Papers

Modeling heterogeneous evacuation behavior under a moving threat is difficult because human perception, memory, and evidence evaluation are not well captured by fixed rules. We propose a novel LLM-powered agent-based framework to represent these internal decision processes. Each pedestrian agent perceives a private symbolic ASCII view, maintains a Memory-based Knowledge Graph derived solely from individual observations, and makes decisions through persona-conditioned prompts under a common sampling configuration. A compressed decision context with stateless memory preserves trial-and-error experience across turns while excluding reasoning traces, and a validation engine separates behavioral choice from physical feasibility by executing routes only over observed terrain. We evaluated eight personality compositions in eight paired randomized blocks within a simulated public plaza. Usable-exit knowledge was strongly associated with evacuation success: 89.5% of agents possessing such knowledge evacuated, compared with 1.05% of those without it. Personality compositions also differed in their evaluation of remembered threat evidence: the proportion of danger assessments varied by 0.265, while high-urgency, low-directness decisions ranged from 11.41% to 34.33%. After direct threat sightings, responses converged, with 99.6% of assessments classifying the situation as dangerous. Movement was selected in 99.8% of decisions. Overall, evacuation outcomes were strongly associated with information access, while evacuation time was jointly associated with spatial geometry, information, and affect. The framework provides an auditable approach to generating endogenous behavioral heterogeneity through persona-conditioned LLM agents in crowd-evacuation simulations.

The orbit selected by a magnetic particle in a viscous liquid under a rotating field is commonly described in the instantaneous Stoner–Wohlfarth limit, in which the magnetic moment always occupies a minimum of the anisotropy energy. In this limit, precession out of the field plane exists only for reduced fields $B_0/B_a<1/\sqrt2$, and stronger fields admit only planar synchronous rotation or libration. We study a macroscopic egg-yolk particle, a printed shell containing two freely rotating permanent magnets in fluid-filled cavities, driven by a compensated rotating field and tracked optically. In addition to synchronous rotation, precession, and libration, the particle exhibits a polar phase: above the instantaneous bound and at high frequency, the shell axis leaves the field plane and locks onto a narrow cone about the rotation axis. We extend the model by a finite viscous friction between the magnets and the shell. The extension introduces a single dimensionless parameter, the ratio $\kappa$ of inner to outer rotational friction, and reduces to the instantaneous theory as $\kappa\to0$. Numerical phase diagrams show that increasing $\kappa$ tilts the bistable band to higher fields at higher frequencies and extends stable precession above $B_0/B_a=1/\sqrt2$, whereas for large $\kappa$ planar libration returns at high frequency. With a calibrated anisotropy field, relaxation rate, and $\kappa$ of order unity, the model reproduces the terminal state of all measured records and their tilt angles, including the polar cone. In the model the polar state is maintained by a steady rotation of the magnets relative to the shell, driven by the field and anisotropy torques and dissipated by the inner friction; it therefore exists only for intermediate $\kappa$.

This paper develops a Quantum optimisation Unit Commitment (UC) framework that benefits from Pauli Correlation Encoding (PCE) as a qubit reduction preprocessing technique and Sample-based Quantum Diagonalisation (SQD) as a hybrid post-processing refinement method. The UC problem is formulated in binary form, then transformed into a QUBO problem and mapped onto an Ising representation suitable for adiabatic quantum evolution within the Qibo framework. This study analyses how PCE and SQD techniques affect qubit scalability, computational effort, feasibility, and probability of recovering the optimal solution as the number of generators increases. The results show that PCE reduces the effective size of the encoded problem, SQD improves the concentration of probability on feasible and optimal solutions, and their combined application provides the best overall behaviour in several scalable case studies, achieving more reliable solutions with lower effective computational cost than the unreduced formulation. The repository is available open source in Github (link is not yet available until work is published. However, if requested by the reviewers, we can make it open for a scific time window, if requested).

Weakly breaking a continuous symmetry in an ordered phase can convert its Goldstone modes into topological collective bands. We establish this mechanism in a neutral dipole condensate whose conserving parent supports two independent Goldstone phase modes. Weak real flavor mixing pins the phases and selects a chiral condensate. The resulting gyroscopic coupling acts on their winding polarization texture, producing a pseudo-Goldstone sector containing a topological lowest band. Restoring dipole conservation forces the two modes to meet at zero frequency, where their separate band Chern numbers cease to be defined. The same parent dipole charges define a tensor current whose circular response permits model-assisted reconstruction of low-energy embedded local Berry curvature in the benchmark regime. Analytical stability bounds and a large-occupation limit provide a controlled realization of this mechanism.

