Cosmic shear is a powerful probe of cosmological distances, matter abundance and clustering in the low-redshift Universe. Cosmological parameter extraction from cosmic shear data is limited by our understanding of baryonic astrophysics, which severely restricts the range of scales used in such analyses. We show that the remaining scales are largely perturbative and can be accurately described with two-loop effective field theory (EFT) predictions. We present the first consistent analysis of the public cosmic shear data from the DES-Y3 catalogs in EFT at the two-loop order, renormalizing small-scale sensitivity in cosmic-shear predictions via a lensing-counterterm expansion and accounting for the intrinsic alignments of galaxies with spin-2 EFT predictions. We constrain the lensing amplitude competitively with standard (empirically-modeled) methods, finding $S_8 = 0.783^{+0.038}_{-0.031}$ ($S_8 = 0.802^{+0.031}_{-0.026}$ with BAO). The perturbativity of cosmic shear suggests novel opportunities for testing new physics with ongoing and upcoming cosmic shear experiments like Roman, Euclid, and LSST. As an example, we derive matter clustering constraints within the dynamical dark energy model from a combination of our DES-EFT cosmic shear likelihood, early-universe CMB priors, DESI BAO, and supernovae data, finding $S_8 = 0.824\pm 0.029$, indicating no $S_8$ tension in the growth of cosmic structure regardless of the underlying cosmological model and expansion history.

We report on a universal topological dichroism of chiral three-dimensional systems in response to the chirality of light. We show that chiral topological invariants result in integer-quantized dichroic excitation rate differences. Moreover, we demonstrate that such topological effects arise more generally from coupling optical chirality to higher tensor Berry curvatures and Dixmier-Douady invariants of quantum states, including Hopf indices. We finally propose an experimental setup that leverages superchiral light as a smoking-gun probe of chiral band topologies in three-dimensional materials. Our findings establish an optical route for probing to date unobserved chiral electronic band topologies.

The number of spatial degrees of freedom (NDoF) and channel strength in antenna systems are examined within a geometric framework. Starting from a correlation-operator representation of the channel between transmitter and receiver regions, we analyze the associated eigenspectrum and relate the NDoF to its spectral transition (corner). We compare the spectrum-based effective NDoF and effective rank metrics, clarifying their behavior for both idealized and realistic eigenvalue distributions. In parallel, we develop geometry-based asymptotic estimates in terms of mutual shadow (view) measures and coupling strength. Specifically, we show that while the projected length or area predicts the number of usable modes in two- and three-dimensional settings, the coupling strength determines the average eigenvalue level. Canonical configurations of parallel lines and regions are used to derive closed-form asymptotic expressions for the effective NDoF, revealing significant deviations from the spectral corner in closely spaced configurations. The results illustrate that these are physically grounded. The proposed theory and techniques are computationally efficient and form a toolbox for estimating the modal richness in near-field channels, with implications for array design, inverse problems, and high-capacity communication systems.

The kSZ effect has recently emerged as a powerful probe for precision cosmology through its ability to reconstruct the large-scale velocity field. In particular, the kSZ-reconstructed velocity-galaxy cross-correlation is sensitive to signatures of primordial non-Gaussianity through its imprint on the galaxy bias. The kSZ velocity reconstruction is performed using small-scale information from CMB temperature and galaxy overdensities. As the sensitivity of these measurements improves, systematic effects such as extragalactic foreground contamination present in CMB maps become increasingly important. We present a study of foreground biases to the kSZ-reconstructed velocity-galaxy cross-correlation. We derive the relevant foreground contributions from the thermal Sunyaev-Zel'dovich effect and the cosmic infrared background, modeling them using a halo model description of the dominant one- and two-halo terms. We compare our analytic predictions to measurements obtained using ACT DR6 temperature maps and DESI Legacy Imaging Survey galaxies, finding qualitative agreement. We introduce a parity-odd estimator constructed from antisymmetric combinations of tomographic velocity-galaxy correlations and show analytically that, under the Limber approximation, this estimator entirely cancels the foreground contamination while preserving the full cosmological signal without loss of signal-to-noise. Finally, we apply this parity-odd estimator to the data combination mentioned above and show that the fit to the velocity-galaxy correlation is dramatically improved compared to the analysis without mitigation; our estimator detects the signal at 11$σ$, with an amplitude consistent with recent studies.

