We consider a holographic Einstein-Maxwell model in five dimensions with pure gauge and mixed gauge-gravitational Chern-Simons terms to study anomaly-induced transport in the presence of explicit symmetry breaking. We include the full backreaction of the scalar field and gauge fields on the metric and compute the anomalous transport coefficients using Kubo formulae involving charge and energy current correlators. Our findings reveal that, in the presence of explicit symmetry breaking, anomaly-induced transport phenomena can extend beyond anomalous currents and affect the non-anomalous sector as well. The transport coefficients exhibit a clear dependence on the symmetry-breaking mass parameter, highlighting the interplay between quantum anomalies and explicit symmetry breaking in holographic systems.

Sensing the direction of arrival and polarization of impinging signals is a key prerequisite for beamforming and interference mitigation in modern wireless communication systems. Dynamic metasurface antennas (DMAs) can multiplex direction- and polarization-dependent field information onto a single detector by sequentially switching between programmable configurations. This makes DMAs attractive for joint direction-of-arrival and polarization (DoA-P) estimation with a single radio-frequency chain. Experimental demonstrations have so far relied on random pre-measured configuration sequences because optimizing the configurations requires an accurate forward model of the fabricated DMA. Here, we use an experimentally calibrated model based on multiport-network theory (MNT) to optimize DMA configuration sequences for DoA-P estimation. Our experimentally calibrated MNT model predicts the dual-polarized far-field response of our 96-element DMA for arbitrary admissible configurations, enabling model-based optimization without additional radiation-pattern measurements. We optimize sequences using effective-rank-based surrogate objectives and compare them with random sequences as a function of the sequence length and the noise level. The optimized sequences yield the largest gains in the intermediate-SNR and intermediate-sequence-length regime, where the inverse problem is neither noise-limited nor already solved by random diversity. We also tackle a dual-source scenario involving a jammer and a desired transmitter. Our results illustrate some of the potential in the context of jamming-resilient communications that is unlocked by experimentally calibrated MNT models for fabricated DMAs.

Orbital energy splittings are important quantum dot parameters for the operation of hole spin qubits. They are known to depend on the lateral confinement of the quantum dots. However, when changing top, plunger gate voltages, which are the typical control parameter for qubit applications, such energy splitting changes are typically negligible, both as measured in experiment and as assumed in effective theories. Here, we study the singlet-triplet (ST) splittings, which depend on the orbital splittings, of a double quantum dot (DQD) in a Ge/SiGe heterostructure using photon-assisted tunneling (PAT) and pulsed-gate spectroscopy. We find that the ST splittings have a surprising, strong dependence on the top gate voltages, leading to anomalous PAT measurements. We combine data from both measurements in a model that well describes the linear gate-voltage dependence of the ST splittings. Finally, we show that the ST splittings of the two dots exhibit similar linear gate-voltage dependences when the device is retuned such that their ratio is significantly different.

We introduce a quantum algorithm for simulating the dynamics of electrical circuits consisting of resistors, inductors and capacitors (aka RLC circuits) along with power sources. Given oracle access to the connectivity of the circuit and values of the electrical elements, our algorithm prepares a quantum state that encodes voltages and current values either at a specified time or the history of their evolution over a time-interval. For an RLC circuit with $N$ components, our algorithm runs in time $\textsf{polylog}(N)$ under mild assumptions on the connectivity of the circuit and values of its components. This provides an exponential speed-up over classical algorithms that take $\textsf{poly}(N)$ time in the worst-case. Our algorithm can be used to estimate energy across a set of components or dissipated power in $\textsf{polylog}(N)$ time, a problem that we prove is BQP-hard and therefore unlikely to be efficiently solved by classical algorithms. The main challenge in simulating the dynamics of RLC circuits is that they are governed by differential-algebraic equations (DAEs), a coupled system of differential equations with hidden algebraic constraints. Consequentially, existing quantum algorithms for ordinary differential equations cannot be directly utilized. We therefore develop a quantum DAE solver for simulating the time-evolution of linear DAEs. For RLC circuits, we employ modified nodal analysis to create a system of DAEs compatible with our quantum algorithm. We establish BQP-hardness by demonstrating that any network of classical harmonic oscillators, for which an energy-estimation problem is known to be BQP-hard, is a special case of an LC circuit. Our work gives theoretical evidence of quantum advantage in simulating RLC circuits and we expect that our quantum DAE solver will find broader use in the simulation of dynamical systems.

