We construct effective $\mathrm{U}(2)$ Chern-Simons-Ginzburg-Landau theories for Abelian and non-Abelian fractional quantum Hall hierarchies for those which had previously been described only through categorical data or trial wavefunctions. Our framework captures both Abelian hierarchy states built on half-filled Pfaffian-type parents and non-Abelian hierarchies emerging from Abelian states. It reproduces all filling fractions obtained from wavefunction and categorical constructions and, moreover, uniquely determines the corresponding topological orders. We also identify an intriguing particle-hole symmetry relating two hierarchy sequences, one built on a trivial insulator and the other on the $ν=1$ integer quantum Hall state, which respectively generate the Read-Rezayi sequences and their particle-hole conjugates under the same hierarchy construction.

We combine the highest resolution N-body simulation of a $\sim 10^{12}\, M_\odot$ $Λ$CDM halo (Aquarius-A) with the {\sc GALFORM} galaxy formation semianalytic model to study the full satellite population expected in a MW-like galaxy. The model assumes that galaxies only form in subhalos whose peak circular velocity exceeds the H-cooling threshold, all of which are well resolved in the simulation. The number of luminous subhalos ever accreted into the main halo is thus well defined, and implies that the total number of MW satellites, down to arbitrarily low luminosity, should not exceed a few hundred. The model tracks satellites even after their halos cease to be resolved ("orphan" galaxies), and includes a novel treatment of dark matter and stellar tidal stripping which takes into account that all $Λ$CDM subhalos survive until the present because of their cuspy inner density profiles. After accounting for tides, our results match well the massive end of the observed MW satellite mass function and predict that a large number of ultra-faint dwarfs are missing from the current MW satellite census. The missing UFDs are predicted to avoid the innermost regions of the host, and to have properties that overlap with those of the many ultra-faint compact MW satellites (UFCSs) discovered recently, with properties intermediate between globular clusters and dwarf galaxies. Our results suggest that many UFCS systems are dark matter-dominated dwarfs with velocity dispersions between $1-3$km/s, which have survived disruption because they reside in the dense cusp of $Λ$CDM subhalos. UFCSs should have mean densities of order $10^{10}$-$10^{11}\,M_\odot/$kpc$^3$, higher than those of more extended ultra-faint systems. If confirmed, our results would provide support for the cuspy nature of $Λ$CDM dark matter halos and for the hydrogen-cooling threshold for galaxy formation.

The Difference-of-Gaussian (DoG) is a widely used operator across applications, including image processing (feature and edge detection), quantum machine learning, and finite-difference methods (approximations of the Laplacian-of-Gaussian). In this paper, we construct an explicit quantum block encoding of the DoG operator on a periodic grid, exploiting its natural probabilistic structure. The central observation is that the DoG admits a natural decomposition to two normalized Gaussian distributions, each preparable by explicit and efficient circuits, with the negation encoded using a single Pauli-$Z$ gate on a branch-indicator qubit. This enables the operator's block encoding to be directly mapped to the Linear Combination of Unitaries framework without requiring signed amplitude loading, quantum random-access memory, or any other black-box oracles. The proposed method achieves a constant subnormalization factor $λ= 2$ independent of the grid size $N$, the spatial dimension $D$, and the stencil width. Additionally, we show that the DoG operator is diagonalized by the discrete Fourier basis, which allows us to derive an exact closed-form expression for the block-encoding success probability in terms of the input signal's power spectrum, weighted by the operator's transfer function. Finally, we prove that the expression reduces to $O(h^4)$ scaling with respect to grid spacing $h$ as the periodic grid becomes finer. This implementation provides an explicit construction method for a tunable, wide-stencil bandpass filter whose frequency response is controlled by two Gaussian scale parameters.