The directed flow ($v_1$) of identified hadrons ($π^{\pm}, K^{\pm}, p, \bar{p}, ϕ, Λ$, and $\barΛ$) is studied in symmetric nuclear collisions (O+O, Cu+Cu, Ru+Ru, Au+Au, and U+U) at $\sqrt{s_{NN}} = 200$ GeV using the string-melting version of a multiphase transport model with improved quark coalescence. The mid-rapidity $v_1$-slope ($dv_1/dy$) and its charge-dependent splitting ($Δdv_1/dy$) between particles and anti-particles are investigated as a function of nuclear mass number ($A$) and collision centrality in both low-$p_\mathrm{T}$ (0.2$-$2.0 GeV/$c$) and high-$p_\mathrm{T}$ (2.0$-$5.0 GeV/$c$) regions. At low-$p_\mathrm{T}$, the $v_1$-slope shows weak system-size dependence, while at high-$p_\mathrm{T}$ strong system-size dependence is found and it becomes negative with nuclear mass number, reflecting the hard-soft asymmetry in particle production. The charge-dependent splitting $Δdv_1/dy$ reveals a striking baryon-meson dichotomy: baryon pairs ($p-\bar{p}$ and $Λ-\barΛ$) exhibit significant splitting that grows with system size, whereas meson pairs ($π^+-π^-$ and $K^+-K^-$) show minimal splitting. The effect of final state hadronic interactions on the $v_1$-slope is found to be negligible confirming that it is primarily generated during the partonic phase and coalescence process. A comparison of the AMPT results with measurements from the STAR experiment at RHIC in Au+Au collisions establish the transported quark contribution as a baseline for the observed charge-dependent $v_1$ splitting, on top of which electromagnetic field effects must be considered.

We present SNID-SAGE (SuperNova IDentification-Spectral Analysis and Guided Exploration), a framework for supernova spectral classification with both a fully interactive graphical interface and a scriptable command-line pipeline for large-scale processing. The pipeline combines deterministic spectral preprocessing, FFT-based cross-correlation against a curated template library, ranking of candidate matches using a composite quality metric, and consolidation of redshift and classification solutions into a single result with associated quality and confidence estimates. SNID-SAGE includes an upgradeable template library (about 6000 spectra), interactive line identification with velocity measurements, and optional natural-language summaries of classification results. We evaluate SNID-SAGE using two complementary tests: (i) leave-one-out cross-validation, in which each template spectrum is matched against the remainder of the library; and (ii) large-scale application to WISeREP spectra with valid coverage across the 4000-7000 A interval, irrespective of spectral type, comprising approximately 46 000 spectra, with redshift validation against known host-galaxy measurements where available. The full validation results and the SNID-SAGE framework are publicly available, supporting integration into spectroscopic survey workflows.

Multicomponent gel systems have garnered much interest due to their compelling mechanical properties in the past decade. Yet, some mechanisms associated with multicomponent gels, such as sequential gelation, have been explored primarily in the context of chemical nonreversible polymeric and protein gels than in physical reversible colloidal ones. In this study, we use mesoscale simulation techniques to model the sequential gelation of two-component colloidal systems whose components' interspecies and intraspecies electrostatic interactions can be modified independently. We show that by simply leveraging temporal control and interspecies interactions, we can construct markedly different networks; from double networks to mixed and core-shell composite structures of varying coarseness and heterogeneity natures. These findings present a compelling case for further exploration of multicomponent colloidal systems.