Implicit full waveform inversion (IFWI) introduces implicit neural representations to parameterize the subsurface velocity model as a continuous function of spatial coordinates, which alleviates the dependence on the initial model and improves inversion flexibility. However, IFWI still requires a large number of iterative updates for each new exploration area, leading to slow convergence, high computational cost, and a lack of mechanisms to share prior knowledge across different geological settings, thereby limiting its efficiency and generalization capability. To further accelerate convergence and enhance cross-area generalization, we propose a meta-learning-based implicit full waveform inversion method, referred to as Meta-learning-enhanced implicit full waveform inversion (Meta-IFWI). In this framework, the subsurface velocity model is represented using an implicit neural network with periodic activation functions (SIREN), while a meta-learning strategy is employed to pretrain a single network on multiple velocity inversion tasks. Through this process, the network learns shared inversion priors and rapid adaptation strategies across different geological scenarios. For a new inversion task, the pretrained Meta-IFWI model can be efficiently adapted to the observed seismic data with only a few gradient updates, significantly reducing the number of iterations required for inversion. Numerical experiments conducted on in-distribution models, including layered synthetic models and the Overthrust model, as well as out-of-distribution complex models such as Marmousi 2, demonstrate that, compared with conventional IFWI, the proposed Meta-IFWI achieves improved inversion accuracy while substantially accelerating convergence and reducing computational cost. Moreover, Meta-IFWI exhibits enhanced robustness and stronger cross-area generalization capability.

Geoscientists often solve inverse problems to estimate values of parameters of interest given relevant data sets. Bayesian inference solves these problems by combining probability distributions that describe uncertainties in both observations and unknown parameters, and we require that the solution provides unbiased uncertainty estimates in order to inform risk-based decisions. It has been known for over a century that employing different, but equivalent parametrisations of the same information can yield conditional probabilities that are mathematically inconsistent, a property referred to as the BK-inconsistency. Recently this inconsistency was shown to invalidate the solutions to physical problems found using several well-established methods of Bayesian inference. In this study, we explore the extent to which this inconsistency affects solutions to common geophysical problems. We demonstrate that changes in parametrisations result in inconsistent conditional probability densities, even though they represent exactly the same information. We show that this can affect Bayesian posterior solutions dramatically across various geoscientific problems using real and synthetic data. Given that deterministic inversion is often equivalent to finding the maximum a posteriori solution to specific Bayesian problems (the mathematical equations to be solved are identical), the BK-inconsistency also results in inconsistent solutions to deterministic inverse problems. Indeed, we show that solutions can potentially be designed, simply by changing the parametrisation. This study highlights that a careful rethinking of Bayesian inference and deterministic inversion may be required in physical problems: the effects that we demonstrate are likely to affect past and present inverse problem solutions in a variety of different fields of application.

Identifying the physical mechanism driving blazar flares remains a central challenge in high-energy astrophysics. We show that the energy dependence of the standard deviation of the polarization angle variability ($σ_\text{PA}$) provides a powerful and robust discriminator of blazar flaring mechanisms. Using particle-in-cell-integrated polarized radiative transfer simulations, we perform to-date the most rigorous statistical analyses of polarization variability. We demonstrate that magnetic reconnection and magnetized turbulence imprint qualitatively distinct energy dependence of $σ_\text{PA}$ that directly reflect their different magnetic field evolution and particle transport. Reconnection predicts higher $σ_\text{PA}$ with higher photon energy till the synchrotron spectral peak, whereas turbulence produces nearly flat $σ_\text{PA}$ across the synchrotron spectral component. These trends are resilient to realistic observational limitations. Applying our results to optical and IXPE data of Mrk~421 and 1ES~1959+650, we find strong evidence for reconnection-driven flares embedded in a turbulent blazar zone. Energy-dependent $σ_\text{PA}$ emerges as a decisive new probe of particle acceleration in relativistic jets.