We investigate the motion of a spherical microswimmer in a planar Poiseuille flow using analytical calculations and numerical simulations. Our results show that the microswimmer's orientation undergoes periodic oscillations governed by pendulum-like dynamics. The oscillation period is proportional to the channel width and to the complete elliptic integral of the first kind evaluated at the maximum orientation angle, and inversely proportional to the square root of the product of the maximum flow speed and the self-propulsion speed. Based on the net displacement along the flow direction within one oscillation period and the signs of the maximum and minimum velocities, we identify five motion states: upstream, oscillatory upstream, zero-drift oscillatory, oscillatory downstream, and downstream motion. The net displacement is jointly determined by the ratio of the self-propulsion speed to the maximum flow speed and the complete elliptic integrals of the first and second kinds. The signs of the maximum and minimum velocities are determined by the speed ratio and the cosine of the orientation angle. Flow nonuniformity promotes upstream migration, whereas inertial lift produces negligible radial displacement during one oscillation period. These findings identify the key parameters governing the motion of spherical microswimmers and provide significant implications for understanding microorganism motility and designing microrobots with prescribed motion states.

We will re-examine the leading post-Newtonian (1PN) cross terms of hierarchical triples obtained by Lim and Rodriguez (LR) with a two-parameter multiple-scale expansion in the hierarchy parameter $\varepsilon=a_1/a_2$ and the 1PN parameter $\delta$, which disagree with the effective-field-theory result of Kuntz, Serra, and Trincherini (KST) at the orders $\delta\varepsilon^{3/2}$ and $\delta\varepsilon^{7/2}$. Reconstructing the LR calculation, we show that the $\delta\varepsilon^{3/2}$ “libration” term [LR Eq.~(4.5)] originates in the averaging measure: the quadrupole periodic solutions are made mean-free with respect to the outer true anomaly but re-substituted under the time average. The resulting term, evaluated in closed form, reproduces the implemented one exactly; with the time measure required of a canonical generating function it vanishes, in agreement with KST. Equation~(4.5) is one term of the flow of a removable Hamiltonian whose companion terms are absent, which is why it fails the rationality and Hamiltonicity tests. A calculation carried out consistently with a single phase variable yields the complete, gauge-equivalent secular equations, whereas LR's implementation combines a true-anomaly quadrupole solution with an eccentric-anomaly 1PN solution. Two structural defects of the implementation do not contribute to these terms. The $\delta\varepsilon^{7/2}$ term of LR has the correct mass dependence only for $m\ll m_3$, and its angular structure disagrees with KST and violates the Hamiltonicity test. Finally, integrations with LR's secular code show that the resonant ZLK modulations reported by LR survive the removal of Eq.~(4.5), whereas their accelerated merger with the octupole disappears.

Fast Radio Bursts (FRBs) are spatially and temporally compact sources at cosmological distances. As background sources, they will be uniquely sensitive to the gravitational lensing of exoplanets outside of our own galaxy. We present a method to detect extragalactic exoplanets using planetary echo nanolensing-periodic, nanosecond-scale variations in the relative time of arrival (ToA) between an initial FRB and its microlensed echo as the planet orbits its host star. For a simple binary lens model, we demonstrate that measuring the amplitude and period of these ToA fluctuations enables a determination of the exoplanet mass and orbital parameters. FRBs will be most sensitive to echo nanolensing by lenses within ten megaparsecs of the Milky Way as well as within ten megaparsecs of the FRB host, opening the door to detections of planets at a range of redshifts. We estimate that at least one in a million FRBs will exhibit this phenomenon (i.e. an optical depth of $\tau_l = 10^{-6}$). While current burst rates and low repeating-FRB fractions make a detection challenging in the immediate term, upcoming high-volume surveys and next-generation arrays (such as the SKA Phase 2) will bring the unambiguous detection of extragalactic exoplanets across cosmological redshifts into possibility.

