Papers

Global connectivity in complex systems often emerges from local interactions, yet it remains unclear whether sophisticated agent strategies are required for such reorganisation. Here we identify a minimal mechanism by which heterogeneous mobility can generate system-wide connectivity when agents move within a structured multi-attractor landscape. In an agent-based model, a small fraction of higher-mobility agents explores the environment while the majority remains locally constrained. Configurational transitions are strongly localised at inter-attractor boundaries, where local crossing events accumulate over time to produce an expanding transition network and a percolation-like shift from fragmented to globally connected regimes. The core phenomenon persists under pure random-walk dynamics, showing that neither optimisation nor goal-directed behaviour is necessary. Interface-sensitive exploration nevertheless increases the transition rate by approximately four- to fivefold per exploratory movement relative to the random-walk baseline, thereby accelerating network integration. A novelty term produces only a small and non-uniform additional rate increase and no consistent improvement in unique-edge production. By contrast, when landscape structure is removed, transition-network connectivity arises through unconstrained spatial mixing, eliminating the boundary-mediated interpretation of the process. These results identify a minimal mechanism through which simple stochastic movement and spatial constraints generate large-scale connectivity. Interfaces between basins emerge as critical mediators linking local dynamics to global organisation, with potential implications for systems in which movement occurs across structured environments.

Understanding the chemistry related to the early stages of star formation is of great importance, as it is linked to the beginnings of the most complex chemistry in the interstellar medium. In this context, we investigate the chemical behaviour of simple cyano-bearing molecules and formylium ions isotopologues in a sample of massive infrared-quiet molecular cores. Using archive ALMA Band 7 data of 37 early molecular cores embedded in ATLASGAL clumps, we obtain abundances of HC$_{3}$N, H$^{13}$CN, HN$^{13}$C, H$^{13}$CO$^+$, and HC$^{17}$O$^+$. We used various statistical methods, including hierarchical clustering, to analyse the correlations between molecular abundances, ratios and temperature. We find that HN$^{13}$C, H$^{13}$CO$^{+}$, and HC$^{17}$O$^{+}$ abundances correlate positively with kinetic temperature, suggesting temperature-driven chemical regulation in young massive cores. A similar trend is observed for H$^{13}$CN, although the limited number of detections prevents a definitive conclusion. HC$_3$N abundances show no dependence on temperature within the 40-100 K range, suggesting a chemical steady state between gas-phase production and grain-surface depletion. Similarly, the H$^{13}$CN/HN$^{13}$C ratio, measured in only six regions, suggests no correlation with temperature, differing from findings at lower temperatures. Using a hierarchical clustering method based on abundance ratios, novel in astrochemistry, we identified chemically distinct core groups that align with thermal conditions. Additionally, we provide HC$^{17}$O$^+$ detections for 28 cores-a significant expansion of existing literature-and find evidence that H$^{13}$CO$^{+}$ transitions may have higher optical depths than commonly assumed. These results are important because characterizing the chemical state of early star-forming stages is essential for understanding the onset of the most complex chemistry.

Quasiparticle poisoning bottlenecks superconducting qubits, limiting coherence and the scalability of quantum processors. In this work, we systematically investigate quasiparticle poisoning in superconducting qubits under three infrared (IR) shielding configurations, ranging from a dedicated multi-layer design to a simplified implementation. By measuring quasiparticle-induced parity switching, we demonstrate a suppression of the switching rate by over four orders of magnitude via the implementation of improved shielding. In the best configuration, the rate decreases over time following cooldown and reaches 0.069$\,$Hz on day 34, corresponding to an anticipated quasiparticle density per Cooper pair of $1.88\times10^{-11}$. To our knowledge, this represents the lowest quasiparticle density reported in the literature to date. The remaining quasiparticle population is likely dominated by sporadic phonon bursts stemming from mechanical stress release in the on-chip films, as well as from the surrounding environment. The effective qubit temperature follows the phonon bath down to 17$\,$mK, enabling initialization errors of $\sim 0.01\%$ for 3$\,$GHz qubits. These results demonstrate that proper IR shielding and thermalization are essential for suppressing quasiparticle poisoning and enabling high-coherence, scalable superconducting qubit systems.

