Papers

Quantum computers offer a route to outperform classical methods in tasks such as molecular simulation, motivating hybrid algorithms like the Variational Quantum Eigensolver (VQE) for near-term devices. Silicon spin qubits are a promising platform for scalable quantum computation, but their performance is limited by hardware imperfections – most notably charge-noise-induced potential fluctuations and static miscalibration of gate-electrode voltages – which degrade quantum gate fidelities and, ultimately, algorithmic accuracy. Here we develop a hardware-algorithm co-simulation framework for silicon quantum-dot processors that links 3D electrostatics to effective $g$-factors and exchange couplings, and propagates voltage-level noise through realistic control pulses. Using VQE for $\mathrm{H}_2$ ground-state energy estimation as a circuit-level testbed, we study both static scaling/offset errors on the gate-electrode voltages and stochastic fluctuations modeled as random-telegraph noise with tunable amplitudes and switching times. At the gate level, we show that exchange-based two-qubit gates are roughly an order of magnitude more sensitive to these types of noise than ESR-driven single-qubit rotations. Quantum process tomography and Kraus-operator analysis further distinguish coherent and incoherent contributions and quantify the fraction of error that is, in principle, correctable by a compensating unitary. Embedding these noise models into the VQE circuit, we identify regimes of miscalibration strength and noise switching time compatible with chemically accurate energy estimates, and discuss how statistical post-processing based on the full distribution of noisy energy estimates could further improve accuracy.

As quantum networks evolve from experimental testbeds to fault-tolerant systems, the primary performance metric shifts from physical link fidelity to end-to-end logical error rate. However, current control planes remain ill-equipped for this transition: routing decisions are typically decoupled from Quantum Error Correction (QEC) strategies, relying on topology or scalar fidelity metrics that fail to predict how specific physical noise structures interact with logical codes. Optimizing this coupled route-and-code performance requires precise, real-time visibility into network error biases, yet traditional active tomography is operationally prohibitive due to throughput collapse and service interruption. We present SCOPE (Syndrome-based COntrol PlanE), a network-layer architecture that enables joint routing and coding optimization using purely passive telemetry. Instead of injecting probes, SCOPE harvests error syndromes – the parity-check outcomes naturally generated by QEC decoders during user service. By aggregating these signals, SCOPE's inference engine reconstructs the network's time-varying error map, capturing complex, context-dependent noise correlations. This visibility drives a decision engine that proactively pushes optimal route-and-code configurations to source nodes. NetSquid and IBM-calibrated simulations show that SCOPE reduces estimation error by more than 60% relative to a standard EM baseline. In large-scale networks, this precision reduces logical error rates by 30-35% (up to 65%) against topology-aware baselines.

Atomic clocks have made time and frequency the most precisely measured quantities in physics, progressing from microwave standards that realize the SI second to optical clocks with unprecedented precision. A nuclear clock transfers the frequency reference from an electronic to a nuclear transition, and the uniquely low-lying, laser-accessible isomeric transition in $^{229}$Th currently offers the most practical route to compact, robust timekeeping and sensitive tests of fundamental physics. Realizing such a clock requires turning spectroscopy of the $^{229}$Th nuclear resonance into a stable discriminator for steering a traceable oscillator. Here we demonstrate a $^{229}$Th nuclear clock by stabilizing a continuous-wave, narrow-linewidth 148.4-nm vacuum-ultraviolet (VUV) laser to a resolved, weakly temperature-sensitive nuclear transition in $^{229}$Th$:$CaF$_2$ crystals. A $10$-$\mu\mathrm{W}$ VUV source generated by four-wave mixing in cadmium vapour and phototube-based frequency-modulation absorption readout provide a fast, high-signal-to-noise nuclear discriminator. The clock reaches a fractional frequency instability of $5\times10^{-13}/\sqrt{\tau/\mathrm{s}}$ for averaging time $\tau$. Clock-transition frequencies measured in two independently fabricated crystals agree at the $10^{-13}$ level and are consistent with previous VUV-comb measurements on other $^{229}$Th:CaF$_2$ crystals. These results establish laser-addressed nuclei as operational clock references and provide a reproducible solid-state platform for compact nuclear clocks, nuclear quantum sensors and precision tests of fundamental physics.

