Papers

Gravitational waves from binary black hole mergers remain among primary sources for ground-based and space laser interferometers. Primordial binary black holes (PBHs) can form binaries in the early Universe or at the matter-dominated stage in virialized dark matter halos at redshifts $z\sim 7-15$. We study enhancement of primordial binary PBH merger rate in virialized dark matter halos due to baryon accretion in the post-recombination epoch within two accretion models onto individual PBH – Bondi-Hoyle-Littleton (BHL) and Park-Ricotti (PR), representing two extreme cases of the accretion efficiency. We calculate modification of the initial PBH mass function and their fractional contribution to dark matter. A significant enhancement in the binary PBH merger rate is found for the late three-body channel, which was previously treated as subdominant. In the case of delayed virialization onset at $z<10$, merger rates of dynamically formed PBH binaries are limited by the existing LVK binary BH detections. An increased merger frequency is revealed for PBH binaries with highly asymmetric mass ratios. We also calculate expected detection rates of binary PBH mergers for the TianQin space-based gravitational-wave interferometer and show them to be optimistic in the BHL accretion case even for very low initial PBH abundances $f\sim 10^{-6}$.

Core-collapse supernova gravitational waves may carry information about the dense matter equation of state (EoS), which describes the relation between pressure, density, temperature, and composition. This work tests a crucial question for physical inference: can a machine learning model trained on a finite simulation catalogue predict EoS parameters for an EoS family that was absent during training? Under standard random cross-validation, a LightGBM regressor appears highly successful, yielding $R^2=(0.70,0.67,0.60)$ for the nuclear incompressibility, symmetry energy, and slope parameter $(K_0,J,L)$. However, under Leave-One-EoS-Out (LOEO) validation, where all waveforms from a single EoS are withheld, the model fails, yielding mean absolute errors of $(44.57,3.19,30.54)$ MeV and negative pooled $R^2$ scores, performing worse than a baseline mean predictor. This generalisation gap persists across linear models, random forests, neural networks, and gradient-boosted trees. Restricting inputs to physical features (bounce amplitude, bounce width, peak frequency) reduces template leakage, the memorisation of related templates shared across random splits, but does not restore reliable EoS extrapolation. In contrast, a progenitor mass case study shows that classification generalises to unseen rotation speeds, while continuous mass regression compresses predictions towards the catalogue interior. These results demonstrate that while machine learning successfully interpolates within current waveform catalogues, this does not imply robust physical inference for unseen EoS models. Future pipelines should adopt leave-family-out validation, wider simulation coverage, and physics-aware inference frameworks.

Recent baryon acoustic oscillation (BAO) measurements from the Dark Energy Spectroscopic Instrument (DESI), in combination with CMB and supernova data, show a mild preference for dynamical dark energy over flat $\Lambda$CDM. They can also drive the best-fit effective neutrino mass to unphysical negative values, motivating models that mimic this effect through late-time expansion physics. The sign-switching cosmological constant ($\Lambda_s$CDM) model addresses this by introducing an AdS-like negative vacuum energy density at high redshifts ($z > z^\dagger$) that transitions to a dS-like positive density at low redshifts. While original fits assumed a discontinuous step function transition, we generalise the dynamics using a smooth hyperbolic tangent parametrisation, $\Lambda(z) \propto \tanh[\Delta(z^\dagger - z)]$. We constrain the transition redshift $z^\dagger$ and smoothness parameter $\Delta$ using background distance data from DES-SN5YR (with Dovekie recalibration) and DESI 2024 BAO. We further incorporate a compact redshift space distortion (RSD) $f\sigma_8$ compilation. The joint data do not prefer the smooth sign-switching model over flat $\Lambda$CDM, yielding nearly identical $\chi^2_{\text{min}}$ values, while information criteria penalise the additional parameters. The transition smoothness remains unconstrained and dominated by the prior volume ($\Delta = 24.75^{+17.42}_{-17.48}$), indicating that current data cannot distinguish between a sharp transition and a smooth dynamical crossover. This work does not directly constrain the physical sum of neutrino masses $\sum m_\nu$; rather, it shows that current late-time background and growth data alone cannot resolve the transition details. We discuss the implications of this null detection and present projections for next-generation surveys.