Ising machines are a promising approach to solve combinatorial optimization problems. They map these problems onto the Ising model and search for low-energy configurations. However, navigating the rugged energy landscapes of these systems remains difficult. To improve this navigation, classical adiabatic annealing has been proposed in the literature as a heuristic optimization method for classical Ising machines. Using this technique, the Hamiltonian of the Ising machine is gradually transformed from an easily solvable Hamiltonian to the target Hamiltonian. However, its purported effectiveness is primarily motivated by an analogy to quantum adiabatic annealing, and systematic benchmarking has remained limited. In this work, we analyze the classical adiabatic annealing technique using continuation methods. Motivated by insights from this analysis, we propose an optimized annealing strategy we refer to as hybrid classical adiabatic annealing. We benchmark our proposed strategy using MaxCut instances with up to 800 spins and problems with external fields, for which it achieves a marginal improvement for a limited set of problems. We conclude that, although theoretically motivated and occasionally beneficial, the hybrid strategy does not offer a sufficient practical advantage over simpler, existing techniques.

Searches for gravitational waves (GWs) from isolated supermassive black hole binaries (SMBHBs) in pulsar timing array (PTA) data require simultaneous estimation of signal and noise parameters, so the dimensionality of the fit scales with the number of observed pulsars. This computational difficulty is exacerbated when source evolution from GW emission is included, since retaining both Earth and pulsar terms introduces the unknown pulsar distances. Existing frequentist methods such as the $\mathcal{F}$-statistic are restricted to non-evolving sources. In addition, they often rely on a noise covariance estimated from the same data and then held fixed during the signal search, which can bias parameter estimates. We present a Generalized Likelihood Ratio Test and the associated $\mathcal{T}$-statistic that overcomes the aforementioned limitations. This formulation extends earlier work in which the dimensionality of the fitting problem was drastically reduced by semi-analytical maximization of the likelihood over the pulsar phase parameters, followed by efficient global optimization over the remaining parameters using Particle Swarm Optimization. Our simulations demonstrate that for an evolving SMBHB signal with chirp mass $\mathcal{M}=10^{9.2} M_\odot$ and signal-to-noise ratio $20$, this detection statistic achieves a $100\%$ detection probability at a false-alarm probability of $0.06$ in a 30-pulsar timing array, which is characterized by a $100 \mathrm{ns}$ root-mean-square white noise residual and pulsar-specific red noise. For the 30-pulsar timing array at signal-to-noise ratio $10$ and false-alarm probability $0.06$, $\mathcal{T}$ detects $99/100$ realizations, outperforming the $\mathcal{F}_p$ statistic evaluated with the $H_0$-fitted covariance, which detects $71/100$ realizations.

Machine-learned interatomic potentials (MLIPs) have had a profound impact on molecular modelling in recent years, promising to resolve the long-standing tension between the scale and accuracy of simulations. There has been a proliferation of new models and designs, and recently the paradigm of “foundational” MLIPs has become prevalent. Broadly speaking, foundation models are trained on large diverse datasets and promise to work well for new systems with minimal updates required. However, in such a new and fast moving field, there are many unanswered questions. In this article, we set out to articulate and explore what we see as the most important among these questions. We start by developing a working definition for foundational MLIPs and use this definition to frame the subsequent open questions. Despite the rapid progress in the field of MLIP models, we believe that these are fundamental questions which will continue to define cutting edge research in MLIPs in the years to come.