The Optimal Polynomial Intersection (OPI) problem is the following: Given sets $S_1, \ldots, S_m \subseteq \mathbb{F}$ and evaluation points $a_1, \ldots, a_m \in \mathbb{F}$, find a polynomial $Q \in \mathbb{F}[x]$ of degree less than $n$ so that $Q(a_i) \in S_i$ for as many $i \in \{1, 2, \ldots, m\}$ as possible. Decoded Quantum Interferometry (DQI) is a quantum algorithm that efficiently returns good solutions to the problem, even on worst-case instances (Jordan et. al., 2025). The quality of the solutions returned follows a semicircle law, which outperforms known efficient classical algorithms. But does DQI obtain the best possible solutions? That is, are there solutions better than the semicircle law for worst-case OPI instances? Surprisingly, before this work, the best existential results coincide with (and follow from) the best algorithmic results. In this work, we show that there are better solutions for worst-case OPI instances over prime fields. In particular, DQI and the semicircle law are not optimal. For example, when the lists $S_i$ have size $ρp$ for $ρ\sim 1/2$, our results imply the existence of a solution that asymptotically beats the semicircle law whenever $n/m \geq 0.6225$, and we show that an asymptotically perfect solution exists whenever $n/m \geq 0.7496$. Our results generalize to Max-LINSAT problems derived from any Maximum Distance Separable (MDS) code, and to any $ρ\in (0,1)$. The key insight to our improvement is a connection to local leakage resilience of secret sharing schemes. Along the way, we recover several re-proofs of the existence of solutions achieving the semicircle law.

We rigorously prove the bifurcation of slow-moving pattern interfaces with general direction in a two-dimensional Swift-Hohenberg-type model close to a Turing instability for a large class of nonlinearities. These interfaces describe the invasion of stripe and hexagonal patterns into the spatially homogeneous state and model a possible mechanism for pattern formation, as observed in a wide range of real-world applications. For this, we develop a rigorous framework to establish the existence of such solutions using spatial dynamics and non-standard centre manifold theory. Our approach exploits geometric and algebraic structures generic to $\mathrm{O}(2)$-symmetric pattern-forming systems near a Turing instability, and addresses fundamental technical challenges due to a non-uniform spectral gap around the imaginary axis, quadratic resonances induced by the hexagonal structure, and the high-dimensional phase space of the reduced equations.

A basic challenge in experimental physics is the extraction of information related to variables that are not directly measured. The challenge is particularly severe in quantum systems where one may be interested in correlations of operators that are not diagonal in the measurement basis. In this paper we take a step towards addressing this issue in the context of Boson superfluids, where standard in-situ imaging yields only the spatially resolved density, leaving the phase field - crucial for identifying topological defects such as vortices and confirming superfluidity - indirectly encoded. Previous work has shown that the location of vortices in the phase field may be detected, but has not solved the problems of fully reconstructing the phase or identifying the charge (vortex vs. antivortex). This paper shows that a combination of a deep machine learning (ML) model and classical computer vision post-processing steps can address this gap. We use realistic snapshots of the thermal state of a two-dimensional BEC in a harmonic trap using synthetic data obtained from projected Gross-Pitaevskii equation simulations to train a U-Net-based architecture to infer the absolute values of the phase field gradients from an observed density field, and then employ a separate ML model to locate the positions of the vortex cores and a post-processing graphical analysis to determine with high accuracy the phase field, including the quantized charge of each vortex.

Planet formation remains a fundamentally important yet poorly understood process. Protoplanetary disks, the birthplaces of planetary systems, exhibit a wide range of substructures that are increasingly interpreted as signatures of interactions with forming planets. However, the direct detection rate of protoplanets within these disks remains low, leaving critical gaps in our understanding of the physical mechanisms driving their formation and early evolution. In this chapter, we review recent efforts by the high-contrast imaging community to directly observe forming protoplanets and their immediate environments. These observations aim to provide key constraints on thermal and accretion processes, planetary growth, and the formation of circumplanetary disks and satellite systems. We also propose a path forward for deriving observational estimates of the planet mass-to-radius ratio ($M_p/R_p$), a crucial parameter for distinguishing between competing formation models and understanding the thermal evolution of young planets. Finally, we highlight how upcoming instruments on the Extremely Large Telescope (ELT), with their unprecedented combination of high spatial and spectral resolution, will transform our ability to probe planet formation at the smallest and most critical scales.

