We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT temperature maps, we detect the kSZ signal at high significance, reaching signal-to-noise ratios of up to $\sim$9 for BGS and $\sim$7.5 for ELGs in optimal stellar-mass selections. Together with the LRG measurements presented in Paper I, these constitute the most significant kSZ detections from any spectroscopic survey to date. We perform the analysis in both real and harmonic space, obtaining consistent results. By splitting both tracers into stellar-mass bins, we study the scaling of the kSZ amplitude with galaxy properties. Combining the kSZ measurements with ACT Data Release 6 (DR6) CMB lensing maps enables a joint calibration of the galaxy-halo connection and the gas fractions of host halos. For the BGS galaxies, we observe low gas fractions around the virial radius relative to standard expectations, likely attributable to active galactic nuclei (AGN) activity. We find some evidence for higher-mass halos retaining a larger fraction of their baryons, consistent with more efficient feedback in lower-mass systems. For the ELG sample, dominated by blue, star-forming galaxies, we provide the first detection of the gas distribution in ELG host halos. The ELGs appear to exhibit relatively high gas fractions, which points to the possibility of weaker feedback (due to e.g. low AGN and supernova feedback activity) at their mass scale. Finally, we present generalized Navarro-Frenk-White (GNFW) fits to the harmonic-space measurements, providing a compact parametrization of gas profiles for forward modeling in large-scale structure analyses.

We present the most precise measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect around luminous red galaxies to date, detecting the signal at $18σ$ significance in both harmonic and configuration space. Our analysis cross-correlates 2.4 million spectroscopic LRGs from the Dark Energy Spectroscopic Instrument (DESI) DR2 sample with Data Release 6 (DR6) of the Atacama Cosmology Telescope (ACT). We develop a novel harmonic-space cross-correlation approach using momentum-weighted kSZ templates, yielding nearly uncorrelated bandpowers within a framework consistent with other large-scale structure analyses. By incorporating the LRG halo occupation distribution (HOD) and its uncertainty, we convert measured galaxy gas profiles into halo gas profiles and provide generalized Navarro-Frenk-White (GNFW) fitting profiles, providing empirical targets for tuning feedback efficiency in hydrodynamical simulations and for baryonic modeling in large-scale structure analyses. We find strong evidence that gas profiles do not trace dark matter, providing direct evidence for gas redistribution beyond gravitational collapse. Comparing to hydrodynamical simulations, our measurements favor feedback efficiencies exceeding those in the Battaglia profile, suggesting more efficient gas ejection in group-scale halos than previously predicted. Splitting by redshift, we detect the kSZ signal at SNR $\approx 5$--$10$ in each of four bins and find amplitude evolution consistent with the expected decline in mean halo mass at fixed comoving number density. Splitting by stellar mass, we study the scaling of kSZ amplitude with galaxy properties. Together with BGS and ELG measurements in Paper II, these results span $0.1 \lesssim z \lesssim 1.6$ across three galaxy populations, demonstrating the potential of spectroscopic kSZ to map circumgalactic gas and constrain baryonic feedback.

Disks (Keplerian or otherwise, particulate or fluid) are often assumed to have densities that drop off vertically as Gaussians. Recent mm-wave imaging of circumstellar debris disks contradicts this assumption, revealing vertical profiles in dust that resemble Lorentzians. As part of the ARKS ALMA Large Program, we calculate how Lorentzians and Gaussians define an evolutionary sequence for disks of gravitationally scattering (viscously stirring) particles. When orbits are crossing and eccentricities $e \gg$ inclinations $i$, each scattering changes a particle's inclination by $\pm \,Δi \propto i$. A random walk with fixed steps in $Δi/i = Δ\ln i$ produces a log normal $i$ distribution, whose thick tail at large $i$ leads to thick Lorentzian tails in density. This result holds independent of the origin of the large eccentricities; what matters is that relative motions parallel to the disk midplane are faster than perpendicular motions. After enough scatterings, $i$ comes into equipartition with $e$, $Δi$ stops exponentiating, and the vertical density profile relaxes to a Gaussian. We estimate the numbers and masses of perturbers needed to stir themselves and observable dust grains in Lorentzian and Gaussian debris disks imaged by ARKS. The big bodies may be sufficiently few in number as to be collisionless, in which case their masses range from the Moon to several Earths. But if Pluto-sized or smaller, the big body stirrers may be so numerous and collide so frequently that they can source the collisional cascades that produce observable dust.

