Papers

Interaction quenches in strongly correlated electron systems provide a powerful route to probe nonequilibrium many-body dynamics. For the Hubbard model, nonequilibrium dynamical mean-field theory has revealed coherent post-quench oscillations, dynamical crossovers, and long-lived transient regimes. However, these studies are largely restricted to spatially homogeneous dynamics and therefore neglect the role of spatial structure formation during ultrafast evolution. Here we investigate interaction quenches in the half-filled Hubbard model using a real-space time-dependent Gutzwiller framework. We show that homogeneous nonequilibrium dynamics is generically unstable: even arbitrarily weak spatial fluctuations grow dynamically and drive the system toward intrinsically inhomogeneous states. Depending on the interaction strength, the post-quench evolution exhibits spatial differentiation, nucleation, and slow coarsening of Mott-like domains. Our results establish spatial self-organization as a generic feature of far-from-equilibrium correlated matter and reveal a fundamental limitation of spatially homogeneous nonequilibrium theories.

In a one-dimensional ferromagnet-superconductor nanowire, magnetism can suppress superconductivity except where the Zeeman field is suppressed, for example domain wall superconductivity (DWS) near magnetic domain walls or multi-domain-averaged superconductivity (MDAS) in multi-domain states where the net magnetization over the coherence length averages to nearly zero. Here we study full-shell InAs/EuS/Al nanowires using scanning SQUID magnetometry and transport, and find superconductivity in the Al shell only when the EuS is in a multi-domain state, consistent with both DWS and MDAS, and absent in the saturated single-domain state. Scanning SQUID magnetometry further shows that the EuS magnetic texture is position dependent and reconfigurable by small changes in external magnetic field, including moving a well-defined domain wall at $\approx$5.5 $\mu$m/mT with sub-mT fields, implying that any associated localized superconducting region would likewise be movable. Such magnetic texture controlled superconductivity along a nanowire may be useful for topological qubits, Andreev spin qubits, superconducting logic, and memory devices.

Plexcitonic assemblies are hybrid materials composed of a plasmonic nanoparticle and molecular or semiconducting emitters whose electronic transitions are strongly coupled to the plasmonic mode. This coupling hybridizes the system modes into upper and lower polariton branches. The strength of the interaction depends on the number of emitters and on their orientation and spatial arrangement relative to the metallic surface. These structural factors have profound consequences for the ensuing photoexcited dynamics. Despite the extensive spectroscopic work on plexcitonic systems, direct understanding of the molecular geometry at the metal interface remains limited. In this work, we present a comprehensive structural characterization of one of the most widely studied plexcitons formed by the cyanine dye 5,5',6,6'-tetrachloro-1,1'-diethyl-3,3'-di(4-sulfobutyl)-benzimidazolocarbocyanine (TDBC) and silver nanoprisms using a combination of NMR, THz-Raman spectroscopy, and DFT calculations. By comparing the signals from the monomeric and aggregated forms of TDBC with that of the plexciton, we identify shared spectral fingerprints that reveal how molecular packing is modified when the aggregate adsorbs on the silver surface. We observe Raman modes specific to plexciton systems, and identify NOESY cross-peaks in the aliphatic region, that along with THz-Raman modes in the 10-400 cm$^{-1}$ region are sensitive indicators of aggregation geometry and adsorption. We find that isolated TDBC monomers adopt an asymmetric conformation in which both sulfobutyl chains lie on the same side of the chromophore, while J-aggregates adopt a symmetric up-down alternation of the chains from molecule to molecule. This work establishes the molecular geometry of a prototypical TDBC-silver plexciton, providing a structural benchmark for understanding geometry-dependent photophysics in hybrid exciton-plasmon systems.

