In this study we adapt a classical cosmology measurement, the volume or number density test, to a modern synthesis of observed galaxy evolution. We do this by using measured galaxy mass functions and the history of galaxy evolution through star formation and galaxy mergers, inspired by the latest results from deep extragalactic surveys. We develop a new framework using measured galaxy volume number densities as a function of redshift and volume to determine cosmological parameters, especially those which alter the volume of the Universe at a given redshift. Whilst this is a classic cosmology test proposed since at least the 1930s, it has largely been abandoned for decades due to uncertainties in galaxy evolution which make it difficult to trace galaxy populations through time. However, recent advances in our understanding of star formation and the merging history of galaxies allow us to revise this method to uncover and measure cosmological parameters, especially those which involve the nature of dark energy. We present a modified version of the volume test, called the revised evolutionary volume Tolman test, using properties of known galaxy evolution as part of the cosmological calculation. We show how this method can successfully be applied and is competitive with other major cosmological measurement methods, including those using supernova and the CMB, when the merger and star formation histories can be measured accurately to between 1 to 10 percent. This accuracy is not yet achievable, but we discuss how future missions will allow these astrophysical quantities to be known at this level. Within this measurement accuracy we can measure the dynamical properties of dark energy, including its evolution through its equation of state. We also give a fuller accounting of the future use of this new method with upcoming galaxy surveys such as Euclid and LSST/Rubin.

Benchmarks for large language models (LLMs) have progressed from snippet-level function generation to repository-level issue resolution, yet they overwhelmingly target implementation correctness. Software architecture tasks remain under-specified and difficult to compare across models, despite their central role in maintaining and evolving complex systems. We present ArchBench, the first unified platform for benchmarking LLM capabilities on software architecture tasks. ArchBench provides a command-line tool with a standardized pipeline for dataset download, inference with trajectory logging, and automated evaluation, alongside a public web interface with an interactive leaderboard. The platform is built around a plugin architecture where each task is a self-contained module, making it straightforward for the community to contribute new architectural tasks and evaluation results. We use the term LLMs broadly to encompass generative AI (GenAI) solutions for software engineering, including both standalone models and LLM-based coding agents equipped with tools. Both the CLI tool and the web platform are openly available to support reproducible research and community-driven growth of architectural benchmarking.

One-dimensional crystals serve as a versatile platform for engineering nontrivial states, which can be easily explored in transport configurations. In this work, we analyze the properties of a periodic structure composed of an H-shaped unit cell, which forms a periodic ladder-shaped system. Using tight-binding models, group-theoretical considerations, and standard band topology, we uncover the influence of bound states in the continuum (BICs) and quasi-BICs formed in the original finite geometry on the creation of nontrivial band states. By designing various textures for the onsite energies, we discovered a topological band inversion between quasi-BIC-induced bands, leading to the emergence of topologically protected edge states that are characterized by a quantized Zak phase. Additionally, we found an on-site configuration that exhibits robust flat bands, induced by a symmetry-protected BIC and linked to special one-sided localized edge states. We present a detailed analysis of the mechanisms driving both effects and discuss the crucial role of symmetry in characterizing the topological phases of these systems.

Transmission matrices are valuable tools to describe and control light transport through scattering media. There are only a few cases where the transmission matrix can be compared to microscopic theories. Here we measure the polarization-complete transmission matrix of a single dielectric sphere using off-axis holography with angle scanning and reconstruct complex fields in both transmission and reflection under circular polarization. After aberration correction and angular mapping, the scattering amplitude extracted from the transmission matrix closely follows Mie theory. This work provides a calibrated benchmark for angle-resolved transmission matrix measurement and enables quantitative characterization of spherical and quasi-spherical scatterers.

Alternate bases are a numeration system that generalizes the Rényi numeration system. It is common in this context to construct examples or counter-examples by specifying the expansions of $1$ in the desired system. While it is easy to show when a system with given expansions of $1$ exists in the Rényi case, the same is not true in the alternate case. In this article, we establish conditions for given words to be the expansions of $1$ in the alternate case. To do so, we use a fixed point theorem on matrices defined from the expansions and obtain the elements of the base from the components of the fixed point. We also obtain a partial result for the uniqueness of such a base. In the latter parts of the article, we use similar techniques to prove the existence of bases with a given sequence of $B$-integers.

