Papers

Metastability in open quantum systems is usually inferred from spectral separation in the Liouvillian, which governs unconditional, ensemble-averaged dynamics. We show that this diagnosis is incomplete at the level of individual quantum trajectories: conditioned realizations of the same unconditional dynamics can bypass, transiently access, or operationally preserve a metastable memory, depending on the monitored channel and the observed record. We demonstrate these mechanisms in a driven-dissipative nonlinear oscillator realizing a quantum associative memory, by comparing spectra, target fidelities, and phase-space distributions. The non-Hermitian dynamics obtained by post-selecting on the absence of detected events supports metastable retrieval, but with a distinct long-time fate: normalization selects the least-decaying mode of the non-Hermitian spectrum rather than the addressed memory branch. In contrast, stochastic jump trajectories can preserve retrieval over extended times when the post-measurement update remains compatible with the coherent memory structure. Thus trajectory-level metastability is not determined by the averaged generator alone; it requires compatibility between the monitored channel, the measurement record, and the metastable manifold.

Neural quantum states (NQSs) have emerged as a powerful ansatz for quantum dynamics. Their high entanglement capacity promises to overcome the entanglement barrier. However, existing time-dependent NQS methods are ill-equipped to propagate sparsely supported initial states due to the inherent mismatch between the supports of such states and their time derivatives. To address this issue, we introduce the interpolation sampling method as a novel form of importance sampling, where samples are drawn from a distribution that interpolates between the wave function and its time derivative. Combined with a global-in-time variational principle, we demonstrate with the example of the two-dimensional transverse-field Ising model that interpolation sampling allows for accurate propagation of extremely peaked states that standard wave function sampling could not tackle. We further improve sampling efficiency by introducing (i) a configuration-time joint sampling scheme where spin configurations and time are both treated as random variables, and (ii) a hybrid strategy for sample proposal that incorporates the knowledge of a Krylov subspace. Our work extends the scope of time-dependent NQS methods to a wider range of physically relevant scenarios, while challenging the prevailing reliance on the Born distribution and its close variants as the default basis for sampling.

The Bott-Duffin theorem shows that any arbitrary positive real rational function of finite order, representing a passive network, can be represented by a finite number of positive value resistors, capacitors and inductors. It is shown here that if the positivity restriction is lifted, any rational function or polynomial of any order may be represented by a network of (possibly negative) inductors, capacitors and resistors. When there are no repeated roots this is a sum of simple sub-circuits each of which contains no more than four components. When there are repeated roots a more complex circuit is required, here featuring iterated Wheatstone bridges of special form.

Quasicrystals lack the translational symmetry that underlies Bloch decomposition and Brillouin-zone integration, making full-band momentum-resolved electronic structure difficult to formulate and compute. We develop a systematically convergent reciprocal-space tight-binding framework for a broad class of quasicrystals. The method combines two systematically refinable components: a Fourier-module scattering-channel Hamiltonian that yields local spectral and current-current correlation quantities at each physical momentum, and an expanding hierarchy of pseudo-Brillouin zones that converts the resulting local quantities into bulk thermodynamic observables through an exact local-to-global relation. Applied to the Penrose and Ammann-Beenker models, the framework uncovers full-band momentum-resolved quasibands and a multichannel mechanism for pseudogap formation, both beyond the scope of low-energy effective models. It further resolves Zeeman-driven gap closings and reopenings, quantized Chern plateaus, and the phason invariance of bulk spectral and topological observables. This framework provides a unified reciprocal-space route to full-band spectral and topological properties of quasicrystals.