Recent advancements in neutral atom platforms have enabled exploration of early fault-tolerant (FT) architectures for applications with quantum advantage, such as quantum dynamics simulations. An efficient fault-tolerant architecture has both spatially efficient quantum error correction codes (low qubit overhead), and efficient methodologies (transversal based gates, extractor based gates, etc.) for logical computation, to minimize overall execution time. Achieving the right balance between space and time can be critical for enabling early FT demonstrations of quantum advantage. In this work, we identify bottlenecks in existing spatially efficient schemes, which tend to be very serial, and do not take advantage of unutilized space. We introduce a teleportation-based scheme that leverages the reconfigurable connectivity of neutral atoms to parallelize logical operations. Our approach achieves up to \textbf{$\mathbf{\sim 3 \times}$ speedup} over extractor architectures at no extra space cost and achieves the best spacetime performance among other viable architectures before accounting for external \textit{resource-states}. To rigorously evaluate performance, we construct explicit quantum advantage benchmarks and \textit{simulate} compilation to a fault-tolerant instruction set, including low-level gate scheduling and shuttling patterns, and resource-state nondeterminism. We find that our speedups still apply and report exact space-time cost along with success probabilities, identifying architectures capable of achieving quantum advantage \textbf{with as little as $\mathbf{11,495}$ atoms and a runtime of $\mathbf{\sim 15}$ hours}.

Self-interacting dark matter (SIDM) is the leading framework resolving small-scale cold dark matter (CDM) crises, yet high-redshift SIDM constraints are fundamentally limited by degeneracies between dark matter microphysics and galaxy formation astrophysics. We demonstrate that the UV luminosity function alone cannot constrain SIDM: star formation suppression from SIDM halo core formation is fully absorbed by modest adjustments to standard astrophysical parameters. We show that 21 cm reionization topology breaks this degeneracy completely, providing a nuisance-immune probe: the SIDM-enhanced duty cycle of ionizing photon escape leaves a morphological signature fully independent of star formation efficiency. Combining JWST UVLF measurements with SKA1-Low forecasts, constant-cross-section SIDM with $σ/m \gtrsim 1$--$2\ \mathrm{cm^2/g}$ is either excluded or detectable across all physically motivated star formation coupling strengths. Our results establish a robust new avenue to probe dark matter microphysics in the early Universe.

In this paper, we give a mathematical proof that bounds the number of CNOT gates required to synthesize an $n$ qubit phase polynomial with $g$ terms to be at least $O(\frac{gn}{\max (\log g, 1)})$ and at most $O(gn)$. However, when targeting restricted hardware, not all CNOTs are allowed. If we were to use SWAP-based methods to route the qubits on the architecture such that the earlier synthesized gates are natively allowed, we increase the number of CNOTs by a routing overhead factor of $O(\log n) \leq α\leq O(n \log^2 n)$. However, if we only synthesize allowed gates, we do not need to route any qubits. Moreover, in that case the routing overhead factor is $1 \leq α\leq 4 \simeq O(1)$. Additionally, since phase polynomials and Hadamard gates together form a universal gate set, we get qubit routing for almost free.

This work proposes a bootstrapping with positivity methodology to study random $U(N)^{D}$ invariant tensors in the large $N$ limit. As has been done for $U(N)$ invariant random matrices, we combine the Dyson-Schwinger equations and positivity constraints of moments to approximate the moments of such tensor models. As examples, we bootstrap the quartic and two hexic rank three tensor models. All models studied converge quickly, and for those which have known analytic formulae, they converge to such solutions. We conjecture new explicit formulae for all moments of the rank three quartic model and support this conjecture using bootstrapped results and explicit double-series computations with 'feyntensor'.