Cell invasion and spatial pattern formation are two distinct manifestations of cellular self-organisation in development, regeneration, and disease. Here, we develop and analyse a unified theoretical framework that links these two seemingly different behaviours within a single mechanistic model for adhesion-mediated self-organisation in growing cell populations. Using a multiscale analysis, we show that the balance between cell-cell adhesion, self-diffusion, and proliferation controls the emergence of distinct collective dynamics. We find that for weak adhesion, tissues invade through stable monotone fronts. As adhesion increases, invasion slows, fronts become unstable, leading to aggregates and spatial patterns emerging behind the advancing edge. In two spatial dimensions, these instabilities generate fingering morphologies reminiscent of dysregulated invasion in cancer. Crucially, we show that density-dependent regulation of adhesion suppresses these instabilities and restores cohesive tissue expansion. Together, our results identify adhesion strength and its regulation as key determinants of whether tissues invade cohesively or fragment into patterns, and provide a unified framework for understanding collective migration, morphogenesis, and dysregulated growth.

NASA's Habitable Worlds Observatory (HWO) will search for biosignatures on Earth-like exoplanets using reflected light spectroscopy. A critical instrument design parameter is resolving power, which must balance biosignature detectability against exposure time and detector noise constraints. We assess the resolving power needed to detect and characterize key biosignature gases and habitability indicators including O$_2$, O$_3$, H$_2$O, CH$_4$, CO$_2$ and CO across atmospheres representing the Archean, Proterozoic, and Phanerozoic Earth. We combine analytical detectability calculations spanning spectral resolutions ($λ/Δλ$) $R=20$-$5000$ with atmospheric retrievals using the rfast radiative transfer model and pyEDITH exposure time calculator for realistic wavelength-dependent noise modeling. In the visible ($0.4$-$1.0$ $μ$m), the nominal resolution $R_{Vis}=140$ is sufficient for detecting O$_2$ in Phanerozoic-like atmospheres. Higher resolutions could theoretically reduce exposure times for low-O$_2$ Proterozoic atmospheres, but require $>10\times$ reductions in dark current and could increase H$_2$O detection exposure times by $\sim 2\times$, penalizing the foundational habitability constraint that anchors downstream biosignature searches. The most efficient path for low-O$_2$ atmospheres may instead be indirect inference via O$_3$, whose Hartley-Huggins bands are detectable at $R_{UV}\sim 7$. In the near-IR ($1.0$-$1.7$ $μ$m), $R_{NIR}\geq40$ is necessary to avoid a degeneracy between CO$_2$ and CO that could produce false positive detections of abundant CO. The nominal $R_{NIR}=70$ is sufficient for characterizing all Earth-through-time cases. These results support HWO's current baseline resolution choices and provide actionable guidance for finalizing spectrometer requirements while maintaining technological feasibility for the search for life on exoplanets.

We study the power of quantum witnesses under perfect completeness. We construct a classical oracle relative to which a language lies in $\mathsf{QMA}_1$ but not in $\mathsf{QCMA}$ when the $\mathsf{QCMA}$ verifier is only allowed polynomially many adaptive rounds and exponentially many parallel queries per round. Additionally, we derandomize the permutation-oracle separation of Fefferman and Kimmel, obtaining an in-place oracle separation between $\mathsf{QMA}_1$ and $\mathsf{QCMA}$. Furthermore, we focus on $\mathsf{QCMA}$ and $\mathsf{QMA}$ with an exponentially small gap, where we show a separation assuming the gap is fixed, but not when it may be arbitrarily small. Finally, we derive consequences for approximate ground-state preparation from sparse Hamiltonian oracle access, including a bounded-adaptivity frustration-free variant.

The Dark Energy Spectroscopic Instrument (DESI) provides an unprecedented opportunity to test deviations from general relativity (GR) that introduce a new physical scale within its redshift range. Using the connection between a Yukawa-like potential and the Hu-Sawicki $f(R)$ model, we place strong constraints on the range of a hypothetical fifth force mediated by a massive scalar field. We analyze the power spectrum measurements from DESI Data Release 1 using a baseline EFT model that employs the fkpt approach for the loop integrals. We find no evidence for deviations from GR and obtain the constraint $\log_{10} |f_{R_0}| < -4.59$ (95\% C.L.). This corresponds to an upper bound at redshift zero on the scale at which corrections to GR become important, $λ< 17.81$ Mpc, or equivalently, a lower bound on the mass of the additional gravitational mediator of $m_ϕ> 3.60 \times 10^{-31}$ eV. We find that the modified gravity parameter $f_{R_0}$ is largely orthogonal to the cosmological parameters in the model, such that no additional projection effects relative to the GR case are introduced in this Full-Shape analysis. Furthermore, a second modified gravity parameter, the power index $n$, which modulates the time-variation of the associated mass, is found to be consistent with previous analyses that fixed it to unity. Adding DESI BAO data or other cosmological probes does not significantly change these results. The conclusions remain similar if the background evolution is described by evolving dark energy instead of a cosmological constant. Additionally, we test the robustness of the baseline model by varying the maximum wavenumber used in the Full-Shape analysis and analyzing the DESI targets separately. Finally, we analyze the degeneracies between the modified-gravity parameters and the sum of neutrino masses.