Bright squeezed vacuum (BSV) light has a vanishing mean optical electric field yet can strongly enhance strong-field nonlinear responses beyond the conventional semiclassical paradigm. Here we examine this scenario in the light-matter strong-coupling regime by investigating resonant multiphoton ionization of atoms driven by BSV, using a fully quantum treatment of both the electron and the field. Our results show that the photoelectron energy spectrum exhibits an anomalous Autler-Townes splitting whose magnitude grows with the Above-threshold-ionization (ATI) order, rather than remaining essentially ATI-order independent as in the case of coherent driving. This behavior reflects a general scaling with the number of absorbed photons and originates from the broad photon-number fluctuations of the driving field together with the resulting electron-field entanglement. We further show that the BSV-induced enhancement of ionization yields evolves with intensity, crossing over from the $g^{(p+1)}$ limit to the $g^{(p)}$ limit as Rabi oscillations become established. These results identify a quantum regime of strong-field ionization governed by the interplay of photon statistics, nonlinear transitions, strong coupling, and nonseparable light-matter dynamics.

Fractional Chern insulators (FCIs) realize fractional quantum Hall topology in lattice bands, but their excitation spectra remain far less understood than their ground states. Here we establish a theoretical principle relating the periodic electron-density modulations of flat Chern bands to the many-body gap and excitation spectrum of FCIs. Contrary to the conventional view that such density modulations are detrimental to fractional topology, we show that different reciprocal-lattice Fourier components play sharply distinct roles: components at smaller reciprocal lattice vectors suppress the FCI gap, whereas components at larger reciprocal lattice vectors enhance it. By suppressing the harmful small-wave-vector components and amplifying the beneficial large-wave-vector components, the gap enhancement can, in principle, be made arbitrarily large within the projected flat-band theory. Moreover, the same enhancement factor rescales the full low-energy spectrum, making the FCI excitation spectrum predictable from the corresponding Landau-level problem. We further generalize this correspondence to non-Abelian states. Applying this principle to moiré Chern bands, we identify these reciprocal-lattice density components as practical diagnostics for robust FCIs.

The traveling salesman problem (TSP) is a classic NP-hard problem. Held–Karp dynamic programming~\cite{held1962dynamic, bellman1962dynamic} solves it exactly in $O(n^2 2^n)$ time, a barrier that has stood for over six decades. Whether quantum computing can surpass $O^*(2^n)$ is a central open question. The authors of~\cite{ambainis2019quantum}\ (SODA~2019) claimed a query complexity of $O^*(1.727^n)$, but we identify a structural counting error: when corrected, their scheme requires $\Omega^*(2^n)$ queries and offers no advantage over classical Held–Karp. We design a quantum divide-and-conquer framework: partition $n$-vertex set into $k$ subsets, classically precompute shortest paths within each, then search over all $k$-partitions via quantum minimum finding. We prove $k=3$ achieves $O^*(1.890^n)$, and $k=4$ attains the global optimum $O^*(1.866^n)$, the first quantum algorithm to surpass $O^*(2^n)$ for general TSP. To convert the query bound into a time-complexity advantage, we overcome the oracle-construction bottleneck by preparing a set partition state, requiring $O(n^2)$ gates and $O(n)$ depth. Leveraging structured state preparation, we achieve a total time complexity of $O^*(1.866^n)$. Qiskit simulations on $n=6,7$ achieve $98.9\%$ and $100\%$ accuracy.

This study investigates the analytical solvability of the Klein-Gordon and Duffin-Kemmer-Petiau (DKP) equations for a scalar particle interacting with a transcendental $\alpha$-attractor-type potential, $V(x) = V_0 e^{a \tanh(bx)}$. We first address the problem of integrability within the framework of Picard-Vessiot theory. By analyzing the differential field extensions associated with the system, we demonstrated that the differential Galois group is the full special linear group $SL(2, \mathbb{C})$. Given that this group is not solvable, we provide rigorous proof for the non-existence of Liouvillian solutions, effectively ruling out any expression in terms of primitives and elementary functions. Building upon this result, we further establish that wavefunctions cannot be represented as finite compositions or transformations of classical special functions, such as those of the Bessel, Whittaker, or Heun families. This second conclusion is supported by the “double-transcendence” of the potential; we prove via the Hermite-Lindemann theorem that no rational coordinate transformation $z(x)$ exists that could map the physical equation into an ordinary differential equations(ODE) with rational coefficients. Consequently, the $\alpha$-attractor potential is strictly non-integrable and lies entirely outside the landscape of solvable relativistic quantum systems.

