Magnetoelectric systems offer potential for device applications exploiting coupled states between electric and magnetic properties. Among magnetoelectric materials, \FNO has attracted special attention because of its pronounced dielectric signal at high magnetic transition temperatures. However, the magnetic ground state, which is essential information for understanding its unusual magnetoelectricity, remains unclarified. Here, we report a noncollinear magnetic ground state of Fe$_{4}$Nb$_{2}$O$_{9}$. To examine the magnetoelectric effect associated with sequential magnetic and structural transitions upon cooling, we conducted combined x-ray diffraction, magnetic susceptibility, magnetization, dielectric constant, and magnetodielectric experiments. Powder neutron diffraction experiments revealed a series of magnetic Bragg peaks and clear splitting of peaks via structural transition. Magnetic Rietveld refinements, combined with group theory analysis, determined a noncollinear antiferromagnetic structure including a significant $c$-axis moment component at 1.5 K. This study provides insights into the understanding of its magnetoelectric properties.

Fluctuations are an intrinsic feature of many-body systems, and their full statistical distributions reveal a wealth of information about the underlying physics. Of particular interest are non-Gaussian, extreme-value statistics that arise when nontrivial correlations and criticality dominate over the central limit theorem. Strikingly, in two-dimensional (2D) quantum fluids, such effects have been predicted to manifest in the order parameter distribution in the Berezinskii-Kosterlitz-Thouless (BKT) superfluid phase, which approaches a universal extreme-value form in the low-temperature limit. Here, we measure the order parameter statistics of 2D Bose gases across the BKT critical point using matter-wave interferometry. This allows us to confirm the predicted convergence of the observed statistics to a universal Gumbel distribution at low temperatures, to the 0.1% level of the probability density. Furthermore, the intrinsic precision of the atom interferometer allows the robust extraction of higher-moment observables such as skewness and kurtosis; in particular, we report direct measurements of the Binder cumulant which allows us to precisely identify the onset of the phase transition. Extending this approach to the investigation of non-equilibrium systems, we probe vortex unbinding dynamics following a quench across the BKT critical point and identify parameter-independent scaling behaviour of higher moments.

Analyses of type Ia supernovae have helped us shed light on the existence and nature of dark energy. Most of these analyses have relied on Bayesian techniques. In this work, we rely on resampling techniques to analyse supernova data. In particular, we use the generalised least squares method together with Jackknife and Bootstrap techniques to estimate parameters of $Λ$CDM, flat $Λ$CDM, $w$CDM, flat $w$CDM, and flat $w_0\,w_a$CDM models from the recent PantheonPlus and SH0ES data. For completeness, we also perform Bayesian analysis using Markov chain Monte Carlo (MCMC) and nested sampling algorithms, and compare the results. We note that resampling techniques can help highlight the limitations of the data. For instance, we see that the Jackknife method estimates a strong positive correlation between $h$ and $M$ and higher standard deviations for both. This may have significant implications for the Hubble tension. We conclude with a discussion of our results.

As the recurrent nova T Coronae Borealis (T CrB) approaches its next predicted thermonuclear eruption, it is currently exhibiting a "super-active state" (SAS) characterized by enhanced multiwavelength emission similar to the behavior recorded prior to the 1946 outburst. We present a multiwavelength analysis of the SAS and the subsequent "faint state" using observations from HST, Swift, NuSTAR, and XMM-Newton. Our results indicate that the SAS was driven by an increase in the mass accretion rate, which caused the accretion disk's boundary layer to become optically thick. A weighted least squares regression analysis quantifies the evolution of the accretion components, displaying a highly significant (4.5$σ$) increase in the luminosity of the optically thin cooling flow (L$_{cf}$) and a marginal (2.58$σ$) decrease in the optically thick boundary layer luminosity (L$_{bb}$) as the system transitioned into the faint state. We find that this dimming is consistent with an intrinsic change in the accretion flow rather than dust obscuration, supported by the lack of infrared excess and the stability of the 2175 Å feature. Additionally, a time-series analysis using autoregressive modeling to account for correlated red noise revealed no significant periodicities, thereby disputing the previously reported $\sim$6000 s signal. These findings suggest that the pre-outburst evolution of T CrB is characterized by significant changes in the accretion disk structure and boundary layer, providing a self-consistent physical framework for the system's behavior as it approaches eruption.