We consider a wide class of $2D$ tight - binding models of solid state physics. These models are, in the most general case, non - homogeneous. The topological invariant ${\cal N}_3$ responsible for the quantization of the Hall conductivity, for the specific case of the integer quantum Hall effect in $2D$, is expressed through the Wigner transformation of the two-point electron Matsubara Green function. We express this invariant as a pairing of the element of the $K^{-1}$ group (generated by the Green function) with the specific element of the cyclic cohomology group $HC^3$. According to a set of local index theorems the values of ${\cal N}_3$ can be shown to be integer for a limited class of tight - binding models. We concentrate on systems with a spectral gap, with the chemical potential inside the gap and an invertible Dirac operator $\hat Q$ throughout the Matsubara-frequency domain. The mobility-gap case is not considered here and will be addressed in forthcoming publications.

We present an X-ray spectro-polarimetric study of the nearby type-1 active galactic nucleus NGC 4151 using two long IXPE observations obtained in 2022 and 2024, supported by simultaneous XMM-Newton and NuSTAR spectroscopy. IXPE measures a polarization degree of $\sim 6-7\%$ above 4 keV, with a polarization angle parallel to the radio jet, and a distinct low-energy component with a different angle, indicating at least two polarized components in the $2-8$ keV band. Previous work interpreted the hard X-ray polarization as evidence for a radially extended slab-like corona. Here we test an alternative scenario in which the observed polarization is produced predominantly by relativistic reflection from an accretion disk illuminated by a compact, lamp-post-like corona. Using recently developed models, we fit the IXPE Stokes spectra with a lamp-post plus distant-torus geometry, including partial-covering absorption and an additional soft polarized power-law component. We find that the data require a low coronal height ($h<9\,R_{\rm g}$ at $3\sigma$) and a relatively large torus opening angle ($>45^\circ$ at 3$\sigma$), while the disk reflection contributes $\sim 20\%$ of the 2-8 keV flux. The soft polarized component carries only $\sim 1-5\%$ of the flux but has a high polarization degree ($>10\%$) and a polarization angle around $20^\circ$. The same configuration provides acceptable fits to the $0.4-79$ keV XMM-Newton and NuSTAR spectra, demonstrating that disk reprocessing by a compact corona can simultaneously account for both the polarization and broadband spectral properties of NGC 4151.

The frequency dependence of opacity is crucial for determining the thermal structure of protoplanetary disks, which in turn influences disk dynamics and planet formation. Yet many disk models adopt simplified thermodynamics, and common radiation-hydrodynamic approaches often use gray opacities, ignore scattering, and yield inaccurate results in regions with intermediate optical depth. We present a comprehensive framework that models stellar irradiation with frequency-dependent absorption and scattering across all optical depths using the Athena++ finite-volume code, extended with multigroup radiation transport and newly implemented radial rays to more accurately represent the stellar flux. To calibrate this framework, we focus exclusively on hydrostatic disk models, allowing us to isolate radiative effects and evaluate the method without additional dynamical complexity. Because dust opacity increases strongly with frequency, ultraviolet stellar irradiation heats the tenuous disk atmosphere while the optically thick midplane remains cooler. This vertical temperature gradient is captured more accurately when more frequency bands are used or when scattering is included. Our hydrostatic models achieve equilibrium temperatures that differ from Monte Carlo radiative-transfer benchmarks on average by 2–5% with 64 frequency bands and 7–11% with 3 bands. Reducing the number of bands lowers computational cost by at least an order of magnitude while increasing the maximum possible temperature deviation only from 8% to 19%. This calibration demonstrates the accuracy and efficiency of the framework and provides a solid foundation for future self-consistent studies of irradiated protoplanetary disks, including fully dynamical simulations and applications involving chemical processes and time-dependent stellar luminosity.