Quasicrystals occupy a distinctive position between the translational order of crystals and the disordered amorphous matter. Simulating this physics has remained challenging, since quasiperiodic structures lack the translational symmetry exploited for crystals and generally require costly diagonalization of large finite approximants. Quasicrystalline order admits two equivalent descriptions, a cut-and-project scheme from a higher-dimensional periodic crystal, and a discrete set of substitution rules acting on a finite alphabet. We show that the latter, written in a numeration system adapted to the substitution, defines a deterministic finite automaton with output, the digits of a site index are fed, and the automaton returns the letter occupying that site. We further exploit another equivalence to a different construction, the transition matrices are exactly the tensors of a matrix product state, whose bond dimension is the number of automaton states and is independent of system size. This allows efficient representation of extremely large tight-binding Hamiltonians in the tensor-train language, thereby yielding an exact matrix product operator for the quasicrystal Hamiltonian at any system size. We show how this framework works for two families of one-dimensional quasicrystals, the metallic-mean and $k$-bonacci families and we explicitly construct the Fibonacci, silver-mean, and Tribonacci quasicrystals. By leveraging efficient tensor-network compression and the kernel polynomial method, we compute spectral densities for chains with more than $10^9$ sites and directly resolve the hierarchical structure of the spectrum.

The $I_{3322}$ inequality is one of the simplest bipartite Bell inequalities, with three possible questions and two possible answers per party. Yet, despite its simplicity, it has long been conjectured by Pál and Vértesi (Physical Review A, 2010) to possess the following quirk: no finite-dimensional quantum strategy can attain its maximal violation, but an infinite-dimensional strategy can. A Bell correlation, with five questions and three answers per party, that provably possesses the same property has since been discovered by Coladangelo and Stark (Nature Communications, 2020). However, proving that the same property holds for $I_{3322}$, which lives in the simplest Bell scenario in which such a phenomenon could occur, has remained elusive. Here, we provide a proof of this conjecture. An approximate proof, containing all the main ideas, was produced by GPT 5.5 Pro after various rounds of interaction. The presentation of this proof was revised substantially by the author for completeness, correctness, and clarity.

A coupled analytical framework is developed to predict the internal boundary layer (IBL) height, wall shear stress and the mean velocity profile downstream of a surface roughness transition in a neutral atmospheric boundary-layer. The new model combines a three-layer analytical velocity formulation with a modified diffusion analogy for the IBL growth rate. The diffusion analogy links the growth rate of the IBL to turbulent diffusion and to mean vertical advection. Our formulation rectifies physical inconsistencies in a previous model that assumed that the turbulent diffusion is controlled only by the upstream surface conditions and that the characteristic streamwise velocity difference caused by streamline displacement is independent of downstream distance from the roughness transition. Key model parameters, namely the turbulent diffusion coefficient and the eddy viscosity augmentation coefficient, are modelled as functions of the upstream-to-downstream aerodynamic roughness length ratio. The coupled model, along with three other analytical models, is tested against twelve datasets covering a wide range of roughness ratios, including wind-tunnel experiments and large-eddy simulations. The new model accurately predicts wall shear stress, mean velocity, and IBL height for all combinations of upstream and downstream roughness values evaluated, for both smooth-to-rough and rough-to-smooth transitions.

Orbit-averaged equations are widely used to model the gravitational-wave-driven evolution of compact binaries. Their validity relies on the radiation-reaction timescale being much longer than the orbital period, an assumption that can break down for highly eccentric systems. In this work, we investigate the impact of orbit averaging on merger-time estimates by comparing orbit-averaged and non-orbit-averaged prescriptions. We apply our analysis to two different astrophysically motivated populations of black hole binaries in hierarchical triple systems, where von Zeipel-Lidov-Kozai oscillations can drive the inner binary eccentricities close to unity. We find that merger-time estimates obtained with orbit-averaged equations remain remarkably accurate across a wide range of eccentricities, even when the orbital timescale exceeds the radiation-reaction timescale. Significant discrepancies arise only for the most extreme and compact binaries, simultaneously characterized by very high eccentricities and small semi-latus recta. In this regime, the merger time becomes strongly dependent on the initial orbital phase, with different phases yielding predictions that can differ by several orders of magnitude. We also compare our results with an orbit-averaged merger-time prescription specifically developed for hierarchical triple systems and find substantial differences between this prescription and both the generic orbit-averaged and non-orbit-averaged calculations in the high-eccentricity regime. While these results demonstrate the robustness of orbit-averaged merger-time estimates for most systems, they also highlight the potential importance of non-orbit-averaged effects when merger times are used to infer compact-binary delay-time distributions and formation channels.