Bell tests based on homodyne detection are strongly constrained in continuous-variable systems. Can Gottesman-Kitaev-Preskill (GKP) encoding turn homodyne detection into a practical tool for revealing Bell nonlocality? We consider a physically motivated model in which each party performs homodyne detection and digitizes the continuous outcome via a fixed periodic binning, corresponding to logical Pauli measurements. Within this framework, we derive a bipartite no-go: CHSH cannot be violated for Bell-pair states. Moving beyond two parties, we show that finitely squeezed GKP-encoded GHZ and W states nevertheless exhibit strong multipartite nonlocality, violating multipartite Bell inequalities with homodyne-only readout. We quantify the required squeezing thresholds and robustness to loss, providing a route toward homodyne-based Bell tests in continuous-variable systems.

Political moderation, a key attractor in democratic systems, proves highly fragile under realistic information conditions. We develop a stochastic model of opinion dynamics to analyze how noise and differential susceptibility reshape the political spectrum. Extending Marvel et al.'s deterministic framework, we incorporate stochastic media influence $ζ(t)$ and neuropolitically-grounded sensitivity differences ($σ_y > σ_x$). Analysis reveals the moderate population -- stable in deterministic models -- undergoes catastrophic collapse under stochastic forcing. This occurs through an effective deradicalization asymmetry ($u_{B}^{\text{eff}} = u + σ_y^2/2 > u_{A}^{\text{eff}}$) that drives conservatives to extinction, eliminating cross-cutting interactions that sustain moderates. The system exhibits a phase transition from multi-stable coexistence to liberal dominance, demonstrating how information flow architecture -- independent of content -- systematically dismantles the political center. Our findings reveal moderation as an emergent property highly vulnerable to stochastic perturbations in complex social systems.

Probing energy-dependent transport in quantum simulators requires preparing states with tunable energy and small energy variance. Existing approaches often study quench dynamics of simple initial states, such as computational basis states, which are far from energy eigenstates and therefore limit the achievable energy resolution. In this work, we propose using wavepackets to probe transport properties with improved energy resolution. To demonstrate the utility of this approach, we prepare and evolve wavepackets on Quantinuum's H2-2 quantum computer and identify an energy-dependent localization transition in the Anderson model on an 8x7 lattice--a finite-size mobility edge. We observe that a wavepacket initialized at low energy remains spatially localized under time evolution, while a high-energy wavepacket delocalizes, consistent with the presence of a mobility edge. Crucial to our experiments is an error mitigation strategy that infers the noiseless output bit string distribution using maximum-likelihood estimation. Compared to post-selection, this method removes systematic errors and reduces statistical uncertainty by up to a factor of 5. We extend our methods to the many-particle regime by developing a quantum algorithm for preparing quasiparticle wavepackets in a one-dimensional model of interacting fermions. This technique has modest quantum resource requirements, making wavepacket-based studies of transport in many-body systems a promising application for near-term quantum computers.