Quantum software bugs often yield silent, incorrect outputs rather than explicit errors, making them particularly difficult to detect and repair with conventional techniques. Although large language models (LLMs) have shown strong performance on classical software engineering tasks, their ability to debug quantum code remains largely unexplored. To bridge this gap, we propose QBugLM, a multi-agent framework that automates the quantum software debugging pipeline, from taxonomy-driven bug injection to LLM-based detection and repair, and finally to simulation-based validation, for framework-agnostic OpenQASM 3.0 programs. We further conduct a comprehensive case study using QBugLM to benchmark two LLMs, Claude 4.6 Sonnet and Qwen3 Coder Next, across different prompting strategies, bug categories, and quantum programs. Our results show that iterative feedback is critical, as a single retry raises Pass@1 from below 25% to above 80%. Moreover, simpler structured prompting can even outperform Chain-of-Thought and ReAct for reasoning-capable models under fixed-resource constraints. Our work takes initial steps toward benchmarking LLM capabilities for debugging quantum programs and offers practical insights to support future efforts in automated quantum software repair.

We examine the non-Markovian dynamics and the generation of quantum coherence and entanglement within a triple-layer graphene (TLG) system embedded in a planar microcavity. Using time-dependent perturbation theory, we derive an exact analytic solution for the system and demonstrate how the confined electromagnetic field mediates quantum correlations between the graphene layers. We employ three complementary measures; the relative entropy of coherence (REC) to quantify quantum coherence, the tangle to assess tripartite entanglement, and a non-Markovianity measure derived from the REC to characterize quantum memory effects. Our analysis reveals that these quantum resources exhibit remarkable sensitivity to various control parameters. Specifically, we demonstrate that the number of cutoff modes, the spatial positioning of the layers, the momentum parameter, and the interlayer rotation angles provide effective control over coherence, entanglement, and memory effects. We further show that these measures exhibit an exceptional sensitivity to the rotation angle between the layers. Ultimately, our results establish cavity-confined TLG as a highly tunable platform for exploring vacuum-mediated quantum phenomena, providing a framework for the precise manipulation of quantum correlations in graphene-based photonic and optoelectronic devices.

The development of multifunctional electronic skin (e-skin) requires materials that combine mechanical flexibility with responsiveness to multiple stimuli. In this work, a flexible PDMS/La0.7Sr0.3MnO3 (LSMO)/MWCNT composite thin film was fabricated via solution casting, using LSMO powder synthesized by a solid-state reaction method. Structural and spectroscopic analyses confirm the formation of single-phase rhombohedral LSMO and successful incorporation of PDMS, LSMO, and MWCNT components. The composite exhibits a smooth and uniform surface morphology, along with significantly enhanced thermal stability, retaining ~70% mass at elevated temperatures. Electrical measurements reveal thermally activated resistivity behavior, enabling temperature sensing functionality. Additionally, the composite shows a notable decrease in resistance under an applied magnetic field, exhibiting magnetoresistance due to spin-dependent transport in the LSMO phase. Mechanical testing indicates elastomeric behavior with a maximum load of ~0.49 N and stretchability of ~26%, along with ductile deformation characteristics. The multifunctional sensing properties arise from the synergistic interaction between the conductive MWCNT network and magnetically active LSMO within the flexible PDMS matrix. Overall, the composite demonstrates a unique combination of thermal stability, mechanical flexibility, and dual sensing capability, making it a promising material for next-generation e-skin applications.

We investigate proton-rich systems beyond the proton drip line, focusing on the notably poorly known 13F and 15Ne and the yet unobserved 14Ne, whose structure properties remain weakly constrained. Using the Gamow shell model (GSM), which consistently incorporates both inter-nucleon correlations and couplings to the particle continuum, we study oxygen, fluorine, and neon isotopes with mass A=12-16. Taking 8C as an inert core, the GSM Hamiltonian based on an effective field theory nucleon-nucleon interaction is optimized for this proton-rich region. The constructed Hamiltonian reproduces the low-lying spectra and decay properties of fluorine and neon isotopes beyond the proton drip line. We quantify many-body configuration and average partial-wave occupancies to elucidate the structural evolution of the drip line nuclei 12-14O, 13-15F, and 14-16Ne. In particular, multi-proton separation energies and spectroscopic factors are analyzed in detail, leading to a prediction for the unresolved ground state of 13F. Furthermore, the candidate 4p emitter 14Ne is theoretically predicted for the first time, providing valuable guidance for future experimental investigations.

