We introduce the Minecraft Dialogue Corpus with Reference (MDC-R). MDC-R is a new language resource that supplements the original Minecraft Dialogue Corpus (MDC) with expert annotations of anaphoric and deictic reference. MDC's task-orientated, multi-turn, situated dialogue in a dynamic environment has motivated multiple annotation efforts, owing to the interesting linguistic phenomena that this setting gives rise to. We believe it can serve as a valuable resource when annotated with reference, too. Here, we discuss our method of annotation and the resulting corpus, and provide both a quantitative and a qualitative analysis of the data. Furthermore, we carry out a short experiment demonstrating the usefulness of our corpus for referring expression comprehension.

Studies in the past few decades have investigated young stellar object evolution based on their spectral energy distribution (SED). The SED is heavily influenced not only by evolutionary stage, but also the morphology of the young star. This work is part of the NEMESIS project which is aiming to revisit star formation with the aid of machine learning techniques and provides the framework for this work. In a first effort towards a novel spectro-morphological classification we analyzed young stellar object morphologies and linked them to the currently used observational classes. Thereby we aim to lay the foundation for a spectro-morphological classification, and apply the insights learned in this study in a future, revisited classification scheme. We obtained archival high-resolution survey images from VISTA for approximately 10,000 literature young stellar object candidates towards the Orion star formation complex (OSFC). Utilizing a Self-Organizing map (SOM) algorithm, an unsupervised machine learning method, we created a grid of morphological prototypes from near- and mid-infrared images. Furthermore, we determined which prototypes are most representative of the different observational classes, derived from the infrared spectral index, via Bayesian inference. We present our grids of morphological prototypes of young stellar objects in the near-infrared, which were created purely from observational data. They are thus non-dependent on theoretical models. In addition, we show maps that indicate the probability for a prototype belonging to any of the observational classes. We find that SOMs created from near-infrared images are a useful tool, with limitations, to identify characteristic morphologies of young stellar objects in different evolutionary stages. This first step lays the foundation for a spectro-morphological classification of young stellar objects to be developed in the future.

The essential postulates of classical thermodynamics are formulated, from which the second law is deduced as the principle of increase of entropy in irreversible adiabatic processes that take one equilibrium state to another. The entropy constructed here is defined only for equilibrium states and no attempt is made to define it otherwise. Statistical mechanics does not enter these considerations. One of the main concepts that makes everything work is the comparison principle (which, in essence, states that given any two states of the same chemical composition at least one is adiabatically accessible from the other) and we show that it can be derived from some assumptions about the pressure and thermal equilibrium. Temperature is derived from entropy, but at the start not even the concept of `hotness' is assumed. Our formulation offers a certain clarity and rigor that goes beyond most textbook discussions of the second law.

Black-box optimization (BBO) addresses problems where objectives are accessible only through costly queries without gradients or explicit structure. Classical derivative-free methods -- line search, direct search, and model-based solvers such as Bayesian optimization -- form the backbone of BBO, yet often struggle in high-dimensional, noisy, or mixed-integer settings. Recent advances use machine learning (ML) and reinforcement learning (RL) to enhance BBO: ML provides expressive surrogates, adaptive updates, meta-learning portfolios, and generative models, while RL enables dynamic operator configuration, robustness, and meta-optimization across tasks. This paper surveys these developments, covering representative algorithms such as NNs with the modular model-based optimization framework (mlrMBO), zeroth-order adaptive momentum methods (ZO-AdaMM), automated BBO (ABBO), distributed block-wise optimization (DiBB), partition-based Bayesian optimization (SPBOpt), the transformer-based optimizer (B2Opt), diffusion-model-based BBO, surrogate-assisted RL for differential evolution (Surr-RLDE), robust BBO (RBO), coordinate-ascent model-based optimization with relative entropy (CAS-MORE), log-barrier stochastic gradient descent (LB-SGD), policy improvement with black-box (PIBB), and offline Q-learning with Mamba backbones (Q-Mamba). We also review benchmark efforts such as the NeurIPS 2020 BBO Challenge and the MetaBox framework. Overall, we highlight how ML and RL transform classical inexact solvers into more scalable, robust, and adaptive frameworks for real-world optimization.

These notes offer an introduction to the functorial and algebraic description of 2-dimensional topological quantum field theories `with defects', assuming only superficial familiarity with closed TQFTs in terms of commutative Frobenius algebras. The generalisation of this relation is a construction of pivotal 2-categories from defect TQFTs. We review this construction in detail, flanked by a range of examples. Furthermore we explain how open/closed TQFTs are equivalent to Calabi-Yau categories and the Cardy condition, and how to extract such data from pivotal 2-categories.

