Latest papers
We prove optimal systolic inequalities for length spaces homeomorphic to a torus of genus one or a real projective plane. In both cases, the optimal constant coincides with the constant from the (reversible) Finsler setting. This…
Binary millisecond pulsars (MSPs) in globular clusters (GCs) are key for binary and stellar evolution studies under extreme conditions. The identification of their optical companion stars is instrumental in order to characterise these…
The destruction of Aharonov-Bohm (AB) caging by interaction and the emergence of interaction-induced chiral currents in flux lattices are two paradigmatic examples of interaction-driven quantum transport. While various mechanisms, such as…
Graph-based recommendations are widely adopted in real-world industrial applications. However, graphs in these systems often reach a massive scale, posing notable scalability and efficiency challenges. This requires techniques that can…
Anomaly detection is inherently characterised by severe class imbalance, making the interpretation of evaluation metrics challenging. Although metrics such as AUROC, AUPR, F1-score, and MCC are widely used, their values convey different…
Pearson correlation is the default measure of association in most statistical software, yet it is only appropriate for pairs of continuous variables with a linear relationship. When variables are binary, ordinal, or categorical, specialized…
This paper is the first in a series devoted to the classification of automorphisms and isomorphisms of twisted Chevalley groups over commutative rings. In the present paper, we prove that every automorphism of a twisted Chevalley group of…
Can vacuum electromagnetic fluctuations shift a bulk Mott transition? Within the Gutzwiller variational method, we derive a criterion that separates collective spectroscopic hybridization from thermodynamic phase control. We show that a…
A statistically reliable parameter-extraction procedure should be validated independently of the physical and detector models to which it will eventually be applied. A template-based inference framework is developed and tested using…
The LHCb topological beauty trigger is the primary set of algorithms for selecting collision events containing $b$-hadrons in the fully software-based LHCb trigger. The algorithms apply monotonic Lipschitz neural networks (NNs) to select…
Compressible multiphase flows involving shocks and material interfaces arise in applications such as bubble collapse and droplet breakup, where strong nonlinear interactions produce complex interface deformation, mixing, and multiscale…
Real data often contains errors, which is why data engineers spend a lot of time creating data cleaning pipelines to ensure the best possible data quality. However, it is often difficult to compare the results of different pipelines and…
We present a generalization of the well-known homogeneous self-dual embedding model, which is widely used in conic optimization. The new embedding applies to a problem of minimizing the sum of two proper lower-semicontinuous convex…
Given a rearrangement-invariant (r.i.) space X, we show that the segment multiplier, the truncated Hilbert transform, and the discrete Hilbert transform (on the associated discretized space) are bounded on X simultaneously. Moreover, this…
In 2011 Hagar & Sergioli proposed a new interpretation of objective probability in deterministic physics. On it, the probability of a physical state supervenes on the resources, energy over time, required to realize it from a given state,…
Computing centers today mostly operate conventional CPU- and GPU-based systems, where the direct way of decreasing energy consumption is a reduction in the applications' runtime. Neuromorphic computing promises an alternative architecture…
The rapid expansion of offshore wind energy is central to the European Union's climate-neutrality targets, with High Voltage Direct Current-connected offshore wind power plants (HVDC-OWPPs) becoming increasingly important for integrating…
We propose a new mathematically exact method for computing unbiased Diffusion Monte Carlo (DMC) estimates of non-local operators. We demonstrate that the current state-of- the-art technique, Forward Walking, is only exact for local…
Tensor decomposition serves as a foundational tool for feature extraction in hyperspectral image classification, a domain classically dominated by the Tucker and Canonical Polyadic decompositions. Although widely adopted, these schemes…
Reliable structure-property modeling is crucial for accelerating materials discovery, where crystal graphs and structure-derived crystallographic descriptions provide complementary geometric and semantic information. Existing multimodal…