The ethanimine molecule, CH3CHNH, is one of the prebiotic molecules detected by astronomers in chemically-rich molecular clouds in the Galactic Center. The observations indicate a non-equilibrium distribution of rotational state populations in both the E- and Z-isomers of ethanimine, resulting from the competition between radiative processes and collisions with background gases such as He and H2. Accurate interpretation of these observations requires the use of radiative transfer models with collisional state-to-state transition processes included. Here, in order to compute cross sections for state-to-state transitions in both ethanimine isomers, accurate potential energy surfaces for their interaction with a He atom were constructed and three complementary methods for inelastic scattering were utilized: full-quantum coupled-channel and coupled-states methods, and the mixed quantum/classical theory. Strong propensities of transitions toward $\Delta j = 0$ and either $\Delta k_a = 0$ (with $\Delta k_c = \pm 1$) or $\Delta k_c = 0$ (with $\Delta k_a = \pm 1$) are reported and the origin of this effect is identified. Small but non-negligible differences between energy transfer in the two isomers, on the order of 10%, were found. The utility of the mixed quantum/classical approach to collisional energy transfer at higher collision energies is discussed.

The information-theoretic concept of identification describes a sender-receiver architecture in which the receiver only checks whether a particular message was sent or not, thereby promising a low-energy receiver design. In low received-energy regimes, quantum receivers are a promising tool for studying the system limits. However, the known information-theoretically optimal identification codes typically assume perfect synchronization. In this work, we study deterministic identification in a satellite setting under explicit synchronization constraints, where a satellite broadcasts the signature of a specific User Equipment (UE) which it assumes to be attached to one out of several possible Ground Station (GS), with the goal of establishing communication with the target UE. Within the proposed design, and assuming a specific phase-encoded coherent-state clock scheme in which the discrete time index is represented by equidistant phase rotations on the unit circle, our results reveal a fundamental asymmetry: At any transmission power, identification performance improves with blocklength, whereas synchronization accuracy degrades. In particular, the energy needed for transmitting the satellite clock to the GS can be several orders of magnitude higher than the one needed for the identification signal. This indicates that synchronization strongly impacts identification performance and motivates the investigation of the error-correcting capabilities of bosonic codes under jitter.

We investigate the properties of heat conduction in a network of harmonic oscillators interacting with heat baths, described by a generalized model of Brownian motion. This model includes noise and dissipation terms in both the momentum and position equations. This generalization is motivated by the requirement of consistency with the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. Because standard definitions of heat current based on velocity become mathematically inconsistent in this framework, we derive an analytical expression for the steady-state heat flow based on an extended framework of stochastic energetics. We confirm that Fourier's law (linear thermal response) is satisfied and that the model naturally captures microscopic thermal boundary resistance, analogous to Kapitza resistance. This demonstrates that our generalized model functions as a valid phenomenological framework for simulating non-equilibrium processes, marking a crucial step toward a unified formulation of stochastic and quantum thermodynamics. Furthermore, we analyze the time evolution of heat conduction by numerically solving the corresponding differential equations for the correlation functions. Unlike standard Brownian motion, the generalized model generates continuous and nowhere differentiable trajectories for both momentum and position (as is characteristic of overdamped dynamics). Finally, we show that the heat current exhibits characteristic transient behavior when the inter-particle interaction is switched on. Specifically, an instantaneous heat flow emerges, whose direction is strictly governed by whether the interaction is attractive or repulsive, significantly differing from the predictions of the standard model.

Direct detections of gravitational waves provide a unique opportunity to probe the astrophysical origin of compact binary mergers. The formation channels of these systems remain highly debated, and a fraction may originate in dynamical environments or active galactic nuclei. Binaries formed in such environments are expected to experience line-of-sight acceleration from their surroundings, which can imprint characteristic signatures on the observed gravitational-wave signal. Here, we re-derive the line-of-sight acceleration effects and implement them in state-of-the-art quasi-circular waveform models with precession and higher-order modes. We also implement the corrections in eccentric waveform models, applying them consistently to all contributing harmonics. Using this model, we investigate the impact of these effects on the inference of line-of-sight acceleration and analyze a few interesting GWTC events observed during the third observing run of LIGO and Virgo. We find no substantial evidence for line-of-sight acceleration in these events. We also show that an inconsistent treatment of line-of-sight acceleration between higher harmonics can lead to biased conclusions. Our model provides a robust framework for uncovering line-of-sight acceleration in current and future gravitational-wave observations, enabling more accurate probes of environmental signatures in compact-binary formation.