Floquet engineering provides a powerful pathway for creating non-equilibrium phases of matter with tailored electronic structures and properties through time-periodic driving. As the original theoretical prototype, graphene established the framework in which the Floquet topological insulator with light-induced anomalous Hall effect was proposed. However, the defining spectroscopic signature of Floquet engineering in graphene--light-induced hybridization (avoided-crossing) gap at Floquet band crossings, has remained experimentally elusive. Here, we report direct observation of Floquet-induced hybridization gap in monolayer graphene under resonant driving by a strong light field. Time- and angle-resolved photoemission spectroscopy reveals gap opening at Floquet band crossings, accompanied by coherent Floquet sidebands. The gap exhibits pronounced momentum anisotropy, featuring two Dirac nodes protected by the spatiotemporal symmetry and tunable by light polarization. These results provide long-sought experimental demonstration of Floquet band engineering in graphene, opening up opportunities for light-field engineered quantum phases in graphene and related materials.

We study the number entropy and quasiparticle width in one-dimensional quasiperiodic many-body localized (MBL) systems and observe slow dynamics that have previously been investigated in detail only in random systems. In contrast, quasiperiodic systems exhibit more structured growth of both observables. We identify the modulation of the Rabi oscillation amplitude of single-particle hoppings as the mechanism underlying the slow growth even deep in the MBL regime. This quantum amplitude modulation and associated beats arise from the interaction between single-particle hopping processes at different positions in the chain. Interestingly, this mechanism is not weakened by increasing the distance between particles and is generic to many-body quantum systems. We develop an analytical model based on the aforementioned mechanism that explains the observed dynamics at all accessible timescales and provides a microscopic picture of the slow dynamics in the MBL regime. Our results are consistent with the stability of the MBL phase in the thermodynamic limit.

We study dispersive decay for non-autonomous Hamiltonian systems. While the general theory for dispersion in such non-autonomous systems is largely open, it was shown \cite{kraisler2025time} that there exists a time-periodically forced one-dimensional Dirac equation with unusually slow dispersive decay rate of $t^{-1/5}$. It is to be expected that such behavior is not generic and requires a very particular forcing term; we provide a more general ansatz and systematic procedure to construct such an equation with a dispersive decay rate no faster than $t^{-1/10}$. Our limitations are purely algebraic and it stands to reason that arbitrarily slow decay, $t^{-\varepsilon}$ for every $\varepsilon > 0$, should be achievable.

Quantum coherence, as a direct manifestation of the quantum superposition principle, is a crucial resource in quantum information processing. Block coherence resource theory generalizes the traditional coherence framework by defining coherence via a set of orthogonal projectors. Within this framework, we investigates the construction and comparison of block coherence measures. First, we propose two universal methods for constructing coherence measures and introduce a two-parameter family of measures based on the $α$-$z$ Rényi relative entropy and a family of measures based on the Tsallis relative operator entropy. Second, through theoretical proofs and numerical counterexamples, we compares the ordering relations and numerical magnitudes among different block coherence measures and establishes a series of universal numerical inequalities to constrain their values. Besides, we also use $C_{α,1}$ to show the role of coherence in complex dynamic evolution of the Kominis master equation that includes recombination reactions.

The scalability of time-dependent partial differential equation (PDE) solvers based on the discontinuous Galerkin (DG) method is increasingly limited by data communication and synchronization requirements across processing elements (PEs) at extreme scales. To address these challenges, asynchronous computing approaches that relax communication and synchronization at a mathematical level have been proposed. In particular, the asynchronous discontinuous Galerkin (ADG) method with asynchrony-tolerant (AT) fluxes has recently been shown to recover high-order accuracy under relaxed communication, supported by detailed analyses of its accuracy and stability. However, the scalability of this approach in modern large-scale parallel DG solvers has not yet been systematically investigated. In this paper, we address this gap by implementing the ADG method coupled with AT fluxes in the open-source finite element library deal.II. We employ a communication-avoiding algorithm (CAA) that reduces the frequency of inter-process communication while accommodating controlled delays in ghost value exchanges. We first demonstrate that applying standard numerical fluxes in this asynchronous setting degrades the solution to first-order accuracy, irrespective of the polynomial degree. By incorporating AT fluxes that utilize data from multiple previous time levels, we successfully recover the formal high-order accuracy of the DG discretization. The accuracy of the proposed method is rigorously verified using benchmark problems for the compressible Euler equations. Furthermore, we evaluate the performance of the method through extensive strong-scaling studies for both two- and three-dimensional test cases. Our results indicate that CAA substantially suppresses synchronization overheads, yielding speedups of up to 1.9x in two dimensions and 1.6x in three dimensions compared to a baseline synchronous DG solver.