Nonlinear magnetic response driven by time-periodic magnetic fields offers a distinct route to probe spin-resolved quantum geometry beyond conventional electric-field-driven nonlinear effects. While linear magnetic responses depend on the Zeeman quantum geometric tensor, the influence of generalized spin-rotation quantum geometries on nonlinear responses has not been established. Here, we develop a microscopic quantum-kinetic framework to elucidate how the Zeeman and spin-rotation quantum geometric tensors govern nonlinear gyrotropic magnetic transport in two-dimensional systems. We derive second-order gyrotropic magnetic currents and reveal a distinct geometric separation: the off-diagonal sector is controlled by the Zeeman symplectic and metric connections, whereas the diagonal sector is dictated by the spin-rotation quantum metric and Berry curvature. This identifies the spin-rotation quantum geometric tensor as a fundamental geometric quantity unique to the nonlinear regime. Applying our theory to massless Dirac fermions, hexagonally warped topological insulator surface states, tilted massive Dirac fermions, and parity-time symmetric CuMnAs, we demonstrate how specific symmetries selectively activate conduction and displacement channels. Our findings link spin-resolved quantum geometry to nonlinear magnetic transport, offering design principles for engineering tailored nonlinear magnetic responses in optoelectronic and spintronic devices.

In this work, we present Multimodal Equivariant Inverse Design Network (MEIDNet), a framework that jointly learns structural information and materials properties through contrastive learning, while encoding structures via an equivariant graph neural network (EGNN). By combining generative inverse design with multimodal learning, our approach accelerates the exploration of chemical-structural space and facilitates the discovery of materials that satisfy predefined property targets. MEIDNet exhibits strong latent-space alignment with cosine similarity 0.96 by fusion of three modalities through cross-modal learning. Through implementation of curriculum learning strategies, MEIDNet achieves ~60 times higher learning efficiency than conventional training techniques. The potential of our multimodal approach is demonstrated by generating low-bandgap perovskite structures at a stable, unique, and novel (SUN) rate of 13.6 %, which are further validated by ab initio methods. Our inverse design framework demonstrates both scalability and adaptability, paving the way for the universal learning of chemical space across diverse modalities.

Transition metal dichalcogenides (TMDs) hold relevance for spin-triplet superconducting phases due to their inherent Ising spin-orbit coupling, but the majority of studies have so far focused on oversimplified models. In this work, we consider a TMD monolayer using a three-orbital model with anisotropic couplings and investigate the emergent superconducting properties when it is placed in proximity to a conventional spin-singlet $s$-wave superconductor. We find that the multiorbital nature of the TMDs lead to superconducting gaps not only at zero energy but also at higher energies, so-called hybridization gaps, which exhibit a complex structure due to the anisotropic couplings, challenging their spectral measurement. Moreover, we find that the inherent Ising spin-orbit coupling induces a spin splitting and a spin polarization along the $z$ direction, which correlates with the emergence of mixed spin-triplet superconducting pairs. These spin-triplet pair correlations appear in the monolayer as a proximity-induced effect due to the impact of the Ising spin-orbit field on conventional spin-singlet $s$-wave superconductivity. Taking realistic parameters for a $\text{MoS}_2$ monolayer, we show that the Ising field is strong enough to induce spin-triplet pair correlations of the same magnitude as their spin-singlet counterparts. We also include Rashba spin-orbit coupling, naturally emerging in a heterostructure and find that it induces equal spin-triplet superconducting pairs that compete with the mixed spin-triplet pairs induced by the Ising spin-orbit coupling. Our findings help understand the superconducting properties of TMDs in proximity to conventional superconductors.

Superconducting resonators and qubits are limited by dielectric losses from surface oxides. Surface oxides are mitigated through various strategies such as the addition of a metal capping layer, surface passivation, and acid processing. In this study, we demonstrate the use of X-ray photoelectron spectroscopy (XPS) as a rapid characterization tool to study the effectiveness cap layers for niobium for further device fabrication. We non-destructively evaluate 17 capping layers to characterize their ability to prevent oxygen diffusion, and the effects of standard fabrication processes – annealing, resist stripping, and acid cleaning. We downselect for resilient capping layers and test their microwave resonator performance.

The rapid rise of artificial intelligence has led to an unsustainable growth in energy consumption. This has motivated progress in neuromorphic computing and physics-based training of learning machines as alternatives to digital neural networks. Many theoretical studies focus on simple architectures like all-to-all or densely connected layered networks. However, these may be challenging to realize experimentally, e.g. due to connectivity constraints. In this work, we investigate the performance of the widespread physics-based training method of equilibrium propagation for more realistic architectural choices, specifically, locally connected lattices. We train an XY model and explore the influence of architecture on various benchmark tasks, tracking the evolution of spatially distributed responses and couplings during training. Our results show that sparse networks with only local connections can achieve performance comparable to dense networks. Our findings provide guidelines for further scaling up architectures based on equilibrium propagation in realistic settings.

