Papers

Quantum error correction (QEC) codes can correct twice as many erasure errors as Pauli errors. Because of this scaling advantage, there is significant interest in developing qubits whose dominant error channel can be converted into erasures via mid-circuit erasure checks. However, such erasure checks come with hardware overhead in practice. End-of-the-line three-state readout, in which one simultaneously measures a qubit's erasure status and computational state, is an alternative to mid-circuit erasure checks that is generally simpler to implement. In this work, we systematically study the conditions required to enable erasure performance—the doubled error-correction capacity—in the surface code with and without mid-circuit erasure checks. We introduce the moonwalking surface code, the time-reversal of the walking surface code, as a zero-overhead circuit with superior handling of leakage and erasure. Specifically, we show that it enables erasure-like logical error rate scaling when combined with three-state measurement if leaked qubits cause two-qubit gates to be skipped and an appropriate decoder is used. Our decoder, based on a branch-and-bound algorithm, specifically incorporates the noise structure of the skip-gate leaked-qubit effect.

The Mid-infrared ELT Imager and Spectrograph (METIS) is one of the first-light instruments of the Extremely Large Telescope (ELT). For the L and M band, the instrument makes use of Teledyne's H2RG detectors, known to be affected by charge migration, also known as the brighter-fatter effect (BFE). In the H2RG detectors this manifests as photo-electrons moving from a central bright pixel to neighboring pixels as the depletion region of the central pixel shrinks with accumulated charge. Due to its effect of `blurring' information, it especially affects direct imaging, transit, and high-resolution spectroscopy applications. We aim to characterize its effect in the METIS H2RG detectors, such that we can remove it without losing information.

Estimating galaxy physical parameters from photometric data is fundamentally challenged by missing measurements that are endemic to astronomical surveys. Using a mock catalog from the Horizon-AGN hydrodynamical simulation that provides the true physical parameters, we evaluate CatBoost, a gradient-boosting algorithm that natively handles missing data, under a deliberately adversarial scenario: we train it on 12 photometric bands with increasing levels of injected missingness (10%, 20%, 30% missing per band) and compare its performance against an idealised parametric spectral energy distribution (SED)-fitting reference that uses complete 26-band photometry (no missing data, all bands available). This asymmetric design represents an upper-bound, best-case baseline for traditional methods. Despite this intentional disadvantage, CatBoost's performance degradation is limited: moving from complete data to 30% missing, mass RMSE increases from 0.08 to 0.18 dex, SFR RMSE from 0.41 to 0.53 dex, and redshift RMSE from 0.20 to 0.28, while bias remains near zero. Against the ideal SED-fitting reference, CatBoost trained on only 12 bands with 30% missing values achieves lower errors for mass (0.18 vs. 0.28 dex) and SFR (0.53 vs. 0.57 dex) and removes the systematic biases present in the SED-fitting results. For redshift, the SED-fitting reference has lower NMAD (0.030 vs. 0.093 at extreme missingness) while CatBoost maintains smaller bias. These results suggest that CatBoost's native handling of missing values can offer practical advantages for extracting galaxy properties from imperfect photometric surveys, at least under the conditions explored here.

In Particle Physics, a search for a new signal process is often based on observing a Poisson-distributed number of events, whose mean contains contributions from background and, if it exists, the hypothesised signal. The discovery significance can be expressed as an equivalent number of standard deviations derived from the $p$-value of the background-only hypothesis. To characterise the experimental sensitivity, one may report the median, assuming a nominal signal strength, of the discovery significance. In this paper, approximate expressions for the median significance are derived both when the expected number of background events is known and when the background rate is uncertain but constrained by a Poisson control measurement. The formulae are based on a test statistic using the profile likelihood ratio, and the median significance is approximated using the Asimov data set. Higher-order asymptotic corrections, based on the Barndorff-Nielsen $r^\ast$ statistic, are incorporated for both the observed and expected discovery significance. The validity of the resulting expressions is compared with Monte Carlo results and with other formulae for expected significance often used in particle physics. The higher-order corrections are found to provide meaningful improvements at small event yields. The results are important for obtaining an accurate assessment of the sensitivity of a planned experiment and for the optimal choice of cuts that determine the expected numbers of signal and background events.