The most widely accepted solution to the Strong CP problem is the QCD axion, whose traditional parameter space is relatively constrained. However, recent studies on exotic axion models have shown that this space can be significantly extended, opening up a wide range of previously unexplored possibilities for model building. I first review the current status of axions and axion-like particles, then focus on the challenges related to the origin of their masses and explore potential connections to other unresolved issues within the Standard Model.

3D metal-organic frameworks (MOFs) are well known effective hosts for luminescent guests that improve tuneability, photostability and material fabricability. 2D guest@MOF systems, while less explored, offer competitive advantages over 3D guest@MOF systems due to their optical transparency, inter-layer spacing, and vertical thinness. This work examines luminescent organic dyes@ZIF-L to establish the underlying mechanisms of guest incorporation in ZIF-L and demonstrate the advantages of the 2D ZIF-L architecture for the material's functional luminescence. Analysing a case study system, fluorescein@ZIF-L (F@ZIF-L), using nanoscale FTIR, diffraction, and topology mapping, confirmed that fluorescein (F) resided in the ZIF-L framework cavities. Supported by surface energy simulations, the extent of guest incorporation was found to be indicated by a morphological continuum, from the characteristic leaf-shaped ZIF-L to rectangular F@ZIF-L. By modifying synthesis temperature and solvent ratios, the luminescent properties of F@ZIF-L could be rationally tuned in terms of guest loading (% mol) and arrangement (i.e. guest monomer to aggregate ratio). When optimised, F@ZIF-L exhibited tuneable emission chromaticity, 99.7% photoluminescent quantum yield, minimal guest leaching in solution over 12 months, and high photostability. Perylene@ZIF-L exhibited unique white light emitting properties, with CIE coordinates (0.33, 0.34) arising from a combination of yellow alpha-phase excimer and blue monomeric perylene emission. Finally, oriented luminescent thin films of guest@ZIF-L materials were grown on malleable Zn foils, demonstrating an in situ fabrication technique. Together, the work highlights the potential for luminescent dye@ZIF-L systems in developing tuneable and resilient luminescent components of next-generation optoelectronics, sensors, and lighting systems.

We construct a compressible isotropic energy on $\mathrm{GL}^+(3)$ combining polyconvexity and global true-stress-true-strain monotonicity (TSTS-M++), answering a question of Wollner, Holzapfel and Neff. For every $\mu>0$ and $k>0$, the energy $W_k(F)=\frac{\mu}{2k}[\exp(k(\lVert F\rVert^2+3J^{-1}+J-7))-1]$, $J=\det F$, is polyconvex and strictly rank-one convex. Its Cauchy-stress response satisfies TSTS-M++ globally if and only if $k\ge1/(8\sqrt3)$. The reference state is stress free with positive infinitesimal shear and bulk moduli. Stress bijectivity has the smaller sharp threshold $k_{\rm B}\approx0.0083$: at equality the stress map is a global homeomorphism with a nondifferentiable inverse, and above it a global smooth diffeomorphism. Thus, for $k_{\rm B}\le k<1/(8\sqrt3)$, the Cauchy-stress map remains globally bijective while TSTS-M++ fails at finite strain. In the TSTS-M++ regime, each prescribed inner radius of a finite plane-strain annulus with a traction-free outer wall has a unique radial equilibrium, and the inner pressure increases smoothly and strictly from zero to infinity. Comparisons with other energies distinguish the roles of polyconvexity, TSTS-M++, reduced convexity and endpoint growth. Under incompressible spherical inflation, global pressure inversion holds for the Demiray family with $b\ge b_*$, including $W_k|_{J=1}$ for $k\ge k_*$ and the stress-free $I_1$-exponential energy, and for the exponentiated Hencky energy when $k_{\mathrm{eH}}>3/8$. Incompressible neo-Hooke instead has a limit point. A further compressible $I_1$ energy retains the global constitutive properties and reference moduli of $W_k$ but exhibits two pressure turning points under incompressible spherical inflation, showing that these properties allow a descending pressure branch.