I analyze the energy-momentum-tensor (EMT) content of the chromoelectric operator that governs the leading interaction of compact charmonium with soft gluonic fields. In the renormalized MS operator basis this interaction separates into a scalar anomaly/sigma branch and a traceless spin-two branch. The forward light-front spin-two term is fixed by partonic plus-momentum fractions and gives a controlled correction to scalar dominance. Off forward, however, the chromoelectric spin-two contraction is not governed by $A_i(t)$ alone; it also contains the combination $3B_i(t)-D_i(t)$, equivalently $6J_i(t)-3A_i(t)-D_i(t)$. This identifies which EMT structures charmonium can access in forward and differential observables, without interpreting the measured slope as a model-independent static three-dimensional mass radius.

We study Dyck paths refined simultaneously by proper area and water capacity, where water capacity is measured above the path and below its lattice-path upper hull. The finite-height ingredients used in the enumeration are classical bounded-height area-polynomial and continued-fraction objects. The upper-hull decomposition produces a coupled area–capacity substitution, which gives an exact four-variable height expansion with denominator branches indexed by the height levels. The full generating function is asymmetric in the two weights, while the height summands admit a symmetric unreduced denominator representation under interchange of the area and capacity weights. In the open square $0<p,q<1$, we prove that the length radius of $G(x,1,p,q)$ is the minimum of the positive real denominator branches. The proof combines uniform normal convergence of the height expansion below this first branch with a Perron-root representation of the branch locations and an interval log-submodularity theorem for spectral radii of weighted paths. On the diagonal $p=q=s$, the classical Chebyshev specialisation gives explicit branch crossings and a $(1-s)^{2/3}$ branch-envelope accumulation law at the Dyck critical point.

In this contribution, we review the physics and phenomenology of nuclear parton distribution functions (PDFs), with a particular focus on the small-x region of nuclear shadowing. We summarise experimental evidence for nuclear modifications of PDFs and discuss their theoretical explanations; in particular, we contrast different models of nuclear shadowing. We also overview model-agnostic extractions of nuclear PDFs from global data on hard processes with nuclei, emphasizing the validity of collinear factorization and the dominance of leading-twist nuclear PDFs. Finally, we discuss perspectives for present and future precision studies of nuclear PDFs and small-x QCD dynamics, including photonuclear reactions in heavy-ion ultraperipheral collisions at the Large Hadron Collider and lepton-nucleus deep inelastic scattering at the future Electron-Ion Collider.

Inertial confinement fusion implosion design requires simultaneous optimisation of strongly coupled target and driver parameters across high-dimensional design spaces. Existing automated design approaches typically rely on non-differentiable radiation-hydrodynamics codes treated as black boxes, making optimisation increasingly expensive as dimensionality grows. In this work, we present a differentiable simulation approach for high-dimensional inverse design of inertial confinement fusion implosions. Automatic differentiation through a differentiable implosion physics model, driven by an external pressure pulse, provides gradients of implosion objectives with respect to design parameters, enabling gradient-based optimisation. The framework is applied to 25 kJ OMEGA-scale direct-drive implosions, optimising 500-parameter laser pulses across sampled target geometries. The optimised pulse recovers a near-isoentropic rise to peak power without that structure being imposed. Neural-network pulse parameterisations are additionally explored as a means of accelerating design-space exploration. These results establish differentiable implosion modelling as a promising tool for ICF design, while motivating further work on adjoint robustness and higher-fidelity differentiable simulators.

Image data regarding galactic morphology is expected to increase both in quantity and quality for the next foreseeable years; thus it is important to explore which deep learning architectures adapted for image classification tasks are cost-effective. Residual and Inception networks are ideal for exploring classification convolutional neural networks (CNNs) due to their computational efficiency, achieved through techniques such as residual connections and parallelized inception modules, enabling deeper networks without excessively increasing computational complexity. In this work, we analyze the performance of ResNet101 and InceptionV4 on a spatially-augmented Galaxy10 DECals dataset. Retaining the ten-class classification of galaxies, we modify the image count of each class. We find that ResNet101 and InceptionV4 models achieved accuracies of $\sim$ 90%, comparable with reported performance in the literature. In terms of performance metrics, ResNet101 is superior to InceptionV4. Our results indicate that either of these CNN architectures could serve as a robust foundation for specialized pipelines for classification of galaxy images from upcoming surveys.