Lattice compression has emerged as a fundamental tuning parameter for nickelate superconductivity. Pressure acts as a trigger to induce superconductivity in bulk Ruddlesden-Popper nickelates. For infinite-layer nickelate thin films, compressive epitaxial strain and rare-earth ion chemical pressure have been used to substantially enhance the superconducting transition temperature ($T_c$). Efforts to go further have been constrained by the limits of epitaxial stability or the challenges of measuring thin films in high-pressure environments. Here, we overcome this limitation by developing a technique to incorporate freestanding infinite-layer $\mathrm{Nd_{0.85}Sr_{0.15}NiO_2}$ membranes into a diamond anvil cell. Using this platform, we observe a strong increase in $T_c$ up to our highest measurement pressure of $\sim$90 GPa, where a superconducting downturn can be observed near liquid nitrogen temperatures. Strikingly, we find a simple linear enhancement of $T_c$ at a rate of 0.65 K GPa$^{-1}$, with no signs of saturation. This suggests that the pairing strength in infinite-layer nickelates can be raised to a surprisingly high scale, using an approach that can be broadly applied to many two-dimensional materials.

The vertical redistribution of materials in the lunar regolith - ranging from continuously produced space-weathering products to sporadic pulses of supernova- or kilonova-derived isotopes - remains a fundamental problem in planetary science. We present a unified stochastic model of regolith gardening induced by the impact flux. Treating gardening as a competition between impact-driven advection and diffusion predicts the maturity profiles of Apollo cores over more than two orders of magnitude in time ($1.4 \times 10^7$ to $4.5 \times 10^8$ years). This model describes well the depth profiles of live Fe60 in Apollo regolith samples, suggesting that supernova dust capture is independent of native iron abundance, and is consistent with a uniform influx at the latitudes of the Apollo landing sites. We extend our model to predict lunar signals for live r-process species that might originate from supernovae or kilonovae: Pu244 tied to terrestrial detections, and I129, Hf182, and Cm247 based on r-process calculations. The Pu244/Fe60 depth profile can probe the origin of Pu244, motivating searches in Artemis regolith samples down to depths O(100) cm.

Low-mass galaxies with intense starbursts exhibit spectra dominated by extreme nebular emission and faint stellar continua. These extreme emission-line galaxies (EELGs) are key laboratories to study star formation, feedback, and ionizing photon escape in low-metallicity environments. We exploit the DESI survey to assemble the k-Means of Extreme Nebulae from DEsi outLiers (k-MENDEL), a statistically robust sample of ~16,000 EELGs at 0.01 < z < 0.96 selected via automatic k-means classification. Using SED fitting and Te-based metallicities, we characterize EELGs including "blueberry" and "green pea" galaxies, spanning stellar masses of 10^6-10^10 Msun and SFRs of 0.1-100 Msun/yr. k-MENDEL extends previous SDSS samples toward higher redshifts and lower metallicities (12+log(O/H) ~ 7.0-8.5). EELGs lie systematically above the star-forming main sequence, with sSFRs up to ~100 Gyr^-1. They follow a shallower mass-metallicity relation offset by 0.3-0.5 dex from local relations, closely resembling young galaxies observed with JWST at z > 3-10. The large intrinsic metallicity scatter, even after projecting along the fundamental metallicity relation, indicates strong departures from simple "bathtub" models, suggesting massive inflows of metal-poor gas followed by strong feedback. While ~6% of the sample shows AGN-like signatures, the most extreme star-forming systems reach high ionization (O32 ~ 5-60) comparable to confirmed Lyman-continuum emitters. Our results support the interpretation of EELGs as short-lived, non-equilibrium phases in the evolution of low-mass galaxies and highlight their importance as nearby analogs of galaxies likely driving cosmic reionization (Abridged).

Transformers have emerged as the dominant neural-network architecture, achieving state-of-the-art performance in language processing and computer vision. At the core of these models lies the attention mechanism, which requires a nonlinear, non-negative mapping using the Softmax function. However, although Softmax operations account for less than 1% of the total operation count, they can disproportionately bottleneck overall inference latency. Here, we use thin-film lithium niobate (TFLN) Mach-Zehnder modulators (MZMs) as analog nonlinear computational elements to drastically reduce the latency of nonlinear computations. We implement electro-optic alternatives to digital Softmax and Sigmoid, and evaluate their performance in Vision Transformers and Large Language Models. Our system maintains highly competitive accuracy, even under aggressive 4-bit input-output quantization of the analog units. We further characterize system noise at encoding speeds up to 10 GBaud and assess model robustness under various noise conditions. Our findings suggest that TFLN modulators can serve as nonlinear function units within hybrid co-packaged hardware, enabling high-speed and energy-efficient nonlinear computation.

