arXiv preprints from January 1, 2026 through September 29, 2026 — 07:12:25 EST
We consider the question of counting the degrees of freedom in theoretical models, with an emphasis on theories of fields and gravity. Among the possible approaches, the Hamiltonian formulation remains one of the most systematic and robust tools. However, it can easily become long and technically involved. In this work, we present a...
Quantum bianisotropy and chirality are fundamental concepts in light matter interaction that describe how materials with broken symmetries respond to electromagnetic fields at the level of macroscopic quantum electrodynamics. In quantum bianisotropy, magnetoelectric (ME) energy plays a critical role in mediating and enhancing light...
This article investigates the holonomy groups of K-contact sub-pseudo-Riemannian manifolds. The primary result is a proof that the horizontal holonomy group either coincides with the adapted holonomy group or acts as its normal subgroup of codimension one. The theory is adapted for metrics of indefinite signature, bypassing the...
Past studies have revealed the dependency of the disc parameters (mass, radius, viscosity, grain fragmentation velocity, dust-to-gas ratio) on the formation of giant planets, where more massive discs seem beneficial for giant planet formation. It is unclear how the different disc properties influence the composition of forming giant...
Data-driven deep learning is considered a promising solution for ground-penetrating radar (GPR) full-waveform inversion (FWI), while its generalization ability is limited due to the heavy reliance on abundant labeled samples. In contrast, Deep unfolding network (DUN) usually exhibits better generalization by integrating model-driven...
Helioseismic and recent asteroseismic observations reveal fine structure in the power spectrum with alternating peaks and troughs above the acoustic cut-off frequency. This structure is interpreted as the interference patterns of high-frequency acoustic waves excited in the solar interior and propagating into the atmosphere, known as...
Physics-Informed Neural Networks (PINNs) provide a mesh-free approach for solving differential equations by embedding physical constraints into neural network training. However, PINNs tend to overfit within the training domain, leading to poor generalization when extrapolating beyond trained spatiotemporal regions. This work presents...
We investigate the open-system dynamics of a micromaser quantum battery in the ultrastrong-coupling (USC) regime. The battery consists of a quantized harmonic mode sequentially interacting, via the Rabi Hamiltonian, with a stream of qubits acting as chargers. USC enhances the charging speed but also induces unbounded energy growth and...
We consider the Robin Laplacian in the exterior of a bounded simply-connected Lipschitz domain in the hyperbolic plane. We show that the essential spectrum of this operator is $[\frac14,\infty)$ and that, under convexity assumption on the domain, there exist discrete eigenvalues below $\frac14$ if, and only if, the Robin parameter is...
The asset pricing literature emphasizes factor models that minimize pricing errors but overlooks unselected candidate factors that could enhance the performance of test assets. This paper proposes a framework for factor model selection and testing by (i) selecting the optimal model that spans the joint efficient frontier of test...
The ribbonlength of a link is a geometric invariant defined as the infimum of the ratio of the length to the width of a folded ribbon realization of the link. In this paper, we prove that if an alternating link admits an alternating diagram with a bipartite dual graph, then its ribbonlength satisfies $$ \mathrm{Rib}(L) \le \sqrt{3} \,...
Despite being under development for over 15 years, transaction throughput remains one of the key challenges confronting blockchains, which typically has a cap of a limited number of transactions per second. A fundamental factor limiting this metric is the network latency associated with the block propagation throughout of the...
Although most theories posit that natural behavior can be explained as maximizing some form of extrinsic reward, often called utility, some behaviors appear to be reward independent. For instance, spontaneous motor babbling in human newborns and curiosity in little kids and other animals seem to elude a simple explanation in terms of...
We prove a new universal identity for umbral operators. This motivates the definition of a subclass satisfying a simplified identity, which we fully characterize. The results are illustrated with common examples of the theory of umbral calculus.
We consider a single large language model (LLM) server that serves a heterogeneous stream of queries belonging to $N$ distinct task types. Queries arrive according to a Poisson process, and each type occurs with a known prior probability. For each task type, the server allocates a fixed number of internal thinking tokens, which...
Flavins are the chromophores in several blue-light-sensitive photoreceptor proteins and act as redox cofactors in many enzymes relevant for biological processes. Despite their biological relevance and numerous, detailed optical investigations of their photophysical properties, the ultrafast nonequilibrium dynamics of their elementary...
We present MoST (Mixture of Speech and Text), a novel multimodal large language model that seamlessly integrates speech and text processing through our proposed Modality-Aware Mixture of Experts (MAMoE) architecture. While current multimodal models typically process diverse modality representations with identical parameters,...
In this proceedings we explore the physics potential of the ESSnuSBplus setup to study beam and non-beam based physics scenarios in both standard and new physics cases. The ESSnuSBplus setup consists of three neutrino sources: the main ESS linac, a low energy monitored neutrino beam and a low energy nuSTORM facility and three...
We obtain a rigidity result for compact three-dimensional Heterotic solitons with parallel non-trivial torsion. We show that they are either hyperbolic three-manifolds or compact quotients of the Heisenberg group equipped with a left-invariant metric. In particular, the latter arise both as solitons with completely skew-symmetric...
This paper introduces an unsupervised health-monitoring framework for turbofan engines that does not require run-to-failure labels. First, operating-condition effects in NASA CMAPSS sensor streams are removed via regression-based normalisation; then a Long Short-Term Memory (LSTM) autoencoder is trained only on the healthy portion of...
Tactile sensors are breaking into the field of robotics to provide direct information related to contact surfaces, including contact events, slip events and even texture identification. These events are especially important for robotic hand designs, including prosthetics, as they can greatly improve grasp stability. Most presently...
Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders and powerful channel codes. However, SSCC often suffers from a pronounced cliff effect in low Signal-to-Noise Ratio (SNR) regimes, where residual bit errors after channel decoding can...
Understanding relationships between attention heads is essential for interpreting the internal structure of Transformers, yet existing metrics do not capture this structure well. We focus on the subspaces spanned by attention-head weight matrices and quantify head-to-head relationships using the Projection Kernel (PK), a...
The accurate identification of historical restoration traces and material degradation is essential for the scientific preservation of ancient bronzes. In this study, the prestigious FUHAO bronze artifact (late Shang period, 13th-11th century BCE) was non-destructively examined using pulsed thermal imaging (PT). By combining single-...
Carrier Frequency Offset (CFO) estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems faces significant performance degradation across heterogeneous software-defined radio (SDR) platforms due to uncalibrated hardware impairments. Existing deep neural network (DNN)-based approaches lack device-level adaptation,...