Fully implicit tensor-product space-time discretizations of time-dependent $(p,δ)$-Navier-Stokes models yield, on each time step, large nonlinear monolithic saddle-point systems. In the shear-thinning regime $1<p<2$, especially as $p\downarrow 1$ and $δ\downarrow 0$, the decisive difficulty is the constitutive tangent: its ill-conditioning impairs Newton globalization and the preconditioning of the arising linear systems. We therefore develop a scalable monolithic modified Newton framework for tensor-product space-time finite elements in which the exact constitutive tangent in the Jacobian action is replaced by a better-conditioned surrogate. Picard and exact Newton serve as reference linearizations within the same algebraic framework. Scalability is achieved through matrix-free operator evaluation, a monolithic multigrid V-cycle preconditioner, order-preserving reduced Gauss-Radau time quadrature, and an inexact space-time Vanka smoother with single-time-point coefficient freezing in local patch matrices. We prove coercivity of the linearized viscous-Nitsche term in the uniformly elliptic regime $ν_\infty>0$ and consistency of the reduced time quadrature. Numerical tests demonstrate robustness with respect to model parameters, nonlinear and linear iteration counts, and scalable parallel performance.

Recent work by Vavrek et al. (2025) showed that machine learning methods can be used to exploit spatial patterns of performance variations within the highly-segmented H3D M400 gamma spectrometer to improve an overall spectroscopic performance metric. That work also introduced the spectre-ml software, which tests various greedy, heuristic, random, and machine learning clustering algorithms to find the best performing mask for excluding detector regions to improve a user-defined performance metric by training on a given dataset. In this work, we build off of Vavrek et al. (2025) and seek to determine to what extent an optimized binary voxel mask trained on a given dataset can generalize to other datasets. In particular, this paper evaluates the transferability of masks trained on one M400 dataset to another M400 detector, in order to determine whether the total effort required in designing masks for different detectors and applications can be substantially reduced by using a single common mask. It also examines testing and training on different subsets of the same dataset to determine the natural level of variability in optimization results. In the inter-detector analysis, as expected, the best performing model on each detector is often one trained on that dataset, with an average performance enhancement of $16\%$ when considering the relative uncertainty in a Doniach fit to the $186$ keV peak. In comparison, the best transferred masks, with the best on average performance metric across all six detectors, show only a slightly smaller improvement of $13\%$ on average. These results suggest that high-performing, well-transferable masks can be shared among detectors, reducing or even eliminating the laborious processes of collecting a training dataset and performing the optimization for each detector, ultimately improving safeguards efficiency.

SNR G106.3+2.7 is a complex TeV emitting source whose emission is still poorly understood. It has especially been at the center of numerous discussions on its potential for being a supernova remnant (SNR) PeVatron, since its gamma-ray spectra seems not to exhibit any significant suppression in the multi--TeV range, up to $\sim 600$ TeV, thereby indicating the presence of $\sim$ PeV particles. We study the hypothesis in which a SNR evolving in a clumpy or cloudy environment is powering the TeV gamma-ray emission, detected mainly from two regions, the "head" and the "tail". We discuss the implications of such an hypothesis. We rely on a simple physically motivated analytical modeling of the shock dynamics and of the content of accelerated particles and confront it to available gamma-ray observations. We find that the current observed TeV gamma-ray emission in the head and tail regions can be accounted for by an active single SNR, with a natural hardening of the spectrum due to the expansion in a clumpy medium or escaping to a dense region in the tail. However, in all scenarios, the broadband gamma-ray emission from the GeV range to the $\gtrsim 100$ TeV range is difficult to reconcile with a standard SNR - whether originating from a thermonuclear or a core-collapse supernova - and instead points toward an association with the pulsar.