As a part of the ESO Instrumentation Program, we already ordered 23 H4RG-15 (2.5 um cut-off) detectors for the instruments MOONS, MICADO, and HARMONI, with more of these detectors planned for future instruments on the ELT as well as possibly other ESO telescopes. As part of our comprehensive detector testing program, we characterize detector persistence at different temperatures between 40 and 85 K, allowing the best-informed choice of operating temperature for the science focal planes. We report the characteristics of persistence as a function of temperature for the 5 MOONS detectors and 10 MICADO detectors that have already been tested between 2019 and 2025. These detectors show a rich variety of persistence behaviour that can be fit with a single persistence model with varying parameters. We produce persistence trap maps and a model for persistence decay for each device, allowing automatic pipeline correction of persistence and also simulation of persistence behaviour of individual detectors using the Pyxel detector simulator. Each detector was unique and had different optimal operation temperatures for reduced persistence. We therefore recommend implementing a flexible thermal interface in the instrument design phase allowing for the detector operating temperature to be optimized after the science detectors have been fully characterized.

Physical systems can process information through their natural dynamics, offering alternatives to conventional digital computing. Reservoir computing offers a basic framework by using a nonlinear substrate to map inputs into rich dynamical states read out by a simple linear layer. Active matter substrates are striking examples; they continuously consume energy and produce entropy. Theoretically, entropy production (EP) can describe the irreversibility and distance from equilibrium. But it remains unclear whether it can track computational capabilities. We address this conceptual gap by analyzing a driven swarm reservoir model. The system EP is computed from phase-space contraction and the bath EP from heat flow, separately, and put in direct association to prediction performance on a Lorenz-63 task. Via force parameter scans, we show that dynamical regimes with the strongest response to a driver as well as dissipation coincide with peak performance. Therein, the dynamical discrepancy between innate (minimal dissipation) and driven transferred heat (maximal dissipation) is sharpest. Generally, driver work and relative differences of driven and undriven EP closely mirror the performance landscape. The system EP, derived from a generalized Liouville-equation estimator, and heat flow provide complementary diagnostics and metrics, which are most robust in the best-performing regime. These results extend prior expectations that dissipation matters for computation by identifying when and how it becomes predictive. They also relate inference power to innate dynamics, pointing to generic principles for physical computing and where EP offers a screening metric for reservoirs and other base substrates.

We study how much of the proto-area response can be inferred from the bulk von Neumann entropy. In the perturbative holographic code setting considered by CCKLP and Witten, we keep the recovery frame fixed and analyze the response averaged over the GUE at second order in the encoding perturbation. Near the maximally mixed bulk spectrum, the response is fixed by the entropy through quadratic order. For $d_1\geq3$, spectral information first enters at cubic order through the third centered moment, so states with the same entropy can have different responses. We determine the resulting response range on small equal-entropy level sets and obtain its sharp leading $D^{3/2}$ dependence, including the coefficient. The corresponding minimax error for prediction from entropy alone is one half of this range. For $d_1=2$, the entropy instead determines the response exactly.