Day-night solid-state power generation is experimentally demonstrated with thermoelectric generators integrated with a tunable radiative coating, which switches between a selective solar absorber during daytime and a radiative cooler during nighttime by temperature without any external control. The self-adaptive radiative coating is carefully designed with thermochromic VO2 thin film on heavily doped silicon substrate along with a phase-shifting silicon spacer in between, whose physical mechanism is elucidated. The fabricated coating exhibits a high solar absorptivity of 0.90 and a low infrared emissivity of 0.23 during daytime, and a high emissivity of 0.85 at night, resulting in large emissivity change of 0.62 within the atmospheric transparency window upon metal-to-insulator phase transition. From outdoor tests in a high vacuum apparatus, the tunable radiative coating in 35-mm squared size achieves 1.64 W/m2 power generation around noon time from a stack of commercial thermoelectric modules of 15 mm squared, which is 32% more from that with a black absorber. At night, it produces 26 mW/m2 power, outperforming the black emitter by 63%. Even exposed the ambient with convective loss, the 2-inch-round tunable coating generates power of 0.48 W/m2 at noon time, 14% more than the black absorber of the same size. The tunable radiative coating covered thermoelectric modules produces open circuit voltages from 433 mV to -62 mV in vacuum and from 300 mV to -51 mV in ambient through 24-hr continuous outdoor tests.

Bellissard's framework uses covariant observables to describe aperiodic solids. We examine how butterfly-like spectra in twisted bilayers can be related to bulk gap labels and topological response. A bulk gap permits a spectral projector and an integrated density of states. A topological response requires an additional pairing of that projector. In an illustrative finite honeycomb bilayer, an exact second-moment identity isolates the interlayer contribution to spectral variance. Angle-resolved spectra, finite state counts, an uncoupled reference, and size and broadening checks show how coupling redistributes spectral weight without assigning a bulk gap label. We then examine the requirements for atomistic electronic-structure calculations, including nonorthogonal orbitals, projected densities of states, and basis functions that move during relative sliding. The resulting framework specifies the steps needed to connect atomistic spectra with bulk state counting and topological response.

We report the acceleration of stable electron beams with energies up to 1.5 GeV using a 50 TW laser pulse guided in a preformed plasma channel generated by an axiparabola-focused heater pulse. Varying the channel length changes the plasma density beyond the channel end and produces distinct electron spectra. A short channel causes a large decrease in bubble size after the truncated channel, leaving only part of the electron bunch in the accelerating phase and resulting in a quasi-monoenergetic peak. For a longer channel ending near the target density down-ramp, the smaller density increase rephases and further accelerates a larger fraction of the bunch, producing a continuous high-charge spectrum. Hydrodynamic and particle-in-cell simulations reproduce the observed spectral evolution. Together, the measurements and simulations identify channel length as a key control parameter in guided laser-wakefield acceleration.

Accurate quasiparticle electronic structures are the foundation for understanding excited-state properties of materials and explaining optoelectronic, quantum, and transport phenomena. First-principles GW calculations nevertheless remain computationally intensive for large or configurationally complex systems. Here we introduce DeepH-GW, a deep-learning framework that predicts an effective GW quasiparticle Hamiltonian directly from atomic structure. Building on the local, equivariant message-passing architecture of DeepH, DeepH-GW is trained on high-fidelity plane-wave GW calculations through a real-space Hamiltonian-reconstruction interface. This approach combines the systematic accuracy and broad chemical applicability of plane-wave methods with linear-scaling neural-network inference. Across the systems examined, DeepH-GW reproduces quasiparticle band structures with errors on the order of a few meV. Moreover, we show that, despite the intrinsic nonlocality of many-body interactions, DeepH-GW exhibits strong cross-scale transferability from relatively small training structures to substantially larger supercells. We demonstrate that the framework can accurately capture GW-level electron-phonon band-gap renormalization through predictions in supercells with thermal displacements, illustrating the power of the approach. DeepH-GW therefore provides a practical route toward large-scale many-body simulations and foundation models for excited-state electronic structure.