Modern and next generation supernova cosmology analyses rely on end to end simulations to train photometric classifiers, characterise selection effects, validate light curve models, and calibrate distance bias corrections. Standard closure tests based on global Hubble diagram summaries can miss multivariate structure that remains in post correction residuals. We introduce a supervised machine learning closure audit that tests whether measured observables can predict the bias corrected Hubble residuals $\Delta\mu$. We apply the audit to LSST Type Ia supernova simulations from two independent analyses: the M23 mock data sets of Mitra et al. (2023), with spectroscopic redshift and photometric redshift samples, and the predominantly photometric LSST like M25 simulation of Mitra et al. (2025). Standard one dimensional Redshift binned diagnostics explain <1% of the residual variance ($R^2 < 0.01$), suggesting apparent closure. In contrast, out of fold LightGBM models recover up to 98.2% of the variance in the simulated residuals ($R^2 = 0.982$), revealing structured residual predictability. Applying the same audit directly to the real Dark Energy Survey 5 Year (DES 5YR) spectroscopic sample yields a held out $R^2 = 0.725$. SHAP feature attribution rankings are highly consistent between independently trained M25 and DES models (Spearman $\rho = 0.802$), with apparent magnitudes, signal to noise ratios, and redshift dominating the shared predictive hierarchy. The resulting scorecard provides a diagnostic protocol for comparing mock ensembles and real observations, identifying residual non closure before cosmological parameters are unblinded.

While the anomalous Hall effect was proposed as a transport fingerprint of altermagnets, it originates from the spin-orbit coupling-induced net magnetization, corresponding to a distinct magnetic phase termed spin-orbit magnetism. However, the microscopic mechanism enabling spin-orbit magnets to yield a prominent anomalous Hall response despite a vanishingly small net magnetization remains elusive. Here, by employing oriented spin group theory and spin-orbit-coupling tensor expansion, we systematically disentangle the perturbative behaviors of orbital and spin magnetizations with respect to spin-orbit coupling in altermagnets. Remarkably, we find that only if the opposite-spin sublattices are connected through a fourfold rotation, the orbital and spin magnetizations exhibit distinct perturbative orders. In these altermagnets, we further discover a coaxial Hall effect characterized by the induced spin and orbital magnetizations aligning parallel to the Néel vector, which we further demonstrate by first-principles calculations in the altermagnet KV$_{2}$Se$_{2}$O. This effect holds great promise for achieving deterministic switching of the Néel order under weak external fields. Our work provides a systematic symmetry approach to identify potential altermagnetic candidates combining a large anomalous Hall effect with minimal net magnetization, paving the way for high-performance, stray-field-free spintronic applications.

Density functional theory (DFT) often is the method of choice for simulating the electronic properties of extended solids and surfaces from first principles due to a favorable compromise between accuracy and computational cost. In the field of heterogeneous catalysis, DFT is indispensable for deriving mechanistic insights and understanding trends in surface reactivity. The accuracy of DFT for surface reaction energetics depends strongly on the exchange-correlation (XC) approximation. We show here that optimization of such XC functionals for surface binding energies can lead to a worse description of surface reaction barriers, unless important physical exact conditions are fulfilled.

Einstein's equations of general relativity are one of the most complicated set of equations in all of physics and, for all but idealized physical settings, can only be solved by numerical methods on high-performance computing systems. Generating such solutions is a veritable Odyssey in its own right with adventures across the fields of mathematical theory, physical interpretation and computing challenges. These endeavors came to fruition in the mid 2000s when the two-body problem of general relativity was finally solved. And not too soon, as these results and their follow-up investigations came to play a key role in the Nobel-Prize winning discovery of gravitational waves by LIGO in 2015.

We present a minimal analytic framework to investigate the star formation efficiency per free-fall time, $\epsilon_{\rm ff}$, in giant molecular clouds (GMCs), focusing on the origin of the observed clustering around $\epsilon_{\rm ff} \sim 0.01$. We model the time evolution of the turbulent velocity dispersion through a momentum balance between stellar feedback and turbulent dissipation, and show that this generically leads to a stable low-efficiency equilibrium with only weak dependence on global cloud properties. We extend the framework by including a phenomenological contribution from gravity-driven turbulence and find that both feedback- and gravity-driven motions converge to similar equilibrium states under typical GMC conditions. The efficiency can be expressed as the ratio between a gravitational velocity scale and an effective feedback velocity scale, providing a physically transparent interpretation of self-regulated star formation. The model provides a simple, physically motivated interpretation of observed gas-star formation scaling relations, including a Schmidt-like scaling at cloud scales and a Kennicutt-like scaling when averaged over cloud populations. Comparison with observed GMC properties shows agreement within a factor of a few and highlights the weak sensitivity of $\epsilon_{\rm ff}$ to cloud parameters. Despite its simplicity, the framework captures the leading-order interplay between turbulence, gravity, and feedback, and provides a physically transparent explanation for the origin and robustness of low star formation efficiencies in GMCs.