Knots and links represent a fundamental motif of non-local connectivity that permeates the physical sciences from string theory to protein folds. While spectral braiding has been explored in two-band non-Hermitian models across various platforms, its direct simulation and characterization on programmable quantum hardware, particularly beyond two strands, remains a formidable challenge due to the limitations of variational optimization in these systems. Here, we introduce a family of non-Hermitian multi-band twister models and implement a non-variational protocol to characterize their complex braided band structures on a programmable superconducting quantum processor. By mapping the winding of eigenstates to the spectral topology, we devise an efficient measurement strategy that extracts braid information, including braid words and knot invariants like the Alexander and Jones polynomials, without requiring full spectral tomography or repeated optimization. We experimentally demonstrate the reconstruction of complicated knots and links such as the Hopf chain and Solomon's knot. Our approach provides a general framework for investigating exotic non-Hermitian topology on near-term quantum devices, opening a route to simulate more sophisticated topological structures in knot theory.

JWST has shown a large diversity in warm Jupiter spectra, despite only small variations in the planetary parameters. However, the main driver of this diversity remains unclear. We aim to identify the mechanisms responsible for the spectral difference of three warm Jupiter-size exoplanets observed by JWST: whereas WASP-80b appears mostly cloud-free, both WASP-107b and WASP-69b have spectra dominated by clouds. We model each planet using the same framework, ADAM (formerly SPARC/MITgcm), which solves for the interactions among cloud transport, radiative transfer, and atmospheric circulation in 3D. We investigate the role of three condensate species, Na$_2$S, KCl, and MgSiO$_3$, and four particle sizes (0.1, 1, 5, and 10 $μ$m). Clouds settle deeper in the atmosphere of the higher-gravity planet WASP-80b than in WASP-107b, reproducing their spectral difference naturally. For WASP-107b, three clouds can reproduce the NIRCam observations: 5 $μ$m Na$_2$S, 1 $μ$m KCl, and 5 $μ$m MgSiO$_3$ models. However, these cannot match the scattering slope observed at shorter wavelengths in NIRISS and the possible silicate feature in the MIRI bandpass, suggesting a multi-modal distribution of clouds. Our model predicts that small silicate particles should be homogeneously distributed and thus cannot account for the difference between the two limb spectra in the MIRI bandpass. Finally, applying the same model to WASP-69b does not yield a partially cloudy dayside solution that fits the emission spectra, as proposed in a previous study. Coupling among 3D circulation, clouds, and radiative transfer can enhance the spectral diversity of warm Jupiter exoplanets, particularly through changes in cloudiness with gravity. The combination of multi-phase, wide-wavelength coverage and models that couple clouds, circulation, and radiative transfer is key to advancing our understanding of these new objects.

Long-range interactions between emitters give rise to collective phenomena, including superradiance, spin squeezing, and coherence protection, that are important to both fundamental physics and quantum technologies. Despite progress in cold atoms, coherent cavity-mediated all-to-all interactions have not yet been realized in a solid-state ensemble. Here we demonstrate such interactions in a $^{171}$Yb$^{3+}$:CaWO$_4$ crystal coupled to a microwave resonator, observing superradiant emission on resonance and unitary one-axis twisting dynamics in the dispersive regime. The same interaction also opens a many-body energy gap that suppresses inhomogeneous dephasing, extending the ensemble Ramsey coherence time from tens of microseconds to milliseconds without decoupling pulses. These results establish a solid-state platform for collective many-body physics with direct implications for quantum technologies. Specifically, the observed one-axis twisting dynamics opens a path towards spin squeezing for entanglement-enhanced quantum metrology, and the extended coherence due to gap-protection is relevant for both microwave photon storage and precision measurement.