Terahertz time-domain spectroscopy (THz-TDS) provides direct access to both spectral information and time-of-flight features, making it attractive for dynamic sensing. However, conventional high-speed THz-TDS methods typically rely on a fixed delay trajectory, limiting their ability to selectively acquire only the relevant temporal window while tracking target motion. Here, we demonstrate motion-tracking THz-TDS based on time-programmable frequency combs (TPFCs), in which the THz measurement window is actively locked to a moving time-domain waveform. By continuously modulating the phase-lock set point of one TPFC, we perform real-time apodized acquisition of a specific temporal window centered on the main THz peak at rates up to 308 Hz. Simultaneously, the residual peak position within the window is detected in real time and fed back to the other comb, enabling the measurement window to follow target displacements exceeding the original acquisition window. The feedback command together with the residual peak position further enables reconstruction of the relative target displacement. As a proof-of-concept demonstration, we use a moving gold mirror to simulate respiration- and heartbeat-related motion superimposed on a much larger displacement representing body motion, and successfully resolve the two vital-sign-related components from the measured displacement. This work extends arbitrary-delay control with TPFCs to THz-TDS and establishes a motion-compensated spectroscopy platform for simultaneous displacement tracking and THz waveform acquisition.

Oxidation and ablation of 200 nm tantalum films were carried out by three routes: (i) femtosecond (fs-)laser direct write, (ii) high-temperature annealing (HTA) in a tube furnace, and (iii) annealing in a 2.45 GHz microwave cavity. Complete conversion of the 200 nm Ta layer into 409 nm of Ta2O5 required one hour at 600 C in the furnace, but only minutes at ~ 50 W of microwave power. Fs-laser (515 nm/200 fs) oxidation of the Ta nano-film set in at an average single-pulse fluence of ~ 0.1 J/cm2 under strong pulse-to-pulse overlap (900 pulses per focal spot), i.e. within a narrow window bounded from above by the onset of ablation. Under microwave annealing, both the cavity resonance frequency and the quality factor Q changed markedly at the metal-to-oxide transition, reflecting the collapse of the real and imaginary parts of the permittivity at 2.45 GHz. This dielectric contrast turns the cavity into a sensor: the oxidation can be followed in real time from the shift of the cavity resonance, providing a non-invasive, in-situ diagnostic tool.

Machine learning capabilities are expanding into scientific domains at an accelerating pace. When applied to high-energy physics pattern discovery, they will generate candidates faster than traditional evaluation can absorb. ML finds patterns in past data it is inherently post hoc. Whether those patterns reflect structure or coincidence is unknowable at discovery time; this limitation applies equally to human and computational pattern-finding. What differs is scale: ML candidate generation is effectively unbounded, while human evaluation capacity remains fixed. When generation rate exceeds evaluation bandwidth, binary accept/reject degenerates to random sampling. Information-theoretically, the only response that preserves ranking under finite evaluation budget is stratification. By focusing on stratification rather than binary filtering, rule adjustments can be made retroactively, thresholds tuned as results accumulate, and evaluation bandwidth focused on top-ranked candidates. This paper attempts to codify those criteria, proposing seven computationally evaluable standards for stratifying ML-generated patterns. The goal is not to deliver verdicts but to prioritize which candidates merit pre-registration and longitudinal tracking. The framework preserves the essential paradigm: pattern plus theory equals potentially real physics. Patterns alone, however striking, remain candidates until theoretical understanding arrives. Making these criteria explicit enables prefiltering at scale while creating a collaborative resource rather than a competitive one. ML capabilities extend what physicists can search while preserving how physicists evaluate. We offer this provisional framework for community calibration, with the goal of developing validation infrastructure before the capability fully arrives.

We present an extended Ginzburg-Landau (GL) method for calculating the superconducting coherence length and magnetic penetration depth at temperatures well below the transition temperature $T_{\mathrm c}$. In contrast to conventional GL theory, which expands the free energy in both the order parameters and their gradients, our method applies a perturbative expansion only to the covariant-gradient terms, while retaining the full dependence on the superconducting order parameters. The coefficients of these terms are determined from finite differences of microscopic free energies evaluated at small imposed pair momenta. The method applies to both single-band and multiband superconductors and therefore provides a framework for incorporating more realistic electronic structures. For the models examined here, the extended GL method agrees well with real-space Bogoliubov-de Gennes (BdG) calculations over a wide temperature range, while requiring substantially less computational effort.