Spacing, the difference between consecutive order statistics, has two features that reflect the modality of the data. Consistent, stable values occur around modes while local increases mark the transitions between them. These features not only signal multi-modality, they also locate modes and anti-modes. Dimodal is an R package for detecting and evaluating these situations. It includes parametric feature models and bootstrap tests for spacing smoothed by low-pass filtering, non-parametric runs and permutation tests for the interval spacing, and a fusion of changepoints in the raw spacing. We introduce the analysis, describe the package, its implementation and performance, and apply it to identifying Kirkwood gaps in the asteroid belt. We also present ports of the software, with DimodalCPy a command-line program written in C with a Python interface.

Grid state qubits offer a hardware-efficient approach to large-scale fault-tolerant quantum computing. They access the information redundancy required for quantum error correction by exploiting the large Hilbert space naturally available in harmonic oscillators. Superconducting architectures are particularly suitable to implement grid state qubits due to their fast and high-fidelity operations. Grid states in superconducting circuits enable quantum error correction (QEC) with performance beyond break-even. However, the state preparation and measurements (SPAM) errors of grid states has been a significant limitation to computational performances. In this work, we leverage high-performance QEC to enable repeat-until-success state preparation of both cardinal and magic states of the single-mode grid-state qubit. We combine this with an improved measurement protocol that corrects for both finite-energy envelope and auxiliary qubit readout errors, and increases robustness to photon loss. Our experiments, using both techniques, achieve a combined state-preparation and measurement error below $10^{-3}$. This represents two orders-of-magnitude improvement over the state of the art, bringing this platform on par with standard SPAM error levels measured in transmon qubits.

The unavoidable dissipation of heat in electronic nanostructures is a crucial problem, specially when their operation requires low temperatures. It demands finding devices able to control and redirect the excess heat, ideally without perturbing the electrostatic environment. We propose three-terminal junctions working either as thermal routers or as thermal single-pole double-throw switches controlled by a single external knob. Two models are discussed based on resonant tunneling energy filters and different couplings to the heat source: (i) Phase-coherent contact via a scanning tip modulates the relative amount of the two output currents via position-dependent quantum interference; (ii) Coupling via a gate voltage tunable filter selectively switches one of the currents in the presence of dephasing. In the later case, we find that the heat flow using ideal filtering is bounded by fourth the open conductor current.

We present a study of femtoscopic correlation functions for $K^{-}d$ and $K^{+}d$ pairs, and compare our results with recent measurements by the ALICE Collaboration in both Pb-Pb and high-multiplicity $pp$ collisions. The kaon-deuteron wave functions are derived from scattering amplitudes using a unitarized chiral effective theory model describing the elementary interactions of $K^{\pm}$ mesons with nucleons. We then evaluate the $K^{\pm}d$ strong scattering amplitudes by solving the Faddeev equations within two distinct frameworks: the Impulse Approximation and the Fixed Center Approximation, which accounts for multiple scatterings. We also incorporate the long-range Coulomb effects between the kaon and the deuteron. We show that the $K^{-}d$ correlation function exhibits large sensitivity to both the size of the emitting source and the relative momentum of the pair, being heavily influenced by rescattering processes. In contrast, the $K^{+}d$ correlation function is dominated by the weakly repulsive $K^{+}N$ interaction, showing deviations from purely Coulombic behavior only at small emission source sizes. Our predictions are in agreement with the ALICE experimental data, and also with the energy-shift and width of the $1s$ level of the kaonic deuterium preliminary results from the SIDDHARTA 2 Collaboration.

