arXiv preprints from January 1, 2026 through September 24, 2026 — 04:01:49 EST
The light deflection under a strong gravitational field, referred to as strong gravitational lensing, provides a powerful probe of spacetime geometry. Besides, laboratory analogue models are employed to study the effects of curved spacetime and explore the design of optical devices. Here, applying the framework of analogue gravity, we...
The identification, control and theoretical modelling of spin-triplet superconductors (STC) remain a central theme in quantum materials research. Intrinsic STC are rare but offer rich condensate properties and unique surface properties allowing insights into the nature of the spin-triplet order, and promising applications in quantum...
Chromospheric heating is an important ingredient in the energy budget of the solar atmosphere, which is challenging to quantify from observations. By using 3D radiative magnetohydrodynamic simulations of the solar atmosphere combined with non-LTE spectral synthesis, we estimated chromospheric heating from synthetic spectra and studied...
We develop a fractional-order Ginzburg-Landau (GL) framework for nonreciprocal superconducting transport in Josephson junctions formed by fractal superconductors or superconducting media with nonlocal correlations, separated by a noncentrosymmetric normal layer. We show that nonreciprocity and the superconducting diode effect arise...
We theoretically propose a nonlinear spin-wave Doppler effect, in which the time-dependent motion of a magnetic energy boundary acts as an active frequency modulator, directly converting boundary-induced phase dynamics into instantaneous spectral synthesis for propagating spin-wave modes. In contrast to the conventional linear Doppler...
Quantum computers are inherently noisy, and a crucial challenge for achieving large-scale, fault-tolerant quantum computing is to implement quantum error correction. A promising direction that has made rapid recent progress is to design hardware that has a specific noise profile, leading to a significantly higher threshold for noise...
Astrophysical dynamos feature various spatial structures and dynamical regimes, ranging from hemispherical magnetic fields to the random reversals of the geodynamo. The recently observed Tayler-Spruit dynamo has been invoked to explain angular momentum transport in stellar radiative zones and magnetar formation in a proto-neutron star...
We consider correctly defining the perturbative expansion in a discrete gravity (simplicial or Regge calculus) needed to study physical effects like graviton loop corrections to Newton's potential. For the symmetric derivative $Δ^{(s)}_λ=i\sin p_λ$ in the finite-difference action, the propagator has a graviton pole at...
Recurrent fluorescence (RF) is an important relaxation mechanism in polycyclic aromatic hydrocarbons (PAHs), which could stabilize them and contribute to the production of aromatic infrared bands that are observed in the infrared spectra of the interstellar medium (ISM). In this theoretical work, a statistical model of relaxation by...
We present a detailed vetting analysis of the TESS candidate TOI 864.01, initially identified as a potential ultra-short-period (P ~ 0.52 d) Earth-sized planet orbiting an M-dwarf. Using 12 sectors of TESS photometry spanning a multi-year baseline, we recover a robust periodic transit-like signal. While the recovered transit depth is...
We consider here several aspects of the following challenging question: is it possible to use a passive cloak to make invisible a dielectric inclusion on a finite frequency interval in the quasistatic regime of Maxwell's equations for an observer close to the object? In this work, by considering the Dirichlet-to-Neumann (DtN) map, we...
The accurate modeling of non-covalent interactions between helium and graphitic materials is important for understanding quantum phenomena in reduced dimensions, with the helium-benzene complex serving as the fundamental prototype. However, creating a quantitatively reliable potential energy surface (PES) for this weakly bound system...
Actin filaments, crosslinkers and myosin molecular motors form contractile networks. For instance, the cell cortex is a thin network below the cell membrane ; contraction of the cell cortex allows cells to round up during cell division. Contractile actin-myosin networks are often represented at large scale by continuous theories such...
Asymptotic grand unification is an alternative framework to traditional quantitative unification, as the renormalisation flow leads towards an ultra-violet safe fixed point. Phenomenologically, 5-dimensional realisations permit new particles with masses as low as the TeV scale, well below the usual unification scale. We explore the...
Recent advances in quantum technologies and related experiments have created a need for highly accurate, versatile, and computationally efficient simulation techniques for the dynamics of open quantum systems. Long-lived correlation effects (non-Markovianity), system-environment hybridization, and the necessity for accuracy beyond the...
We propose a graph-based, multi-fidelity learning framework for the prediction of stationary Navier--Stokes solutions in non-parametrized two-dimensional geometries. The method is designed to guide the learning process through successive approximations, starting from reduced-order and full Stokes models, and progressively approaching...
Over the past decade, ALMA has uncovered a range of substructures within exoKuiper belts, pointing to a population of undetected planets. With JWST's sensitivity, we now have the opportunity to identify these planets thought to be responsible for the observed substructures in debris discs. We present Cycle 1 JWST/MIRI 11.4 μm...
Optical aberrations and instrument resolution can affect the observed morphological properties of features in the solar atmosphere. However, little work has been done to study the effects of spatial resolution on the dynamical processes occurring in the Sun's atmosphere. In this work, owing to the availability of high-resolution...
Frequencies of low-degree solar p modes are sensitive to activity over the entire Sun, including the unobservable far-side hemisphere. When frequency shifts extracted from week-long BiSON datasets are fitted to a linear combination of observed near-side activity and a far-side proxy made from the near-side measures shifted by half the...
We present a microscopic analysis and evaluation of the dielectric susceptibility of a dielectric medium consisting of vector-type two-energy-level atoms responding on a weak probe mode when the atoms are driven by a strong coherent field. Each atom, in an environment of others, exists as a quasiparticle further structuring a bulk...
Quantum machine learning (QML) is expected to offer new opportunities to process high-dimensional data efficiently by exploiting the exponentially large state space of quantum systems. In this work, we apply quantum extreme reservoir computing (QERC) to the classification of microstructure images of polymer alloys generated using...
We propose a neural network-based model capable of learning the broad landscape of working regimes in quantum dot simulators, and using this knowledge to autotune these devices - based on transport measurements - toward obtaining Majorana modes in the structure. The model is trained in an unsupervised manner on synthetic data in the...
Sea ice harbours a rich community of well-adapted microorganisms that inhabit liquid micro-spaces where extreme conditions prevail. Currently at risk under climate change, the sea-ice microbiome holds mysteries about evolution of life on Earth and possibly elsewhere, which require methodological innovation to be unravelled. Gaining...
Mapping microstructure to properties is central to materials science. Perhaps most famously, the Hall-Petch relationship relates average grain size to strength. More challenging has been deriving relationships for properties that depend on subtle microstructural features and not average properties. One such example is the initiation...
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures using a low-dimensional data representation. We use the Atmospheric Big Challenge (ABC) database, a publicly available dataset with over 100,000 simulated...