Ghost imaging uses two light beams correlated in the transverse position, time, or frequency to create an image of a spatial, temporal, or spectral object. We propose a scheme of time-to-space ghost imaging for creating a spatial image of a temporal object, enabled by two spatio-temporally correlated light beams. Assuming a spatio-temporal Gaussian Schell model for the description of the source, we obtain analytical expressions for the point-spread function of the system and its temporal resolution. We show how the required source of partially coherent light can be realized by a combination of a diffraction grating and a spatial light modulator. As follows from our analysis, the temporal resolution of a time-to-space imaging system is determined by the duration of the laser pulses used and the transverse coherence length imposed by the spatial light modulator, does not depend on the resolution time of the photodetectors, and can reach the sub-picosecond range.

We investigate the effect of spatial exchange anisotropy on the spin-$1/2$ kagome antiferromagnet using Schwinger-boson mean-field theory. The anisotropy is introduced by strengthening the Heisenberg exchange along one set of nearest-neighbor bonds relative to the other two, and is controlled by a parameter $δ$ that measures the deviation from the isotropic limit. Incorporating the reduced lattice symmetry, we construct the corresponding projective-symmetry-group ansätze and focus on representative $0$- and $π$-flux states connected to the conventional $q=0$ and $\sqrt{3}\times\sqrt{3}$ kagome states. We find that anisotropy predominantly reconstructs the low-energy spinon sector, leading to a strong softening of the lowest spinon branch and a downward shift of the two-spinon continuum. At sufficiently large $δ$, the spinon gap closes at ansatz-dependent values, signaling an instability toward spinon condensation and the onset of magnetic order. From the soft Bogoliubov eigenmodes, we reconstruct the associated incipient spin textures and show that the resulting magnetic orders are intrinsically anisotropic, with suppressed moments on strongly coupled bonds and enhanced moments on more weakly connected sites. These results provide a microscopic picture of how exchange anisotropy drives the transition from kagome spin-liquid states to magnetic order, and offer a framework for interpreting recent experiments on anisotropic kagome materials, particularly titanium-based spin-$1/2$ compounds.

We consider the problem of quantum channel certification to unitary, where one is given access to an unknown $d$-dimensional channel $\mathcal{E}$, and wants to test whether $\mathcal{E}$ is equal to a target unitary channel or is $\varepsilon$-far from it in the diamond norm. We present optimal quantum algorithms for this problem, settling the query complexities in three access models with increasing power. Specifically, we show that: (i) $Θ(d/\varepsilon^2)$ queries suffice for incoherent access model, matching the lower bound due to Fawzi, Flammarion, Garivier, and Oufkir (COLT 2023). (ii) $Θ(d/\varepsilon)$ queries suffice for coherent access model, matching the lower bound due to Regev and Schiff (ICALP 2008). (iii) $Θ(\sqrt{d}/\varepsilon)$ queries suffice for source-code access model, matching the lower bound due to Jeon and Oh (npj Quantum Inf. 2026). This demonstrates a strict hierarchy of complexities for quantum channel certification to unitary across various access models.

Continuous data assimilation (CDA) nudges observational data into governing equations to recover the underlying flow and improve predictions. Existing rigorous CDA analyses focus primarily on incompressible flows, yet no physical flow is perfectly incompressible. Approximating a slightly compressible flow with an incompressible model introduces non-negligible model errors. Data assimilation for compressible flows remains challenging due to strong nonlinearities and the presence of shocks. We design an algorithm that addresses the limitations of velocity-only nudging for slightly compressible flow. This work incorporates both velocity and pressure data from the slightly compressible flow and nudges both quantities into the incompressible Navier--Stokes equations. Our analysis shows that the model error decays exponentially in the initial error, with an asymptotic residual of order $\mathcal{O}(H)$, where H denotes the observation resolution. The analysis also identifies a scaling for the pressure nudging parameter $μ_1 = O(1/H^2)$ that ensures effective assimilation. We validate the theoretical results through a suite of numerical experiments: a convergence study confirming optimal rates, a modified Taylor--Green vortex benchmark demonstrating synchronization of energy, enstrophy, and pressure, and an acoustic wave propagation test that isolates the role of pressure nudging and achieves a $97.9\%$ reduction in pressure error relative to velocity-only assimilation. Together, these results provide a foundation for discrete error estimates and realistic compressible applications.