This thesis investigates the magnetic, spectral, and transport properties of strongly correlated electronic systems, with a primary focus on the Hubbard model and its extensions relevant for real materials. Within the dynamical mean-field theory (DMFT) framework, different regimes of interaction strength, temperature, doping, and magnetic field are explored, highlighting the central role of local electronic correlations in shaping spectral reconstruction and nontrivial transport responses. For the antiferromagnetic Hubbard model under a Zeeman field, magnetoresistance and local metamagnetism are characterized, revealing the coexistence of distinct energy scales associated with charge and spin degrees of freedom. A minimal, purely correlation-driven mechanism for generating spin-polarized charge transport in structurally conventional collinear antiferromagnets is identified, controlled by the simultaneous breaking of particle--hole symmetry and antiferromagnetic sublattice equivalence. Finally, these concepts are applied to correlated materials with strong spin--orbit coupling, such as Sr$_2$IrO$_4$ and Sr$_3$Ir$_2$O$_7$, and to nanoparticle solids dominated by Coulomb blockade and disorder. The results show how ideas developed in correlated lattice models provide a unified interpretation of metal--insulator transitions and spectral reconstruction in complex systems.

The aim of this paper is to provide a comparison of channel characteristics for vehicle-to-vehicle (V2V) communication at 60 GHz and 80 GHz frequency bands in a high-mobility scenario where two vehicles pass each other in opposite directions. The study is based on measurements of the time-varying channel impulse response capturing the behavior of multi-path propagation during vehicle motion. By directly comparing these two frequency bands under identical measurement conditions, we attempt to quantify the differences in power delay profile, root mean square (RMS) delay spread, RMS Doppler spread, and intervals (regions) of stationarity in time domain. The results show that these bands do not differ significantly, but the 80 GHz band exhibits somewhat greater RMS delay spread and RMS Doppler spread when calculated over the entire delay-Doppler spectrum, and conversely exhibits shorter stationarity regions. However, the characteristics of the measurement setup in the two bands and their influence on comparative measurements must be considered. In particular, attention must be paid to the impact of antennas.

To treat a problem with a Quantum Processing Unit (QPU), it must be transformed into a sequence of quantum operations, or gates: this is the quantum description of the problem. These operations are either packed into a query (i.e. quantum algorithm primitive) that encodes the problem, or used to construct the cost function for Variationnal Quantum Algorithm (VQA). Typical queries are the problem Hamiltonian Simulation (HS) and the problem Block-Encoding (BE). To construct the circuits associated with the quantum description, the problem must be mapped as a Linear Combination of Hermitian (LCH) or a Linear Combination of Unitary (LCU) matrices. All the summed Hamiltonian matrices or unitary matrices must have a known decomposition in basic gates. The complexity of this query should be incorporated into the quantum algorithm's query complexity, thereby limiting the processing possibilities of QPU for many problems. Qubitization constructs a specific query that respects single-qubit behavior when expressed in the appropriate basis. In this work, we extend the notion of qubitization to Hamiltonian matrices used to map the problem of interest. These methods concern almost all the problems implemented on QPUs: from second-quantization chemistry operators to graphs associated with Partial Differential Equations (PDE), or sparse matrices. This work underlines interesting properties associated with the qubitized Hamiltonian basic gate decomposition. It includes the ability to switch from LCH to LCU, to map non-Hermitian problems, and to construct the different quantum circuit primitives (queries) needed for the quantum description of the problem. We also provide a list of qubitized Hamiltonians that are used for the matrix decomposition of many structured matrices. These structured matrices are associated with graph adjacency matrices that can be combined to implement structured matrices.