In [97,99,100], an fl-RDT framework is introduced to characterize \emph{statistical computational gaps} (SCGs). Studying \emph{symmetric binary perceptrons} (SBPs), [100] obtained an \emph{algorithmic} threshold estimate $α_a\approx α_c^{(7)}\approx 1.6093$ at the 7th lifting level (for $κ=1$ margin), closely approaching $1.58$ local entropy (LE) prediction [18]. In this paper, we further connect parametric RDT to overlap gap properties (OGPs), another key geometric feature of the solution space. Specifically, for any positive integer $s$, we consider $s$-level ultrametric OGPs ($ult_s$-OGPs) and rigorously upper-bound the associated constraint densities $α_{ult_s}$. To achieve this, we develop an analytical union-bounding program consisting of combinatorial and probabilistic components. By casting the combinatorial part as a convex problem and the probabilistic part as a nested integration, we conduct numerical evaluations and obtain that the tightest bounds at the first two levels, $\barα_{ult_1} \approx 1.6578$ and $\barα_{ult_2} \approx 1.6219$, closely approach the 3rd and 4th lifting level parametric RDT estimates, $α_c^{(3)} \approx 1.6576$ and $α_c^{(4)} \approx 1.6218$. We also observe excellent agreement across other key parameters, including overlap values and the relative sizes of ultrametric clusters. Based on these observations, we propose several conjectures linking $ult$-OGP and parametric RDT. Specifically, we conjecture that algorithmic threshold $α_a=\lim_{s\rightarrow\infty} α_{ult_s} = \lim_{s\rightarrow\infty} \barα{ult_s} = \lim_{r\rightarrow\infty} α_{c}^{(r)}$, and $α_{ult_s} \leq α_{c}^{(s+2)}$ (with possible equality for some (maybe even all) $s$). Finally, we discuss the potential existence of a full isomorphism connecting all key parameters of $ult$-OGP and parametric RDT.

The standard cosmological model is challenged by an ever-growing collection of observations, which invites (and stimulates) inquiry into possible additions and/or alterations. One such alteration comes from letting cosmic isotropy -- as demanded by the cosmological principle -- go, whilst maintaining only homogeneity. This study concerns Bianchi models, a class of anisotropic, homogeneous spacetimes, and in particular their perturbations. Knowledge of their properties under perturbations (such as allowed wavemodes) aids in understanding cosmological signatures of such universes, e.g. CMBs, and thus allows for comparsion to observation and the theory of the standard model. This study develops linear perturbation theory of general Bianchi models, by working in a frame such that metric components depend solely on (cosmic) time. Perturbation equations in the Newtonian gauge, but for arbitrary metric, are derived for energy density $ρ$, (relativistic) pressure $p$, momentum density $q$, and anisotropic stress $π$, for the case of scalar and pure tensor perturbations. For the former, the equations for density and pressure are combined to yield the equivalent of the Mukhanov-Sasaki equation for Bianchi models. For a specific choice of metric and fluid flow $u$, the Friedmann equations for Bianchi models are also formulated, as this knowledge is necessary to fully formulate the perturbation equations. Finally, the obtained results are applied to the formulations of density contrasts in an Einstein-de Sitter universe and a Bianchi I universe.

The lowest eigenstates of the hopping matrix on the line graph of a cubic lattice with periodic boundary conditions are highly degenerate, they form a lowest flat band. Further, these states are localized. If one considers a repulsive bosonic Hubbard model on this lattice it is possible to construct exact multi-particle ground states simply by putting particles in the localized single particle ground states such that they avoid each other. This can be done up to a certain critical particle number $N_c$. We prove that at this particle number the ground state entropy is subextensive $\propto N_c^{2/3}$. For lower densities the entropy is extensive. We further show that the problem is related to the number of 4-cycle decompositions of the cubic lattice with periodic boundary conditions.