We study Gaussian wave packet solutions for Maxwell's equations in an isotropic, inhomogeneous medium and derive a system of ordinary differential equations that captures the leading-order correction to geodesic motion. The dynamical quantities in this system are the energy centroid, the linear and angular momentum, and the quadrupole moment. Furthermore, the system is closed to first order in the inverse frequency. As an immediate consequence, the energy centroids of Gaussian wave packets with opposite circular polarisations generally propagate in different directions, thereby providing a mathematical proof of the spin Hall effect of light in an inhomogeneous medium.

Jets are collimated clusters of particles formed by the hadronization of partons following a hard interaction. In proton-proton ($pp$) collisions at the Relativistic Heavy Ion Collider (RHIC), jet production is dominated by $gg$ and $qg$ partonic processes, allowing us to directly probe the gluon parton distribution function (PDF) in the proton in a way complementary to deep inelastic scattering. In this paper, we report the double-differential inclusive-jet cross sections as a function of jet transverse momentum, $p_{\rm T}$, and pseudorapidity, $η$, at center-of-mass energies $\sqrt{s} = 200$ and $510$~GeV, from $pp$ collisions studied with the STAR detector. The jet $p_{\rm T}$ is corrected for underlying event contributions by applying an off-axis cone method. At mid-pseudorapidity, $|η| < 0.9$, the kinematic coverage of our data extends to $0.07 < x_{\rm T} \text{ (}= 2p_{\rm T}{} / \sqrt{s} \text{)} < 0.5$ and $0.03 < x_{\rm T} < 0.31$ at $\sqrt{s} = 200$~and 510 GeV, respectively, where the gluon PDF is poorly constrained by the TeV-scale $pp$~($p\bar{p}$) colliders. The inclusive jet cross sections are compared to the next-to-next-to-leading order perturbative quantum chromodynamics calculations using several recent PDF sets as inputs. These results will further constrain the gluon PDF, help tune Monte Carlo generators, and provide critical reference data needed to study the quark-gluon plasma.

Quantum optomechanical STIRAP (Stimulated Raman Adiabatic Passage) is investigated for a system of two mechanical modes coupled to an optical mode. We show analytically that in a system without loss, fractional STIRAP can generate a mechanical Bell state from a single phonon Fock state of one of the mechanical modes with the other mechanical mode in the vacuum state, and a product state from a coherent state. Relative phases between Fock basis components in the final state of STIRAP are determined by the phonon-number parity of the initial state. Furthermore, the system is numerically studied to determine the effects of dissipation, and it is concluded that high-fidelity entanglement can be achieved via fractional STIRAP using state-of-the-art cryogenic cooling and mechanical devices. Finally, an interferometric protocol using time-reversed fractional STIRAP is proposed to quantify entanglement between two mechanical modes.

Quantum metric learning enhances machine learning by mapping classical data to a quantum Hilbert space with maximal separation between classes. However, on current NISQ hardware, this mapping process itself is prone to errors and could be fundamentally incorrect. Verifying that a quantum embedding model successfully achieves its promised separation is essential to ensure the correctness and reliability. In this paper, we propose a practical black-box verification protocol to audit the performance of quantum metric learning models. We define a setting with two parties: a powerful but untrusted prover, who claims to have a parameterized unitary circuit that embeds classical data from different groups with a guaranteed angular separation, and a limited verifier, whose quantum capabilities are restricted to performing only basic measurements. The verifier has no knowledge of the implementation of the prover, including the structure of the model, its parameters, or the details of the prover measurement setup. To verify the separation between different data groups, the proposed algorithm must overcome two key challenges. First, the verifier is ignorant of the prover's implementation details, such as the optimization cost function and measurement setup. Consequently, the verifier lacks any prior information about the expected quantum embedding states for each group. Second, the destructive nature of quantum measurements prevents direct estimation of the separation angles. Our algorithm successfully overcomes these challenges, enabling the verifier to accurately estimate the true separation angles between the different groups. We implemented the proposed protocol and deployed it to verify the QAOAEmbedding models. The results from both theoretical analysis and practical implementation show that our proposal effectively assesses embedding quality and remains robust in adversarial settings.