We investigate, both analytically and numerically, the scattering of quasi-one-dimensional quantum droplets from Pöschl-Teller potential wells and barriers. For attractive wells, we find a sharp transition between complete reflection and transmission at a critical incident velocity for both small and large flat-top droplets. The scattering interactions differ: small, soliton-like droplets form a spatially symmetric trapped mode at the critical velocity, showing their compressibility and coherence characteristics, while large droplets develop a spatially asymmetric trapped state, revealing incompressibility and internal structure. The critical velocity depends non-monotonically on atom number: it rises in the small, compressible-droplet regime, falls in the incompressible, flat-top regime, and turns at the crossover point. We also show that the reflectionless well generates a $π$-phase shift, strongly altering droplet-droplet collisions relative to free space. The persistence of a confined mode after collisions between trapped and incident droplets depends sensitively on their relative phase. For the repulsive barrier, we identify regimes of complete reflection, partial return, and full transmission, depending on incident velocity, barrier height, and particle number. Our predictions match direct numerical simulations in all cases.

Foreground removal remains an ongoing challenge in radio cosmology, and increasingly sensitive experiments necessitate more robust analysis techniques. In this work, we model simulated data from a single-dish intensity mapping experiment, and use the Gibbs sampling and Gaussian constrained realisation (GCR) techniques to draw samples from the posterior probability distribution of the model parameters. This allows for a separation of the foregrounds and 21 cm signal at the map level, as well as recovery of the 1-dimensional HI power spectrum to within statistical uncertainties. Despite the model consisting of over 2 million free parameters in the example presented here, these methods allow us to sample from the Bayesian posterior at a rate of $<30$ seconds per iteration. This framework is also resilient to frequency channel flagging (e.g. due to RFI excision), with the GCR steps effectively in-painting the missing data with statistically-consistent model realisations. The power spectrum is recovered accurately in the presence of strong foreground contamination and RFI flagging -- the estimate falling within $2σ$ of the true model in our example, similar to the commonly-used transfer function correction method. Statistical realisations of foreground and HI maps are also recovered, with associated uncertainties available from the full joint posterior distribution of all parameters.

The layered delafossite-like antiferromagnet AgCrSe$_2$ is a superionic conductor at high temperatures and has been reported to exhibit anomalous Hall behavior and Kondo physics at low temperatures. These extraordinary transport properties have been established almost exclusively on single crystals grown by chemical vapor transport, raising questions about the role of growth-induced off-stoichiometry. Using elemental analysis, single-crystal X-ray diffraction, and magnetization measurements, we show that such crystals are indeed systematically off-stoichiometric, with a general composition of Ag$_{1-x}$Cr(Se$_{2-y}$Cl$_y$) ($x \approx y \approx 0.08$) arising from the use of CrCl$_3$ as a transport agent. This off-stoichiometry manifests in altered magnetic properties, most notably a suppressed Néel temperature of 46\,K compared to 58\,K in stoichiometric polycrystalline samples prepared by solid-state synthesis. By optimizing an Ag/Se self-flux growth method, we obtained large single crystals of AgCrSe$_2$ that recover the magnetic transition temperature and saturation field of stoichiometric powder samples. These results establish self-flux growth as a route to high-quality stoichiometric AgCrSe$_2$ single crystals and provide a reliable platform for reassessing whether the reported anomalous transport phenomena are intrinsic or arise from off-stoichiometry.

The 21cm emission line from neutral hydrogen (HI) contained within galaxies provides a way to make accurate spectroscopic redshift determinations in the radio part of the spectrum. Large radio arrays such as SKA-MID are coming online that will have the sensitivity and survey time required to catalogue hundreds of thousands to millions of HI galaxies, opening up the possibility of studying the cosmological large scale structure using this technique. The expected number counts and clustering properties of the galaxies are still quite poorly understood however. We use three different simulated galaxy catalogues to predict the properties of the HI galaxy distribution that SKA-MID will be able to observe, along with estimates of the error on these predictions due to modelling uncertainty. The simulations in question are from S$^3$-SAX (semi-analytic models based on the Millennium dark matter-only simulation); GAEA (an updated semi-analytic model partially calibrated on hydrodynamical simulations); and IllustrisTNG (a hydrodynamical simulation). We present predictions for galaxy number counts as a function of sensitivity cut and redshift, and use these to forecast the cosmological performance of a proposed SKA-MID cosmological survey. Finally, we fit a halo occupation distribution model to low-redshift angular correlation functions to constrain clustering properties of multiple sub-volumes of the simulations to gain insight into the expected variation (sample variance) over smaller survey areas.