When do three-dimensional conformer ensembles improve molecular property prediction beyond two-dimensional fingerprints? We provide the first systematic, mechanistically grounded answer. Through ~1,000 experiments spanning 13 model configurations, 14 regression targets, and 2 classification targets across MoleculeNet, QM9, and MARCEL benchmarks, we discover selective complementarity: conformer ensemble statistics extracted via Distribution Kernel Operators (DKOs) yield statistically significant RMSE reductions on solvation-dependent properties (ESOL -11.0%, p < 10^{-9}; FreeSolv -13.5%, p < 3x10^{-5}; 10-seed paired validation) while providing no benefit for electronic or steric tasks. Three lines of evidence confirm this selectivity has a physical rather than statistical basis: improvement is larger under scaffold splits than random splits (+11.9% vs. +8.5% on ESOL), concentrates on large, flexible molecules (+18.9% for heaviest quartile), and grows monotonically with training data. We establish a four-tier performance hierarchy: end-to-end 3D GNNs (SchNet, PaiNN; 21-42% over fingerprints) >= engineered physicochemical descriptors (PMI/SASA/USR) > Morgan fingerprints + XGBoost > all neural conformer ensemble methods, confirmed by two architecturally diverse GNNs and revealing that the pre-computed feature bottleneck limits ensemble approaches. Feature attribution and mutual information analysis expose the mechanistic asymmetry: conformer mean features carry 2-8x more information per feature than fingerprint bits, yet covariance features contribute <2% of model signal, explaining why five simple scalar invariants outperform all complex covariance architectures (p < 0.001). These findings yield an empirical property taxonomy and a practical decision framework for when conformer generation is worth the investment.

There is a well known correspondence between geometric curve flows in the Euclidean plane and solutions of the modified Korteweg-de Vries (mKdV) equation. For each type of mKdV travelling wave, the resulting geometric curve flows are derived here through a simple quadrature formula and studied in detail. These curve flows can be divided into two broad types: travelling loops, and rotating loops. Travelling loops are shown to arise from mKdV solitons, cnoidal (Jacobi cn) and dnoidal (Jacobi dn) waves, the latter being periodic. Rotating loops comprise asymptotically circular ones that are obtained from both mKdV solitary waves on a non-zero background and mKdV rational waves, as well as periodic ones that are produced by mKdV rational elliptic (cn and dn) waves. A specialization of periodic loops, both open and closed, is shown to yield rational cosine loops. An explicit description of each of these types of curve flows is used to characterize their main features, including the condition under which closed loops exist.

We use symmetry arguments combined with density functional theory to demonstrate that surfaces of centrosymmetric crystalline materials host surface phonons that are chiral. As model systems, we study slabs of highly symmetric AB rocksalt compounds, and find surface-localized phonons whose atomic displacements exhibit chiral motion. We further show that these chiral surface phonons generate in-plane magnetic moments at the surface. Our results indicate that chiral phonons can emerge in all crystalline materials as a result of reduced symmetry at surfaces or interfaces. These findings establish surfaces as a previously overlooked source of chiral phonons and their associated magnetic moments, which could play a role in surface-sensitive measurements.

Clapeyron's Theorem of classical linear elasticity provides a way to explicitly express the energy stored in an equilibrium configuration in terms of the work of the forces applied on the boundary. We derive several new integral relations which can be viewed as nonlinear analogs of this classical result, reinterpreting them as rather general statements within Calculus of Variations. These relations reflect specific properties of Lagrangians, that we call “partial variational symmetries”, since they are more general than classical variational symmetries. In the framework of nonlinear elasticity, partial variational symmetries, such as scale invariance, or scaling homogeneity, lead, via Noether's analysis to different nonlinear generalizations of Clapeyron's Theorem that combine naturally the work of physical and configurational forces. We present a series of illuminating examples showing the effectiveness of the obtained general results in different problems of nonlinear elasticity.