Conventional polarization detection relies on external filters, which incur significant efficiency loss and polarization crosstalk, especially in the deep ultraviolet band where subwavelength nanofabrication is challenging. Here, we report that monoclinic \b{eta}-Ga2O3 exhibits intrinsic giant polarization dichroism, allowing near-ideal polarization photodetection without external optical elements and coherent polarization-division multiplexing (PDM) capability. The giant dichroism originates from the crystallographic symmetry-driven selectivity of optical transitions, which, combined with a large valence band splitting, results in vastly distinct absorption for orthogonal polarizations. A theoretical analysis of the transition selection rules in \b{eta}-Ga2O3 reveals only the E//c-polarized vb1-to-conduction band transition is activated, within the 245-258 nm spectral window. An admirable polarization ratio surpassing 500 and a polarization crosstalk ratio below 0.2% is hence achieved. The polarization-sensitive photodetector exhibits a high responsivity of 73 A/W and fast response (20 ms). Furthermore, we showcase its practical utility in PDM free-space communication, successfully decoding encoded optical signals, and demonstrate its capability for high-fidelity Stokes vector retrieval. The intrinsic anisotropy of \b{eta}-Ga2O3, dictated by its crystal symmetry, lays the groundwork for filter-free, high-fidelity polarization polarimetry. This work further paves the way for a general design principle in next-generation optoelectronics that harness polarization transition selection rules.

We prove localization (near the bottom of the spectrum) for certain non-stationary variants of the Anderson model in three dimensions. More specifically, we prove a Wegner estimate, which implies localization by existing work. Two key inputs are a deterministic quantitative unique continuation theorem by Li and Zhang [Duke Math. J. 171(2): 327-415, 2022] and some combinatorial decompositions/bounds for non-stationary random potentials proved by the author [Commun. Math. Phys. 407:64, 2026].

We investigate the phase diagram and critical properties of a one-dimensional $\mathbb{Z}_{2}$ lattice gauge theory describing an orthogonal metal, where spinless fermions and Ising spins are minimally coupled to a deconfined $\mathbb{Z}_{2}$ gauge field. Working at half-filling of fermions, we derive an exact gauge-invariant formulation that maps the model onto decoupled XXZ and transverse-field Ising chains. This mapping enables a controlled low-energy field-theory description in terms of a perturbed Luttinger liquid and Ising conformal field theories. Combining analytical arguments with numerical simulations, we determine the full phase diagram and identify various critical and multi-critical regimes. Along a specific multi-critical line, where the fermionic and bosonic velocities coincide, we find strong evidence for an emergent superconformal symmetry. Our results establish a minimal lattice realization of emergent superconformal criticalities in a gauge-matter system and provide a route toward its exploration in quantum simulators.

Value-based approaches such as Value Sensitive Design (VSD) enable technology designers to engage with and integrate human values in technology through a tripartite methodology of conceptual, empirical, and technical investigations. However, VSD contains pitfalls in both translating values to requirements and a lack of normative grounding, leading to adaptations such as Jacobs' Capability Sensitive Design (CSD). Inspired by CSD and extensions of the design approach, we propose the concept of creating -Sensitive Design (-SD); a meta-framework to embed various political or ideological values as norms in a design research process. We exemplify this through \emph{Dependency}-Sensitive Design (DSD), combining ideas from Kittay's critiques of classical liberal theory within a practical VSD framework. Finally, we push for further work combining philosophy and design in areas beyond CSD and DSD.

In this work, recent results on the moments of balanced Pólya urns are generalized to unbalanced urns, with the condition that the expected change in total activity at each step is constant. We also provide applications of our results to the degree distributions of random trees grown by uniform attachment with freezing and to the degree distribution of hooking networks; in both cases we prove a normal limit law with convergence of all moments.