We propose a method to suppress collisional loss in strongly dipolar, rotationally excited ultracold molecules using a combination of static (dc) and microwave (ac) electric fields. By tuning two excited pair molecular rotational states into a Förster resonance with a dc field, simultaneously driving excited rotational transitions with an ac field removes all long-range bound states, allowing near complete suppression of all two- and three-body collisional loss channels. While permitting tunable dipolar and anti-dipolar interactions, this bound-state-free ac/dc scheme is not subject to photon-changing collisions that are the primary source of two-body loss in shielding with two microwave fields, used to achieve the first molecular Bose-Einstein condensate [Bigagli et al., Nature 631, 289 (2024)]. Using NaCs as a representative example for strongly dipolar molecules, close-coupling calculations are performed to show that bound-state-free shielding can achieve ratios of elastic-to-loss rates $\gtrsim 10^{6}$ at 100 nK, with currently accessible ac and dc field generation technologies. This work opens new opportunities for realizing large, long-lived samples of strongly interacting degenerate molecular gases with tunable long-range interactions.

Each cycle of a quantum computation requires a quantum state initialisation. For semiconductor-based quantum platforms, initialisation is typically performed via slow microwave processes and usually requires cooling to temperatures where only the lowest quantum level is occupied. In silicon, boron atoms are the most common impurities. They bind holes in orbitals including an effective spin-3/2 ground state as well as excited states analogous to the Rydberg series for hydrogen. Here we show that initialisation temperature demands may be relaxed and speeds increased over a thousand-fold by importing, from atomic physics, the procedure of optical pumping via excited orbital states to preferentially occupy a target ground state spin. Spin relaxation within the orbital ground state of unstrained silicon is too fast to measure for conventional pulsed microwave technology, except at temperatures below 2 K, implying a need not only for fast state preparation but also fast state readout. Circularly polarised ~10 THz photon pulses from a free electron laser meet both needs at temperatures above 3 K: a 9 ps pulse enhances the population of one spin eigenstate for the "1s"-like ground state orbital, and the second interrogates this imbalance in spin population. Using parameters given by our data, we calculate that it should be possible to initialise 99% of spins for boron in strained silicon within 250 ps at 3 K. The speedup of both state preparation and measurement gained for THz rather than microwave photons should be explored for the many other solid state quantum systems hosting THz excitations potentially useful as intermediate states.

Distinguishability is central to quantum information theory, but a quantitative measure for distinguishing topological defects–realizations of generalized symmetries in quantum field theory (QFT)–has been lacking. We introduce the notion of the defect relative entropy to fill this gap for topological defects in two-dimensional conformal field theories (CFTs). For defects on a circle, we derive a universal formula that reduces defect relative entropy to a Kullback–Leibler divergence determined entirely by the modular $\mathcal{S}$-matrix and defect coefficients. Thus, the algebraic data governing modular transformations also determines defect distinguishability. A striking consequence is that certain distinct defects can have vanishing relative entropy when restricted to one side, implying that an observer confined to that side cannot distinguish them. This gives rise to information-theoretic equivalence classes of defects, which we term defect relative sectors. We further introduce the sandwiched defect Rényi relative entropy and defect fidelity, derive general formulas for these quantities. Explicit calculations in the Ising model, tricritical Ising model, and $\widehat{su}(2)_k$ WZW models illustrate our results.

Polaron formation in pump-probe experiments is an inherently non-equilibrium phenomenon, driven by the ultrafast coupled dynamics of electrons and phonons, and culminating in the emergence of a localized quasiparticle state. In this work, we present a first-principles quantum-kinetic theory of polaron formation that captures the real-time evolution of electronic and lattice degrees of freedom in presence of electron-phonon coupling. We implement this framework to investigate the ultrafast polaron formation in the prototypical polar insulator MgO. This approach allows us to determine the characteristic timescales of polaron localization and to identify its distinctive dynamical fingerprint. Our results establish clear and experimentally accessible criteria for identifying polaron formation in pump-probe experiments.