This study aims to identify cell microenvironment parameters that can be robustly estimated from IMPULSED diffusion MRI signals and to develop a reliable mapping-based estimation framework. Diffusion MRI signals were simulated using the established IMPULSED model with one pulsed gradient spin echo sequence and two oscillating gradient spin echo sequences at different frequencies. Five cellular parameters were considered: cell diameter ($d$), intracellular diffusion coefficient ($D_{in}$), intracellular volume fraction ($V_{in}$), extracellular diffusion coefficient ($D_{ex}$), and the frequency-dependent slope of $D_{ex}$ ($\beta_{ex}$). Parameter uncertainty was quantified using Jacobian-based sensitivity analysis at an SNR of 30, representing clinically achievable conditions on a 1.5T MRI scanner. To enable direct parameter mapping, signals were logarithmically transformed, reduced in dimension using principal component analysis, and then used to estimate parameters with linear regression, fourth-order polynomial regression, and a fully connected four-layer neural network. Model validation was performed in vitro using MC38 cell lines. Uncertainty analysis identified $d$, $V_{in}$, and $D_{ex}$ as robustly derivable parameters, each with relative uncertainty below 1.0. Among the tested models, the four-layer neural network performed best, with mean absolute errors of 1.7 $\mu$m for $d$, 5.06% for $V_{in}$, and 0.28 $\mu$m$^2$/ms for $D_{ex}$. In vitro validation showed a 6.7% error in cell diameter estimation. These results demonstrate that IMPULSED dMRI can support robust estimation of key cell microenvironment parameters and provide a practical framework for noninvasive assessment of tumor microenvironment changes during radiation therapy response monitoring.

Dynamical mean-field theory (DMFT) maps deterministic chaos in random recurrent neural networks to an effective Gaussian process, usually treated as an ensemble description rather than a predictor of individual trajectories. Contrary to this view, we show that the chaotic mean-field process of the Sompolinsky–Crisanti–Sommers model can be perfectly predictable at the level of a single neuron. When the nonlinearity has a Gaussian or faster Fourier decay, the exact continuous past of one realization determines its entire future: the conditional prediction error vanishes despite a positive Lyapunov exponent. We trace this result to complex-time singularities of the self-consistent covariance through the Paley–Wiener criterion. A Lanczos/Krylov representation turns the covariance into a state-space predictor and defines $\alpha$, the rate at which predictive information is transferred to higher temporal modes. For smooth odd nonlinearities in this predictable class, the Krylov rate and the largest Lyapunov exponent scale differently near the chaotic transition, demonstrating that predictive complexity and microscopic instability are distinct characteristics of the dynamics. Resolving the first $p$ Krylov modes yields a prediction horizon that grows as $\log p$ and enables finite-network forecasts from a single neuron's observed past, without knowing the connectivity and without observing the rest of the network. Thus, the mean-field power spectrum becomes a diagnostic of whether apparent variability reflects irreducible fluctuations or hidden deterministic structure encoded in the observed past.

Generalized entropy measures are widely used to characterize localization and multifractality, and the regime \(q>1\) is often empirically found to exhibit improved numerical stability and cleaner scaling behavior. Here, we develop a fluctuation-stability framework for generalized entropy diagnostics and show that weak-amplitude spectral fluctuations are amplified for \(q<1\) and suppressed for \(q>1\), thereby providing a theoretical basis for the physically robust \(q>1\) regime. A thermodynamic scaling analysis further identifies an asymptotically stable regime beyond a critical threshold. As an application, we introduce the entropy-gradient susceptibility \(\chi_q\) as a coarse-grained probe of spectral heterogeneity. Using the Aubry-André and generalized Aubry-André models, we demonstrate that \(\chi_q\) sharply distinguishes homogeneous localization transitions from mobility-edge coexistence regimes. Our results establish fluctuation stability as a guiding principle for generalized entropy diagnostics in quasiperiodic systems.

Adaptive variational quantum algorithms like ADAPT-VQE construct tailored ansätze by iteratively selecting operators from a pool using gradient-based criteria. While this avoids oversized parameter spaces, repeatedly scanning the full pool incurs a classical cost that scales linearly with pool size-a major bottleneck for systems with long-range interactions or large operator sets. Here, we reformulate adaptive operator selection as a graph-based decision problem and introduce a graph neural network (GNN) policy that predicts the next entangling operator directly from the interaction graph and state-dependent observables. Training data are generated from exact simulations of disordered long-range spin chains, using gradient magnitudes as supervision signals. The learned policy accurately reproduces the dominant structure of the greedy gradient-based selection rule, significantly outperforming heuristics based solely on interaction strength. Integrated into a variational quantum eigensolver (VQE) workflow, this GNN-VQE approach achieves energy errors close to standard ADAPT-VQE while drastically reducing full-pool gradient evaluations. To test transferability beyond spin models, we evaluate the policy on small active-space molecular benchmarks (LiH and BeH_$2$). We find the GNN is highly effective as a shortlist generator: exact rescoring over just a few GNN-proposed candidates recovers near-oracle rollout behavior while searching only a small fraction of the pool. These results demonstrate that adaptive circuit construction contains learnable structure that can be exploited to accelerate variational quantum algorithms.