We present new HI observations of Cloud-9 with the Five-hundred-meter Aperture Spherical Telescope (FAST), measuringvtotal flux of 0.35 +- 0.03 Jy km/s. Combined with Very Large Array (VLA) data, the HI shows a two-component structure: a compact, kinematically quiescent core and an extended envelope. The outer component exhibits a coherent velocity gradientvof ~25 km/s across ~7 kpc. The position-velocity structure does not support rotation; instead, the gradient is consistent with ordered large-scale motion, induced by environmental interaction with M94. The coexistence of a compact, kinematically quiescent core and an extended structured envelope is difficult to reconcile with a unbound or purely gaseous system. While the extended component is more naturally interpreted as environmentally shaped gas, the compact core suggests gravitational confinement beyond that provided by the observed baryonic content, without requiring strict long-term dynamical equilibrium. Deep optical limits further rule out a significant stellar component. Taken together, our results indicate that Cloud-9 is most naturally interpreted as a dark matter-dominated system undergoing environmental interaction. The observed morphology and kinematics are consistent with a stripped RELHIC scenario, in which a compact gas-rich core is embedded within an extended envelope shaped by ram-pressure interaction with the circumgalactic medium of M94.

Twisted bilayer graphene reconstructs from weak breathing corrugation to large common bending near the magic angle, but the origin of this collective crossover has remained unclear. Here we show that the crossover is a soft-mode condensation of layer-symmetric $A_1$ moiré flexural phonons: these modes soften on the breathing branch, lose stiffness near the magic angle, and freeze into the bending morphology. We call this mechanism Moiré Phonon Condensation (MPC). At $\theta=1.08^\circ$, it is extremely surprising that displacements of all 11164 atoms in the moiré supercell, with a maximum atomic position shift of 2.30 Angstrom, is captured by only two $A_1$ phonon modes at more than $99.5\%$ spectral weight. A first-harmonic continuum theory identifies a dimensionless control parameter of the phenomenon, showing that as the twist approaches the magic angle, the growing moiré length scale amplifies a smooth stress-bending competition until the flexural stiffness changes sign. Mode-resolved tight-binding calculations further show that the condensed phonon coordinates are electronically active. This work identifies MPC as a twist-controlled structural order parameter for moiré reconstruction.

We present the first panchromatic JWST transmission spectrum of an ultra-hot Jupiter, combining NIRISS and NIRSpec observations to constrain KELT-7\,b's atmospheric properties. We show evidence for charge migration in our NIRISS SOSS observation between 1–1.5~$\mu$m, a wavelength range crucial to test for enhanced H$^-$ previously inferred from HST WFC3/IR G141 observations. We mitigate charge migration by fitting the ramp after extracting 1D stellar spectra at the group level. This “late-ramp-fit” method accurately calculates KELT-7\,b's transmission spectrum between 1–1.5~$\mu$m at higher signal-to-noise. Using the transit-derived stellar mean density during stellar property inference reveals that KELT-7 is a $640\pm100$ Myr-old, $[\text{Fe}/\text{H}]=0.46\pm0.02$ star. Combined with NIRSpec and re-reduced WFC3/UVIS G280 data, our free retrieval analysis shows strong evidence for H$_2$O, CO$_2$, and TiO among high-temperature species, but not H$^-$ or clouds. Unaccounted-for systematics may therefore bias longer-wavelength WFC3/IR G141 transit depths shallower. Our free retrieval, two equilibrium retrievals, and self-consistent grid fit all prefer a high metallicity but find discrepant C/O ratios. Agglomerated together, we constrain a super-stellar $\text{M/H}=92^{+24}_{-23}\times$~Solar and C/O~$\leq0.9$, suggesting enhanced metal accretion in the later stages of KELT-7\,b's formation. Our GCMs explain the observed lack of limb asymmetry with superrotating jet-driven efficient horizontal mixing. The stark contrast between our panchromatic analysis and prior analyses on subsets of these data demonstrates the value of broad wavelength coverage for the comprehensive study of exoplanet atmospheres.

The paper is devoted to the study of the connection between the numerical dispersion arising in FDTD modeling of electromagnetic signal propagation in nondispersive homogeneous media optically different from vacuum and the Courant number in the 2D case. The main results are formulated in the form of four statements, as well as a number of corollaries and remarks that determine the nature of the numerical dispersion, the optimal value of the Courant number and the limitations of the method. It is proved that the optimal choice of the Courant number eliminates the numerical dispersion and extends the capabilities of the developed numerical algorithm to media, which refractive index lesser than refractive index of vacuum, as well as media with negative refraction.