The PADME Experiment at Laboratori Nationali di Frascati is designed to search for the Dark Photon, a hypothetical gauge boson responsible for the interaction between the visible and the hidden sector. PADME explores the process of annihilation of beam positrons with the electrons in a fixed target, employing the missing mass technique: in case the annihilation results in the associate production of one visible and one Dark photon, the first can be registered by the experiment's electromagnetic calorimeter and the Dark Photon mass can be reconstructed knowing the beam energy. This paper presents the analysis techniques that are being employed for the PADME data, as well as the background composition and rejection procedure.

We present a fully automated framework for extracting interatomic force constants (IFCs) directly from X-ray thermal diffuse scattering (TDS) data. By formulating scattering intensity as a differentiable function of a symmetry-reduced IFC parameterization, we enable gradient-based optimization via direct, Cholesky-based sampling of correlated atomic displacements at thermal equilibrium. This approach bypasses the computational bottleneck of repeated Hessian matrix diagonalizations, significantly accelerating the inversion process. Benchmark tests demonstrate that the framework accurately recovers ground-truth IFCs and phonon dispersion relations, providing a robust, high-throughput pathway for studying lattice dynamics across diverse crystalline materials. This method bridges the gap between experimental observations and computational modeling, enabling the direct integration of TDS data into the refinement of high-fidelity inter-atomic potentials.

Overmassive black hole galaxies (OBGs) at redshifts $z \sim$ 10, or 450 Myr after the Big Bang, are one of the most puzzling discoveries by the James Webb Space Telescope to date because they formed by such early epochs and their black-hole to stellar mass ratios are a hundred times higher than those in galaxies today. Here we show that OBGs are simply the result of DCBH birth in primordial halos at early times. A 70,000 M$_{\odot}$ DCBH forming at $z =$ 25.7 in our cosmological simulation grows at about half the Eddington rate to $6.0 \times 10^6$ M$_{\odot}$ by $z =$ 10.1. Its host galaxy reaches a stellar mass of $4 \times 10^8$ M$_{\odot}$, a metallicity $Z =$ 0.1 Z$_{\odot}$, a star formation rate of 2 M$_{\odot}$ yr$^{-1}$, and $M_{\rm BH}/M_{\ast}$ $\sim$ 0.01, on par with OBGs like GN-z11, UHZ1, and GHZ9 at $z =$ 10.6, 10.1, and 10.2, respectively. Our simulation, the first to follow the coevolution of a DCBH and its host galaxy for several hundred Myr, shows that this ratio is a natural result of initial suppression of star formation by the DCBH and the later, violent blowout of metals by Pop III supernovae. Our models provide an excellent match to the spectra of UHZ1 and GHZ9 at $z =$ 10.1 and 10.4, respectively.