The key-value (KV) cache has become the dominant contributor to memory consumption in large language model (LLM) inference. Although offloading KVCache from GPU high-bandwidth memory (HBM) to CPU DRAM alleviates device memory pressure, DRAM remains capacity-limited and costly for large, persistent workloads. Solid-state drives (SSDs) provide a cost-effective alternative, but naive SSD-based paging is fundamentally bandwidth-bound due to limited PCIe throughput and per-device bandwidth constraints. In this paper, we observe that KVCache activations in real-world workloads exhibit strong and stable correlations. We term this phenomenon KVCache Co-Activation, where accessing a KV entry is often accompanied by a stable and recurring set of other KV entries. Leveraging this property, we present Swarm, an SSD-based KVCache offloading system that converts bandwidth-bound single-device access into parallel I/O across multiple SSDs. Specifically, Swarm clusters co-activated KV entries offline and distributes the resulting clusters across SSDs using graph-based placement with selective replication to maximize parallel I/O bandwidth. At runtime, Swarm performs load-balanced cluster retrieval and dynamically adapts clustering and caching decisions to sustain high bandwidth utilization under evolving access patterns. Evaluations show that Swarm reduces I/O time by 2.41x and improves effective bandwidth utilization by 2.72x.

This paper presents a unified decision-making framework that integrates Hybrid Markov Decision Processes (HMDPs) with Model Predictive Control (MPC), augmented by velocity-dependent safety margins and a prediction-aware hysteresis mechanism. Both the ego and surrounding vehicles are modeled as HMDPs, allowing discrete maneuver transition and kinematic evolution to be jointly considered within the MPC optimization. Safety margins derived from the Intelligent Driver Model (IDM) adapt to traffic context but vary with speed, which can cause oscillatory decisions and velocity fluctuations. To mitigate this, we propose a frozen-release hysteresis mechanism with distinct trigger and release thresholds, effectively enlarging the reaction buffer and suppressing oscillations. Decision continuity is further safeguarded by a two-layer recovery scheme: a global bounded relaxation tied to IDM margins and a deterministic fallback policy. The framework is evaluated through a case study, an ablation against a no-hysteresis baseline, and largescale randomized experiments across 18 traffic settings. Across 8,050 trials, it achieves a collision rate of only 0.05%, with 98.77% of decisions resolved by nominal MPC and minimal reliance on relaxation or fallback. These results demonstrate the robustness and adaptability of the proposed decision-making framework in heterogeneous traffic conditions.

In this work, we simulate the spectral emissivity of various stoichiometric crystal phases of Mo$_x$Si$_y$ compounds using density functional perturbation theory. The dielectric function, including electronic and ionic contributions, is calculated for each phase. We use the bulk properties obtained to simulate the optical absorption spectrum originating from the compound in thin film ($\sim$20 nm) form. We find that most thin films of Mo$_x$Si$_y$ are metallic, however, our results indicate that their emissivity is not simply correlated with the Mo content. For hot metallic films at around 900 K, we predict a maximal emissivity between 5-10 nm thickness. Our results are in good qualitative agreement with experiments, confirming that the emissivity of hexagonal MoSi$_2$ is much lower than in the tetragonal phase. This is related to the small band gap (hexagonal MoSi$_2$) and low density of states at the Fermi level (tetragonal MoSi$_2$). Furthermore, test calculations on defected MoSi$_2$ demonstrate that the infrared emissivity of MoSi$_2$ thin films can be substantially increased by introducing defects.

The growing adoption of RISC-V in high-performance and scientific computing has increased the need for performance-portable code targeting the RISC-V Vector (RVV) extension. However, current compiler infrastructures provide limited end-to-end support for generating optimized RVV code from high-level representations to low-level implementations. In particular, existing MLIR distributions lack practical lowering paths that map high-level abstractions to RVV intrinsics, limiting their applicability for production-ready RISC-V kernels. This paper presents a compilation approach that combines MLIR with xDSL to bridge the missing lowering stages required for RVV code generation. Using custom intermediate representations and transformation passes implemented in xDSL, we systematically translate high-level operations into specialized, hardware-aware C code invoking RVV intrinsics. The resulting kernels are emitted as portable C functions that can be directly integrated into existing applications, enabling incremental adoption without modifying surrounding software stacks. We demonstrate the approach on the General Matrix Multiplication (GEMM) kernel and evaluate the generated micro-kernels on two real RISC-V platforms, the K230 and the BananaPi F3, comparing against OpenBLAS for both square-matrix benchmarks and transformer-based workloads derived from the BERT-Large model. When integrated into a matrix multiplication kernel, the proposed approach consistently outperforms OpenBLAS, reaching up to 12.2 GFLOPS compared to the baseline's 5.1 GFLOPS and providing performance improvements between 10--35\% across the evaluated workloads. These results demonstrate that combining MLIR with xDSL provides a practical pathway to portable, optimized code generation for RISC-V platforms.