Inspiralling supermassive black-hole binaries (SMBHBs) are expected to be the main source of the nanohertz gravitational-wave background (GWB) targeted by pulsar timing arrays (PTAs). We provide a simple and general analytic expression for the probability distribution function (PDF) of the GWB characteristic strain squared $h_c^2$ in the limit of a large but finite effective number of sources, $N$, relevant for the lowest-frequency bands where PTAs are most sensitive. Explicitly, we show that for $N \gg 1$, the PDF of the rescaled variable $y \equiv h_c^2/\overline{h_c^2}$ takes the universal self-similar form $P(y) \simeq N^{1/3} \mathcal{P}(N^{1/3} (y -1))$, where $\mathcal{P}$ is the reflected map-Airy distribution. The effective number of in-band sources $N$ is fully specified by the mean $\overline{h_c^2}$ and the cubic shot-noise strain scale $\overline{h_0^3}$, a new summary statistic of the GWB that depends only on the local properties of the SMBHB population. This result is universal: it applies to any population of SMBHBs, regardless of whether they are circular or eccentric, and of the mechanism dominating orbital hardening. We explicitly quantify the accuracy of the large-source-count PDF for a simple but physically realistic SMBHB model, and outline its practical application to PTA data analysis.

A recent paper published on Nature [Nature,646,813(2025)] by Aziz and Howl, claims that quantum particles become entangled when they interact gravitationally, even if the gravitational potential is treated classically. We show that the entanglement found by the authors stems from discarding some of the transition amplitudes, which, when kept, guarantee that an initially factorized state remains so over time. Therefore, no entanglement is generated by the classical gravitational interaction in the scenario considered by the authors.

This study presents a multi-task machine learning framework for simultaneous morphology classification and physical parameter estimation of eclipsing binaries using photometric light curves. We train Random Forest and XGBoost ensemble models on 845 of 995 well-characterized systems comprising three morphological configurations by extracting 51 domain-specific features from each phase-folded light. To assess generalization, 15% of systems were withheld as an independent test set before any model training. On this held-out set, the XGBoost model yields $R^2$ values of 0.88 for the effective temperature ratio, 0.91 for the primary surface potential, 0.92 for the secondary surface potential, 0.89 for inclination, and 0.77 for the mass ratio. Morphology classification achieves 95.4% accuracy on the cross-validation set with per-class F1 scores exceeding 0.90, while the held-out test set confirms generalization with 90.7% accuracy. We present a catalog of estimated physical parameters and classifications for these systems, identifying thousands of high-confidence candidates. Morphological classifications are independently validated against the OGLE Online Catalog of Variable Stars (OCVS), achieving a contact recall of 0.99 across 104692 matched systems. The model's generalization capability is validated by cross-matching predictions with independent Kepler catalogs, achieving 77% classification accuracy and recovering physical parameters with systematic deviations consistent with known selection biases, third-light dilution, and methodological differences between photometric and spectroscopic approaches. This work confirms that machine learning ensembles, when coupled with physics guided post-processing, can effectively bridge the gap between massive photometric surveys and detailed astrophysical characterization.

Quantum Signal Processing (QSP) and Quantum Singular Value Transformation (QSVT) provide an efficient framework for implementing polynomials of block-encoded matrices, and thus offer a systematic approach to quantum algorithm design. However, despite a number of recent advances, important limitations remain. In particular, QSP can only transform unitary matrices, by applying a polynomial to their eigenvalues, while QSVT is a singular-value transformation and thus one can only obtain the polynomial of Hermitian matrices. As a consequence, these techniques do not directly apply to an arbitrary non-Hermitian matrix that is not diagonalizable. In this work, we propose a simple yet powerful method to extend these ideas to arbitrary square matrices by acting on their eigenvalues. To this end, we introduce the notion of an $n$-regular block encoding, namely, a block encoding whose $k$-th power reproduces the $k$-th power of the encoded matrix for every $0 < k < n$. We show that applying QSP to any unitary with this property is equivalent to applying a polynomial of degree at most $n$ to the block-encoded matrix, independently of its internal structure. Moreover, we provide a simple construction that transforms any block encoding into an $n$-regular one using only $O(\log n)$ ancillary qubits and operations. Finally, we show that this construction induces the desired transformation on the eigenvalues associated with the Jordan normal form of the matrix.