In classical optimal transport, the contributions of Benamou$-$Brenier and McCann regarding the time-dependent version of the problem are cornerstones of the field and form the basis for a variety of applications in other mathematical areas. In this article, we characterize solutions to the martingale Benamou$-$Brenier problem as $\textit{Bass martingales}$, i.e. transformations of Brownian motion through the gradient of a convex function. Our result is based on a new (static) Brenier-type theorem for a particular weak martingale optimal transport problem. As in the classical case, the structure of the primal optimizer is derived from its dual counterpart, whose derivation forms the technical core of this article. A key challenge is that dual attainment is a subtle issue in martingale optimal transport, where dual optimizers may fail to exist, even in highly regular settings.

We initiate a systematic study of 3-dimensional `defect' topological quantum field theories, that we introduce as symmetric monoidal functors on stratified and decorated bordisms. For every such functor we construct a tricategory with duals, which is the natural categorification of a pivotal bicategory. This captures the algebraic essence of defect TQFTs, and it gives precise meaning to the fusion of line and surface defects as well as their duality operations. As examples, we discuss how Reshetikhin-Turaev and Turaev-Viro theories embed into our framework, and how they can be extended to defect TQFTs.

This article is a short version of a longer article to appear in Physics Reports (cond-mat/9708200). The essential postulates of classical thermodynamics are formulated, from which the second law is deduced as the principle of increase of entropy in irreversible adiabatic processes that take one equilibrium state to another. The entropy constructed here is defined only for equilibrium states and no attempt is made to define it otherwise. Statistical mechanics does not enter these considerations. One of the main concepts that makes everything work is the comparison principle (which, in essence, states that any two states of the same chemical composition can be connected by an adiabatic process) and we show that it can be derived from some assumptions about the pressure and thermal equilibrium. Temperature is derived from entropy, but at the start not even the concept of `hotness' is assumed. Our formulation offers a certain clarity and rigor that goes beyond most textbook discussions of the second law.

In this work we present (and encourage the use of) the Williamson theorem and its consequences in several contexts in physics. We demonstrate this theorem using only basic concepts of linear algebra and symplectic matrices. As an immediate application in the context of small oscillations, we show that applying this theorem reveals the normal-mode coordinates and frequencies of the system in the Hamiltonian scenario. A modest introduction of the symplectic formalism in quantum mechanics is presented, useing the theorem to study quantum normal modes and canonical distributions of thermodynamically stable systems described by quadratic Hamiltonians. As a last example, a more advanced topic concerning uncertainty relations is developed to show once more its utility in a distinct and modern perspective.

We introduce a family of states, the fPEPS, which describes fermionic systems on lattices in arbitrary spatial dimensions. It constitutes the natural extension of another family of states, the PEPS, which efficiently approximate ground and thermal states of spin systems with short-range interactions. We give an explicit mapping between those families, which allows us to extend previous simulation methods to fermionic systems. We also show that fPEPS naturally arise as exact ground states of certain fermionic Hamiltonians. We give an example of such a Hamiltonian, exhibiting criticality while obeying an area law.

We present long-term (4-10 years) trends of light pollution observed at 26 locations, covering rural, intermediate and urban sites, including the three major European metropolitan areas of Stockholm, Berlin and Vienna. Our analysis is based on i) night sky brightness (NSB) measurements obtained with Sky Quality Meters (SQMs) and ii) a rich set of atmospheric data products provided by the European Centre for Medium-Range Weather Forecasts. We describe the SQM data reduction routine in which we filter for moon- and clear-sky data and correct for the SQM "aging" effect using an updated version of the twilight method of Puschnig et al. (2021). Our clear-sky, aging-corrected data reveals short- and long-term (seasonal) variations due to atmospheric changes. To assess long-term anthropogenic NSB trends, we establish an empirical atmospheric model via multi-variate penalized linear regression. Our modeling approach allows to quantitatively investigate the importance of different atmospheric parameters, revealing that surface albedo and vegetation have by far the largest impact on zenithal NSB. Additionally, the NSB is sensitive to black carbon and organic matter aerosols at urban and rural sites respectively. Snow depth was found to be important for some sites, while the total column of ozone leaves impact on some rural places. The average increase in light pollution at our 11 rural sites is 1.7 percent per year. At our nine urban sites we measure an increase of 1.8 percent per year and for the remaining six intermediate sites we find an average increase of 3.7 percent per year. These numbers correspond to doubling times of 41, 39 and 19 years. We estimate that our method is capable of detecting trend slopes shallower/steeper than 1.5 percent per year.