This work inspects the thermally activated transfer of solute particles across the interface between two interstitial solid solution phases that equilibrate internally by fast diffusion on conserved arrays of sites. When each phase is considered as an ergodic ensemble of particles, statistical mechanics predicts the occupancy of the transition states at equilibrium to depend on the barrier energy and on the chemical potentials and vacancy fractions in each of the phases. A rate law for the non-equilibrium interfacial transfer, based on a constant transition probability between activated states, naturally satisfies the principle of detailed balance. Contrary to Butler-Volmer-type laws, values of the particle chemical potentials enter explicitly rather than through their difference. This, along with the dependency on the vacancy fractions, implies here an exchange flux density that depends explicitly on the compositions at equilibrium. The results can explain experimental observations of a drastic slow-down in the charging of metal hydrides near phase transformations or miscibility-gap critical points.

Transition-metal dichalcogenides of the pyrite-marcasite family are model systems of crystal chemistry. A few of these show polymorphism. The theoretical ground state of CoSe2 is marcasite, but the material is typically synthesized in the pyrite structure. Polymorphism has been observed in nanoparticles and synthetic control of the polymorphs of CoSe2 has not been achieved. We have synthesized material libraries of the Fe1-xCoxSe2 series by combining combinatorial deposition and ex-situ selenization. The approach allows to efficiently explore substitution ranges and crystal structures that form for different synthesis conditions. We find that higher levels of Co content x within the marcasite structure are possible when synthesizing at low temperatures. At a synthesis temperature of only 250{\deg} C, we have successfully synthesized marcasite CoSe2 as the majority phase. Density functional theory simulations reveal that the two isomorphs of CoSe2 are extremely close in energy and that the orthorhombic phase is the energetic ground state. Our experimental and theoretical data show that the marcasite structure is the equilibrium phase of Fe1-xCoxSe2 in the entire composition range.

The evaluation of the electrostatic potential is fundamental to the study of condensed phase systems. We discuss the calculation of the relevant lattice summations by Ewald-type techniques. A model charge density is introduced, that cancels multipole moments of the crystalline charge distribution up to a desired order, for accelerating convergence of the Ewald sums. The method is applicable to calculations of bulk systems, employing arbitrary unit cells in a classical or quantum context, and with arbitrary basis functions to represent the charge density. The efficacy of the method is demonstrated on the calculation of the fundamental gap of the gallium arsenide bulk semiconductor, as a prototype example, where significantly accelerated convergence is numerically confirmed, due to a reduction of the number of two-electron integrals that need to be computed. The approach clarifies a decades-old implementation in the CRYSTAL code.

Twisted graphene provides a tunable platform for studying superconductivity in two dimensions. In the presence of electric currents and magnetic fields, vortices determine the phenomenological properties of the material. Related studies usually address bulk properties averaging over ensembles of vortices. Here, we employ a gate-defined Josephson junction as a single-vortex sensor, enabling direct access to individual vortex dynamical events. Our measurements reveal that, at elevated temperatures (T > 100 mK), vortices enter the superconducting leads via classical thermal activation over energy barriers. At lower temperatures (T < 90 mK), we observe macroscopic quantum tunneling through these barriers. The data are consistent with a sharp, first-order type quantum-to-classical transition. From our measurements, we extract vortex entry and exit energy barriers on the order of a few Kelvin and estimate the barrier thickness to be approximately 100 nm, corresponding to about one tenth of the device width.

We investigate the possibility of the emergence of ultra-complex conductivity diagrams in the nearly free electron approximation for metals with cubic symmetry. Estimates show that the emergence of such diagrams requires the Fermi level to fall into very narrow energy intervals within the conduction band. In our view, this circumstance is mostly due to the high symmetry and the simplest analytical form of the dispersion relations $\epsilon ({\bf p})$ under consideration.