Observing the Epoch of Reionisation using 21cm radio interferometry has proven to be a challenging task. Extraction of the extremely faint redshifted signal is complicated by the presence of bright foregrounds, radio frequency interference (RFI), and systematic artefacts. We discuss the challenge of accounting for systematic effects, particularly cable reflections, that appear in the visibility data obtained from 21cm interferometers. Cable reflections cause attenuated copies of the foreground signal to appear outside the 'foreground wedge' region in which foreground contamination is supposed to be localised. We build on the hydra-pspec Gibbs sampler to implement a model of the systematics as a multiplicative effect in delay-fringe rate space. We include this model in the inference of the joint posterior distribution, in addition to the 21cm signal, its power spectrum, and foregrounds. This allows the systematics contribution to be marginalised, rather than filtering it out and causing additional signal loss. We demonstrate the method on simulated visibility data for a single baseline, showing that the 21cm delay power spectrum can be recovered well regardless of the location of the systematics in delay-fringe rate space. Our implementation is suitable for modelling other multiplicative factors on the visibilities, e.g. residual gain errors.

The Standard Model (SM) predicts the universality of lepton couplings with the electroweak gauge bosons. Semileptonic decays of $b$-hadrons provide a powerful framework for testing the SM and probing possible New Physics effects. In particular, the processes mediated by charged-current interactions benefit from a relatively large branching fractions and theoretically well-controlled hadronic matrix elements. This contribution presents three recent results from the LHCb experiment: the first measurement of the ratio of branching fractions $\mathcal{R}(D^{**})$ using $B^{-} \to D^{**0} τ^{-} \barν_τ$ decays, the determination of the branching fraction for $Λ\to p μ^{-} \barν_μ$ and the extraction of form-factor parameters from $B^0 \to D^{*-} μ^{+} ν_μ$ decays.

The study of Entanglement Asymmetry has emerged in recent years as a powerful tool to characterise the symmetry properties of quantum states in relation to a given charge operator through the lens of entanglement. While extremely powerful and general, the standard definition of asymmetry introduces significant non-Gaussian features in free-fermionic systems, leading to certain analytical limitations. In this work, we introduce an asymmetry measure that remains strictly within the Gaussian manifold and analyse its properties. In particular, we show that it quantifies the minimal distance between a Gaussian state and the manifold of symmetric Gaussian states. We further demonstrate that this measure captures the established dynamical signatures of entanglement asymmetry, such as the Mpemba effect, symmetry restoration, and the lack thereof. The Gaussian structure allows these novel asymmetry measures to be computed exactly using correlation matrix techniques, and to be described asymptotically through the quasiparticle picture. We also comment on the possibility of using charge fluctuations to characterise the asymmetry of a Gaussian state.

This is a brief overview of the connection between neutron skin thickness in finite nuclei and the equation of state of neutron-rich matter, with applications to neutron stars. Multiple experimental probes are discussed, including dipole polarizability, parity-violating electron scattering, heavy-ion fragmentation, quasi-free scattering, and ultraperipheral collisions. A consistent picture emerges from Bayesian analyses combining experimental data and energy density functionals, providing constraints on the symmetry energy and its slope.

Africa is the primary source of cyclonic vortices over the tropical Atlantic. Over both land and sea, these vortices are entwined with deep convective activity, with the majority being African Easterly Wave troughs. Their convective interactions have downstream impacts, since the same vortices provide the seed population for Atlantic basin tropical cyclone (TC) genesis. Understanding the dynamics of East Atlantic seed populations, particularly the processes that distinguish vortices which undergo cyclogenesis, is crucial for understanding the formation of Atlantic hurricanes and model representations of their populations. Here we investigate these questions in three one-year, atmosphere-only global km-scale Met Office Unified Model simulations. We use objective tracking algorithms to independently identify seed vortices, easterly waves, TCs, and Mesoscale Convective Systems (MCSs), benchmarking against reanalysis and satellite-derived climatologies. Despite the simulations displaying comparable continental vortex populations, we show that the highest-resolution simulation with explicit convection produces fewer, weaker hurricanes than coarser, parameterised counterparts due to a failure to amplify vortices crossing the West African coastline. We identify a failure to maintain strong top-heavy mass flux profiles experienced by seeds as the primary cause, demonstrating profiles' roles in low-level circulation development through vortex stretching. Using MCS tracks, we show that systematic differences in convective organisation between the simulations can explain the differences in mass flux profiles, and thus vortex evolution. Deficiencies in the explicit simulation stem from underestimation of MCS stratiform components, a bias shared with other explicit convection models; and a latitudinal offset between offshore seed vortex and MCS trains.