Prediction-market probabilities increasingly appear in news coverage, yet little is known about which market movements become news or how much trading money sits behind the numbers journalists quote. Unlike a poll, a market price can be moved by anyone willing to trade, so the cost of manufacturing a number that circulates as news bears directly on the information environment. We link 173.7 million signed Polymarket trades to news coverage from 2024-2025. From 6,990 articles mentioning prediction-market venues, an LLM-based, human-validated matcher extracts 1,582 sentences quoting market odds and attributes 918 to the specific market whose price they cite. We then detect 44,976 price dislocations, movements of at least five percentage points backed by concentrated one-sided trading, and ask whether a market is cited more often afterward. In the days after a dislocation, a market's citation rate is about 33% higher than its matched baseline (log citation-rate ratio $\tau_{\mathrm{cite}}=0.283$, permutation $p=0.001$), robust to binary and Poisson count outcomes. Yet move size is not the strongest predictor of citation: prominence dominates (standardized $\beta=0.610$ vs. $\beta=0.159$ for move size). Finally, we combine the dollar flow behind a given price change with observed citation rates into a metric we call epistemic leverage, the dollars needed to move a market five points and have the move cited. It stays near \$0.7-1.0 million across prominence quintiles, because cheaper-to-move markets are proportionally less likely to be cited. The implied threat model centers not on the long tail of cheaply moved markets but on the few prominent markets newsrooms treat as informational infrastructure, where a seven-figure price of influence sits within the budgets of actors with a large stake in the quoted number. We release aggregate event-study data and validation materials.

Rotating magnetic microparticles are building blocks for field-driven assembly and microrobotic control. As the elementary interaction rule for larger assemblies, pair motion in these systems is governed not only by magnetic forcing, but also by hydrodynamic coupling and other long-range interactions. Here we develop a reduced framework for two synchronized rotating magnetic particles by resolving the interactions into radial components that change the interparticle distance and transverse components that rotate the line of centers. The competition between magnetic dipolar interaction, additional radial repulsion, and rotation-induced transverse coupling selects three pair-motion modes: rigid-body rotation, contact-separation rotation, and irreversible separation. We derive transition criteria for the rigid-body state, reversed orbital motion, and the separation boundary, and obtain an asymptotic solution for the separation dynamics. Lattice Boltzmann simulations of particles rotating near a wall provide a hydrodynamic realization of the model, in which inertial secondary flow generates radial repulsion and rotational flow produces transverse coupling. The resulting phase diagram in the physical $(\mathrm{Re},C_m)$ plane is consistent with the reduced-model predictions. These results provide design rules for programming elementary pair interactions in rotating magnetic-particle systems and may help guide the control of microrobotic assemblies.

A static deformation of graphene can act on its Dirac electrons as a valley-odd magnetic field. In sublattice-gapped graphene this field makes the two valleys add in the parity-odd response rather than cancel. We derive the equilibrium thermodynamics of this effect and separate it from the finite-frequency transport response. At fixed electrochemical potential, reversing the pseudomagnetic field removes every nonzero pseudo-Landau level in the continuum theory. The remaining grand-potential difference is fixed by the spectrally asymmetric zeroth level. The static charge response is a thermally broadened plateau confined to the gap and has no metallic $m/|\mu|$ tail. Near a band edge, pseudofield reversal transfers $\mathrm{B}\ln2$ of entropy per unsplit zero-mode state in the low-temperature window. The fixed-$\mu$ heat capacity has two side lobes per edge and a universal peak $0.439229\,D_B k_{\mathrm B}$. We then formulate a definite constant-gate-voltage circuit and show that the measured sheet heat capacity depends on the electrical boundary condition. The full massive-Dirac density of states and an exact finite-field pseudo-Landau-level calculation give the same gate crossover in their common limit. At fixed carrier number, the low-temperature edge value is $-2(\ln2)^2 D_B k_{\mathrm B}$, rather than a node. A finite geometric capacitance gives a continuous and experimentally tunable interpolation. Finally, we give a trace-free triaxial strain geometry, a disorder–interaction window, and realistic calorimetric and quantum-capacitance scales. The field-reversal protocol isolates an equilibrium electromechanical anomaly without a real magnetic field.