The cosmic chronometer (CC) method provides a direct measurement of the expansion history of the universe, $H(z)$, from the differential ages of passively evolving galaxies. However, most CC analyses rely on high-quality spectroscopy to select passive galaxies, measure age-sensitive spectral features, and control stellar-population systematics. We build on existing works that use the D4000 spectral break as a proxy for measuring galaxy ages and apply it to a photometry-selected galaxy sample from VIPERS PDR2 in the range $0.5 \le z \le 0.8$. Our goal is to extend the scope of the standard CC framework to photometric surveys. To achieve this, we first selected a massive and passive galaxy sample using rest-frame colors and mass. Second, we designed a Bayesian framework to infer full galaxy age posteriors in fine redshift bins, using a D4000-age-metallicity grid from stellar population synthesis models. We marginalized over metallicity, using a Gaussian metallicity prior to break the D4000-age-metallicity degeneracy. Subsequently, we derived age-difference posteriors between redshift bins by convolving their age posteriors. Finally, using the median and errors extracted from the differential age posteriors, we calculated the weighted average $H(z)$ over our selected redshift range. We obtain $H(z=0.65)=93.68\pm28.27\,{\rm (stat.)}\pm10.67\,{\rm (syst.)}\ {\rm km\,s^{-1}\,Mpc^{-1}}$, which is consistent with existing spectroscopic CC measurements and with the $\Lambda$ cold dark matter ($\Lambda$CDM) model prediction from Planck at the same redshift. This result provides a proof of concept for extending direct $H(z)$ measurements from cosmic chronometers to photometric and spectro-photometric surveys, where larger samples can compensate for lower spectral resolution, provided that passive-galaxy selection, metallicity priors, and stellar-population systematics are carefully controlled.

Domain-wall(DW) networks are known to approach a relativistic scaling regime on fixed radiation- and matter-dominated backgrounds, forming the basis of the no-frustration conjecture. However, this picture assumes that the defect network remains gravitationally subdominant. We investigate the self-consistent evolution of DWs by coupling the velocity-dependent one-scale model to the Friedmann equation and radiation energy transfer. The resulting autonomous system allows the cosmic expansion history to evolve dynamically rather than being imposed externally. We demonstrate analytically that gravitational backreaction qualitatively changes the phase-space structure: the radiation-era scaling solution, which is a stable attractor on a fixed background, becomes a saddle once the expansion rate is promoted to a dynamical degree of freedom. Furthermore, we establish that no stable fixed point exists within the physical phase space. Consequently, the scaling regime survives only as a transient stage, and all trajectories are driven toward a wall dominated and kinematically frustrated state in which the walls freeze in comoving coordinates. Our results demonstrate that the scaling attractor is not preserved in self-gravitating DW networks and reveal the generic late-time frustration dynamics of wall domination.