China has undertaken unprecedented, state-driven vegetation restoration on a continental scale. This large-scale land-surface intervention offers a rare opportunity to assess how deliberate biospheric change influences climate-relevant processes, especially the hydrological cycle. Of particular interest is how increased water use by additional vegetation affects terrestrial water availability, including streamflow that sustains both ecosystems and human society. Here we evaluate the methodological basis for addressing this question in light of recently available data on hydrological change in China. Revisiting the atmospheric branch of the hydrological cycle, we argue that water yield depends fundamentally on vegetation-induced changes in atmospheric circulation. When the effects of vegetation on atmospheric dynamics are neglected, as in moisture-recycling-based approaches, the analysis is predisposed by construction toward diagnosing a negative effect of additional vegetation on water yield. Given the nonlinear dependence of precipitation on atmospheric moisture, we further suggest that streamflow reductions associated with added vegetation in dry regions reflects a transient phase of early ecological succession rather than a long-term outcome. As ecosystems mature and regional moisture regimes evolve, this relationship may reverse, generating a positive feedback between vegetation cover and water availability. We briefly discuss recent observational evidence consistent with this interpretation. We conclude that robust assessment of vegetation impacts on water yield requires frameworks that explicitly couple vegetation change, atmospheric processes, and hydrological responses. Such an approach is essential for distinguishing short-term trade-offs from longer-term system trajectories and for informing sustainable land management under continued ecosystem restoration and conservation.

Scaling laws for turbulent thermomagnetic convection of a high-Pr fluid in a square cavity are obtained through direct numerical simulations and formulated via theoretical arguments informed by the numerical data. A regime consistent with an ultimate-like scaling $Nu \sim Ra_m^{1/2} and Re \sim Ra_m^{1/2} emerges after the laminar-to-turbulent transition and persists for more than an order of magnitude. Evidence is provided that this heretofore unseen behavior stems from the ability of the magnetic force to facilitate the ejection and advection of thermal plumes across the fluid bulk.

Super-resolution (SR) techniques based on deep learning have recently emerged as a promising approach to enhance the spatial resolution of computational fluid dynamics simulations while containing computational cost. In this paper, we investigate several SR architectures to improve coarse-grid simulations of mesoscale atmospheric flows, with training data generated from simulations of the weakly compressible Euler equations. We compare a baseline convolutional neural network (CNN), an attention-enhanced CNN, a multi-scale CNN designed to capture flow structures across different spatial scales, and a diffusion-based SR model. The methods are evaluated on two standard atmospheric benchmarks: the rising thermal bubble and the density current. Results show that the baseline CNN can accurately reconstruct simpler flow features, while more complex flows require multi-scale architectures. Overall, SR based on the multi-scale CNN provides the best balance of accuracy, robustness, and computational efficiency, outperforming even a state-of-the-art diffusion-based approach. We also analyze the sensitivity of the models to the size of the training dataset, highlighting limitations and trade-offs of the proposed SR strategies.

We study the superconducting diode effect (SDE) in a diffusive superconductor - normal metal (SN) bilayer subjected to an in-plane magnetic field. The supercurrent flows along the layers, perpendicular to the field. The SDE, manifested as an asymmetry in the critical (depairing) currents and kinetic inductance for opposite current directions, arises from an orbital mechanism due to the inhomogeneous distribution of the Meissner currents caused by a spatially varying superfluid density. Recently, Levichev et al. [Phys. Rev. B 108, 094517 (2023)] demonstrated the realization of this effect in such a structure, supporting numerical calculations for an ideal interface with an experiment. In this work, we investigate the influence of a nonideal interface with finite resistance on the SDE. Employing an analytical approach, we focus on limiting cases corresponding to weak intralayer inhomogeneities. We find that the strength of the SDE depends nonmonotonically on the interface resistance when the bilayer thickness is small compared to the coherence length. Remarkably, a nonideal interface can enhance the SDE compared to the ideal case.