Double white dwarfs (DWDs) in the Laser Interferometer Space Antenna (LISA) band are major Galactic gravitational-wave sources, but many tight DWD progenitors may reside in hierarchical triples. Triple evolution can alter both the production rate and parameter distributions of LISA DWDs. Using the Multiple Star Evolution (MSE) code, we study how the adiabatic mass-loss model (Ge model) and the SCATTER formalism for triple common-envelope (TCE) evolution affect triple-channel LISA DWD formation. Our main model evolves 10^5 triples with both ingredients. Three control models, each with 10^4 triples, vary the mass-transfer stability criterion to the original MSE polytropic model, remove SCATTER, or adopt low metallicity (Z=0.001). We also evolve 10^6 isolated binaries with the same framework as a binary-channel reference. Systems that are dynamically unstable under the polytropic model can instead undergo stable Roche-lobe overflow under the Ge model. This sustained mass transfer modifies the donor envelope, reduces its binding energy, and helps the subsequent common-envelope phase form a close DWD rather than a merger. The Ge model increases the triple-channel LISA DWD yield by about 60% relative to the polytropic model, while SCATTER changes the integrated yield by only about 3%. After residence-time weighting, triples contribute about 1.3e7 LISA-band DWDs, including 1.4e4 individually resolvable systems. In the combined triple-plus-binary normalization, the binary channel contributes 3.1e6 LISA-band DWDs and 4.7e3 resolvable systems; these are the binary share of the combined population, not the binary-only Galactic estimate. The main triple model has a flatter, higher-q mass-ratio distribution than the polytropic-model triples, is dominated by He-CO and He-He binaries, and produces rare eccentric systems only when a tertiary star remains bound.

We introduce the basics of Effective Field Theories, using the Standard Model Effective Field Theory as our central example. The first part of this chapter gives a pedagogical introduction to EFTs - including matching, resummation and the construction of an operator basis - with explicit examples and provides a starting point for newcomers. The second part reviews the current status of SMEFT and collects suitable references for those who want to go deeper.

Reducing the energy cost of computation-a pressing issue in the age of AI-requires a framework for circuit design based on information thermodynamics. By extending non-equilibrium statistical mechanics to information thermodynamics, it has been shown that a probability flow carrying information-hereinafter referred to as an 'information current'-is driven by its conjugate thermodynamic force, namely 'information affinity'. Since information affinity plays a role analogous to that of voltage in an electrical circuit, it is suggested that information transport also follows a linear response relationship analogous to Ohm's law. However, despite this theoretical prediction, experimentally establishing an Ohm-like constitutive relation for information transport remains an important unsolved problem. Here, we realise an information engine consisting of two magnetic skyrmions undergoing Brownian motion at room temperature. We demonstrate that the resulting information current is proportional to the information affinity generated by Maxwell's demon over a relatively wide range, establishing Ohm's law for information. Furthermore, we clarify that, in real information circuits, both Ohm's law for information and Kirchhoff's voltage law must be slightly modified to account for interactions between information carriers and the scattering of the information current.

We attempt to measure the weak lensing of the Lyman-$\alpha$ forest by projecting a quadratic estimator of the forest-forest and quasar-forest pair correlations, built from the DESI DR1 data, onto deflection templates constructed from low-redshift galaxies and quasars from DESI and BOSS. After validating deflection templates against the ACT DR6 and Planck PR4 CMB lensing maps and testing the estimator with injected displacements we measure the lensing amplitude $A_L$ on the data. Consistent with predictions in the literature, the current generation of public data does not have sufficient signal-to-noise to measure this effect unequivocally: we find the lensing amplitude $A_L=0.42\pm0.43$ from the forest auto-correlation and $0.87\pm0.48$ from the quasar–forest cross-correlation. These two nearly independent measurements combine to $A_L=0.62\pm0.33$, consistent with both the fiducial value $A_L=1$ and with no lensing.

In molecular machine learning (ML), significant progress has been made on integrating fundamental thermodynamic relations into ML models. Such physics-informed approaches can be categorized as hard-constrained, where the thermodynamic relations are embedded in the model architecture, and soft-constrained, where relations are included in the training loss. While both approaches have been applied to various property prediction tasks, a systematic comparison on experimental data is lacking. We herein compare hard- and soft-constrained approaches on a numerically challenging case study: the prediction of vapor pressure, saturated liquid and vapor molar volumes, and enthalpy of vaporization as functions of temperature for single-species vapor-liquid equilibrium, related by the exact Clapeyron equation. Furthermore, soft-constrained approaches in molecular ML typically balance data and physics losses with a fixed weighting factor, requiring careful tuning. To overcome this, we investigate the augmented Lagrangian method (ALM), well established in constrained optimization. We find that for the soft-constrained approach, using the ALM improves prediction performance in terms of constraint satisfaction by factor 2 and reduces training epochs compared to using a fixed penalty by 30%. Hence, in the soft-constrained approach, the use of the ALM is always recommended. The hard-constrained approach, which entails additional architectural design choices, can reach on par accuracy with the soft-constrained approach, at even higher thermodynamic consistency, reaching 12 orders of magnitude closer approximation of the Clapeyron equation. Overall, the hard-constrained approach is most promising when thermodynamic consistency is critical, yet requires tailoring the ML model architecture to the respective thermodynamic relation.