As it is well known, solutions of equations of nonlinear elastodynamics, representing extremals of the action functional, can form shocks. We adapt the classical approach of Emmy Noether to such singular extremals and derive the appropriately generalized integral relations within Calculus of Variations. We apply them to elastodynamical extremals with shocks, obtaining new integral relations involving kinetic and elastic energies. For the extremals representing thermodynamically admissible (entropy) solutions of the corresponding hyperbolic Euler-Lagrange equations, the classical equalities, characterizing the variational approach of Noether, expectedly transform into ineqalities. We show that, rather remarkably, despite the crucial role of material velocity in the fully inertial energy redistribution processes, the corresponding kinetic energy can be completely eliminated from the expression for the dynamically stored elastic energy, even in the presence of shocks.

We investigate connected sequential geometric structures in correlated neutral meson systems within the framework of Bargmann invariants. Building upon previously developed third- and fourth-order rephasing-invariant geometric structures involving decay-projected conditional states, we introduce a connected sequential fourth-order Bargmann invariant in which the decay-projected states associated with two decay channels are linked through a direct overlap between the corresponding projected states. This construction incorporates explicit projection-projection correlations within the cyclic overlap chain. The connected sequential invariant encodes the geometric relation between decay-projected states, thereby extending the geometric correlation framework developed for correlated neutral meson systems. To characterize the resulting geometric structures, we define rephasing-invariant ratios that quantify connected sequential correlations and provide a direct comparison with the previously studied disconnected geometric correlations. The behavior of these quantities is analyzed in the regime of small CP violation using the standard rephasing-invariant interference parameters together with a small-asymmetry expansion. We show that the connected sequential ratios exhibit characteristic scaling behaviors governed by both mixing asymmetry and relative interference-phase alignment, leading to geometric scaling properties distinct from those of the disconnected structures. We further discuss the geometric interpretation of the connected sequential invariants and their possible relevance to correlated neutral meson systems. The resulting framework extends the hierarchy of Bargmann invariant geometric correlations associated with neutral meson mixing and decay, providing a complementary geometric perspective on CP-sensitive interference phenomena.

An external magnetic field is applied to the classical hydrogen atom treated in classical electromagnetic theory including classical electromagnetic zero-point radiation. In an earlier article, it was shown that the average value of each of the electron's action variables appears as a discrete value, corresponding to a representation of the rotation group, because of resonance between the periodic orbit of the electron and the random classical zero-point radiation. Here it is shown that, in the presence of a magnetic field and because of resonance, the classical orbital motion of the electron is in resonance with random classical zero-point radiation only for orientations of the orbit which take integer values for the angle made with the direction of the magnetic field, but excluding the m=0 orientation where the magnetic field is parallel to the orbital plane of the electron. Classical electromagnetic explanations are given for the Stern-Gerlach result, and for the Zeeman effect.

We study the problem of implementing a quantum channel using a small ancilla with classical randomization and postselection on an output failure flag. The simulation is probabilistic, but exact conditioned on success. We prove that any unital channel on a $d$-dimensional system can be simulated with ancilla dimension $k$ and success probability $\Omega(\frac{k}{\log d})$. Equivalently, every unital channel on $n$ qubits can be simulated with constant success probability using only $O(\log n)$ ancillary qubits. We show that this tradeoff is best possible by constructing a family of channels which cannot be simulated with success probability better than $O(\frac{k}{\log d})$. We also show that the class of highly noncommutative channels, which includes random channels, admits constant-success simulation with just a single ancillary qubit. We further show that this model of simulation necessarily fails for strongly non-unital channels and discuss possible extensions involving adaptivity. On the technical side we rely on a partition-based protocol and matrix concentration inequalities, including the recent refinement of noncommutative Khintchine inequalities due to Bandeira, Boedihardjo and van Handel.