\textbf{Background} The reach of \textit{ab initio} theory has greatly increased in recent decades. However, predicting the location of the drip lines remains challenging due to uncertainties in nuclear forces and difficulties in describing nuclei that behave as open quantum systems. \textbf{Purpose} In this work, we extend the \textit{ab initio} Gamow Density Matrix Renormalization Group (G-DMRG) approach to the regime of broad many-body resonances to pave the way for systematic tests of nuclear forces in light exotic nuclei. \textbf{Methods} To stabilize calculations, we introduce a new truncation scheme in the reference space, and propose an orbital ordering based on entanglement considerations. We then show how continuum couplings increase entanglement in the many-body problem, and propose a new truncation scheme to stabilize the renormalization and accelerate calculations in extreme conditions. Finally, we demonstrate that natural orbitals can be used to efficiently describe broad resonances by introducing a new ordering scheme and by redefining the reference space based on occupations. \textbf{Results} Leveraging our findings, we propose a recipe to converge \textit{ab initio} G-DMRG calculations and apply it in low-lying states of \isotope[5,6]{He} and \isotope[4]{H}, demonstrating control of the renormalization and the emergence of convergence patterns. We also obtain the first direct \textit{ab initio} calculation of the $J^π= {1/2}^+$ ground state of \isotope[5]{H}. \textbf{Conclusions} We demonstrate that entanglement due to continuum couplings can be controlled in extreme conditions and successfully extend the G-DMRG approach in the regime of broad many-body resonances.

At the heart of quark confinement and hadronization, the physics of flux strings has recently become a focal point in the field of quantum simulation of high-energy physics (HEP). Despite considerable progress, a detailed understanding of the behavior of flux strings in quantum simulation-relevant lattice formulations of gauge theories has remained limited to the lowest truncations of the gauge field, which are severely limited in their ability to draw conclusions about the quantum field theory limit. Here, we employ tensor network simulations to investigate the behavior of flux strings in a quantum link formulation of $2+1$D quantum electrodynamics (QED) with a spin-$1$ representation of the gauge field. We first map out the ground-state phase diagram of this model in the presence of two spatially separated static charges, revealing distinct microscopic processes responsible for string breaking, including a two-stage breaking mechanism not possible in the spin-$\frac{1}{2}$ formulation. Starting in different initial product state string configurations, we then explore far-from-equilibrium quench dynamics across various parameter regimes, demonstrating genuine $2+1$D real-time string breaking and glueball-like bound state formation, with the latter not possible in the spin-$\frac{1}{2}$ formulation. In and out of equilibrium, we consider different values and placements of the static charges. Finally, we provide efficient qudit circuits for a quantum simulation experiment in which our results can be observed in state-of-the-art ion-trap setups. Our findings lay the groundwork for quantum simulations of flux strings towards the quantum field theory limit.

We present cosmological parameters measurements from the full combination of DESI DR1 galaxy clustering data described with large-scale structure effective field theory. By incorporating additional datasets (photometric galaxies and CMB lensing cross-correlations) and extending the bispectrum likelihood to smaller scales using a consistent one-loop theory computation, we achieve substantial gains in constraining power relative to previous analyses. Combining with the latest DESI baryon acoustic oscillation data and using cosmic microwave background (CMB) priors on the power spectrum tilt and baryon density, we obtain tight constraints on the $Λ$CDM model, finding the Hubble constant $H_0=69.08\pm 0.37~\mathrm{km}\,\mathrm{s}^{-1}\mathrm{Mpc}^{-1}$, the matter density fraction $Ω_m=0.2973\pm 0.0050$, and the mass fluctuation amplitude $σ_8 = 0.815\pm 0.016$ (or the lensing parameter $S_8\equivσ_8\sqrt{Ω_m/0.3}=0.811\pm 0.016$), corresponding to $0.6\%$, $1.7\%$, and $2\%$ precision respectively. Adding the Pantheon+ supernova sample (SNe), we find a preference of $2.6σ$ for the $w_0w_a$ dynamical dark energy model from low-redshift data alone, which increases to $2.8σ$ when exchanging the SNe with Planck CMB data. Combining full-shape data with BAO, CMB, and SNe likelihoods, we improve the dark energy figure-of-merit by $18\%$ and bound the sum of the neutrino masses to $M_ν<0.057$ eV in $Λ$CDM and $M_ν<0.095$ eV in the $w_0w_a$ dynamical dark energy model (both at 95\% CL). This represents an improvement of $25\%$ over the background expansion constraints and the strongest bound on neutrino masses in $w_0w_a$CDM to date. Our results suggest that the preference for the normal ordering of neutrino mass states holds regardless of the cosmological background model, and is robust in light of tensions between cosmological datasets.