Surface characterization is essential for revealing the structural, chemical, and physical properties of materials. Yet high-resolution methods such as atomic force microscopy (AFM) require complex equipment and delicate skillsets, making them particularly challenging for applications involving soft and biological materials in liquids. Here, we propose and validate an innovative motion-enabled sensing scheme that uses untethered micromotors as robotic probes to interact with surfaces or objects, with their motion responses serving as sensing signals for characterization. This sensing concept is validated by employing 3D electrokinetic tweezers, which control micro/nanoparticles with up to 20 nm positioning precision in solution, to drive Au microsphere motors along designed scanning paths. When the motors encounter local chemical or structural variations, their locomotion changes, allowing motion itself to serve for the detection. This effort enables untethered motors, for the first time, to detect biomolecular patterns and lithographically defined microridge arrays in liquid environments. The work establishes robotic locomotion as a new sensing modality, opening a wireless, solution-compatible, and low-cost technical pathway to standard surface sensing.

We herein study both the Joule-Thomson (JT) expansion process and the geodesic properties of a charged anti-de Sitter (AdS) black hole arising in modified gravity with nonlinear electrodynamic (NLED) sources. Our thermodynamic study reveals that the black hole charge has the most pronounced impact on the JT behaviour. The nonlinear electromagnetic sector together with the modified gravity parameters introduces further corrections to the inversion temperature and the associated cooling characteristics. At astrophysically relevant distances, the geometry closely reproduces expected outcomes.

We investigate how magnetic fluctuations influence spin-orbit torque in ultrathin-film magnetic heterostructures whose Curie temperature $T_C$ is suppressed by confinement. Above $T_C$, the damping-like contribution to spin-orbit field is significantly enhanced while the field-like contribution is suppressed, with the two contributions exhibiting opposite field dependencies. We show that these behaviors are consistent with fluctuation driven mixing between the longitudinal and transverse interfacial spin conductances, which enhances absorption of transversely polarized spin current by the ferromagnet. This mechanism can be activated below $T_C$ by engineering the microscopic magnetic state and by harnessing spin current-generated short-wavelength magnons, suggesting a spintronic analog of heat-assisted magnetic recording.

The three-dimensional galaxy power spectrum is a powerful probe of primordial non-Gaussianity (PNG) and additional general relativistic (GR) effects on large scales, which can be constrained by current and upcoming large-scale structure surveys. In this work, we forecast the measurability of local PNG and linear-order relativistic effects in the spherical Fourier-Bessel (SFB) power spectrum for DESI, Euclid, and SPHEREx surveys. A Chebyshev-decomposition scheme is employed to accelerate the multi-tracer SFB power-spectrum calculations. Fisher forecasts establish baseline constraints and test the sensitivity of $f_{\rm NL}$ constraints to SFB mode cuts and to the marginalization over primordial cosmological parameters, while simulated Bayesian inference is used to quantify the impact and measurability of relativistic effects. We find that neglecting GR effects can bias $f_{\rm NL}$ constraints at the $1$-$3\sigma$ level for Euclid and SPHEREx. The degeneracy between GR and PNG terms is strongly tracer dependent, with the degradation of $\sigma(f_{\rm NL})$ ranging from a few percent to nearly a factor of two when the GR amplitudes are varied. Lensing can be detected at high significance for several tracers, while multi-tracer analyses substantially improve the measurability of the Doppler term. Assuming GR, we show that relativistic clustering partially breaks the exact $b_\phi f_{\rm NL}$ product degeneracy present in Newtonian linear power-spectrum analyses, although the resulting $b_\phi$ constraints remain weak for the survey configurations considered. The joint PNG-GR inference consistently propagates uncertainty in $b_\phi$ into the marginalized $f_{\rm NL}$ constraint. This firmly establishes the path toward extracting cosmological information from ultra-large-scale galaxy clustering.

We investigate the Casimir response of a massive scalar field in a torsionless helicoidal spacetime with Levi-Civita connection. The background is ultrastatic and curved, with scalar curvature \(R=-2\Omega^2\), and its off-diagonal metric component induces a geometric coupling between angular and axial quantum numbers. We show that individual modes exhibit a linear helicoidal splitting, whereas the linear contribution cancels in the nonchiral vacuum sum. The leading Casimir correction is therefore quadratic in the twist and defines a helicoidal vacuum susceptibility after local ultraviolet subtractions. For a cylindrical Dirichlet cavity, we compute this scheme-defined susceptibility and the associated correction to the radial Casimir force. The results identify torsionless helicoidal geometry as a controlled setting in which mode-level chirality produces a finite quadratic response of vacuum fluctuations.