Residual foreground contamination in thermal Sunyaev-Zeldovich (SZ) Compton-$y$ parameter maps ($y$-maps) arises mainly from Galactic emissions -- thermal dust and synchrotron radiation -- on large angular scales, and from cosmic infrared background (CIB) anisotropies on small scales. Unlike the thermal SZ effect, Galactic foregrounds are strongly polarized. Exploiting this distinction, we introduce a hybrid Needlet Internal Linear Combination (Hybrid NILC) method that combines Planck total-intensity and polarization frequency maps in the component-separation pipeline, thereby improving the suppression of residual Galactic emission while preserving the unpolarized SZ signal by leveraging the intrinsic $TE$ and $TB$ correlations of thermal dust and synchrotron. Using Planck PR4 data, we find that the Hybrid NILC $y$-map exhibits about $40\,\%$ lower cross-correlation with the IRAS dust tracer than the standard temperature-only Planck $y$-map, indicating reduced residual Galactic contamination. Simulations further indicate that, for future high-sensitivity surveys such as LiteBIRD, the Hybrid NILC will become increasingly effective at suppressing Galactic residuals. We further address small-scale extragalactic contamination by selectively deprojecting specific moments of the CIB using a Constrained Hybrid NILC variant, achieving an improved balance between CIB suppression and noise penalty compared to previous implementations in the literature. These novel approaches -- particularly the joint use of temperature and polarization in component separation -- offer a powerful framework for disentangling polarized and unpolarized signals.

The control of active colloidal particles via optical traps is a cornerstone for research of matter at the micron and nanometer scale. A central challenge in this domain is the derivation of optimal transport protocols that minimize the mean work required to move a particle over a finite-time interval. Here we present a Ritz method in which open-loop protocols are constructed from a global basis of Chebyshev polynomials and optimised by a genetic algorithm. We apply the method to study optimal transport of an active particle, which is modelled as a force-dipole (or a stresslet) near a no-slip wall. The methodology is validated in the limits of zero activity and infinite wall separation, where it successfully recovers the known analytical protocols and the theoretical minimum work. Crucially, we demonstrate that the presence of the boundary breaks the time-reversal symmetry of the optimal protocol found in bulk solutions. This symmetry breaking is shown to be a complex function of the transport direction and the particle's intrinsic activity. Because the presented approach requires only the capability to simulate stochastic trajectories, it offers a robust, principled framework for optimizing transport protocols in complex fluid environments that remain inaccessible to exact analytical treatment.

Background: Neutron-rich nucleus $^{44}$S lies in the region where traditional $N=28$ shell closure weakens, leading to the emergence of shape coexistence and large-amplitude collective motion (LACM). Understanding the nature and degree of shape mixing in this nucleus remains an important and fascinating problem. Purpose: We investigate the manifestation of shape fluctuations in $^{44}$S and examine how the electric transitions and the spectroscopic factors from one-neutron knockout reactions can serve as probes of shapes mixing. Method: The antisymmetrized molecular dynamics combined with the generator coordinate method (AMD+GCM) is used to study the structure of $^{44}$S and $^{43}$S. Calculations are performed by using Gogny effective interactions with two different parameter sets, D1S and D1M, to explore the interaction dependence of shape mixing. Monopole and quadrupole transition strengths and spectroscopic factors are evaluated. The cross sections for the $^{44}$S$(p,pn)^{43}$S reaction are calculated within the distorted wave impulse approximation (DWIA). Results: The calculations reveal a strong interaction dependence of shape fluctuation in $^{44}$S. The structural differences obtained from D1S and D1M interactions produce distinct patterns of the electric transitions, the spectroscopic factors, and the cross sections for $^{44}$S$(p,pn)^{43}$S knockout reaction. Conclusion: The population of $3/2^-$ and $7/2^-$ states of $^{43}$S is particularly sensitive to the underlying shape fluctuation in $^{44}$S. Thus, the measurement of $^{44}$S$(p,pn)^{43}$S reaction can provide a direct experimental probe.