The use of noise-robust qubit encodings provides a way of extending the lifetime of quantum information at the hardware level. In this work, we introduce the spin Kerr-cat encoding, which leverages a clock transition in the spectrum of quadrupolar nuclei (having spin length $I\geq 1$) to achieve a first-order suppression of noise leading to qubit dephasing. The basis states of the spin Kerr-cat qubit are given by the two lowest levels of a $\mathbb{Z}_2$-symmetric nuclear-spin Hamiltonian and are well approximated by spin cat states. We compute the dephasing time of the spin Kerr-cat qubit under a model of $1/f$ noise, as well as relaxation of the qubit due to breaking of the $\mathbb{Z}_2$ symmetry by charge-noise-induced fluctuations of the quadrupolar tensor. Using measured parameters for antimony (${}^{123}\mathrm{Sb}$) donors in silicon, we estimate that a coherence time of $T_2^*=100$ s could be achieved with this encoding. We propose a two-qubit gate mediated by hopping electrons and estimate that with an enhancement of measured quadrupolar splittings by a factor of $\approx 4$, a gate fidelity of $99\%$ could be achieved for spin Kerr-cat qubits encoded in ${}^{123}\mathrm{Sb}$ nuclear spins, neglecting errors that impact the electron while it is being shuttled and read out.

Higher-order interaction networks are typically modeled using hypergraphs or simplicial complexes, where interactions explicitly involve more than two nodes. Here we demonstrate that effective higher-order dynamical constraints emerge naturally on the 1-skeleton of a graph, provided the interaction carries nontrivial topological structure. We study phase-oscillator dynamics with edge phase lags modeled as a $U(1)$-valued connection. This structure induces a gradient Sakaguchi--Kuramoto-type flow and an associated twisted Laplacian whose spectrum depends on the cohomology class of the connection. We prove that the associated twisted Laplacian admits a zero mode if and only if the connection is cohomologically trivial, that is, when all cycle holonomies vanish. Consequently, synchronization is obstructed not by local pairwise mismatches, but by intrinsic topological frustration on cycles. We derive that the smallest eigenvalue of the twisted Laplacian scales with the magnitude of the holonomy, and its spectral transitions accurately predict the loss of stability of the phase-locked state as frustration is increased. For the specific case of constant phase lag, we analytically derive the critical transition point, $α_c = π/3$ for a pentagonal cycle, which is in quantitative agreement with previously reported numerical thresholds. Our results establish a spectral framework linking dynamical frustration to network cohomology, and show that transitions in remote synchronization are shaped by cycle-level topological constraints.

Energy systems optimisation models are a leading tool for informing decisions in the energy transition. However, these models often remain opaque, and results are frequently presented without a clear discussion of their epistemic limitations. We propose Diagnostic Modelling as a framework wherein modellers critically interrogate their models and explore uncertainties to uncover mechanistic explanations that offer policy-relevant insights. Mechanistic explanations provide fundamental understanding that remains valid despite model uncertainty and does not depend on detailed knowledge of a specific model. By adopting a more open and transparent approach to engaging with energy systems models, Diagnostic Modelling encourages the participation of a broader range of decision-makers, thereby building consensus in support of the energy transition.