This is the second paper of this series in which we prove we can do without dark matter using spacetime with extra dimensions compactified to a hypersphere with radius R. Here we prove cosmological structures can grow even in a Universe without dark matter, provided that extra dimensions are contracting.

An interacting many-body system being localized in the presence of disorder can fail to serve as its own bath. In an electronic system, the charge and spin degrees of freedom can act as thermal baths for each other. In this paper, we study the stability of an Anderson insulator in the spin sector with respect to charge doping. We consider one-dimensional two-component fermions in a lattice with large onsite repulsion ($t-J_{XX}$ model) and with a single hole in a random magnetic field. In the absence of the hole the spin sector is localized in arbitrarily weak random magnetic fields. We argue that a single hole thermalizes the spin chain in the weak disorder limit. In this regime our numerical results indicate ergodicity of the system as a whole and delocalization of the hole. At larger magnetic fields the hole eventually localizes with a finite localization length, and the Anderson spin insulator is restored.

The electron-positron Future Circular Collider will provide an unprecedented opportunity for precision studies at the $Z$ pole. In addition to improving the electroweak measurements pioneered at LEP, Tera-$Z$ statistics and modern jet flavor reconstruction could make rare, flavor-resolved final states accessible as precision observables. We study the exclusive four-body processes $e^+e^-\to Z\to Q\bar Q\ell^+\ell^-$ with $ Q=c,\,b$ and $\ell=\mu,\,\tau$ as probes of flavor-specific new physics contact interactions. A fast analysis yields representative multi-TeV reaches for vector-current interactions involving bottom or charm quarks and muons or taus, providing a baseline for future detector-level studies. For charm-current interactions, the projected direct sensitivities are comparable to those obtained indirectly from electroweak precision observables. Two-dimensional fits further show that these processes retain quark-flavor information that can be poorly resolved by the renormalization-group-induced electroweak response. These results illustrate how flavor-resolved four-body $Z$ processes can bridge the electroweak and flavor programs at FCC-ee, opening a new class of complementary precision observables.

The rapid adoption of generative artificial intelligence (GenAI) in higher education has introduced a critical pedagogical paradox: while these systems possess extraordinary capacity for information retrieval and synthesis, their default operational mode of supplying immediate, unprompted answers actively undermines the cognitive processes upon which genuine scientific understanding is built. This paper presents NuPaD (Nuclear & Particle Physics – Deep Learning Tutor), a novel pedagogical framework designed for the graduate-level subatomic physics curriculum. For such advanced courses, instruction naturally shifts toward inquiry-driven, problem-based learning, making it an ideal environment to use GenAI to explore complex, open-ended physical questions rather than merely querying established facts. The framework consists of three tightly coupled and easy-to-use components: a primary agent instruction file that enforces a structured problem-based learning protocol, a purpose-built textbook optimized for precise parsing by privacy-preserving local GenAI, and a concise companion file that bridges the knowledge gap between the textbook and GenAI, alongside a comprehensive dynamic skill set for specialized tasks. We explain in detail the architectural principles of the modular NuPaD framework, the design philosophy of the Markdown-native textbook format, and the underlying GenAI regulation principles. By redefining the interaction loop between student and model, this framework transforms GenAI from a passive answer engine into an active, personalized tutor, ensuring that it accelerates rather than bypasses the development of deep learning and scientific reasoning.

The $J^{P}=2^{+}$ $cc\bar c\bar s$ and $bb\bar b\bar s$ tetraquarks are studied in parallel within the two-point QCD Sum Rules framework using the same symmetric axial-vector$\otimes$axial-vector interpolating current. The current-specific OPE sectors retained through dimension seven within the stated background-field truncation are evaluated with a common symbolic construction, with the bottom channel obtained by the heavy-flavour replacement $c\to b$. The same pole-dominance and OPE-convergence criteria are imposed in both channels. The adopted charm region is $\sqrt{s_0}=5.7\GeV$ with $3.6\le M_B^2\le4.3\GeVsq$, whereas the bottom region is $\sqrt{s_0}=14.3\GeV$ with $9.8\le M_B^2\le10.8\GeVsq$. At representative Borel points, the extracted masses are $5.239\GeV$ and $13.832\GeV$, respectively. After the QCD-input, continuum-threshold, and Borel-window variations are combined, the final results are $m_{cc\bar c\bar s,\,2^+}=5.239\pm0.061\GeV$ and $m_{bb\bar b\bar s,\,2^+}=13.832\pm0.059\GeV$.