We iteratively model the GWTC-5.0 binary-black-hole census with three components. First, a physically normalized population from Rapster globular-cluster simulations spans cluster mass, metallicity, formation redshift, compactness, and natal black-hole spin. Hierarchical mergers reproduce higher-mass events and their larger effective-spin dispersion, provided black holes are born with zero natal spin. Second, a phenomenological field (isolated-binary) channel supplies the low-mass, preferentially aligned population. Its inclusion flattens the cluster compactness likelihood, permitting ordinary dense globular-cluster birth radii without requiring nuclear-cluster-like conditions. Finally, residual tension at $15$–$30 M_\odot$ motivates an intermediate-mass isotropic component representing field remnants reprocessed in clusters. This is a hypothesis, not a detection: current numerical support precludes a reliable evidence comparison. Physical normalization converts the high-mass rate into $\hat{f}_{\rm GC}\simeq0.39\%$, with local rates $R_{\rm cl}\simeq9.1$ and $R_{\rm field}\simeq16.0$ Gpc$^{-3}$ yr$^{-1}$. The model predicts linked mass-spectrum breaks near $35$ and $70 M_\odot$, a $q\simeq0.5$ feature from first-plus-second-generation pairings, and a symmetric effective-spin distribution that broadens sharply above $45 M_\odot$. These correlated, mass-resolved predictions can be tested as the gravitational-wave census grows.

Nucleon sigma terms are important for the decomposition of the nucleon mass and for searches for new physics beyond the Standard Model involving scalar interactions. A persistent tension between lattice QCD and phenomenological determinations may be due to uncontrolled excited-state contamination in lattice QCD analyses. In previous work at $m_\pi=429~\rm MeV$, we showed that this contamination is dominated by $N\sigma$ states and can be strongly suppressed with a variational analysis using $N$ and $N\sigma$ operators. In this talk, we present preliminary results at $m_\pi=222~\rm MeV$, where the $\sigma$ becomes unstable and decays into $\pi\pi$. We investigate whether the same small variational basis can remove the expected $N\pi\pi$ contamination through the overlap of the $N\sigma$ operator with these states.

The quest for autonomous alignment and maintenance of complex free-space optical systems is increasingly urgent for large-scale neutral-atom quantum processors. Leveraging a high-finesse optical cavity as a sensitive probe, we introduce a data-driven framework for structural diagnostics and closed-loop control that achieves cold-start convergence within tens of seconds. These results establish a rapid, scalable diagnostic-control methodology for autonomous alignment and continuous maintenance of complex free-space optical architectures.

The detection of the redshifted 21 cm signal from neutral hydrogen during the epoch of reionization remains one of the central challenges in contemporary cosmology. Although upcoming radio interferometers are expected to measure 21 cm fluctuations at a few percent precision, an independent confirmation is essential to ensure robustness against instrumental systematics and foreground contamination. In this work, we propose a novel real-space stacking technique to detect the 21 cm signal, guided by the presence of dark gaps in quasar absorption spectra during the late stages of reionization ($z \sim 5.0$-$6.1$). Using a semi-numerical reionization model, we show that stacking 21 cm images on long dark gaps (length, $L > 32~h^{-1}\mathrm{cMpc}$ and threshold flux, $F_{\mathrm{th}} < 0.005$) should reveal a strong emission signal with a peak mean-subtracted 21 cm brightness temperature of $\delta \tilde{T}_b \sim 2-3~ mK$ for a volume-weighted average neutral fraction of $x_{\mathrm{HI}} \sim 0.1$ at $z = 5.9$. We further extend our analysis to realistic reionization lightcones, incorporating thermal noise and foreground avoidance effects, generated for two different reionization histories. In an optimistic foreground avoidance scenario (wedge field of view $\theta < 20^\circ$), a sample of roughly 100 dark gaps is sufficient to achieve a combined root-sum-square signal-to-noise ratio exceeding 10 for both reionization models, while a more conservative wedge avoidance may require more dark gaps for a solid detection. Given the large number of quasars known at $z > 6$, a detection of this stacked signal may thus already be within reach of existing optical (i.e., VLT, Keck) and 21 cm observatories (i.e., HERA, SKA). This synergistic approach offers a promising pathway towards a direct and statistically robust detection of the cosmological 21 cm signal.