Magneto-mechanical resonators (MMRs) are passive, wirelessly read sensors whose small size, miniaturizability, and low cost make them attractive for tracking and for sensing physical and chemical quantities. Their operation relies on a permanent-magnet rotor whose mechanical resonance encodes the sensing and tracking information. The bearing suspending this rotor is therefore decisive both for in-operation performance and for manufacturability. The original design suspends the rotor on a thin thread, which is nontrivial to assemble. This work investigates the impact of that structural design choice by introducing an alternative bearing in which the spherical rotor magnet rests in a cup-shaped industrial jewel. A dynamic model of this Jewel-MMR is derived, including the angle-dependent dry friction torque at the jewel contact. From it, a geometric trade-off between friction torque and resilience against unwanted oscillation modes is identified. Since the conventional quality factor loses its meaning under dominant dry friction, a two-tiered framework is proposed that compares MMR variants by estimation precision at equal magnet size and natural frequency. Both variants are characterized at a fixed pose on a Helmholtz-coil detection platform. The Jewel-MMR is self-aligning, requires fewer adhesive bonds and alignment steps, and the prototypes built here were assembled in less than half the time. Its response signal decays faster, so that under laboratory noise conditions the natural frequency and the orientation are recovered more precisely from the thread variant; these orientation figures quantify repeatability, not absolute accuracy. The jewel bearing, however, tolerates larger deflection angles and thus a stronger signal, which reverses this relation above a noise level determined in a simulation-based robustness analysis, indicating an advantage at reduced signal-to-noise ratio.

Oxidative stress is a key factor in low fertility outcomes during assisted reproduction technology (ART) and contributes to poor sperm quality. Conventional assessment relies on bright-field microscopy, which lacks the quantitative sensitivity to resolve subcellular structural and biophysical changes without exogenous contrast agents, a requirement that can introduce cytotoxic effects and compromise cell viability. This study uses QPM as a label-free, high-throughput method to demonstrate how ascorbic acid reduces the impact of oxidative structural degradation in Sahiwal bovine spermatozoa. To illustrate this pathology, severe oxidative stress was experimentally induced using hydrogen peroxide (H2O2), and two doses of ascorbic acid (1 mg/ml and 8 mg/ml) were tested to evaluate dose-dependent antioxidant recovery in structurally damaged sperm. QPM was used to quantify structural changes in key biophysical parameters, including dry mass, optical thickness, volume, surface area, sphericity, and surface area-to-volume ratio, as well as intracellular texture parameters. Under acute oxidative stress, bovine spermatozoa exhibited significant reductions in optical thickness and dry mass, alongside measurable changes in intracellular structural organization, collectively indicative of oxidative stress-induced morphological degradation. Co-treatment with ascorbic acid resulted in partial, dose-dependent structural preservation, with the 8 mg/ml formulation demonstrating statistically significant attenuation of these structural changes compared to the 1 mg/ml treatment group. These findings suggest that QPM-derived biophysical parameters may serve as promising, label-free structural indicators for characterizing oxidative damage in bovine spermatozoa. Future studies should incorporate functional validation to determine whether this structural preservation translates to improved outcomes in ART.

The entanglement entropy of quantum systems typically exhibits both ultraviolet and infrared (IR) divergences. In the low-frequency limit, the IR divergence is intimately tied to the unbounded spatial delocalization of zero-modes, a pathological feature common to both coupled harmonic oscillators and massless scalar fields. In this work, we demonstrate that this infinite growth is naturally resolved by invoking the Extended Uncertainty Principle (EUP), which introduces large-length-scale geometric corrections to the canonical commutation relations. By exactly solving the simple harmonic oscillator under the EUP framework, we establish the existence of an intrinsic geometric confinement that enforces a strict upper bound on the position variance, limits spatial delocalization, and introduces an intrinsic localization length scale related to the background Ricci scalar. We extend this regularizing mechanism to many-body systems by evaluating the entanglement entropy and entanglement spectrum of a one-dimensional harmonic chain and a massless scalar field. We show that the EUP-induced spatial bounds prevent the accumulation of low-lying long-wavelength modes, keeping the entanglement spectrum discrete and evenly gapped even in the strictly massless limit. This non-vanishing modular gap effectively caps the local entanglement temperature of the vacuum. Consequently, the entanglement entropy saturates to a finite value, providing a robust, geometric resolution to the zero-mode IR divergence problem in quantum field theory.