The third and fourth density and acoustic virial coefficients of neon were determined at temperatures between 10 and 5000 K from first principles employing the path-integral Monte Carlo (PIMC) approach. For these calculations, we used the pair potential of Hellmann $\textit{et al.}$ [J. Chem. Phys. 154, 164304 (2021)], which is based on supermolecular $\textit{ab initio}$ calculations with basis sets of up to octuple-zeta quality and levels of theory up to coupled cluster with single, double, triple, quadruple, and perturbative pentuple excitations [CCSDTQ(P)]. The potential also accounts for relativistic, retardation, and post-Born$-$Oppenheimer effects and is provided with reliable uncertainty estimates. To incorporate nonadditive interactions, we developed a nonadditive three-body potential based on extensive supermolecular CCSD(T), CCSDT, and CCSDT(Q) calculations with basis sets of up to sextuple-zeta quality. This potential also accounts for relativistic effects. The very small nonadditive four-body contributions to the fourth virial coefficients were considered using a relatively simple nonadditive four-body potential based on supermolecular CCSD(T) calculations. We calculated the third and fourth density and third acoustic virial coefficients directly by PIMC and the fourth acoustic virial coefficient indirectly using thermodynamic relations between the density and acoustic virial coefficients. The uncertainties of the pair potential and those estimated for our nonadditive three-body potential were rigorously propagated in the PIMC calculations into uncertainties for the virial coefficients. These uncertainties are distinctly smaller than those of almost all of the corresponding experimental virial coefficient data.

Hydrogen absorption significantly alters the mechanical properties of steel. However, absorbed hydrogen also influences its electronic and magneto-structural properties, helping to interpret how hydrogen is incorporated. This study therefore investigates the influence of hydrogen incorporation on the electronic and magneto-structural properties of X2CrNi18-9 stainless steel in different microstructural states. Microstructural characterization included analytic electron microscopy mapping, X-ray diffraction and thermodynamic stability maps to evaluate grain size, dislocation density and chemical homogeneity. The electronic properties were characterized using the Seebeck coefficient, while the magneto-structural properties were investigated using diffuse neutron scattering and small-angle neutron scattering (SANS). Hydrogen incorporation showed clear changes in the Seebeck coefficients. Magnetic SANS in conjunction with diffuse neutron scattering indicates the existence of nanoscale inhomogeneities with the same fcc structure as the bulk, but with correlation lengths of a few nanometres. The size of these inhomogeneities increased with hydrogen incorporation, suggesting that hydrogen preferentially accumulates in their vicinity. However, no direct correlation between the electronic and magneto-structural properties and the dislocation density could be demonstrated. We suggest that studies such as these will lead in the medium term to the development of guidelines for material design to make steels more resistant to hydrogen.

Coupled excitable systems can generate a variety of patterns. In this work, we investigate coupled Chialvo maps in two dimensions under two types of nearest-neighbor couplings. One coupling produces ringlike patterns, while the other produces spirals. The rings expand with increasing coupling, whereas spirals evolve into turbulence and dissipate at stronger coupling. To quantify these patterns, we introduce an analogue of the discriminant of the velocity gradient tensor and examine the persistence of its sign. For ring-type patterns, the persistence decays more slowly than exponentially, often following a power law or stretched exponential. When spiral structures remain intact, persistence saturates asymptotically and can exhibit superposed periodic oscillations, suggesting complex exponents at early times. These behaviors highlight deep connections with the underlying dynamics.

Symmetry provides powerful non-perturbative constraints in quantum many-body systems. A prominent example is the Lieb-Schultz-Mattis (LSM) anomaly – a mixed 't Hooft anomaly between internal and translational symmetries that forbids a trivial symmetric gapped phase. In this work, we investigate lattice translation operators in systems with an LSM anomaly. We construct explicit lattice models in two and three spatial dimensions and show that, after gauging the full internal symmetry, translation becomes non-invertible and fuses into defects of the internal symmetry. The result is supported by the anomaly-inflow in view of topological field theory. Our work extends earlier one-dimensional observations to a unified higher-dimensional framework and clarifies their origin in mixed anomalies and higher-group structures, highlighting a coherent interplay between internal and crystalline symmetries.

We study how energy and quantum entanglement are transferred when two identical CFTs are entangled locally. This is probed by considering a local operator insertion in one of the CFTs. When the CFTs have holographic duals via the AdS/CFT correspondence, the transfer happens through an AdS wormhole that allows signal propagation even beyond the horizon from one AdS boundary to the other; we demonstrate this in explicit CFT calculations. We argue that this transmission is possible because the insertion of a local operator is not a unitary process but a regularized version of projection measurement, and that this is interpreted as quantum teleportation. We also find that this leads to a phenomenon opposite to scrambling, where mutual information, instead of being suppressed, gets enhanced by the insertion of a local operator excitation.