We develop a rigorous analytical framework for metastable stochastic transitions in Landau-type gradient systems inspired by QCD phenomenology. The functional $F(σ;u)=\int_Ω[\fracκ{2}|\nablaσ|^2+V(σ;u)]\,dx$, depending smoothly on a control parameter $u\in\mathcal U$, is analyzed through the Euler-Lagrange map $\mathcal{E}(σ;u)=-κΔσ+V'(σ;u)$ and its Hessian $\mathcal{L}_{σ,u}=-κΔ+V''(σ;u)$. By combining variational methods, $Γ$- and Mosco convergence, and spectral perturbation theory, we establish the persistence and stability of local minima and index-one saddles under parameter deformations and variational discretizations. The associated mountain-pass solutions form Cerf-continuous branches away from the discriminant set $\mathcal D=\{u:\det\mathcal L_{σ,u}=0\}$, whose crossings produce only fold or cusp catastrophes in generic one- and two-parameter slices. The $Γ$-limit is taken with respect to the $L^2(Ω)$ topology, ensuring compactness, convergence of gradient flows, and spectral continuity of $\mathcal L_{σ,u}$. As a consequence, the Eyring-Kramers formula for the mean transition time between metastable wells retains quantitative validity under both parameter deformations and discretization refinement, with convergent free-energy barriers, unstable eigenvalues, and zeta-regularized determinant ratios. This construction unifies the classical intuition of Eyring, Kramers, and Langer with modern variational and spectral analysis, providing a mathematically consistent and physically transparent foundation for metastable decay and phase conversion in Landau-QCD-type systems.

Doppler lensing, a relativistic effect resulting from the peculiar velocities of galaxies along the line of sight, provides insight into the large-scale structure of the Universe. Relativistic simulations are essential for modeling Doppler lensing because they incorporate gravity and motion in spacetime. We compare two relativistic $N$-body simulation frameworks, $\texttt{GEVOLUTION}$ and $\texttt{SCREENING}$, to calculate Doppler lensing convergence in cosmic voids of different sizes and halos of different masses. Our analysis reveals scale-dependent performance: $\texttt{SCREENING}$ shows larger differences in small voids (radius range: 15--25 Mpc/h) with a mean absolute relative difference of 38.5\%, due to linearized dynamics failing in nonlinear regimes. Medium voids (25--35 Mpc/h) show better agreement (9.5\% mean difference). For large voids (35--45 Mpc/h), $\texttt{SCREENING}$ exhibits intermediate differences (16.9\% mean difference) with central instabilities. Moreover, our Doppler convergence analysis with massive halos ($10^{11.5}$--$10^{14} {~h^{-1}\mathrm{M}_\odot}$) demonstrates excellent consistency (1.6--3.6\% mean difference). These findings provide clear guidance for simulation choice: $\texttt{GEVOLUTION}$ is recommended for precision studies critical to $Λ$CDM or modified gravity tests, while $\texttt{SCREENING}$ offers a computationally efficient alternative for relativistic treatments with large catalogs of voids and halos, assisting future astrophysical surveys.

We consider the following task: how for a given quantum state $ρ$ to find a grounded Hamiltonian $H$ satisfying the condition $\mathrm{Tr} Hρ\leq E_0<+\infty$ in such a way that the von Neumann entropy of the Gibbs state $γ_H(E)$ corresponding to a given energy $E>0$ be as small as possible. We show that for any mixed state $ρ$ with finite entropy and any $E>0$ there exists a solution $H(ρ,E_0,E)$ of the above problem (unique in the non-degenerate case) which we call optimal Hamiltonian for the state $ρ$. Explicit expressions for $H(ρ,E_0,E)$, $γ_{H(ρ,E_0,E)}(E)$ and $S(γ_{H(ρ,E_0,E)}(E))$ are obtained. Analytical properties of the function $E\mapsto S(γ_{H(ρ,E_0,E)}(E))$ are explored. Several examples are considered. We also consider a modification of the above task in which arbitrary Hamiltonians (not necessarily grounded) are considered. The basic application motivated this research is described. As examples, new semicontinuity bounds for the von Neumann entropy and for the entanglement of formation are obtained and briefly discussed (with the intention to give a detailed analysis in a separate article).