Functional materials realize functionalities through pre-designed structures, whereas physical neural networks are trained by prescribing input-output behavior. Unifying these views would allow materials to acquire functions directly from dynamical tasks. Here we introduce an in situ local learning framework for dynamic network materials. A forward drive and a time-reversed adjoint error drive are applied to the same mechanical network, enabling the material to compute gradients of a time-domain loss through its own dynamics. The resulting update rules are local, compatible with the principle of physical learning. Each bond or node requires only co-located forward and adjoint fields. The method trains spring constants, nodal masses, bond damping coefficients and nodal damping coefficients, and programs dynamical functions including broadband wave cloaking, evanescent-wave imaging, passive transient output enhancement and vowel classification. These examples involve distinct physical mechanisms, such as wave scattering, near-field information transfer, dissipative non-normal dynamics and machine learning, but are obtained by simply changing the loss function, rather than leveraging expert knowledge. Therefore, dynamic network materials can act both as programmable matter and as physical neural networks, providing a route to material systems that learn temporal responses in situ.

Molecular and material properties, from the polarizability to the elastic constants, are described by tensors. Their behavior under rotations is made explicit when a tensor is decomposed into irreducible parts that transform independently. In Cartesian form these parts are the symmetric and traceless irreducible Cartesian tensors (ICTs), whose decomposition and coupling underlie selection rules, orientational averages, and the use of symmetry. The decomposition is a textbook result at rank two, but higher rank and the intrinsic symmetry of physical tensors make it nontrivial. What has been lacking, unlike in the well-established spherical formalism, is a general construction for a given intrinsic symmetry, together with reusable operators that extract the ICTs and rebuild the original tensor exactly. Here, we develop such a construction and obtain these operators explicitly. These operators depend on rank and symmetry alone, and therefore each need only be built once and then applied to any tensor of that class. Building on them, we further obtain the Cartesian harmonics of a vector and the operators that couple two ICTs into a third, both central to equivariant machine learning. The construction is demonstrated on the elastic tensor, in both its second-order form of rank four and its third-order form of rank six. The ICTs of the rank-4 tensor also define a rotation- and scale-invariant measure of anisotropy, which we evaluate across the first-principles elastic tensors of crystalline materials from the Materials Project. The construction is implemented in the open-source package natto, which produces the operators in both exact symbolic and numerical form.

The electromagnetic vacuum stress tensor in a system consisting of classical point-like atoms on a cubic lattice is derived directly from the electric field and, alternatively, using the known more phenomenological formula involving the (usually unknown) derivative of the dielectric tensor. The results agree. The stress tensor contains a nontrivial constant and therefore cannot be obtained from macroscopic electrodynamics alone. A system consisting of a mosaic of randomly oriented grains of a cubic crystal is used as a model of an amorphous solid. The electromagnetic stress tensor in this system is deduced by averaging the corresponding quantity in a cubic crystal over all orientations. Two components remain: the component in the direction of the electric field and the component perpendicular to it. The transverse component agrees with the analogous quantity for liquids derived by Peierls in an entirely different way.

This paper develops a phase-reduced description of transonic buffet, treating buffet as a stable autonomous fluid limit cycle that is weakly perturbed by harmonic structural motion. When combined with aerodynamic work, the phase reduction model yields closed-form expressions for the equivalent aerodynamic damping and stiffness, together with a unified description of phase locking, phase slipping and aeroelastic stability of the fluid-structural system. The resulting analysis provides new insight into the mechanisms governing aeroelastic instability in oscillatory flows, including aerodynamic damping maps, singular behaviour at zero detuning, and broad regions of subcritical aeroelastic instability.