We investigate UV absorption lines tracing cool gas in eight bright ($-21.9 < M_\mathrm{UV} < -20.5$) galaxies at $z=7.2-10.6$ using deep archival JWST/NIRSpec medium-resolution spectra. The eight galaxies were homogeneously selected based on wavelength coverage and data quality from 362 galaxies at $z>7$ available to date, and all eight were observed as part of the SPURS program. We identify multiple absorption lines of low-ionization species (LIS) in five galaxies, while the remaining three show only one or no significant detections. The average LIS equivalent widths $\mathrm{EW}_{\mathrm{LIS}}$ indicate weaker absorption lines in compact ($r_\mathrm{e}\lesssim100$ pc) galaxies with high $L_{\mathrm{H}\beta}/L_{\mathrm{UV}}$ and $\Sigma_{\mathrm{SFR}}$, suggestive of absorption-line suppression due to intense star formation or nuclear activity. We simultaneously fit multiple LIS lines, accounting for both covering fraction $C_f$ and column density $N$, and find that the five galaxies follow the local $C_f$-$N$ relation. Through the LIS-line fitting, we derive chemical abundance ratios. The five galaxies have abundance ratios similar to those of damped Ly$\alpha$ (DLA) systems at $z\sim5-7$ in the [Si/O]-[C/O] and [Fe/Si]-[Al/Si] planes, suggesting that their absorbing gas is similar to that of DLAs. We find that two galaxies at $z\sim7$ are already highly Fe-enriched, with $\mathrm{[Fe/Si]}\simeq-0.2$, near the solar abundance ratio. While the high Fe enrichment may originate from early Type-Ia supernovae (SNe Ia) or pair-instability supernovae (PISNe), these two galaxies also show $\mathrm{[Al/Si]}\sim0$, with no signature of the strong odd-even effect expected from PISNe, in which odd-$Z$ elements are suppressed relative to even-$Z$ elements, favoring SNe Ia.

Systematic surveys of filaments have been conducted to study their properties and their relationship to the process of star formation. In this paper, we use synthetic Herschel observations derived from 3D numerical simulations to compute column density maps, then use the FILFINDER algorithm to identify filaments. We obtain a large sample of 8,832 filaments that we further decompose into 110,193 branches. We characterize the physical properties of these filamentary structures and explore their correlations with embedded clumps. Furthermore, we directly compare our synthetic results with an observational catalogue of 32,059 filaments from the Herschel Infrared Galactic Plane Survey (Hi-GAL). Our results show that filaments are central to the star formation process, hosting $94\%$ of clumps from synthetic observations and $93\%$ of stars from our 3D numerical simulation. Filaments that host clumps have higher median column densities ($1.1\times10^{21}\,\rm{cm}^{-2}$) than those without ($3.8\times10^{20}\,\rm{cm}^{-2}$). We find power-law distributions for our synthetic filament masses and lengths, with power-law indexes of $\alpha_{\rm M}=-0.86$ and $\alpha_{\rm L} = -1.71$, respectively. We also find that the relation between the density of filaments and the background density is $N_{\rm{fs}} \propto N_{\rm{bs}}^{0.78}$. The measured properties of the filaments from the 2D synthetic observations are qualitatively consistent with those of the filaments from the Hi-GAL survey.

We report the discovery of 11 X-ray flares from 7 M dwarfs previously unknown to exhibit flaring activity, by cross-matching eROSITA observations of bright, nearby M dwarfs with the Chandra telescope archive. To analyze the properties of these flares in a broader context, we compile the sample of all reported X-ray flares from the 15 M dwarfs identified as flaring in the literature. We use this combined sample to derive constraints on the X-ray flare frequency distributions of M0-M6 stars. The average flare occurrence rate we measure is $\sim 10^{-1}\,\rm ks^{-1}$ (corresponding to $\sim 9$ flares per day). The X-ray flares in this sample span energies from $10^{29}\,\rm erg$ to $10^{33}\,\rm erg$ and exhibit a strong correlation between flare strength and duration. The flare properties we characterize include their durations, flux and temperature enhancements, and temporal asymmetries. Using these results and recent simulations of flare-driven atmospheric escape, we derive an upper limit on the time required for habitable Earth-like planets orbiting these M dwarfs to completely lose their atmospheres: 0.5-30 Myr.