We use high-resolution UV-to-optical imaging from the Hubble Space Telescope (HST) to construct spatially resolved spectral energy distributions (SEDs) for seven nearby ($z<0.07$) hard (14--195$\,$keV) X-ray-selected broad-line active galactic nuclei (AGN) with $L_{\rm bol}=10^{43.26}-10^{45.34}\,\rm{erg\,s^{-1}}$. The high spatial resolution of HST, which physically resolves structures on the scale of $\sim$50$\,$pc at $z=0.05$, enables the separation of AGN and host-galaxy emission through morphological decomposition with GALFIT, yielding improved measurements of AGN properties compared to those obtained with lower-resolution Swift UV/Optical Telescope (UVOT) data. AGN UV magnitudes derived from HST imaging (e.g., F225W) can differ by more than a magnitude from those from Swift/UVOT UVM2 due to extended nuclear emission. Additionally, the inclusion of high-resolution data at longer wavelengths (e.g., F814W) can significantly affect the resulting SED fit. Comparing fits of accretion disk and extinction models using HST and Swift/UVOT data, we find significant differences in the resulting parameters, with average differences of 2.0$\,$eV in the maximum disk temperature and 2.2$\,$mag in the AGN host-galaxy extinction. These differences ultimately lead to significant changes in bolometric luminosities and X-ray bolometric corrections, with the HST-based fits yielding average increases of $\sim$0.57$\,$dex and $\sim$0.66$\,$dex respectively. This demonstrates host-galaxy contamination in unresolved UV--optical data can strongly bias SED-based estimates of disk temperatures, extinction, bolometric luminosities, and X-ray bolometric corrections in AGN. Large-area, high-resolution imaging surveys from Euclid and the Nancy Grace Roman Space Telescope will extend these techniques to much larger AGN samples, enabling uniform, high-precision SED measurements in the near-IR.

This thesis is framed within the field of Mathematical Relativity and is organized into six chapters. After an introduction to the topic in Chapter 1, Chapter 2 reviews and further develops the formalism of hypersurface data, which provides the unifying framework for the entire thesis. In Chapter 3 we study the characteristic Cauchy problem from a fully detached perspective. Chapter 4 is devoted to the Killing initial data problem, also analyzed within this detached framework. In Chapter 5 we investigate the transverse (or asymptotic) expansion of the metric at a general null hypersurface. Finally, Chapter 6 addresses the geometry of conformal null infinity.

The concept of cavity funneling has emerged recently as a promising route towards creating indistinguishable photons from highly dephased emitters. So far, all suggested solutions are solely based on dielectric cavities that require extremely high quality factors that are difficult to reach at visible wavelengths. Here we suggest a hybrid funneling architecture where a dephased emitter is coupled to a plasmonic nanoresonator that is enclosed by an outer dielectric cavity. The estimated lower limit of the outer cavity quality factor is found to be $\sim2$ orders of magnitude lower compared to a cascaded cavity system. Furthermore, the surrounding topology of our approach allows for a partial direct coupling between the emitter and the outer cavity which in turn can increase the overall system extraction efficiency $\left(β\right)$ by a factor of 12, boosting the probability of photon collection.

The anomalous magnetic moment of the tau lepton, $a_τ$, represents a fundamental test of the Standard Model (SM) and a high-sensitivity probe for New Physics in the third generation of leptons. Due to the tau's extremely short lifetime, traditional spin-precession measurements remain inaccessible, necessitating innovative experimental strategies at high-energy colliders. This review provides a comprehensive overview of the current experimental landscape, highlighting the recent paradigm shift from LEP-era constraints to the unprecedented precision reached at the LHC. We emphasize the importance of Ultra-Peripheral Heavy-Ion Collisions (UPCs), which act as a ``photon-photon collider'' of extreme intensity. By leveraging the $Z^4$ enhancement of the coherent photon flux in Lead-Lead ($PbPb$) interactions, these collisions provide a theoretically robust ``quasi-static'' environment. These results are critically compared with the latest measurements from proton-proton collisions, including the recent CMS observation of the $γγ\to ττ$ process and the ATLAS constraints from the high-mass Drell-Yan tail. We evaluate their complementarity and the challenges related to Effective Field Theory validity at the TeV scale. Finally, we outline the future prospects for $a_τ$ at Belle II and the Future Circular Collider (FCC) stages. While FCC-hh in $PbPb$ mode provides a theoretically clean environment, its sensitivity remains limited to $\mathcal{O}(10^{-2})$. Conversely, the next generation of lepton facilities, specifically Belle II and FCC-ee, aims for the $\mathcal{O}(10^{-5})$ level, required to probe SM electroweak loop corrections. Long-term projections for a high-energy Muon Collider suggest a potential reach of $\mathcal{O}(10^{-6})$.