Context: Modern cosmological simulations rely on sophisticated assumptions and generate rich, highly complex datasets. Interpreting their results in order to extract new scientific insights remains challenging. Existing visualisation tools offer powerful capabilities but often come with a relatively high barrier for entry, and are not designed with a focus on knowledge discovery through real-time, intuitive visual analytics. This stands in contrast to other research domains, such as bioinformatics, where visual analytics tools have become deeply embedded in scientific discovery workflows. Aim: Our goal is to complement the existing ecosystem of cosmological visualisation tools with a lightweight, user-friendly application that supports visual analytics and frictionless dissemination of results to the scientific community. Methods: We developed ARGOS, an open-source, web-based environment for real-time visual analytics, tailored to cosmological simulation outputs and designed with an emphasis on user experience. ARGOS combines GPU-accelerated browser rendering for interactive exploration of large datasets with a template-driven approach that enables rapid adaptation to other types of data and analysis workflows. Importantly, ARGOS combines catalogue-level and object-level exploration, allowing users to move seamlessly from large ensembles of objects to snapshots of individual objects. Results: We demonstrate how ARGOS can support intuitive visual data exploration through example dashboards for multiple cosmological particle datasets, and illustrate broader applicability with dashboards for SKIRT synthetic multi-band imaging data products. Source code is freely available at https://github.com/pvaut/skirt-argos under the MIT licence. A reference deployment, including sample data, is available at https://skirt-argos.ugent.be.

We identify a Hall response carried by optically induced interband coherence rather than by a non-equilibrium band population. In a weakly doped zinc-blende semiconductor, a longitudinal dc field drives a transverse flux of the conduction–valence coherence created by near-gap light. Angular averaging eliminates the homogeneous coherence density, while a lateral boundary converts the transverse flux into an antisymmetric, edge-localized, helicity-odd polarization. The resulting Kerr signal requires neither spin-orbit coupling nor a spin, valley, or orbital accumulation within an individual band. Within the eight-band Kane model, we derive the boundary kinetic equation and obtain a complex propagation length controlled by optical detuning and interband dephasing. The edge profile is monotonic at optical resonance and develops damped spatial oscillations away from it. The response is enhanced by electron–hole asymmetry and by strong interband mixing, making narrow-gap semiconductors especially favorable to observe the effect. These results establish dc-driven Kerr microscopy as a direct probe of an interband-coherence Hall effect and of multiband quantum kinetics in real space.

In this work we study the high-temperature limit of the Schwarzian Field Theory probability measure. We show that on large scales this limit concentrates on jump processes, while its small-scale behaviour is governed by a process which we call Schwarzian Field Theory on the real line. This Schwarzian Theory on the real line can be viewed as the infinite-volume version of the Schwarzian Field Theory. In addition to showing this local convergence, we also provide a systematic treatment of the Schwarzian Theory on the real line. This includes the calculation of the correlation functions and a corresponding uniqueness theorem.

We introduce a variational framework for approximating the time-evolution operator $\hat{U}(t)$ within a physically motivated operator manifold, reformulating quantum dynamics as a tractable problem in operator space using stationary action principle. For periodically driven systems, the resulting approximate evolution operator directly yields an effective Floquet Hamiltonian, offering a non-perturbative alternative to conventional expansion-based methods. The framework is systematically improvable by enlarging the operator pool and naturally incorporates symmetries and physical constraints. When the operator manifold is chosen from the terms of a truncated Magnus expansion, the variational procedure effectively resums the Magnus series within the restricted space, significantly enhancing accuracy. We benchmark the approach on the driven Rabi model, the driven Lipkin-Meshkov-Glick model, and the one-dimensional driven Ising chain, yielding effective Floquet Hamiltonians that are systematically more accurate than low-order Magnus expansions, particularly in regimes where the latter converge poorly, and illustrating applicability to systems with exponentially large Hilbert spaces. Although we focus here on Floquet systems, the formalism applies equally to generic time-dependent Hamiltonians, providing a versatile tool for non-equilibrium quantum dynamics.