Secondary electron emission (SEE), arising from the interaction of energetic electrons with material surfaces, can induce deleterious effects in vacuum radio-frequency (RF) systems, notably multipacting, thereby degrading performance and threatening device integrity. Despite extensive efforts, effective and widely adopted mitigation strategies remain limited. Here, we report an approach to simultaneously tailor SEE and electrical conductivity using nanometric multi-element multilayers deposited by atomic layer deposition (ALD). The design and fabrication of these heterostructures are presented, and a range of films is systematically characterized to establish correlations between emission properties, electrical conductivity, chemical and structural features. We demonstrate that such heterostructures enable combinations of total electron emission yield (TEEY) and conductivity unattainable in single-phase materials, including regimes combining high TEEY with relatively high conductivity and low TEEY with low conductivities. These results open new avenues for the rational design of functional surfaces for vacuum electronic applications.

The weak guidance approximation suppresses the longitudinal field component $E_z$, and with it an entire class of linear magneto-optic interactions. We derive and experimentally verify a transverse Faraday effect in step-index multimode fibres that couples $E_y$ into $E_z$. Using speckle decorrelation we isolate the linear Faraday signal from the quadratic Cotton-Mouton background, confirming four predictions: the effect vanishes without a strong index step, scales with launch angle, is completely polarisation-selective relative to the field, and tracks Verdet dispersion. Under 0.24 T we observe $\Delta\rho \approx 0.16$ for perpendicular input and a complete null for parallel input.

Solomonoff's universal inductive inference [Inf. Control. 1964] is one of the most general frameworks for learning from sequential data and predicting future observations. It provides prediction guarantees for any computable stochastic source. We ask whether an analogous universal theory of induction can be developed for quantum systems. To this end, we introduce universal quantum inductive inference, a framework for learning and predicting quantum sources that may exhibit arbitrary correlations and entanglement across time. Given the outcomes of past measurements and the corresponding post-measurement quantum systems, the learner produces a joint state that predicts the next measurement outcome and post-measurement system while preserving correlations with the past systems. We model a quantum source as a multipartite quantum state whose description is generated by an unknown $s$-bit program within a given time bound. The learner is required to produce a state that is $\epsilon$-close in trace distance to the target with probability at least $1-\delta$. We establish an information-theoretic inference algorithm with round complexity $O(s\epsilon^{-2}\delta^{-1})$. We further prove a matching lower bound in the relevant parameter regime, even for classical sources. As a second result, we construct a non-i.i.d. state tomography algorithm that outputs a classical description of the conditional state of the next system given past measurement outcomes. Our information-theoretic tomography algorithm achieves round complexity $O(s\min\{2^s,2^n\}\epsilon^{-2}\delta^{-1})$, where $n$ is the number of qubits received in each round. Finally, we investigate the computational hardness of universal quantum inductive inference under quantum cryptographic assumptions.

Grover's algorithm achieves a quadratic speedup for unstructured search when a global oracle for the target set is available. However, its success probability is generally below $100\%$. To overcome this issue, Long presented a modified version of Grover's search algorithm by introducing a phase-matching condition, which can search for the target set with zero theoretical failure rate. Nevertheless, in many applications, the target set is determined by the intersection of multiple constrained sets. Most existing Grover-based methods are limited to the intersection of only two sets and are not always successful in searching for the target set. In this work, based on Long's method, we propose an algorithm for exactly searching the intersection of multiple sets. We derive and prove a phase-matching condition for searching the intersection exactly. Furthermore, we present a quantum circuit that implements exact intersection search. Finally, we support our theoretical results with numerical simulations.