Optical cavities have been widely applied to manipulate the properties of solid state materials inside them. We propose that in systems embedded within optical cavities driven by incident pump light, the pump induces generic phase transitions into new nonequilibrium steady states. This effect arises from the ponderomotive potential, the effective static potential exerted by the pump on the low energy degrees of freedom, which exhibits a universal steplike structure that pushes the matter degrees of freedom in the direction that redshifts the cavity photon modes. For a two dimensional electron liquid in a driven cavity, this steplike potential pushes the electron density to jump to a smaller value so that a hybrid cavity photon mode is redshifted to slightly below the pump frequency. Similarly, for a dirty superconductor in such a driven cavity, this potential acts on the superconducting order parameter and causes a first order phase transition to a new steady state with a smaller gap. By realistic electromagnetic modeling of the cavity that includes all cavity modes, we construct the nonequilibrium phase diagrams for experimentally relevant devices.

Magnetic Particle Imaging (MPI) is a promising tomographic technique for visualizing the spatio-temporal distribution of superparamagnetic nanoparticles, with applications ranging from cancer detection to real-time cardiovascular monitoring. Traditional MPI reconstruction relies on either time-consuming calibration (measured system matrix) or model-based simulation of the forward operator. Recent developments have shown the applicability of Chebyshev polynomials to multi-dimensional Lissajous Field-Free Point (FFP) scans. This method is bound to the particular choice of sinusoidal scanning trajectories. In this paper, we present the first reconstruction on real 2D MPI data with a trajectory-independent model-based MPI reconstruction algorithm. We further develop the zero-shot Plug-and-Play (PnP) algorithm of the authors -- with automatic noise level estimation -- to address the present deconvolution problem, leveraging a state-of-the-art denoiser trained on natural images without retraining on MPI-specific data. We evaluate our method on the publicly available 2D FFP MPI dataset ``MPIdata: Equilibrium Model with Anisotropy", featuring scans of six phantoms acquired using a Bruker preclinical scanner. Moreover, we show reconstruction performed on custom data on a 2D scanner with additional high-frequency excitation field and partial data. Our results demonstrate strong reconstruction capabilities across different scanning scenarios -- setting a precedent for general-purpose, flexible model-based MPI reconstruction.

Floquet code is a dynamical quantum memory with a periodically evolving logical space. As a defining feature, the code exhibits an anyon automorphism after each period, giving rise to a non-trivial evolution of each logical state. In this paper, we study the Floquet code under local decoherence and perfect measurements and demonstrate that below the decoherence threshold, the code is in a robust phase characterized by the anyon automorphism. We first derive the 3D statistical mechanics model for the maximum likelihood decoder of the 2D Floquet code under local Pauli decoherence. We identify a class of two-qubit Pauli channels under which the 3D statistical mechanics model becomes decoupled 2D models and obtain the threshold for such decoherence channels. We then propose a diagnostic of the anyon automorphism in the presence of local decoherence. We analytically show that this diagnostic distinguishes the Floquet code from the toric code under repeated syndrome measurements and undergoes a phase transition at the threshold.

We conduct a comprehensive study of anomalous charge transport in the quantum sine--Gordon model. Employing the framework of Generalized Hydrodynamics, we compute Drude weights and Onsager matrices across a wide range of coupling strengths to quantify ballistic and diffusive transport, respectively. We find that charge transport is predominantly diffusive at accessible timescales, indicated by the corresponding Onsager matrix significantly exceeding the Drude weight -- contrary to most integrable models where transport is primarily ballistic. Reducing the Onsager matrix to a few key two-particle scattering processes enables us to efficiently examine transport in both low- and high-temperature limits. The charge transport is dictated by non-diagonal scattering of the internal charge degree of freedom: At particular values of the coupling strength with diagonal, diffusive effects amount to merely subleading corrections. However, at couplings approaching these points, the charge Onsager matrix and corresponding diffusive time-scale diverge. Our findings relate to similar transport anomalies in XXZ spin chains, offering insights through their shared Bethe Ansatz structures.