Turbulence within the intracluster medium (ICM) influences galaxy cluster thermodynamics and virialisation, contributing to non-thermal pressure support and impacting hydrostatic mass estimates. Characterising this turbulence through thermodynamic fluctuations remains observationally challenging due to the non-linear relationships between observables such as density and pressure, and the underlying velocity field. This study aims to constrain the properties of ICM turbulence by performing a comprehensive reanalysis of the Sunyaev-Zel'dovich (SZ) surface brightness fluctuations based on Planck survey observations of the Coma cluster. We analyse the 2D power spectrum of SZ fluctuations, modelling the underlying 3D pressure fluctuation power spectrum assuming Kolmogorov-type turbulence. We infer key parameters from a simulation-based inference framework relying on normalizing flows to accurately recover posterior distributions. By constraining the pressure fluctuation power spectrum, we are able to infer the properties of turbulence in the Coma cluster, finding a large injection scale of $l_{\text{inj}} = 540^{+450}_{-200}$ kpc, a slope of $\alpha = 3.50_{-0.46}^{+0.50}$ (under Gaussian prior), and a substantial 3D Mach number of $\mathcal{M}_{3D} = 0.60^{+0.13}_{-0.09}$. These values correspond to turbulent velocities in the range $\sigma_{v,\text{ }3D} = 357-1095$ km/s and a non thermal pressure fraction of $P_{\text{turb}}/P_{\text{tot}} = 0.17_{-0.04}^{+0.06}$. Our results are consistent with recent direct velocity measurements from XRISM, supporting a scenario of significant turbulence in the Coma cluster and highlighting the complex interplay of dynamical processes within its ICM. Our simulation-based inference approach applied to SZ fluctuations paves the way for systematic multi-probe studies combining SZ and X-ray data, as well as direct and indirect observations.

Novel experiments in transmission electron microscopy often require the development of specialized imaging and spectroscopy states, such as for flexible momentum-resolved high energy-resolution spectroscopy. This task is complicated by the need to align and configure many different lenses, and by ambiguity around the locations of various imaging and diffraction planes. Here we develop a versatile digital twin for simulating the electron beam trajectory throughout an electron microscope, and we develop the calibration procedures required for accurate prediction of microscope states. This allows the user to quickly and easily determine the correct lens values for setting up new condenser or projector modes. Automatic procedures to change lens settings and measure the resulting changes can be used to close the loop. With the accelerating development of machine learning and artificial intelligence tools, we also believe a physically-informed model of the microscope can serve as a valuable tool for automated microscopy and AI/ML integration.

Brownian noise in the thin-film mirror coatings of optical reference cavities is a fundamental limitation in precision metrology, including gravitational-wave detectors and optical atomic clocks. We demonstrate a monolithic fused silica resonator that eliminates the use of thin-film coatings by operating via total internal reflection (TIR), achieving a finesse of 1225 and an optical mode volume of \qty{50}{mm^3}. To our knowledge, this is the largest mode volume reported for any coating-free monolithic resonator, comparable to state-of-the-art reference cavities. We use the cavity to frequency-stabilize an Nd:YAG laser, and demonstrate its application to precision metrology by operating it in a passive ring gyroscope configuration. This platform circumvents the dominant noise source of conventional reference cavities and provides a pathway toward cryogenic silicon TIR resonators that could surpass current frequency stabilization limits.

Stellar bars are a major driving force in the secular evolution of their host galaxies. To better understand the connections between the 3D bar density structure, its orbital composition, stellar populations, and underlying dark matter distribution, it is desirable to construct detailed dynamical models of barred galaxies. However, only a few external barred galaxies have been studied in this way so far. We present a new Schwarzschild orbit superposition code for triaxial potentials with figure rotation and test it extensively using mock data from an N-body simulation of a strongly barred galaxy. We investigate the recovery of model parameters in the nearly face-on case which was not previously considered. In particular, we demonstrate a 10% accuracy of both the pattern speed and mass-to-light ratio and a 20% accuracy for the dark matter halo mass scaling at the inclination 20{\deg}. Surprisingly, we obtain a similarly accurate result for the pattern speed in an exact face-on limit, where conventional methods such as Tremaine-Weinberg are no longer applicable. This result suggests that varying the pattern speed at fixed bar length, corresponding to the transition between slow and fast bars, alters the distribution function in a way that produces a systematic change in the vertical velocity distribution, which can not be compensated by the in-plane velocity components.