We investigate flux dynamics in the high-entropy alloy superconductor (TaNb)0.7(HfZrTi)0.5 after annealing (as-cast, 500 {\deg}C, 550 {\deg}C, and 1000 {\deg}C) using a sensitive ac composite magnetoelectric method that measures the complex ac magnetostrictive coefficient (d{\lambda}/dH)ac. The resulting vortex phase diagrams show that intermediate annealing (500-550 {\deg}C) induces nanoscale clustering, enhances pinning, and produces a pronounced fishtail effect with successive elastic- and plastic-vortex-glass regimes. Flux-jump instabilities appear at 550 {\deg}C and persist at 1000 {\deg}C, indicating strong pinning and thermomagnetic instability in the low-temperature, low-field regime. Remarkably, the 1000 {\deg}C sample exhibits a two-step superconducting response-a double plateau or drop in d{\lambda}'/dH and two dissipation peaks in d{\lambda}”/dH-demonstrating the coexistence of two superconducting phases with distinct irreversibility and critical-field value. We further show that the resolvability of the two-step (d{\lambda}/dH)ac signature is governed by the topological connectivity of the phase-separated microstructure, which controls magnetic shielding between the TaNb-rich network and the (TaNb)0.7(HfZrTi)0.5 parent phase. These results establish a direct microstructure-vortex-state correlation and provide a route to tailoring flux pinning in chemically complex superconductors via thermal processing.

A major issue in exploiting plasmonic cavities as key components in nanotechnology is the effect of radiative and absorption losses on their electrodynamic behavior. Treating them as open-systems, we derive a time-local, completely positive master equation that retains non-secular interference between decay pathways and reduces to the standard secular description when the environment resolves polariton splitting. When it does not, the theory predicts order-one deviations from secular leakage dynamics, including bath-induced coherences and stabilization of dark polaritons, and provides a simple design criterion based on the ratio of polariton splitting to reservoir linewidth. A time-resolved leakage measurement, such as transmission, reflectivity, or photoluminescence, can be used to observe these effects.

Fluid mixtures that exhibit an azeotrope cannot be purified by simple bulk distillation. Consequently, there is strong motivation to understand the behavior of azeotropic mixtures under confinement. We address this problem using an ML-enhanced classical density functional theory (cDFT) applied to a binary Lennard-Jones mixture that exhibits azeotropic phase behavior. As proof-of-principle of a "train once, learn many" strategy, our approach combines a neural functional trained on a single-component repulsive reference system with a mean-field treatment of attractive interactions, inspired by the connection between cDFT and local molecular field theory. The theory faithfully describes capillary condensation and results from grand canonical Monte Carlo simulations. Moreover, by taking advantage of a known accurate equation of state, the "neural LMFT" we present well-describes bulk thermodynamics by construction. Exploiting the computational efficiency of neural LMFT, we systematically evaluate adsorption selectivity across a wide range of compositions, pressures, temperatures, and wall-fluid affinities. In cases where the wall-fluid interaction is the same for both species, we find that the pore becomes completely unselective at the bulk azeotropic composition. Strikingly, this unselective point persists far from liquid-vapor coexistence, including in the supercritical regime. Analysis of the bulk equation of state across a wide range of thermodynamic state points shows that the azeotropic composition coincides with equal partial molar volumes and an extremum in the isothermal compressibility. A thermodynamic analysis demonstrates that unselective adsorption corresponds to an aneotrope (a point of zero relative adsorption) and an extremum in the interfacial free energy. We also find that the two interfaces of the slit pore behave independently down to remarkably small slits.

We investigate the microwave-power dependence of magnon-photon coupling in a yttrium iron garnet-sphere/split-ring-resonator hybrid system at room temperature and demonstrate that nonlinear spin-wave interactions suppress the coupling through power-induced dissipation of magnetostatic modes. At low microwave power, the modes exhibit pronounced level repulsion, evidencing strong coupling to the microwave field. As the power increases, however, magnon linewidth broadening progressively weakens the coupling and ultimately suppresses it entirely below a threshold external magnetic field. We show that this behavior originates from Suhl's first-order instability: magnetostatic modes, which couple to the resonator, parametrically excites two counter-propagating magnons at half its frequency, causing modes below the threshold external magnetic field to vanish. In contrast, magnon modes above the threshold field remain robust even at high power, as the instability criterion is not satisfied in that regime. These results reveal a well-defined nonlinear boundary for magnon-photon coupled systems and highlight a favorable regime for exploiting nonlinear magnonics for frequency conversion, switching, and other functional magnonic devices.