A recent experiment [Cohen et al., Science 382, 542 (2023)] observed a robustly quantized $e^2/2h$ conductance in a quantum point contact between fractional quantum Hall edges (a quantum Hall transformer), which then vanishes at low temperature. While this behavior can be described by a boundary sine gordon (BSG) model derived from electron tunneling, the microscopic motivation for such strong tunneling is unclear. We use an alternative model based on sliding charge density waves and a density inhomogeneity to clarify the BSG description and calculate the conductance over the full range of transmission. Using a perturbative method and a matrix product state calculation, we draw a quantitative connection between the BSG model and the physical quantum Hall system.

We consider the estimation of an unknown parameter $θ$ through a quantum probe at thermal equilibrium. The probe is assumed to be in a Gibbs state according to its Hamiltonian $H_θ$, which is divided in a parameter-encoding term $H^{\rm P}_θ$ and an additional, parameter-independent, control $H^{\rm C}$. Given a fixed encoding, we find the maximal Quantum Fisher Information attainable via arbitrary $H^{\rm C}$, which provides a fundamental bound on the measurement precision. We elucidate the role of quantum coherence between encoding and control in different temperature regimes, which include ground state metrology as a limiting case. In the case of locally-encoded parameters, the optimal sensitivity presents a $N^2$-scaling in terms of the number of particles of the probe, which can be reached, at finite temperature, with local measurements and no entanglement. We apply our results to paradigmatic spin chain models, showing that these fundamental limits can be approached using local two-body interactions. Our results set the fundamental limits and optimal control for metrology with thermal and ground state probes, including probes at the verge of criticality.

Bernal bilayer graphene exhibits a band gap that is tunable through the infrared with an electric field. We show that sublattice odd commensurate twisted bilayer graphene (C-TBG) exhibits a band gap that is tunable through the terahertz with an electric field. We show that from the perspective of terahertz optics the sublattice odd and even forms of C-TBG are "inflated" versions of Bernal and AA stacked bilayer graphene respectively with energy scales reduced by a factor of 110 for the 21.79 degree commensurate unit cell. This lower energy scale is accompanied by a correspondingly smaller gate voltage, which means that the strong-field regime is more easily accessible than in the Bernal case. Finally, we show that the interlayer coherence energy is a directly accessible experimental quantity through the position of a power-law divergence in the optical conductivity.

We present a method for associating labeled directed graphs to finite-dimensional Lie algebras, thereby enabling rapid identification of key structural algebraic features. To formalize this approach, we introduce the concept of graph-admissible Lie algebras and analyze properties of valid graphs given the antisymmetry property of the Lie bracket as well as the Jacobi identity. Based on these foundations, we develop graph-theoretic criteria for solvability, nilpotency, presence of ideals, simplicity, semisimplicity, and reductiveness of an algebra. Practical algorithms are provided for constructing such graphs and those associated with the lower central series and derived series via an iterative pruning procedure. This visual framework allows for an intuitive understanding of Lie algebraic structures that goes beyond purely visual advantages, since it enables a simpler and swifter grasping of the algebras of interest beyond computational-heavy approaches. Examples, which include the Schrödinger and Lorentz algebra, illustrate the applicability of these tools to physically relevant cases. We further explore applications in physics, where the method facilitates computation of similtude relations essential for determining quantum mechanical time evolution via the Lie algebraic factorization method. Extensions to graded Lie algebras and related conjectures are discussed. Our approach bridges algebraic and combinatorial perspectives, offering both theoretical insights and computational tools into this area of mathematical physics.