We classify superfusion categories describing two-dimensional fermionic systems equipped with the universal fermion-parity symmetry, implemented by a topological defect line (TDL) $Z$, and an additional $\mathbb{Z}_2$ flavor symmetry generated by a $W$ TDL. Depending on whether $W$ is m-type or q-type, its fusion rules lead to three distinct classes, and solving the super-pentagon equations yields 16 consistent superfusion categories. These are labeled by invariants $(ν_W,ν_Z,ν_{WZ})$, which determine the $\mathbb{Z}_8$ anomaly classes of the symmetries generated by $W$, $Z$, and $WZ$. We also provide explicit realizations using multiple Majorana fermions and comment on implications for fermionic CFTs and gapped phases.

Lie-Poisson classical field theory is a field-theoretical model embedded in a non-commutative structure related to the framework of Poisson electrodynamics. In this paper, we follow the recently developed action principle for Lie-Poisson electrodynamics to derive the conservation laws of the theory. The energy-momentum tensor is obtained, along with the conserved electric charge and the momentum operator. We consider non-interacting examples for real and complex scalar fields, as well as the Dirac field, within the $κ$-Minkowski spacetime framework. In the latter case, we show that the non-relativistic limit for the $κ$-Minkowski Dirac equation introduces an orbital Zeeman coupling term for the fermionic fields, and the energy shift in the first excited state depends exclusively on the $κ$-parameter.

We show how equivariant localization can be used to compute the on-shell action for supersymmetric $D=5$ $AdS$ rotating, charged black holes in theories of supergravity with higher derivatives. An exact match with a dual field theory computation of the superconformal index in a Cardy-like limit is achieved.

The Wide-field Spectroscopic Telescope (WST) is a proposed 12-meter segmented facility optimized for seeing limited observations in the visible and designed to operate both a high-multiplex multi-object spectrograph and a panoramic integral field spectrograph (IFS). The WST IFS concept builds on instruments such as MUSE at the VLT (Very Large Telescope), using field splitters and image slicers to reformat a large field into pseudo-slits feeding spectrographs with two optimized spectral channels. This paper presents the spectrograph architecture developed for the WST IFS, aiming to achieve high through put and image quality over a wide wavelength range in a cost-effective manner. We investigate the use of curved detectors as a means to simplify the spectrograph layout, reduce aberrations, and potentially improve efficiency. This study establishes a promising baseline for the IFS spectrographs and assesses the benefits of incorporating curved sensors that can guide the development of future large-scale integral field spectrographs.

We introduce a three-dimensional model for polyelectrolyte hydrogel filaments operating in a fluid environment under an electric field. The formulation builds on a morphoelastic framework for inextensible and unshearable rods, such that the filament's activity is encoded in electric-field-induced spontaneous curvatures, while hydrodynamic interactions are captured via a local approximation of Stokes flows. We employ this framework to investigate the prototypical case of a filament with elliptic cross-section clamped at its base. Under a constant and uniform electric field aligned with its axis, the filament undergoes flutter instability beyond a critical field strength, as revealed by a linear stability analysis. Depending on the model parameters, the instability is characterized by either two- or three-dimensional self-sustained oscillations. We further examine this behaviour through numerical simulations in the post-critical regime, showing that flutter may develop into large amplitude planar oscillations or more complex three-dimensional motions, through a secondary bifurcation. Although the study represents a first step towards extending state-of-the-art models for polyelectrolyte hydrogel filaments to three dimensions, the richness of the resulting dynamics achievable under time-independent forcing underscores the potential of the proposed actuation mechanism for the design of biomimetic cilia and soft robotic systems.

We study theoretical uncertainties in predicting top-quark pair-production near threshold at the LHC using the non-relativistic QCD framework. We include variations in the top-quark mass and width, the strong coupling $α_s$, renormalization and factorization scales, and parton distribution functions, as well as uncertainties from the color-singlet and octet Green's functions that describe quasi-bound toponium formation. These uncertainties are compared with those from standard fixed-order QCD predictions, and implications for ATLAS and CMS analyses are discussed. For the LHC at 13 TeV center-of-mass energy, the integral of the top-quark pair invariant-mass distribution from 340 to 350 GeV is 11.67 pb with ${}^{+1.43}_{-1.47}$ pb uncertainty. The corresponding excess after subtracting the POWHEG-BOX result is 4.15 pb with the same uncertainties.