Coarse-grained models of chaotic systems neglect unresolved degrees of freedom, inducing structured model error that limits predictability and distorts long-term statistics. Typical data-driven closures are trained to minimize error over a single time step, implicitly assuming Markovian dynamics and often failing to capture long-term behavior. Recent approaches instead optimize losses over finite trajectories. However, when such trajectory-based training is carried out with deterministic pointwise losses, it introduces a fundamental mathematical degeneracy. We prove that optimizing pointwise deterministic losses such as mean squared error over chaotic trajectories suppresses predictive variance, with corresponding loss of physical variability in long integrations. In contrast, strictly proper scoring rules avoid this degeneracy. By targeting forecast distributions rather than realized trajectories, they remove the penalty against predictive spread and align the long-lead optimum with the invariant measure. Using quasi-geostrophic turbulence as a canonical chaotic system, we validate this theory: one-step-trained closures fail to capture stable coarse-grained dynamics, while deterministic closures optimized over trajectories exhibit the variance-loss tendency predicted by our analysis. Stochastic closures calibrated over trajectories using the energy score, however, overcome both structural limitations, yielding skillful ensemble forecasts and realistic long-term statistics. Our results establish that both stochastic modeling and trajectory-based calibration are essential for faithfully representing the dynamics of coarse-grained systems.

We show that hadrons in QCD follow a spectrum determined by string dynamics characterized by a universal Hagedorn temperature linked to the string tension. While this behavior was recently established for light hadrons and glueballs, we demonstrate that the same dynamics describes the heavy-flavor sector. After separating the current quark masses, the resulting spectrum reproduces lattice QCD thermodynamics of charmed hadrons and the observed spectra of hadrons across quark flavors without additional parameters. These results reflect the universal confining dynamics of QCD through the string tension.

The Sourlas-Lechner-Hauke-Zoller (SLHZ) scheme for quantum annealing uses the parity to encode logical variables and has several advantages, but it has not been implemented for large-scale quantum annealers. If the SLHZ-based approach can be implemented on currently available quantum annealers, we can evaluate its performance. An efficient method to embed the parity-encoded model into the hardware graphs of available quantum annealers is one of the key elements for this approach. We propose a qubit-efficient embedding scheme for parity-encoded Hamiltonians on quantum annealers with the Zephyr connectivity. We give an explicit constructive embedding of the interaction graph of an intermediate Hamiltonian, which contains only one- and two-body interactions, into the Zephyr graph. Our embedding maps each spin to a two-qubit chain using systematic chain-assignment rules. Its validity is verified via the resulting chain-to-chain connectivity. Our embedding also offers practical flexibility. Chains assigned to ancillary spins allow reduction to a single physical qubit, leading to options to avoid inactive qubits. The number of required qubits per spin in the parity Hamiltonian is three, which is fewer than that for a known embedding scheme for the Pegasus graph.

We examine scattering amplitudes for an arbitrary number of photons in a class of non-null background electromagnetic fields, studying tree-level and one-loop amplitudes in scalar and spinor quantum-electrodynamics in backgrounds defined by a gauge field $A_μ(\mathfrak{n}\cdot x)$ for $\mathfrak{n}^2\neq 0$. Motivated to account for more physically realistic laser-plasma dispersive properties, our approach overcomes prior work studying such amplitudes in a constant background field and relaxes the familiar null criterion assumed for plane waves. Master Formulae for the $N$-photon amplitudes dressed by the non-null background are constructed using the first-quantised worldline formalism, which can systematically account for all orders in the non-null parameter, $\mathfrak{n}^2$, treated here as an expansion parameter. These are derived from worldline representations of the coordinate and momentum space propagators (and their LSZ-truncated amplitudes) and the effective action, each incorporating the non-null background non-perturbatively. We then outline a partial resummation of their expansions in $\mathfrak{n}^{2}$. A special exactly solvable case of non-null constant crossed fields without photon insertion in the effective action is explored to test the Master Formulae that result. The validity of the presented master formulae is further checked against known expressions for the wavefunction and non-linear Compton scattering in a non-null background to lowest order in the non-null parameter.

Quantum trajectories are Markov chains modeling quantum systems subjected to repeated indirect measurements. Their stationary regime depends on what observables are measured on the probes used to indirectly measure the system. In this article we explore the properties of quantum trajectories when the choice of probe observable is randomized. The randomization induces some regularization of the quantum trajectories. We show that non-singular randomization ensures that quantum trajectories purify and therefore accept a unique invariant probability measure. We furthermore study the regularity of that invariant measure. In that endeavour, we introduce a new notion of ergodicity for quantum channels, which we call multiplicative primitivity. It is a priory stronger than primitivity but weaker than positivity improving. Finally, we compute some invariant measures for canonical quantum channels and explore the limits of our assumptions with several examples.