The role of stellar chromospheres in the chemistry, mass loss, and evolution of cool evolved stars remains poorly understood. We present high-resolution ultraviolet spectra of the nearby Mira-type AGB star R~Leo obtained with STIS on board the Hubble Space Telescope. We focus on two strong chromospheric diagnostics, the Mg\,ii h & k resonance lines and the C\,ii] 2325\,Å\ multiplet, and model their formation with the NLTE radiative-transfer code RH using phase-dependent hydrodynamic atmospheric structures that include pulsation-driven shocks. The observed C\,ii] multiplet ratios imply an electron density of order $10^9\,\mathrm{cm^{-3}}$. The RH contribution functions show that the C\,ii] emission is strongly localized in a compact shock-heated shell at the first temperature peak of the model atmosphere, near $R\simeq1.8~R_{\rm phot}$, where $T\sim10^4$\,K and the local electron density is a few $10^8\,\mathrm{cm^{-3}}$. In contrast, the Mg\,ii h & k lines probe a more extended region ($R< 16~R_{\rm phot}$), with the line cores forming at greater radial distances than the wings. The Mg\,ii h line is reproduced more reliably than the k line, which is more strongly affected by circumstellar and interstellar absorption. As an additional low-opacity kinematic check, the semi-forbidden Al\,ii] $\lambda2669$ line shows a projected stellar-rest-frame blueshift of $\sim6~{\rm km~s^{-1}}$, consistent with shock-related motions expected in Mira atmospheres. Overall, the compact C\,ii] formation region, the extended Mg\,ii contribution functions, and the strong phase dependence of the synthetic Mg\,ii profiles support a picture in which pulsation-driven shocks shape the ultraviolet chromospheric emission lines in Mira variable stars.

We consider a generic case of neutrally wetting microswimmers in symmetric mixtures of two phase separating fluids, using hydrodynamic simulations. The swimmers spontaneously emulsify the two fluids into bicontinuous foam-like state. The two principal activity components: source dipole (self-propulsion) and force dipole (active mixing), create a twofold mechanism to stabilise the structures. When the self-propulsion is too strong, the swimmers cross the interfaces rapidly and the two fluids will phase separate. Below this threshold, the active stresses from the force dipoles, stabilise a dynamic and bicontinuous foam-like state. When the activity is turned off, the system relaxes into a kinetically trapped bicontinuous state, with particles permanently trapped at the interfaces. Our results provide a microscopic route to tunable active emulsions, with implications for bacterial suspensions and synthetic active matter.

Green's function-based downfolding methods construct effective Hamiltonians of reduced dimension that capture dynamical correlations of an electronic environment through effective potentials acting on the active space only. Using methods based on the constrained random phase approximation (cRPA) and moment RPA (mRPA), we construct static effective Hamiltonians that include screening through the environment. We derive expressions for the energy contribution from the environment and for the effective one- and two-body terms, taking into account double-counting corrections. cRPA requires additional consideration due to its frequency dependence, while mRPA provides a static Hamiltonian by construction. For the ground state energy of benzene and bond dissociation curves, we discuss the differences and similarities between the different flavors of RPA-based screening. We show that downfolding using cRPA describes both dynamical and strong correlation well, while mRPA and cRPA restricted to screening the particle-hole matrix elements can fail to describe bond dissociation due to a dominating dynamical correlation term. In the static limit, these two methods are shown to be almost indistinguishable.

This paper presents a detective scaffolding framework – a three-phase instructional sequence (Hypothesis Activation -> Evidence Structuring -> Causal Integration) in which engineering students investigate a realistic industrial defect scenario using staged in-class polls as designed evidence probes. Unlike conventional uses of student response systems for engagement, the framework positions each poll as an Evidence-Centred Design instrument targeting a specific reasoning capability. In the primary implementation, 80 Year~3 polymer engineering students progressed from prior-knowledge-driven misconception (71% attributing defects to temperature) to complete root-cause convergence (100% identifying humidity; Fisher's exact test, $p < .001$) across four sequenced prompts within a single 90-minute lecture slot. A dual-accuracy analysis revealed that at one intermediate stage, textbook-correct and analytically valid responses diverged, illustrating why conventional scoring can misrepresent reasoning quality. In a transferability study, 26 Year~12 students with no engineering background achieved identical root-cause identification rates across two adapted scenarios, with significant gains in data-analysis confidence and AI explanation ability. The results suggest that the pedagogical structure, rather than disciplinary content, drives the convergence effect, implying portability across disciplines and educational levels.