We formulate a relativistic hydrodynamic theory for fluids with spin and intrinsic dilation charges. Using an entropy-current analysis, we derive constitutive relations featuring a bulk viscosity and a dilation conductivity governing the relaxation and diffusion of dilation charge. Linear mode analysis reveals a gapped dilation excitation and the freeze-out of long-wavelength sound modes, similar to the superhorizon modes in cosmology. In the nonrelativistic limit, the theory reduces to that of microstretch fluids. Upon coupling to electromagnetic field, we show that the scale anomaly permits additional contributions in the electric current, dilation current, and energy-momentum tensor. Our theory naturally applies to nearly conformal fluids undergoing rapid expansion or contraction.

Deep in the Earth's crust, pressure exceeds one thousand times the atmospheric pressure. Water still flows under these conditions, but experiences dramatic changes in structure and fluidity. Using combined dynamic and inelastic light scattering techniques, we simultaneously measure the shear and bulk viscosities of water as a function of pressure. The former increases faster than the latter, so that their ratio shows a two-fold decrease from 0 to 1.6 GPa; we confirm this trend with simulations. We analyze our results in terms of the structural relaxation time $τ$. Contrary to other liquids, pressure initially accelerates relaxation in water. Our measurements reveal that $τ$ reaches a minimum close to 1 ps around 0.5 GPa. We interpret $τ$ as a the equilibration time of hydrogen bonds, and propose that the minimum in $τ$ arises from a structural anomaly which allows fastest interconversion between local structures in water, and generates a cascade of thermodynamic and dynamic anomalies.

The purpose of this paper is to describe and extend the use of the newly-introduced measure, residual estimation risk. Following the seminal work of Bignozzi and Tsanakas, the quantification of residual estimation risk is proposed in a multivariate framework. Our aim is to provide a succinct and practical introduction to the concept, to motivate its use as a back-testing measure, and to provide examples related to credit risk parameter estimation. In section 2, we introduce residual estimation risk defined by various risk measures, and illustrate the calculation using R and SAS. In section 3, we propose a back-testing criterion for the measure, which can be altered to assess model performance for both accuracy and conservatism. In section 4, we conduct back-testing on risk parameter estimates of retail credit portfolios, including multiple back-testing measures for comparison. Finally, we conclude our findings and propose areas for future work in section 5.

The size of gluon occupancies, or equivalently the nuclear gluon TMD, at gluon transverse momentum $k_\perp \le Q_s(Y)$ is evaluated. Without Sudakov corrections the occupations can become arbitrarily large while Sudakov effects lead to maximum occupancies of size $(1/α)^{3/2}$. Results are the same for running coupling and fixed coupling dynamics. The coherent (elastic) TMD and inelastic gluon TMD are the same in the gluon saturation region. The saturated gluons in the light cone wavefunction seem to have little or no interaction among themselves.

The essential requirement for a cubic graph to be called a snark is that it can not be edge-coloured with three colours. To avoid trivial cases, varying restrictions on the connectivity are imposed. Snarks are not only interesting in themselves, but also a valuable test field for conjectures about graphs that are not snarks and sometimes not even cubic. For many important open problems in graph theory it is proven that minimal counterexamples would be snarks. We give two new algorithms for the generation of snarks and results of computer programs implementing these algorithms. One algorithm is for snarks with girth exactly 4 and is used for generating complete lists of girth 4 snarks on up to 40 vertices. The second algorithm lists snarks with girth at least 5 and is used for generating complete lists of such snarks on up to 38 vertices. We also give complete lists of strong snarks (in the terminology of Jaeger) on up to 40 vertices.