We employed molecular dynamics simulations (MD) and Bennett's acceptance ratio method to compute the free energy of transfer (Delta G_trans) of phenol, methane, and 5-fluorouracil (5-FU) between bulk water and water-pNIPAM mixtures with different polymer volume fractions (phi_p). To this end, we first calculate the solvation free energies in both media to obtain Delta G_trans. Phenol and 5-FU (a drug used in cancer treatment) adsorb onto the pNIPAM surface and exhibit negative values of Delta G_trans irrespective of temperature, both above and below the lower critical solution temperature (T_c) of pNIPAM. In contrast, methane changes the sign of Delta G_trans, being positive below and negative above T_c. In all cases, and in contrast with some theoretical predictions, Delta G_trans shows a linear dependence on pNIPAM concentration up to high polymer densities. We also compute the diffusion coefficient (D) of phenol in water-pNIPAM mixtures as a function of phi_p in the dilute limit. Both Delta G_trans and D as functions of phi_p are key inputs to estimate the release halftime of hollow pNIPAM microgels using dynamic density functional theory (DDFT). Our scaling approach reproduces the experimental value of 2200 s for microgels of 50 micrometer radius without a cavity, at phi_p approximately 0.83 and 315 K.

In this work we provide predictions for bottom-strange molecular states within the Hidden Gauge Formalism. We study the coupled-channel scattering of $B^{(*)}\bar{K}^{(*)}$ states and, by fixing only one free parameter to obtain the mass of a new excited $B_s^0$ state seen by the LHCb, we predict the pole parameters of six states in this sector. Concretely, we get that the masses of the flavor partners of the $D_{s0}(2317)$ and $D_{s1}(2460)$ states in the bottom sector are $5760$ and $5802$ MeV for the $B\bar{K}$ ($J^P=0^+$) and $B^{*}\bar{K}$ ($1^+$) states, respectively. Moreover, the recently seen states by the LHCb with masses around $6100$ and $6160$ MeV can be interpreted as $B\bar{K}^*$ and $B^*\bar{K}^*$ molecular states, according to reasonable values of the pole parameters and the splitting between these two states obtained in our calculation.

In light of major developments over the past decades in both quantum computing and simulations on classical hardware, it is a serious challenge to identify a real-world problem where quantum advantage is expected to appear. In quantum chemistry, electronic structure calculations of strongly correlated, i.e. multi-reference problems, are often argued to fall into such category because of their intractability with standard methods based on mean-field theory. Therefore, providing state-of-the-art benchmark data by classical algorithms is necessary to make a decisive conclusion when such competing development directions are compared. We report cutting-edge performance results together with high accuracy ground state energy for the Fe$_4$S$_4$ molecular cluster on a CAS(54,36) model space, a problem that has been included quite recently among the list of systems in the {\it Quantum Advantage Tracker} webpage maintained by IBM and RIKEN. Pushing the limits even further, we also present CAS-SCF based orbital optimizations for unprecedented CAS sizes of up to 89 electrons in 102 orbitals [CAS(89,102)] for the Fe$_5$S$_{12}$H$_4^{5-}$ molecular system comprising twenty five open shell orbitals in its sextet ground state and an active spaces size of 331 electrons in 451 orbitals. We have achieved our results via mixed-precision spin-adapted \textit{ab initio} Density Matrix Renormalization Group (DMRG) electronic structure calculations interfaced with the ORCA program package and utilizing the NVIDIA Blackwell graphics processing unit (GPU) platform. We argue that DMRG benchmark data should be taken as a classical reference when quantum advantage is reported. In addition, full exploitation of classical hardware should also be considered since even the most advanced DMRG implementations are still in a premature stage regarding utilization of all the benefits of GPU technology.