate and air-quality data relevant to their local contexts. RACiMo has involved approximately 515 students from urban, metropolitan, rural, and páramo communities in Santander, Colombia. It has progressed from Arduino-Raspberry Pi stations assembled through a Do-It-With-Others approach to low-maintenance commercial instruments and a multi-municipality network of professional weather and air-quality stations. Its pedagogy has shifted from learning by building sensors to learning by analysing real environmental datasets through Python, Jupyter notebooks, visualisation tools, and student-led research projects. The current RACiMo-Orquídeas implementation expands the network across five municipalities, emphasises local environmental issues such as freight traffic and industrial activity, and provides public access to data through repositories and interactive tools. The paper discusses the trade-offs between openness, educational value, reliability, data quality, sustainability, and scalability. It argues that citizen environmental monitoring can strengthen climate awareness and adaptation when local communities are trained not only to collect data, but also to understand and use it critically.

The kagome metal CsV$_{3}$Sb$_{5}$ hosts an intriguing interplay between charge-density-wave (CDW) order and superconductivity that is highly sensitive to lattice distortions. However, determining the specific roles of the in-plane ($A_{1g,1}$) and out-of-plane ($A_{1g,2}$) symmetric strain channels has been hindered by their intrinsic mixing in conventional piezo-based experiments. Here, we combine in-plane uniaxial strain with direct $c$-axis compression to independently access and disentangle these symmetry-resolved responses in CsV$_{3}$Sb$_{5}$. We reveal that $c$-axis compression drives a massive, linear enhancement of the superconducting transition temperature ($T_c$) alongside a suppression of $T_{\rm CDW}$. The tuning efficiency of this out-of-plane deformation acts with an opposite sign and far exceeds that of in-plane strain, demonstrating that $c$-axis lattice control dictates the phase competition. Furthermore, by isolating the pure elastoresistivity coefficients, we find that the out-of-plane cross-coupling coefficient ($m_{13}$) is comparable in magnitude but opposite in sign to the in-plane response ($m_{11}+m_{12}$). Unlike the sharply peaked in-plane response, $m_{13}$ exhibits a distinct, order-parameter-like onset across the CDW transition. Our results establish that out-of-plane lattice control plays a dominant role in tuning the intertwined states in CsV$_{3}$Sb$_{5}$ and provide a general pathway for resolving strain-coupled electronic responses in layered quantum materials.

We compute the massive particles radial action along hyperboliclike geodesics in various spherically symmetric spacetimes: the standard $4d$ Schwarzschild spacetime, its $d$-dimensional genralization known as Schwarzschild-Tangherlini solutions and for the D3-branes spacetimes, showing useful resummation properties in terms of special (hypergeometric, Fox-Wright) functions in the eikonal limit and generalizing previous results valid for null geodesics. As a consequence, the scattering angle can be resummed too, and we explicitly display the resummed expressions. In addition, in the more interesting situation of a $4d$ Schwarzschild black hole spacetime, following the approach of the quantum Seiberg-Witten curves to the radial equation associated with a massive scalar field, we show that the quantum $a$-cycle (or, equivalently, the \lq\lq renormalized angular momentum") is simply related to radial action also in this massive case, providing fully resummed expressions. Finally, we display the explicit, expanded-form expression of the dual $a_D$-cycle, for which, however, no resummed expressions have been derived yet.

Hands-on telescope experience is often used to drive student engagement in astronomy education, but scaling access to larger groups of students is operationally challenging. Consequently, students encounter only a fraction of the professional workflow, rarely engaging with the rigorous peer-review, time-allocation processes, or automated data reduction pipelines that govern modern research facilities. We present the design of MIRA (Mentored Investigations using Robotic Astronomy), a data management and educational platform that connects Swiss secondary school and undergraduate students with operational robotic observatories. MIRA structures the entire observation lifecycle: proposal, review, acceptance/rejection, scheduling, and observation. Following execution, the platform automatically reduces raw FITS frames (including astrometric calibration and photometry) and serves them via a web-accessible archive accompanied by Python-based analysis tutorials. By separating educational front-ends from low-level telescope controls through Astra and ASCOM Alpaca, MIRA delivers an authentic scientific research workflow that bridges classroom learning with professional observatory operations.