A general implementation of the equation-of-motion (EOM) formalism for correlated many-body states is presented and applied to the description of collective excitations in atomic nuclei. While EOM approaches are traditionally formulated on top of independent-particle reference states, the present work extends the method to correlated reference states generated by modern many-body solvers. This formulation enables a consistent treatment of ground-state correlations and excited-state dynamics within a unified framework. Particular emphasis is placed on collective nuclear excitations employing chiral nuclear Hamiltonians in an ab initio context. The approach is motivated by the renewed interest in EOM techniques across several fields, including quantum chemistry and quantum computing, where they provide efficient and systematically improvable descriptions of excitation spectra. The present results demonstrate that the EOM framework offers a flexible and powerful tool for the microscopic description of nuclear spectroscopy beyond the traditional mean-field paradigm.

Understanding the evolution of magnetic order in the two-dimensional limit remains a central challenge in van der Waals magnets, where thermodynamic measurements are constrained by the femtogram-scale mass of exfoliated flakes. Here, microsecond pulse-heating nanocalorimetry is used to measure the heat capacity and magnetic entropy of CrSBr flakes down to the monolayer limit. The measurements reveal the entropy landscape associated with magnetic ordering, uncovering a decreasing interlayer transition temperature toward the monolayer limit and an entropy-derived effective moment per layer that increases with thickness toward the expected spin-only scale. Thermodynamic anomalies capture a crossover from bulk-like interlayer antiferromagnetism to a regime dominated by intralayer ferromagnetic correlations. A pronounced layer-parity effect further emerges, with odd-layer samples displaying an additional high-temperature contribution associated with uncompensated magnetic layers. Under in-plane magnetic fields applied along the easy axis, antiferromagnetic order is progressively suppressed, allowing extraction of a thickness-dependent characteristic suppression field reflecting weakened interlayer exchange coupling. Entropy analysis further reveals an extended regime of magnetic fluctuations persisting well above the interlayer ordering transition. Together, these results establish nanocalorimetry as a powerful thermodynamic probe of low-dimensional magnetism, providing direct access to magnetic entropy, exchange interactions, and dimensional crossover in atomically thin van der Waals magnets.

We investigate ultrasound attenuation and sound velocity shift in antiferromagnetic spin-1/2 XXZ chains in magnetic field. We relate the sound velocity shift to derivatives of the free energy with respect to exchange interactions, permitting its calculation with integrability techniques at any temperature. Using bosonization, we predict the sound velocity shift exhibits a quadratic temperature correction at low temperatures in the Tomonaga-Luttinger liquid phase. Close to the fully polarized phase, a universal behavior associated with z=2 quantum criticality is found. In the Tomonaga-Luttinger liquid phase, ultrasound attenuation obeys a scaling law as a function of wavelength and temperature. An enhancement of attenuation is obtained near the fully polarized phase.

Magnetic Weber Bars have been proposed to search for gravitational waves in the kHz to GHz regime by exploiting the mechanical deformation of a large magnet induced by a gravitational wave. Here we propose to increase the effectiveness of such devices by considering magnetic field configurations with strong gradients, albeit lower field strengths, such as Halbach arrays. We focus on one of the most challenging but most realistic signals, with short duration and low coherence, exploiting the ring-down period of the mechanical resonator. We show that with demonstrated technology this setup can reach sensitivities of $S_h^{1/2} \simeq 10^{-21}/\sqrt{\text{Hz}}$ at a broad set of frequencies around several resonance peaks at $\sim 10$ kHz, and $S_h^{1/2} \simeq 5 \cdot 10^{-20}/\sqrt{\text{Hz}}$ in a broadband search at higher frequencies. We discuss plausible upgrades to reach $S_h^{1/2} \simeq (10^{-23} - 10^{-21})/\sqrt{\text{Hz}}$ in a broadband search covering 10 kHz - MHz.