Perceptual judgments of sequential stimuli are systematically biased by prior expectations and by the temporal structure of sensory input. In haptic discrimination tasks, these effects often manifest as time-order asymmetries, whereby the perceived difference between two stimuli depends on their presentation order. Here, we introduce a dynamical Bayesian model that accounts for these biases by combining noisy sensory measurements with an evolving internal representation of stimulus intensity. The model formalizes perception as an inference process in which prior expectations are updated by incoming stimuli and propagate in time between observations. We test the model on psychophysical data from vibrotactile discrimination experiments, in which participants compare pairs of sequential stimuli with varying intensities. With a small number of parameters, the model quantitatively reproduces both the direction and magnitude of time-order effects across subjects, as well as the observed inter-individual variability. The inferred parameters provide a compact description of perceptual biases in terms of prior expectations and noise characteristics. Beyond fitting the data, the model induces a transformation of stimulus space, leading to a subject-dependent geometry of perceived stimuli. In this transformed space, perceptual judgments exhibit approximate symmetries that are absent in the physical stimulus coordinates. These results suggest that temporal biases in perception can be understood as a consequence of dynamical inference, and that they impose non-trivial geometric constraints on perceptual representations.

Altermagnets feature unconventional magnetism due to their momentum-dependent spin splitting purely driven by magnetic order, for which a variety of transition-metal-based d-wave altermagnets have been proposed. However, carbon-based altermagnets in graphene structures remain elusive, even though magnetism in graphene nanostructures has been widely demonstrated. Here, we establish a symmetry-guided design principle to engineer i-wave altermagnets in graphene antidot superlattices and demonstrate the emergence of altermagnetic states in specific monolayer and bilayer graphene superlattices. By combining first principles methods and atomistic tight binding models, we show the appearance of an interaction-induced i-wave altermagnetic splitting, stemming from the intrinsic magnetic instability of 2D graphene antidot superlattices. Our work establishes a strategy to engineer i-wave altermagnetism in a graphene platform, putting forward a carbon-based platform for altermagnetic spintronics.

We introduce the concept of Hamiltonian potential variables to map Hamiltonian operators into symplectic operators in a dual space. This generalises the classical trick of switching to a potential variable to obtain a Lagrangian density for the Korteweg-de Vries (KdV) equation. Building on this concept, we present the Lagrangian structure for bi-Hamiltonian systems, discuss the Lenard scheme in the symplectic formalisms, and apply this to construct pairs of Lagrangian multiforms. We discuss the key model of the KdV equation and some dispersionless limits of it. We present a pair of Lagrangian multiforms for these equations, one of which is new. We also consider the examples of polytropic gas dynamics and the constant astigmatism equation, for which no Lagrangian multiforms were previously known.

We present the serendipitous discovery of an overdensity of submillimeter galaxies (SMGs) in the field of SDSSJ0909-0108, a massive z~0.7 post-starburst galaxy from the SQuIGGLE survey. ALMA observations at 870um and 2mm reveal six galaxies within a 35'' region with flux ratios consistent with emission from dust. Given the rarity of 870um sources and the small field-of-view of ALMA, we speculate that some of these sources are physically associated. None of the sources are at the same redshift as the post-starburst, and four do not have spectroscopic redshifts. We suggest that follow-up optical and/or ALMA observations be carried out to measure redshifts for the galaxies in this potential protocluster environment.

We study the impact of neutron-skin thickness on $J/ψ$ photoproduction in ultra-peripheral $^{208}\mathrm{Pb}+{}^{208}\mathrm{Pb}$ collisions. Within the Color Glass Condensate framework, we calculate coherent and incoherent cross sections and examine their dependence on the momentum transfer $|t|$ for different neutron-skin thicknesses. We find a clear imprint of the neutron skin on the $|t|$ spectra: a larger neutron skin leads to a smoother and more extended color-density profile, suppressing the coherent cross section at large $|t|$ while enhancing the incoherent cross section through increased event-by-event configurational fluctuations in the nuclear periphery. We further show that the ratio of incoherent to coherent integrated cross sections provides a particularly sensitive and robust observable, with reduced theoretical uncertainties. These results establish diffractive vector-meson photoproduction in ultra-peripheral collisions as a powerful tomographic tool to constrain the neutron-skin thickness and the transverse gluon distribution at the LHC and future Electron-Ion Colliders.