Primordial non-Gaussianities (PNGs) are a broad class of features in the initial density field that are connected to the particle physics of the early Universe. Measuring the amplitude of these features directly constrains fundamental physics from these earliest epochs and lends insight into energy scales that cannot be probed with terrestrial experiments. Using a new class of simulation methods, we propagate these signatures to their impact on the formation of non-linear structure and quantify the constraining power in non-Gaussian summary statistics of weak lensing, thermal Sunyaev Zeldovich (tSZ), and X-ray surveys. We use semi-analytic baryon models that consistently include astrophysical effects across all these observables, and use foreground modeling approaches that explicitly fold in correlations between the various components. We find that the tSZ and X-ray fields have significant information about PNGs, and additionally can help self-calibrate a broad set of nuisance parameters/models by breaking parameter degeneracies. Using the second and third moments of the lensing, tSZ, and X-ray fields, we find a factor of 2 improvement in PNG constraints relative to using lensing alone. Larger improvements are expected when including more scales and other complementary summary statistics. Our multi-wavelength map maker can be found at https://github.com/DhayaaAnbajagane/Vaanam. The simulations and software pipelines used in this analysis are publicly available.

We consider how the presence of conserved charges affects memory in a classical stochastic process, the symmetric exclusion process, with an observer constantly measuring a single site. We find that the observer's measurement record becomes Markovian (i.e., loses memory) on a timescale that depends on their knowledge of the global charge, namely the total particle number. In particular, when the global charge is unknown a priori, the observer's time series Markovianizes on a timescale constrained by their ability to learn it from their measurement record. Augmenting the observer's record with bulk measurements drives a charge-learnability transition between charge-fuzzy and -sharp phases. We show that the memory timescale tracks the learnability timescale, diverging in the fuzzy phase and remaining finite in the sharp phase.

Temperature plays a crucial role in solid-state materials synthesis, but there is currently no mechanistic theory to explain or predict which temperature is best to conduct a solid-state reaction. Reactions between powder precursors are conventionally assumed to be slow diffusion-limited processes; however, recent in situ experiments show that solid-state reactions can complete in minutes above a critical onset temperature. Here, we present evidence that a transient liquid phase forms above the metastable eutectic temperature, and that this non-equilibrium liquid serves as a fast diffusion medium to intermix precursors and initiate a solid-state reaction. This thermodynamic principle is agnostic to the structure or chemistry of the reactants, and can be applied towards the synthesis and manufacturing of a wide range of complex materials.

Debris disks are dusty structures around mature stars, primarily identified by infrared excesses in the stellar spectra. A subset, known as extreme debris disks (EDDs), exhibits stochastic infrared variability, believed to result from large-scale violent collisions that contribute to the formation or destruction of rocky planetary bodies. We analyze JWST and Spitzer mid-infrared spectra for 21 EDDs to investigate the connection between impact-produced dust mineralogy and the age and dynamical state of these systems during various stages of planet formation and evolution. Our findings indicate that EDDs contain significantly more optically thin, small dust grains compared to those typically seen in protoplanetary and debris disks. Predominantly submicron in size, these grains are thermally altered, as shown by their high levels of silica and crystalline silicate composition. Along with stochastic infrared variability, these features define EDDs as a subclass of debris systems where dust is generated from large collisions between Moon- and Mars-sized bodies. Our results not only provide diagnostic information about the physical conditions of violent events during terrestrial planet formation, aiding in differentiating the complex outcomes of these impacts, but also offer a potential marker for identifying planetary systems experiencing dynamical instability.