Colloidal quantum dots (QDs) are attractive nanoscale emitters, yet their cathodoluminescence (CL) response remains poorly understood and often unstable under electron-beam excitation, limiting CL spectroscopy and electron-beam-based device processing. Here, we investigate the CL mechanism and strategies to improve its stability using highly photostable, structurally homogeneous giant-shell CdSe/CdS QDs combined with in situ CL and photoluminescence (PL) measurements. By identifying distinct signatures of excited states in both lifetime and spectral measurements, we demonstrate that the CL response is governed by electron-beam-induced charging. Charge accumulation drives multiexciton generation even at relatively low currents, leading to a pronounced blueshift, shorter average lifetimes, and rapid cathodobleaching. To test this further, we employ indirect excitation to reach sub-pA currents beyond the limits of typical electron beams, showing that neutral-exciton emission can be partially recovered and cathodobleaching mitigated, although charging cannot be fully suppressed. Furthermore, by replacing long insulating ligands with shorter ones, we improve charge drainage and strongly suppress biexciton formation. Together, these results show that biexciton formation can be controlled by limiting charge accumulation, providing a practical route toward stable CL for spectroscopy, imaging, and electron-beam-compatible photonic devices.

Evolving technologies have traditionally influenced pedagogical practices and Generative AI is one such technology that promises to transform higher education. In this study, we investigate the association between introductory students' preferences for chatbot behavior and their epistemological beliefs surrounding physics. Our context involves a custom built online module on waves containing simulations integrated with a chatbot. While students' chatbot preferences were captured through three provided options (guided-inquiry, direct answer, and a combination of inquiry and answer), their epistemological beliefs were captured through the standardized Epistemological Beliefs Assessment for Physical Sciences (EBAPS) survey. Results highlight that students who preferred chatbots that initially engage them in guided-inquiry but provide answers when explicitly sought (`Combination'), demonstrated sophisticated epistemological beliefs than those who preferred answer-providing chatbots. Notably, we did not observe any association between the EBAPS' total scores among students who preferred guided-inquiry and those who preferred answer-oriented chatbots. Furthermore, the observed differences did not remain statistically significant after applying a Bonferroni-adjusted significance level. Implications of these results for the design and instructional use of chatbots in physics education are discussed.

Deterministic exact inversion of an arbitrary $d$-dimensional unitary requires {$\Theta(d^2)$} coherent forward calls in the worst case. We ask how this cost changes for Hamiltonian evolution $U(x)=\exp(i\sum_j x_jH_j)$ when the generators are known but the parameters are hidden. For one-parameter families with a fixed eigenbasis, we show that additive relations among the distinct eigenvalues determine the optimal query number exactly, and we construct the corresponding inversion protocol. For general families, we prove that repeated symmetry sectors do not affect the exact query complexity and give an automatic construction for combining inverses from inequivalent active sectors. We also give a sufficient phase-alignment condition under which family-specific structure can reduce the query number. These results establish structure-dependent bounds for reversing the unknown dynamics arising in Tavis-Cummings out-of-time-order correlator protocols, collective-spin echo verification, and passive multimode links, without requiring prior knowledge or explicit estimation of the underlying coupling strengths.

The relaxation of the earthquake source following the main shock has been investigated both theoretically and experimentally, based on data regarding the evolution of aftershocks. It is shown that Omori picture of aftershock evolution is not holistic, whereas the Hirano-Utsu representation contradicts observations. Linear and discrete representations are proposed. They are based on original concepts regarding deactivation and the proper time of the source. The difference between the linear and discrete representations lies in the procedure for processing experimental data on aftershocks. In the linear representation, proper time is calculated based on the frequency of aftershocks. In a discrete representation, the source's proper time is measured by an imaginary underground clock, the rate of which differs radically from that of universal time. In the linear representation, the frequency of aftershocks is described by the simplest nonlinear differential equation. In the discrete representation, the aftershock frequency is described by a first-order linear differential equation. It has been found that aftershock activity decays exponentially with the source's proper time. Keywords: earthquake source, foreshocks, mainshock, aftershock theory, Omori law, Utsu's law, proper time, underground clock, deactivation coefficient, source relaxation.