We summarise Sensor Quality Control (SQC) results of non-irradiated silicon sensors for the CMS HGCAL detector, as well as the first detailed annealing campaign with a wafer-scale 120\,\textmu m (Epitaxial) sensor exposed to \(2\times10^{15}\)\,\si{n_{eq}/cm^2} at the Rhode Island Nuclear Science Center (RINSC). For the non-irradiated sensors, we present an overview of the QC workflow developed for HGCAL, including automated handling of vendor data, validation of electrical measurements, and cross-checking of wafer-level characteristics. The study investigates, for the first time, the isothermal annealing behaviour at 60\,\si{\celsius} after annealing periods ranging from 10 to 5000 minutes. Hamburg-model parameters for effective doping concentration changes with annealing time, extracted from full-sensor data, are presented. The post-irradiation behaviour of sensors with hot regions in the pre-irradiation leakage current measurements, as well as epitaxial sensors with stacking faults in individual cells, is also investigated.

The characterization of the quantum critical properties of genuine non-Hermitian many-body systems remains ambiguous as neither the state considered nor the definition of expectation values is unique. In this work, we investigate the quantum critical properties of two models of non-Hermitian XY spin chains with magnetic field. Using exact solutions, we systematically investigate the parameter dependence of the energy, the magnetization as well as the long-distance asymptotic behavior of static correlation functions. We compute expectation values within the standard formalism of quantum mechanics as well as within biorthogonal quantum mechanics and take two different states which one might reasonably consider to be the analog of the ground state of a Hermitian model. The critical properties, including such fundamental characteristics as the phase diagram, depend on both the formalism used as well as the state considered. We provide arguments in favor of the use of standard quantum mechanics. Which state to be taken in computations, depends on the (hypothetical) experimental preparation of the system.

We study a one-dimensional long-range Su-Schrieffer-Heeger model with third-nearest-neighbor hopping and subject to quasiperiodic disorder. In the clean limit, the model hosts phases characterized by winding numbers $W=-1,0,1$ and $2$. The introduction of quasiperiodic disorder profoundly modifies the phase diagram and induces a series of topological phase transitions. Owing to the competition between topological dimerization and localization, topological Anderson insulating (TAI) phases with different winding numbers emerge and can persist even when the spectral gap becomes nearly closed in the strong-disorder regime. In addition, we uncover multiple reentrant topological phase transitions induced by varying either the quasiperiodic disorder strength or the hopping amplitudes. Remarkably, the system exhibits staircase-like topological Anderson transitions, where the real-space winding number evolves through successive quantized steps with increasing disorder strength. Our results demonstrate that the interplay between long-range hopping and quasiperiodic disorder generates a rich landscape of disorder-induced topological phases and reentrant topological transition phenomena.

Polymer self-consistent field theory (SCFT) has recently been established as a promising alternative framework to Kohn-Sham density functional theory (KS-DFT) for modeling quantum many-body systems. It uses real-valued propagators instead of orbitals, simplifying the self-consistent numerical solution. However, SCFT suffers from inaccuracies in heavy-element systems due to the approximate treatment of the Pauli potential, particularly the use of a constant repulsion strength parameter. In this work, we address this central limitation by introducing a Z-dependent Pauli potential that improves agreement with Hartree-Fock (HF) results. Furthermore, we advance SCFT implementation by employing B-spline basis functions-highly localized, piecewise-polynomial functions widely used in atomic structure theory. We demonstrate that B-splines provide a flexible and efficient representation of electronic structure, and present results for atomic binding energies from hydrogen to xenon. Comparisons with HF theory and prior SCFT calculations using Gaussian basis sets highlight the improved accuracy achieved with the Z-dependent potential.

We theoretically investigate circular dichroism in the ion yield following $1+1+1$ ionization of 3-methylcyclopentanone using femtosecond linearly chirped laser pulses, inspired by recent experiments by Das et al. [Phys. Chem. Chem. Phys. 27, 8043 (2025)]. To this end, we numerically solve the time-dependent Schrödinger equation and evaluate the total population in the Rydberg states at the end of the second absorption step. The A-band transition in the first absorption step is treated using state-of-the-art quantum-chemical calculations, whereas the second absorption step is described via an effective model. Within our framework, we identify the interplay between the first and second absorption step as the key explanation for the experimentally observed chirp dependence of the anisotropy. By elucidating this mechanism for the chirp-enhanced signal, our findings contribute towards the development of improved control schemes for chiral molecules.