Resolving degenerate quantum eigenspaces - including topologically ordered ground states and frustrated magnets - requires preparing high-fidelity states that span every direction of the target manifold. Existing variational and projective algorithms do not naturally cover a multi-dimensional degenerate subspace without sequential orthogonality constraints. We introduce the quantum randomized subspace iteration (QRSI), a fully parallel construction that conjugates the Hamiltonian by independent random unitaries across as many branches as the degeneracy g, then invokes any chosen eigenstate-preparation primitive on each branch. The target subspace is identified from the resulting ensemble via standard subspace estimation, either classically through the coefficient matrix or on hardware through Gram-matrix measurements. We prove that the construction spans the full eigenspace almost surely and preserves the spectral gap exactly on every branch. For practical use, we show that these guarantees hold whenever the random rotations satisfy an anti-concentration condition over the degenerate manifold, substantially weaker than full Haar randomness. We demonstrate QRSI on the toric code, recovering all four topological ground states, and on random Hamiltonians with planted degeneracies.

Characterization of the trap rf induced a.c. Zeeman shift is essential for achieving high accuracy in optical ion clocks. In this work, we demonstrate the experimental characterization of this shift using highly charged $\mathrm{Ca}^{14+}$. The transverse component of the a.c. magnetic field is measured using the Autler-Townes splitting of the equally-spaced Zeeman components of the $^{3}\mathrm{P}_1$ when the Zeeman splitting is close to resonance with the trap rf drive frequency. We observe the resulting modulation by performing quantum logic spectroscopy using the co-trapped $\mathrm{Be}^{+}$. The longitudinal component is measured from probing the $\mathrm{Be}^{+}$ magnetic field-insensitive hyperfine transition $|F=2,m_F=0 \rangle \rightarrow | F=1,m_F=0 \rangle$. We confirm the small influence of the a.c. Zeeman shift in highly charged ions. The employed techniques can easily be transferred to other multi-level atomic systems.

Low-frequency charge noise induced by fluctuating electrostatic disorder is a major limitation for semiconductor hole spin qubits. Here, we analyze the quasistatic response of a hole spin qubit to individual two-level fluctuators (TLFs). We show that, due to the anisotropy of the g-tensor, the qubit response depends on the geometry of the fluctuator-induced dipolar perturbation. We then propose a readout protocol that isolates selected g-tensor components through an accumulated Berry phase and estimate, within our readout model, an order-unity signal-to-noise ratio with a total protocol time in the tens of microseconds. Finally, using microscopic simulations, we compute the quantum Fisher information (QFI) to identify magnetic field directions and confinement regimes in which the qubit is most sensitive to disorder-induced variations of selected g-tensor components.

We investigate the static spherically symmetric vacuum solutions in a generalized bumblebee gravity model characterized by non-minimal couplings $B^2 R$ and $B^μB^νR_{μν}$. We demonstrate that the variation of the action and the imposition of the vacuum expectation value constraint are non-commutative, leading to a richer solution space than previously explored. A diverse set of solutions, including naked singularities, black holes, and wormholes, is obtained, and as many as ten exact solutions are presented. The thermodynamic properties of the new black hole solutions are also analyzed, and a subset of these solutions is found to have zero entropy. We argue that if such a non-minimally coupled vector-tensor gravity provides a fundamental description of the universe, it is best described by a Bumblebee-type theory, where the vector field acquires a VEV.

We study time-domain electron interferometry in a Hong-Ou-Mandel (HOM) geometry, where a thin superconductor between two quantum Hall systems acts as the beam splitter. By comparing the measurable current cross correlations at the interferometer outputs with those of a normal-conducting electronic HOM setup, we show that Andreev processes strongly affect the HOM dip. Using a combination of scattering theory and numerical tight-binding simulations for a graphene quantum Hall bar, we show that the change of charge cross correlations can be used to experimentally detect and characterize local and crossed Andreev processes.