Grain charging and gas ionization are important processes in protoplanetary disks. Both occur in mutual collisions between grains, as charge is exchanged between grain surfaces but also released into the surrounding gas as ions. The charge carrier for tribocharging, the origin of the gaseous ions, and their composition are currently unknown. However, it is important to know to validate the significance of these processes under disk conditions. In this work, we approach these questions by detecting molecules ejected during grain collisions by mass spectrometry. As tribocharging works well under normal atmospheric conditions, we use untreated "dirty" particles here. Without collisions, our measurements show a background mix of molecules. Among these are organics, but especially water-related molecules. During collisions, the abundances of not all but quite a few molecules change. Water-related molecules account for one of the largest changing fractions. These results suggest that particle collisions release adsorbates even at very low pressure, which is relevant for protoplanetary disks. As monolayers of water and organics are present on all surfaces in cool to moderately tempered parts of protoplanetary disks, this supports the importance of triboionization in disks.

We prove a conjecture formulated by Bolsinov, Konyaev and Matveev in [7] stating that, integrability of a system of hydrodynamic type ${\bf u}_t=A({\bf u}) {\bf u}_x$ with $\mathfrak{gl}$-regular $A$ at a point $p$ implies the vanishing of the Haantjes tensor of $A$ and of all its symmetries in a neighborhood of $p$. As a consequence, leveraging on the result of [8], in a neighbourhood of an algebraically generic point, any integrable system of hydrodynamic type defined by a $\mathfrak{gl}$-regular operator field can be written as ${\bf u}_t=X({\bf u})\circ {\bf u}_x$ where $X$ is a vector field and $\circ$ is a commutative associative product satisfying Hertling-Manin conditions.

We experimentally demonstrate the generation of sub-two-cycle optical pulses using a cascaded post-compression scheme based on two bulk multi-pass cells. Starting from 220 fs, 100 ${\mu}$J pulses around 1030 nm, sequential spectral broadening and pulse compression reduce the pulse duration first to 50 fs and ultimately to 5.5 fs (1.6 optical cycles) at a central wavelength of 1058 nm. The ultra-broadband spectrum is enabled by a dispersion-controlled cavity. Comprehensive spectral, temporal, and spatial characterization confirms excellent pulse quality. Despite operating the second multi-pass cell at peak powers several hundred times above the critical power for self-focusing in fused silica, no significant spatio-spectral or spatio-temporal distortions are observed, enabling direct use of the compressed 40 ${\mu}$J pulses in further experiments. Numerical simulations of the nonlinear spectral broadening show excellent agreement with the experimental results, supporting the underlying physical picture. These findings establish bulk multi-pass cells as an efficient, compact, and robust platform for generating few-cycle pulses with excellent beam quality, offering considerable potential for strong-field and ultrafast applications, including extreme-ultraviolet generation and isolated attosecond pulse production.

We present a data-driven plasma fluid closure for both linear and nonlinear electrostatic Landau damping in one dimension. A Fourier Neural Operator (FNO) is trained online within a differentiable fluid solver, with the loss computed on trajectories produced by the closed fluid simulation rather than on individual kinetic snapshots. The closure is non-Markovian, acting on a trailing window of the resolved moment history so as to represent the memory of the unresolved dynamics. We demonstrate that a single FNO trained in this way reproduces both linear and nonlinear Landau damping, generalises to initial perturbation amplitudes outside the training set, and remains numerically stable when deployed in independent fluid simulations. In the nonlinear regime the learned heat flux reproduces the resolved-moment dynamics without matching the kinetic heat flux pointwise, behaving as an effective closure that compensates for the truncated higher moments, though the learned specific flux is expected to depend on the numerical scheme and training data. A sensitivity analysis of the trained model shows that it computes a genuine moment-to-flux relation whose reliance on the memory window is physically structured.