We present the results of continuum-extrapolated lattice simulations of quantum chromodynamics (QCD) above the crossover temperature and for unprecedentedly high baryon densities at the physical point, employing the complex Langevin equation. In particular, we determine the QCD equation of state by computing the baryon density as well as the pressure as functions of the baryon chemical potential and the temperature. Potential issues with wrong convergence of complex Langevin dynamics are under control and we indeed find agreement with previous lattice studies working at smaller chemical potentials, as well as with perturbative hard-thermal-loop calculations at high temperatures.

The complexity and significance of multiscale phenomena in fusion energy systems make advanced modeling necessary for designing, optimizing, and safely deploying fusion plants. Tritium accountancy is one of those challenges for deuterium-tritium fusion systems. Its availability is constrained by its short half-life (12.33 years) and limited natural abundance, which require fusion plants to breed tritium onsite. Therefore, accurate tritium accountancy is essential for effective resource management, safety, and economics in fusion plants. Through the U.S. Department of Energy milestone program, Tokamak Energy Ltd. is developing a fusion pilot plant design and evaluating tritium retention and loss in key components and their effect on the fuel cycle. To rapidly explore design trade-offs and quantify design decisions on tritium management, this study presents a multiscale analysis to investigate tritium diffusion, trapping, and recovery in key plasma-facing components. To enhance computational efficiency, we integrate surrogate models at the component-level within a fuel cycle model at the system-level, enabling rapid evaluation of tritium recycling dynamics and inventory under various operational scenarios. The goal of this study is twofold: (1) demonstrate the feasibility of utilizing surrogate models to increase the accuracy of fuel cycle modeling, and (2) rapidly evaluate the performance of fusion technologies to accelerate design iterations. This multiscale model provides the tritium transport and retention behavior and supports the plasma-facing components design optimization in normal and bake-out operations. The work is implemented using the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source application for tritium transport analysis in fusion systems.

The intrinsic incommensurate charge density wave in metal-organic frameworks has remained elusive due to the lack of direct evidence linking atomic-scale structural modulation to macroscopic electronic properties. Using high-quality Pr3HHTP2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) single crystals as a model system, we precisely resolve, for the first time, the incommensurately modulated structure of a conductive metal-organic framework at 100 K (modulation vector q = 0.39143(12) c*) via temperature-dependent single-crystal X-ray diffraction. The subsequent observation of a reversible metal-semiconductor transition around 350 K, which perfectly synchronizes with the disappearance of the structural modulation, provides convincing evidence for the electronic origin of the lattice distortion. Guest water molecules stabilize the modulated phase by synergistically regulating the relative rotation of the linkers and the interlayer spacing, thereby optimizing the inter-linker interactions. This work establishes a concrete experimental criterion for one-dimensional charge density wave in metal-organic frameworks and provides an ideal platform for probing coupled electronic-lattice modulations.

Dusty plasmas, composed of electrons, ions, neutral particles, and charged dust grains, exhibit self-organization phenomena such as string-like structures observed in microgravity experiments. The formation of these structures is influenced by ion wakes generated by streaming ions under external electric fields, as well as by time-evolving plasma inhomogeneities such as ionization waves. Existing ion wake models, such as point charge and Gaussian-based representations, often rely on configuration-specific parameters, limiting their general applicability. In this work, we present a robust and general potential model for dust and ion wake systems under PK-4-like conditions. Using a small set of coefficients determined from molecular dynamics simulations, the model captures the potential distributions for multiple interparticle distances. Its application to test cases and implementation in a small scale dust dynamics simulation demonstrates its applicability to a wide range of dust arrangements beyond string-like configurations.