JWST observations uncovered a large number of massive quiescent galaxies (MQGs) at z>3, which theoretical models struggle to reproduce. Explaining the number density of such objects requires extremely high conversion efficiency of baryons into stars in early dark matter halos. Using stellar kinematics, we can investigate the processes shaping the mass assembly histories of MQGs. We present high-resolution JWST/NIRSpec integral field spectroscopy of GS-9209, a massive, compact quiescent galaxy at z=4.66 ($\log \left (M_{\ast}/M_{\odot} \right) = 10.52 \pm 0.06 $,$R_{eff} = 220 \pm 20$ pc). Full spectral fitting of the spatially resolved stellar continuum reveals a clear rotational pattern, yielding a spin parameter of $\lambda_{R_{eff}} = 0.65 \pm 0.12$. With its high degree of rotational support, this galaxy challenges the scenario of MQGs growing mainly by dry major mergers. This study suggests that at least a fraction of the earliest quiescent galaxies were fast rotators and that quenching was dynamically gentle process, preserving the stellar disc even in highly compact objects. Using Jeans anisotropic modelling (JAM) and a NFW profile, we measure a dark matter fraction of $f_{\rm DM} \left (< R_{eff} \right ) = 6.3^{+2.8}_{-1.7}%$, which is plausible given that this galaxy is extremely compact. Our findings use kinematics to independently confirm the massive nature of early quiescent galaxies, previously inferred from stellar population modelling. We suggest that GS-9209 has a similar structure to low-redshift 'relic' galaxies. However, unlike relic galaxies which have bottom-heavy initial mass functions (IMF), the dynamically inferred stellar mass-to-light ratio of GS-9209 is consistent with a Milky-Way like IMF. The kinematical properties of GS-9209 are different from those of z<1 early-type galaxies and more similar to those of recently quenched post-starburst galaxies at z>2.

We develop tangent space methods for projected entangled-pair states (PEPS) that provide direct access to the low-energy sector of strongly-correlated two-dimensional quantum systems. More specifically, we construct a variational ansatz for elementary excitations on top of PEPS ground states that allows for computing gaps, dispersion relations, and spectral weights directly in the thermodynamic limit. Solving the corresponding variational problem requires the evaluation of momentum transformed two-point and three-point correlation functions on a PEPS background, which we can compute efficiently by using a contraction scheme. As an application we study the spectral properties of the magnons of the Affleck-Kennedy-Lieb-Tasaki model on the square lattice and the anyonic excitations in a perturbed version of Kitaev's toric code.

In this paper we consider projected entangled pair states (PEPS) on arbitrary lattices. We construct local parent Hamiltonians for each PEPS and isolate a condition under which the state is the unique ground state of the Hamiltonian. This condition, verified by generic PEPS and examples like the AKLT model, is an injective relation between the boundary and the bulk of any local region. While it implies the existence of an energy gap in the 1D case we will show that in certain cases (e.g., on a 2D hexagonal lattice) the parent Hamiltonian can be gapless with a critical ground state. To show this we invoke a mapping between classical and quantum models and prove that in these cases the injectivity relation between boundary and bulk solely depends on the lattice geometry.

We prove evaluations of Hankel determinants of linear combinations of moments of orthogonal polynomials (or, equivalently, of generating functions for Motzkin paths), thus generalising known results for Catalan numbers.

The existence of incompatible observables is a cornerstone of quantum mechanics and a valuable resource in quantum technologies. Here we introduce a measure of incompatibility, called the mutual eigenspace disturbance (MED), which quantifies the amount of disturbance induced by the measurement of a sharp observable on the eigenspaces of another. The MED provides a metric on the space of von Neumann measurements, and can be efficiently estimated by letting the measurement processes act in an indefinite order, using a setup known as the quantum switch, which also allows one to quantify the noncommutativity of arbitrary quantum processes. Thanks to these features, the MED can be used in quantum machine learning tasks. We demonstrate this application by providing an unsupervised algorithm that clusters unknown von Neumann measurements. Our algorithm is robust to noise can be used to identify groups of observers that share approximately the same measurement context.

Reduced mathematical models for atmospheric dynamics at various scales have a long and rich history. However, versions of such models that explicitly incorporate moisture and phase changes have been developed only fairly recently. This work merges one of said modeling innovations, namely Smith and Stechmann's \emph{precipitating quasigeostrophic} (PQG) model family, with a triple-deck boundary layer theory due to Klein et al.~that extends the classical QG-Ekman theory by an intermediate \emph{diabatic layer} (DL). A detailed analysis of the Clausius-Clapeyron relation and Kessler-type bulk microphysics closures is included in the systematic derivation of the resulting PQG-DL-Ekman theory. Furthermore, to illustrate some of the model's properties, explicit axisymmetric solutions of the precipitating diabatic layer equations are derived and combined with numerical sample solutions for the bulk flow.

Conceptually different from the decoherence program, we present a novel theoretical approach to macroscopic realism and classical physics within quantum theory. It focuses on the limits of observability of quantum effects of macroscopic objects, i.e., on the required precision of our measurement apparatuses such that quantum phenomena can still be observed. First, we demonstrate that for unrestricted measurement accuracy no classical description is possible for arbitrarily large systems. Then we show for a certain time evolution that under coarse-grained measurements not only macrorealism but even the classical Newtonian laws emerge out of the Schroedinger equation and the projection postulate.