We study the thermodynamic performance of a periodic quantum Otto cycle operating on the single-impurity Anderson model. Using a decomposition of the time-evolution generator based on the principle of minimal dissipation, combined with the numerically exact hierarchical equations of motion (HEOM) method, we analyze the operating regimes of the quantum thermal machine and investigate effects of Coulomb interactions, strong system-reservoir coupling, and energy level alignments. Our results show that Coulomb interaction can change the operating regimes and may lead to an enhancement of the efficiency.

Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening. Yet current generative AI models for materials discovery, which now drive exploration of vast chemical and structural spaces, optimize candidates exclusively for structural stability and functional properties, with no integration of environmental assessment at any stage of the design loop. Prospective and ex-ante life cycle assessment methods exist and have been applied to emerging technologies, but they operate as standalone downstream analyses, not as active constraints within generative or active-learning pipelines. The result is that environmental feedback, even when produced, arrives after design decisions have been made rather than informing them. The disconnect between atomic-scale design and lifecycle assessment (LCA) reflects fundamental challenges: (i) data scarcity across heterogeneous sources, (ii) scale gaps from atoms to industrial systems, (iii) uncertainty in synthesis pathways, and (iv) the absence of frameworks that co-optimize performance with environmental impact. In this Perspective, we propose integrating upstream ML-assisted materials discovery with downstream LCA into the ML-LCA framework, comprising five components: information extraction for building materials-environment knowledge bases, harmonized databases linking properties to sustainability metrics, multi-scale models bridging atomic properties to lifecycle impacts, ensemble prediction of manufacturing pathways with uncertainty quantification, and uncertainty-aware optimization enabling simultaneous performance-sustainability navigation. Case studies spanning polymers, glass, photoresists, and cement demonstrate both necessity and feasibility while identifying material-specific integration challenges.

The performance of large language models (LLMs) on verifiable tasks is usually measured by pass@k, the probability of answering a question correctly at least once in k trials. At a fixed budget, a more suitable metric is coverage@cost, the average number of unique questions answered as a function of the total number of attempts. We connect the two metrics and show that the empirically-observed power-law behavior in pass@k leads to a sublinear growth of the coverage@cost (diminishing returns). To solve this problem, we propose Reset-and-Discard (ReD), a query method of LLMs that increases coverage@cost for a given budget, regardless of the pass@k form. Moreover, given a pass@k, we can quantitatively predict the savings in the total number of attempts using ReD. If pass@k is not available for the model, ReD can infer its power-law exponent. Experiments on three LLMs across coding (HumanEval), math (GSM8K), and reasoning (MMLU-Pro) benchmarks demonstrate that ReD substantially reduces the required attempts, tokens, and USD cost to reach a desired coverage, while also offering an efficient way to measure inference power-laws. ReD's advantage is maintained for imperfect verifiers and outperforms the tested allocation baselines.

We investigate the $\lambda\ph^4+g\ph^6$ model using the renormalization group method and the $\ep$ expansion. This model is used in a situation where the coefficients $\lambda$, $g$ and the coefficient $\tau$ of the term $\tau \ph^2$ depend on two parameters $T$ and $P$, and there is a point ($T_c,P_c$) at which $\tau$ and $\lambda$ are zero. This point is named the tricritical point. The description of a system depends on a trajectory that leads to the tricritical point on the plane ($T,P$). In the trajectories, when $\lambda$ goes to zero fast enough, the description is defined by the $\ph^6$ interaction and then the $\ph^4$ term can be considered as a composite operator. In this case, the logarithmic dimension is $d=3$, and the $\ep$ expansion is carried out in the dimension $d=3-2\ep$. The main exponents of the tricritical model have been calculated in the third order of the $\ep$ expansion. Taking into account the $\ph^4$ interaction, we were able to calculate the value of the parameter that determines the required decrease rate in $\lambda$ to implement the tricritical behavior. The tricritical dimensions of the composite operators $\ph^k$ for $k=1, 2, 4, 6$ have been computed. The resulting values are compared to those known from a conformal field theory and non-perturbative renormalization group.