The pure-loss channel is a fundamental model for describing noise in bosonic quantum platforms. It is characterised by a single parameter, the transmissivity, which quantifies the fraction of the input energy that reaches the output of the channel. In realistic scenarios, however, such as free-space quantum communication, the transmissivity is not fixed but fluctuates from one channel use to another. In this setting, the overall channel is effectively described as a convex combination of pure-loss channels, known as a fading channel. Despite its practical relevance, the quantum Shannon theory of the fading channel has remained largely unexplored. Here, we address this gap, specifically investigating degradability, anti-degradability, entanglement breakingness, and capacities of the fading channel. Of particular relevance to practical quantum-internet applications, we prove that entanglement distribution and quantum key distribution can always be achieved at a strictly positive rate over any fading channel, no matter how noisy it is or how strongly the transmissivity fluctuates, provided the channel is not completely noisy. Moreover, we prove that thermal states, which are optimal for a broad class of static bosonic Gaussian channels, fail to achieve the entanglement-assisted classical capacity of fading channels: non-Gaussian Fock-diagonal states strictly outperform all Gaussian encodings. Most strikingly, we identify regimes where the coherent information of thermal inputs vanishes, while optimized non-Gaussian states achieve strictly positive values, thereby activating the channel for quantum communication. For a paradigmatic binary fading model we establish this result analytically, deriving the exact capacity-achieving state in closed form. For general fading distributions, we design an iterative variational algorithm to optimize the coherent and mutual information.

This study presents a versatile ontology and a useful codification scheme for describing all kinds of engineered living materials (ELMs). The different components of the ontology, namely: families according to the taxonomy for ELMs, industrial applications and synthesis or processing methods, are systematically organized, enumerated, classified, codified and explained. The methodic application of the ontology to a set of 100 relevant examples of ELMs helps to demonstrate its utility and adaptability to many different types of ELMs with a wide range of industrial applications and obtained through numerous synthesis and processing methods. This proves that the developed ontology and codification schemes, with the glossary provided to support its implementation and application, can serve as a comprehensive classification tool for the emergent field of ELMs. Furthermore, the usability of the ELMs ontology and codification by a generative artificial intelligence (AI) is explored and validated by different means, checking that both natural language and the codification are understandable for describing ELMs, verifying that the generative AI adequately codifies examples of ELMs according to the ontology, and validating the synergic applicability of the ontology and codification with generative AI tools for illustrating novel ELMs and supporting their conceptual design. This study is expected to provide a universal language to facilitate communication in the ELMs field and to foster the discovery of new ELMs and related innovations, hoping it may accelerate scientific and technological discoveries.

Moiré superlattices of transition-metal dichalcogenides (TMDs) host strongly interacting Bose-Fermi mixtures in which bosonic excitons coexist with correlated electron lattices. Using ultrafast, time- and energy-resolved photoluminescence (PL) and reflectance microscopy, we show that strong exciton-electron and exciton-exciton repulsion can enable collective ballistic exciton transport in a WSe$_2$/WS$_2$ heterobilayer. The ballistic transport is energy-selective: repulsive interactions drive excitons into a higher moiré exciton band, where enhanced intersite hopping enables rapid spatial expansion. Correspondingly, the exciton mean-squared displacement (MSD) exhibits a quadratic time dependence ($\propto t^2$). This ballistic expansion is enhanced at fractional electron fillings where the electrons form generalized Wigner-crystal (GWC) orders. Afterwards, the system transitions into a mixed electron-exciton Mott state as Auger recombination and density depletion conclude the ballistic expansion. A one-dimensional Bose-Fermi Hubbard model solved using density-matrix renormalization group (DMRG) qualitatively reproduces the measured exciton transport and time-dependent response. It further confirms that strong cross-species interactions allow the electron crystal to perforate the exciton Mott background, accelerating its melting and enhancing exciton motion. Our results establish moiré TMDs as highly tunable platforms for realizing strongly interacting Bose-Fermi mixtures, which we employ here to demonstrate real-time control of intertwined bosonic and electronic order and to establish a route to the exciton insulator-fluid transition.