Nonlocal games provide a unified framework for studying the distinction between classical, quantum, and more general no-signaling correlations. In this work, we develop this perspective by connecting the Bell-locality framework to several complementary mathematical representations of nonlocal games and quantum strategies. We begin with local hidden-variable models, the CHSH inequality, and the role of Bell nonlocality as a device-independent witness of entanglement, and then introduce nonlocal games through the standard predicate/verifier formalism. We next examine a set of representative examples, including XOR games, the GHZ game, graph-based coloring games, the Mermin-Peres magic square game, and Hardy's paradox as a related logical manifestation of nonlocality. Building on this foundation, we compare four closely related representation frameworks: conditional-probability and correlation descriptions, Bell-functional formulations, entangled-value optimization, and the quantum-operator approach together with the Navascues-Pironio-Acin (NPA) hierarchy. These viewpoints are then instantiated for the CHSH, magic square, and GHZ games, showing how each representation emphasizes a different aspect of the same underlying task. Taken together, these examples show that nonlocal games can be studied simultaneously as geometric objects in correlation space, optimization problems over entangled resources, and operator-theoretic constructions. This multi-representation viewpoint clarifies the relation between Bell inequality violations, perfect quantum strategies, pseudo-telepathy, and semidefinite relaxations of quantum correlations.

Altermagnetism generates exchange-type spin splitting without net magnetization and, in its $\it d$-wave form, resembles the angular symmetry of unconventional $\it d$-wave superconductivity. Whether this correspondence bears directly on superconducting instabilities in real correlated materials remains open. Here we study the quasi-two-dimensional vanadium oxychalcogenide CsV$_2$Se$_2$O (CVSO), a square-net $\it d$-wave altermagnet candidate, through combined experimental and theoretical investigation of its lattice structure, electronic structure and transport properties. At ambient pressure, CVSO is a weakly insulating parent state with a density-wave-like anomaly near 100 K, and its bulk properties are most consistent with a G-type compensated antiferromagnetic background. Under compression, the density-wave-like feature is suppressed, the magnetoresistance evolves from predominantly negative to positive, and a superconducting-like resistive downturn emerges below about 3 K. This low-temperature anomaly is reproducible across samples and pressure media, and is suppressed by magnetic field. Room-temperature X-ray diffraction reveals no symmetry lowering, whereas does show a pronounced compressibility anomaly over the same pressure range. CVSO thus reveals a pressure-tuned phase diagram in which a reconstructed weakly insulating parent state gives way to strange-metal-like transport and superconducting-like behavior, echoing broader phenomenology associated with unconventional superconductors, including cuprates and nickelates.

We compute the quantum radiation emitted by wavepackets of relativistic single electrons, both at rest and undergoing uniform acceleration in the Minkowski vacuum of the electromagnetic field. We find that the cubic terms in the original nonlinear action of electrodynamics should be considered in obtaining the quantum radiation to the leading order. We show that the quantum radiation from a single-electron wavepacket at rest vanishes exactly. For a uniformly accelerated electron, the quantum radiated power has secular growth in the long-time regime. We demonstrate that this secular growth has a classical interpretation, and argue that the resummed quantum radiation at late times would not diverge. Regarding experimental proposals for the detection of the Unruh effect from the quantum radiation in the `blind spots' of classical radiation we ascertain that quantum corrections in the two blind spots are fully contributed by the transverse deviation correlators, where the dominant contributions are irrelevant to the Unruh effect in electron microscopes.

We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS) databases spanning friction Reynolds numbers $Re_τ=$ 2000--12000, we infer the eddy viscosity from one-point statistics through the Boussinesq relation. The DNS-inferred eddy viscosity displays configuration-dependent behavior in the outer region, indicating that a single full-depth expression is not uniformly accurate for all three configurations. Building on the interpretation of eddy viscosity as the product of a velocity scale and a length scale, we extend the log-law scaling into the outer region. Specifically, we adopt a stress-based velocity scale and introduce an outer correction function to capture the remaining dependence on the outer coordinate. We then embed a compact parametric form of this correction into a Cess-type framework with van Driest near-wall damping, yielding a full-depth eddy-viscosity model. We assess the model using eddy-viscosity profiles, the log-law indicator function, and skin friction. The results show that the proposed model yields noticeable improvement for open-channel flow while remaining comparable to the classical Cess model for closed-channel flow and pipe flow. These findings underscore the role of outer boundary conditions in shaping the outer-region eddy viscosity and, consequently, mean-flow predictions.