Sample-based Krylov quantum diagonalization (SKQD) is a paradigmatic example of a quantum-centric supercomputing workflow that combines the convergence structure of Krylov quantum diagonalization with classical sampling-based post-processing. It provides convergence guarantees assuming that the important computational-basis configurations can be sampled from a set of Krylov states with sufficient probability. We analyze this assumption under depolarizing noise, deriving shot-count resource estimates that expose an exponential depth penalty, and perform experiments on current noisy hardware with the one-dimensional single-impurity Anderson model on a 20-site (40-qubit) instance. Device noise breaks the practical convergence predicted by the noiseless SKQD analysis, but approximate compilation techniques can compress the Krylov time-evolution circuits before execution. The compressed circuits accumulate less hardware noise, recover the expected energy convergence, and reduce both the quantum shot budget and the classical subspace dimension, remaining beneficial even when classical configuration recovery is applied.

This work compared the radiobiological responses of SAS oral squamous cell carcinoma cells and MCF-7 breast cancer cells following accelerator-based boron neutron capture therapy (BNCT). Neutrons were generated by bombarding a lithium target with proton beams, followed by moderation to obtain sufficient thermal neutrons for BNCT irradiation. Boronophenylalanine (BPA) was used as the boron delivery agent. BNCT-induced biological responses were evaluated by gamma-H2AX immunofluorescence staining, cell-cycle analysis, apoptosis analysis, and clonogenic survival assays. BNCT induced marked gamma-H2AX foci formation in both cell lines, indicating DNA damage-associated responses after irradiation. The two cell lines further showed distinct post-irradiation outcomes. SAS cells exhibited stronger clonogenic suppression and prominent G2/M accumulation, whereas MCF-7 cells showed sustained G0/G1 accumulation and delayed apoptosis. These results suggest that BNCT sensitivity is determined by both boron accumulation and cell-line-specific biological characteristics. This work provides experimental evidence highlighting the importance of tumor-dependent cellular responses in understanding and optimizing BNCT efficacy.

Let $X$ be a toric Fano surface. Let $\pi: \widehat{X} \rightarrow X$ be a toric blow up at a point. We use the Topological Vertex [AKMV] to prove a higher genus, higher winding, open-closed duality between the toric Calabi-Yau 3-folds $K_X, K_{\widehat{X}}$. For $g \geq 0, w \geq 1$, we show the equality $n_g(K_{\widehat{X}}, \pi^*\beta - wC) = (-1)^g N_{g, (w)}^{LMOV}(K_X/L, \beta)$, where $n_g(K_{\widehat{X}}, \pi^*\beta - wC)$ is the genus-$g$, Gopakumar-Vafa invariant of $K_{\widehat{X}}$ in curve class $\pi^*\beta-wC$, where $\beta \in H_2(X, \mathbb{Z})$ and $C$ is the exceptional curve, and $N_{g, (w)}^{LMOV}(K_X/L, \beta)$ is the genus-$g$, LMOV invariant of an outer Aganagic-Vafa brane $L \subset K_X$ in class $\beta$ and representation $(w)$, or the Young Tableau of a single row with $w$ boxes.

The Normalized Energy Density (NED) was introduced in Goto et al.(2011) as a quantity that, unlike the conventional energy, is conserved across material interfaces in a layered elastic medium. Its conservation was proved analytically only for a two-layer structure; for three or more layers it was supported by Monte Carlo simulation. I supply the missing proof for a general multi-layer (n-layer) structure in the 2D SH problem. The key step is to stop treating the angular frequency as a single variable and instead lift the layer phases to independent coordinates on the n-torus. The obstruction identified in the original paper—that the ratio of travel-time combinations is generically irrational, so that the periodicity argument used for two layers fails and disappears, and the proof reduces to Weyl's equidistribution theorem combined with n repetitions of the same elementary integral used in the two-layer case. I prove conservation in two independent settings that together cover all cases of practical interest: travel times that are linearly independent over Q, and commensurable travel times, including the equal-travel-time (Goupillaud) discretization. I also show that an arbitrary layered structure can be subdivided by reflectionless interfaces into one whose travel times take only d distinct, Q-independent values, where d is the dimension of the Q-span of the original travel times; this places the two proved cases at the endpoints d=1 and d=n and isolates the remaining open case 1<d<n in a canonical form.