We investigate the problem of the time reversal symmetry of fluctuations, as witnessed by the average shape of avalanches. This quantity has been measured in a variety of systems, ranging from magnetic materials to earthquakes. Although an asymmetric shape is often observed, which is a signature of a non-equilibrium dynamics, there is no general theoretical control of this feature. In this paper, we propose a non equilibrium extension of a paradigmatic model for “crackling-noise”, the so called ABBM model. Our model is strictly related to the Brownian Gyrator, which has been previously introduced in stochastic thermodynamics as the simplest model for thermal anisotropy, but it can also be framed in the context of rate-and-state models. It reproduces the phenomenology observed in experiments on granular friction, and allows for a systematic theoretical study of the asymmetry. We manage to correlate a measure of asymmetry, that can be easily computed in experiments, with the entropy production rates of the dynamics.

The structural characteristics of n2o-co2 alloys have been studied using transmission electron diffraction (THEED) across the entire range of their mutual concentrations at temperatures of 5 K and 65 K. The ranges in which regular solutions exist and intervals of alloy phase separation have been identified using the dependence of lattice parameters on composition and profile analysis of the diffraction pattern intensity distribution. It was found that maximum solubility values are up to 11 mol.% CO2 in the N2O matrix and up to 30 mol.% n2o in solid co2 at 65 K. The solubility limits for the components at 5 K are less 20 mol.% co2 in crystalline n2o and less than 35 mol.% n2o in a co2 crystal lattice. It was established that the character of n2o-co2 alloy separation corresponds to the mechanism of spinodal decomposition. The relative excess volumes that pertain to the admixture were determined for the CO2 impurity in solid n2o and for n2o impurity in co2 crystal. Conclusions regarding the character of n2o-co2 phase diagram have been made.

We investigate vortex nucleation and transport in a rotating dipolar supersolid arranged in a triangular droplet lattice, exploiting its description as an array of weakly linked condensates. By considering both Josephson and macroscopic self-trapping dynamics, we show that local phase differences between droplets provide a compact and highly predictive framework to explore a wide range of vortex behaviors. In particular, Josephson oscillations can be devised to induce vortex nucleation and motion near the vertices of the low-density hexagonal lattice (between droplets), while self-trapping dynamics induce running phases that enable directed vortex transport, which may be accompanied by vortex-antivortex pair creation and annihilation over finite time scales. Comparison with simulations based on the extended Gross-Pitaevskii equation demonstrates that a three-droplet description is essential to capture vortex motion near hexagon vertices. Together, Josephson and self-trapping dynamics provide a tunable protocol to trigger and track vortex nucleation, transport, and vortex-antivortex pair annihilation, revealing the microscopic topological mechanisms underlying phase slips in rotating dipolar supersolids.

Free-space optical systems are promising candidates for high performance computing and have been particularly successful in the implementation of large-scale convolutions. Convolutions are the key operation in convolutional layers, which are used extensively in modern neural networks, especially in the context of image/video processing and generation. These optical accelerators have demonstrated remarkable performance in both processing rates and energy efficiency. Prior approaches have primarily demonstrated convolutions from a single input channel to one or more output channels. We extend these methods to perform true multi-channel convolutions, where multiple input channels are convolved with their own sets of convolutional kernels onto output channels. We simulate this approach using both ray-tracing and angular spectrum propagation and find the approach is highly-scalable. We then experimentally implement a proof-of-concept prototype to demonstrate multi-channel free-space optical convolutions.

We provide a decomposition of the steady-state entropy production rate associated with an Ornstein-Uhlenbeck process into two contributions: one associated with oscillatory behavior and one associated with nonnormality. We also show that each contribution is associated with a different fundamental trade-off. The oscillatory contribution leads to the dissipation-coherence trade-off for noise-induced oscillations, which bounds the entropy production per oscillatory period by the number of oscillations within one correlation time. Notably, the tradeoff is twice as strict as those conjectured or derived for other systems. The nonnormal contribution leads to a trade-off between entropy production and acceleration of relaxation. We also demonstrate the decomposition using a simple bead-spring model.