Magnetars are extreme neutron stars powered by ultra-strong magnetic fields ($\sim10^{14}$ Gauss) and are compelling engines for some of the most powerful extragalactic transients such as Super Luminous Supernovae, Gamma-Ray Bursts, and Fast Radio Bursts. Yet their formation rate relative to ordinary neutron stars remains uncertain, often precluding direct comparisons with the rates of these extragalactic transients. Furthermore, magnetars have been recently shown to be evolutionarily related to other neutron star classes, complicating the estimate of the exact magnetar fraction within the neutron star population. We study the magnetar birth fraction in core-collapse supernovae using pulsar population synthesis of all isolated neutron star classes in our Galaxy, incorporating self-consistently the Galactic dynamical evolution, spin-down and magneto-thermal evolution. This approach allows us to derive strong constraints from small close-to-complete observational samples. In particular, looking at the age-limited young ($<$2 kyr) neutron star population in the Milky Way we find 24 detected young neutron stars, with only 10 of them (41%) being classical rotational powered pulsars, while the others (59%) are either magnetars or central compact objects, the latter believed to be equally magnetically powered. We further compare the results with the nearby volume-limited class ($<$500 pc) of X-ray Dim Isolated Neutron stars, old nearby magnetars. We conclude that the observed population of isolated neutron stars in the Galaxy can be reproduced only by assuming a core-collapse supernova rate larger than two, and a larger magnetar fraction than previously inferred. By assuming a bimodal initial magnetic field ($B_0$) distribution at birth, we find that the magnetar class peaks between $B_0\sim 1-2.5\times10^{14}$ Gauss and represents on average $\sim50$% of the entire neutron star population.

Many physical phenomena, including thermalization in open quantum systems and quantum Gibbs sampling, are modeled by Lindbladians approximating a system weakly coupled to a bath. Understanding the convergence speed of these Lindbladians to their steady states is crucial for bounding algorithmic runtimes and thermalization timescales. We study two such families of processes: one characterizing a repeated-interaction Gibbs sampling algorithm, and another modeling open many-body quantum thermalization. We prove that both converge in polynomial time for several non-commuting systems, including high-temperature local lattices, weakly interacting fermions, and 1D spin chains. These results demonstrate that simple dissipative quantum algorithms can prepare complex Gibbs states and that Lindblad dynamics accurately capture thermal relaxation. Our proofs rely on a novel technical result that extrapolates spectral gap lower bounds from quasi-local Lindbladians to the non-local generators governing these dynamics.

Strongly-correlated fermion systems on a lattice have been a subject of intense focus in the field of condensed-matter physics. These systems are notoriously difficult to solve, even with state-of-the-art numerical methods, especially in regimes of parameters where degrees of freedom compete or cooperate at similar energy and length scales. Here, we introduce a spin-1 slave-particle technique to approximately treat the t-U-V-J fermionic model at arbitrary electron dopings in an economical manner. This formalism respectively maps the original charge and spin degrees of freedom into effective pseudo-spin and pseudo-fermion sectors, which are treated using a self-consistent cluster mean-field method. We study the phase diagram of the model under various conditions and report the appearance of charge and spin stripes within this formalism. These stripes are a consequence of the cluster mean-field treatment of the pseudo-particle sectors and have not been detected in previous slave-particle studies. The results obtained agree qualitatively well with what more reliable numerical methods capture.

In combinatorial optimization problems with degenerate ground states, fair sampling of degenerate solutions is essential. However, the quantum approximate optimization algorithm (QAOA) with a standard transverse-field mixer induces biases among degenerate states as circuit depth increases. Based on quantum-classical correspondence theory, we propose SBO-QAOA, which employs a temperature-dependent Hamiltonian encoding a Gibbs distribution as its ground state. Numerical simulations show that, unlike standard QAOA, SBO-QAOA yields ground-state probabilities converging to finite-temperature values with uniform distribution among degenerate states. These fairness and temperature-targeting properties are preserved even with only four variational parameters under a linear schedule.