Quantum steering captures the ability of one party, through local measurements on a shared entangled state, to affect the conditional states held by distant parties in a way that admits no local explanation. Its device-independent (DI) quantification – requiring no characterization of any state or measurement – has been developed in the bipartite setting, notably through the framework of assemblage moment matrices (AMMs) [Phys. Rev. Lett. 116, 240401 (2016)], but has remained largely unexplored beyond it. Here, we extend the AMM framework to tripartite steering, covering both the scenario in which two parties jointly steer a third one (2-steer-1) and that in which a single party steers the remaining two (1-steer-2). For each scheme, we construct a semidefinite program that, from the observed correlations – or merely from the violation of a Bell inequality – yields lower bounds on the steering robustness of the underlying assemblage. As a by-product, our bounds also certify, in a DI manner, the incompatibility of the measurements performed by the steering parties.

Modeling the response of driven many-body quantum systems from input–output data is difficult: the dynamics are nonlinear, history dependent, and expensive to simulate as system size grows. A paradigmatic case is High-Harmonic Generation~(HHG), where a strong field drives a medium to emit radiation that is highly sensitive to the drive and encodes long-range temporal correlations. We introduce a dissipative quantum reservoir computing~(DQRC) framework that builds a digital twin of such a system, learning its input–output map directly from data while the reservoir—itself a small open quantum system—stays fixed and only a classical readout is trained. We show that a minimal single-qubit reservoir reproduces the HHG response of a substantially larger Ising spin chain, and on a representative benchmark matches and on several metrics surpasses previously reported temporal convolutional and Kolmogorov–Arnold-network models, while using a simpler, physically realizable system. A single fixed reservoir further generalizes across a broad range of drives, indicating that it learns a shared physical response structure rather than memorizing trajectories. These results establish dissipative quantum reservoirs as compact, physically grounded digital twins for nonlinear, memory-dependent quantum dynamics. Code is available at \href{https://github.com/AI-and-Quantum-Computing/DQuRC}{https://github.com/AI-and-Quantum-Computing/DQuRC}.

We study reduced solutions of Toda systems generated by spherical metrics for an arbitrary complex simple Lie algebra. The main result is an intrinsic centralizer parametrization: for a spherical metric, the reduced family is the positive Iwasawa slice cut out by the centralizer of the principal image of closure of monodromy group. As an application, we transfer existing spherical-metric existence results to the diagonal Toda source tuple.

We study the site-diluted Ising model on the kagome lattice using the Wolff single-cluster algorithm, focusing on both equilibrium and dynamic critical properties. The equilibrium critical exponents $\nu = 1$ and $\gamma/\nu = 7/4$ retain their exact pure Ising values for all spin concentrations $p$ considered, consistent with the marginal irrelevance of disorder at $\alpha = 0$, with the specific heat crossing over from logarithmic to double-logarithmic growth upon dilution. These static results are shared between the kagome and square lattices. On the dynamic side, $z$ decreases upon dilution on both lattice, opposite to what is observed under local dynamics, with evidence of saturation to a $p$-independent value at strong dilution, suggesting a diluted dynamic fixed point. While $z$ is consistent between the two lattices in the pure case, it differs in the diluted regime, an effect we attribute to the two lattices sitting at different positions along the renormalization-group flow between the Ising and percolation fixed points, rather than to a true asymptotic breakdown of dynamic universality.

Weyl geometry, in which the length scale can be chosen independently at each point of spacetime, provides a natural framework for extending general relativity through Weyl invariance, that is, local scale symmetry. We construct a gravitational theory whose Lagrangian is an arbitrary function of the scalar curvature in Weyl geometry and establish the conditions under which the theory is free of ghosts and tachyons around maximally symmetric vacua. For an arbitrary function, Weyl invariance requires a compensating scalar field in addition to the metric and the Weyl vector. By linearizing the action with an auxiliary field, we show that the Weyl vector couples to the scalar sector only through a single combination of the scalar fields. Consequently, the Weyl vector, shifted by the logarithmic gradient of this combination, becomes a Weyl-invariant massive vector field without gauge fixing. In the Einstein frame, given that the graviton is ghost-free, the no-tachyon condition for the Weyl vector, together with the no-ghost condition for the scalaron, the scalar mode associated with the higher-curvature terms, reduces to the positivity of the kinetic coefficient of the compensating scalar. When this coefficient vanishes, the scalaron does not propagate, leaving only the graviton and the massive vector. As an example, we show that for a Lagrangian containing constant, linear, and quadratic curvature terms, both a massive vector and a massive scalaron are necessarily present throughout the stability region, whereas without the linear term the scalaron becomes massless.