Strongly correlated fermionic systems are of great interest in condensed matter physics and numerical methods are indispensable tools for their study. However, existing approaches such as exact diagonalization (ED) and stochastic quantum Monte Carlo methods each suffer from fundamental limitations: ED is hindered by exponential scaling in system size, while Monte Carlo methods are plagued by sign problems and long autocorrelation times. These limitations restrict the accessible parameter space and developing algorithms that efficiently alleviate them remains a central challenge in computational physics. In this work, we propose a hybrid algorithm that combines ED and Hamiltonian Monte Carlo (HMC) to simulate 2D arrays of coupled quantum wires, modeled as interacting fermionic Hubbard chains. We demonstrate how our hybrid implementation of HMC, which we dub H$^2$MC, outperforms either method alone across several key simulation facets. When compared to pure ED, H$^2$MC has a much more favorable computational scaling, which allows us to push simulations to much larger 2D arrays. H$^2$MC also greatly alleviates the sign problem and reduces autocorrelation times when compared to pure HMC formulations utilizing either real or imaginary auxiliary fields. Our formalism demonstrates how complementary strengths of seemingly disparate methods can be leveraged to enable feasible simulations in an extended parameter space.

Wealth taxes are a frequently proposed policy within the post-growth literature, but evaluations of their alignment with post-growth goals, and empirical estimates of their potential effects, are lacking. We contribute to this literature by examining the extent to which different wealth-tax designs can contribute to four goals of a post-growth transition: redistributing wealth; eradicating extreme wealth; curbing rent-seeking; and reducing CO2 emissions. The analysis is based on microsimulation modelling, using household-level data from 18 countries of the 2017 EU Household Finance and Consumption Survey. Our analysis finds that taxes on net wealth are the most progressive and redistributive, while taxes on financial and investment property wealth tend to be more effective at addressing rent-seeking. However, we also identify trade-offs and conflicts between different tax designs and goals. As a result, a broader package of policies will be necessary to navigate these conflicts and mitigate the limitations inherent in any single wealth-tax design.

Characterizing the relation between entanglement and Bell nonlocality is a long-standing open problem, notably challenging in the multipartite case. Here we investigate the effect of superactivation of genuine multipartite nonlocality. Specifically, we show that starting from multipartite states that feature only two-party entanglement (hence almost fully separable), it is possible to obtain GMNL in the many-copy regime. This represents the weakest possible resource for GMNL superactivation. On the technical side, we develop an efficient and practical criterion for certifying GMNL superactivation based on network entangled states, as well as a perfect parallel repetition result for the Khot-Vishnoi Bell game, which are of independent interest.

We study the homological properties of $Δ_{\mathbf{r}}(n_1, \dots, n_e)$, a simplicial complex formed by sequentially gluing complete graphs along $(r_i-1)$-simplices. This construction generates precisely the chordal clique complexes, whose Stanley-Reisner ideals admit 2-linear resolutions. By computing the $f$-vector and evaluating the Hilbert series, we establish explicit graded Betti numbers for all $k$-skeletons. We show that the regularity of these skeletons is $k+1$ and the projective dimension stabilizes at $N_{\mathbf{r}} - r_{\min} - 1$ for $k \ge r_{\min}$, providing a complete classification of when the complex is Cohen-Macaulay, sequentially Cohen-Macaulay, or initially Cohen-Macaulay. We also obtain explicit formulas for the ring multiplicity and reduced Euler characteristic. Applying Alexander duality, we derive the $f$-vector, rational $h$-polynomial, and exact graded Betti numbers of the dual and its skeletons. Furthermore, analyzing these dual skeletons yields a family of complexes that resolve recent open bounds on regularity. Finally, equating the topological and rational evaluations of the Hilbert series produces a new family of combinatorial binomial identities.

We present Quantum Depth Compression (QDC), a general compilation framework that utilizes dynamic circuits to reduce arbitrary quantum circuits to depth linear in the number of non-Clifford gates and to grid connectivity without the need for expensive SWAP-networks. The framework consists of pushing Clifford gates to the end of the circuit, resulting in a sequence of non-Clifford Pauli-phasors followed by an all Clifford sub-circuit, both of which are then reduced to constant depth via dynamic circuits. We show that applying QDC to random Pauli-phasor circuits lowers both their depth and CNOT count compared to a standard alternative compiler.