Consistent with prior qualitative expectations for group IV-VI topological crystalline insulators, this work demonstrates, based on band structure and Chern number calculations, that Pb$_{1-x}$Sn$_x$Se/(PbSe)$_{1-y}$(EuS)$_y$ quantum wells constitute a promising and viable platform for realizing a variety of quantum anomalous Hall phases. The proposed basis transformation procedure for the multiband $\mathit{k} \cdot \mathit{p}$ Hamiltonian enables the treatment of wells grown along arbitrary crystallographic directions while explicitly accounting for the anisotropy of the material's isoenergetic surfaces. Numerical studies of $\langle 111\rangle$-, $\langle 110\rangle$- and $\langle 001\rangle$-oriented quantum wells predict attainable Chern numbers with magnitudes ranging from $1$ to $4$, depending on the quantum well width, Sn content, and relative orientation of the four projected $\mathrm{L}$ valleys with respect to the growth direction. The results further indicate that appropriate strain compensation is required to achieve high-quality quantization of the Hall conductance.

We introduce a class of pseudo-bosonic Klein-Gordon fields in 1+1 dimensions and we discuss some of their properties. This work originates from non Hermitian quantum mechanics and deformed canonical commutation relations. We show that, within this class of fields, there exist a specific subclass with the interesting feature of having finite equal space-time two-points function, contrarily to what happens for {\em standard} Klein-Gordon fields. This, in our opinion, is a relevant aspect of our proposal which is a good motivation to undertake a deeper analysis of this (and related) quantum fields.

We compute one-loop QCD corrections to the triple differential width of the inclusive decay $\bar{B} \to X_c \ell \barν_\ell$ including contributions from all relevant dimension-six operators in the Weak Effective Theory (WET), at leading power in heavy quark expansion. Furthermore we derive for the first time up to order $\mathcal{O}(α_s)$ analytic expressions for the first three moments of the distribution in the lepton energy, hadronic invariant mass and dilepton invariant mass, in the presence of beyond the Standard Model contributions from the WET.

Hidden Markov models (HMMs) are ubiquitous in time-series modelling, with applications ranging from chemical reaction modelling to speech recognition. These HMMs are often large, with high-dimensional memories. A recently-proposed application of quantum technologies is to execute quantum analogues of HMMs. Such quantum HMMs (QHMMs) are strictly more expressive than their classical counterparts, enabling the construction of more parsimonious models of stochastic processes. However, state-of-the-art techniques for QHMM compression, based on tensor networks, are only applicable for a restricted subset of HMMs, where the transitions are deterministic. In this work we introduce a pipeline by which \emph{any} finite, ergodic HMM can be compressed in this manner, providing a route for effective quantum dimension reduction of general HMMs. We demonstrate the method on both a simple toy model, and on a speech-derived HMM trained from data, obtaining favourable memory--accuracy trade-offs compared to classical compression approaches.

Real-time decoding of quantum error correction (QEC) is essential for enabling fault-tolerant quantum computation. A practical decoder must operate with high accuracy at low latency, while remaining robust to spatial and temporal variations in hardware noise. We introduce a hardware-conditioned neural decoder framework designed to exploit the natural separation of timescales in superconducting processors, where calibration drifts occur over hours while error correction requires microsecond-scale responses. By processing calibration data through a graph-based encoder and conditioning a lightweight convolutional backbone via feature-wise linear modulation (FiLM), we decouple the heavy processing of device statistics from the low-latency syndrome decoding. We evaluate this approach using the 1D repetition code as a testbed on IBM Fez, Kingston, and Pittsburgh processors, collecting over 2.7 million experimental shots spanning distances up to d = 11. We demonstrate that a single trained model generalizes to unseen qubit chains and new calibration data acquired days later without retraining. On these unseen experiments, the FiLM-conditioned decoder achieves up to an 11.1x reduction in logical error rate relative to modified minimum-weight perfect matching. We observe that by employing a network architecture that exploits the highly asynchronous nature of system calibration and decoding, hardware-conditioned neural decoding demonstrates promising, adaptive performance with negligible latency overhead relative to unconditioned baselines.