Quantum circuits under sufficiently weak monitoring purify on a timescale $T_P$ exponentially long in the system size. This slowness underlies a universal purification dynamics, whose quantitative description has so far required the replica trick, with a delicate analytic continuation. We show that monitored Clifford circuits on $L$ qudits of prime dimension $q$ bypass this construction entirely: in the scaling limit at fixed $x = t/T_P(L)$, purification reduces to the Markovian decay of the density-matrix rank, an exactly solvable death process descending from infinity. We compute the full scaling functions in compact form: all Rényi entropies collapse onto a universal curve $\langle S(x) \rangle$. Exact stabilizer simulations at $q=2,3,5$ confirm the predictions, with no fitting parameter for the global model and $T_P$ as the only fitted scale for local brick-wall circuits. Also, the replica problem amounts to a tilted version of the same Markov process, in agreement with exact computations from the Clifford commutant. Finally, the quantization of the rank leaves two hallmarks that distinguish Clifford dynamics from generic monitored circuits: the entropy fluctuations saturate at short scaled times $x\to0$ to an $O(1)$ variance, instead of vanishing, and observables develop a temporal modulation periodic in $\log_q x$, which cannot be captured by the replica approach.

Semi-device-independent quantum key distribution leaves the measurement devices uncharacterized while placing a trusted assumption on Alice's source. We formulate this source assumption operationally on Alice's four-preparation ensemble as a scalar bound on one of four physically motivated source tasks: full-label guessing, parity guessing, or their normalized composites with label exclusion. For the two-bit random-access code, we derive the exact classical frontier for each of the four source assumptions. Numerically, the BB84 strategy attains the maximal quantum deviation from all four frontiers, while the preparation-depolarized BB84 family and the direct-sum label-leakage family trace complementary branches of the arbitrary-dimensional quantum boundary for the two exclusion-assisted assumptions. Because all four task values are monotone under input-independent quantum channels, the same scalar source bound constrains every Bob–Eve extension compatible with the complete observed behavior. Using a three-setting extension that separates RAC testing from key generation, we obtain two dimension-independent security certificates over this feasible set: lower bounds on the conditional min-entropy and conditional von Neumann entropy, obtained respectively by direct optimization of Eve's key-guessing probability and by prepare-and-measure semidefinite relaxations based on the Brown–Fawzi–Fawzi variational bound. The exclusion-assisted assumptions certify positive key rates down to nearly vanishing preparation visibility, far beyond full-label or parity guessing alone. Under direct-sum label leakage, all four independently optimized rate bounds remain positive at every sampled incomplete-leakage point and vanish only at complete label revelation. These results show that robust semi-device-independent security depends not only on what Eve can identify, but also on what she can exclude.

While vacuum decay is traditionally described by Euclidean instanton methods, lattice simulations enable real-time modeling of dynamical observables relevant to cosmology and upcoming cold-atom analog experiments. We investigate the relationship between these approaches by extracting ensemble-averaged bubble profiles from zero-temperature simulations of a relativistic scalar field. Our observed profiles differ markedly from the bare Coleman bounce and classical thermal predictions. However, we find that instanton solutions in an appropriately renormalized potential reproduce both the measured profiles and their dependence on the UV cutoff, and predict decay rates consistent with simulations across the parameter range considered. The fact that a single renormalized Euclidean object captures these independent observables provides strong evidence that renormalization accounts for the discrepancy between the two formalisms, and establishes a quantitative link between instanton predictions, lattice simulations, and forthcoming empirical tests of vacuum decay.

Soft de Sitter Effective Theory is a well-motivated candidate for the correct effective late-time description of equal-time correlation functions in de Sitter space. In this work, we study its application to theories that enjoy classical conformal invariance, using the conformally-coupled $\phi^4$-theory as a toy model. While quantum effects generate non-trivial late-time dynamics in such models, we argue that it is not described by the standard construction of the effective theory as discussed thus far in the literature. We show that the tree-level matching of the trispectrum onto the effective theory does not fit into the expected power-counting scheme, and we contrast it with the matching of the tree-level bispectrum in the conformally-coupled $\phi^3$-theory, where it works consistently. We then propose a prescription to identify the leading superhorizon degrees of freedom in such theories, which should serve as the starting point for the construction of their late-time effective description. The interpretation of logarithms of the form $\log(-k\eta)$ in this context is briefly discussed.

Recent studies have identified a new component in black-hole ringdown from merging binaries, termed the direct wave. This component was argued to be tied to the dynamical source evolution near the black-hole horizon, and thus to encode horizon information. Yet a firm theoretical foundation for the direct wave has been lacking. Here we fill this gap by deriving direct waves from first principles in Schwarzschild spacetime, using the causal structure of the Green's function. We show that the direct wave does not vanish and is governed by the near-horizon source dynamics. Our results establish a theoretical basis for direct waves as a probe of near-horizon dynamics, complementary to quasinormal modes.