Papers

A gate voltage can suppress the critical current of a superconducting nanowire, and various scenarios have been proposed to describe these observations. The key difficulty is that these scenarios, including both leakage-driven and field-driven mechanisms, are impossible to disentangle in standard experiments. Here, we resolve this issue by studying a fully suspended superconducting nanowire of amorphous MoGe, separated from the gate by vacuum, eliminating all leakage-driven channels. We measure the phase slip escape rate $\Gamma$ and find a large gate-induced enhancement of $\Gamma$, exponential over six orders of magnitude. Fitting various escape-rate models reveals a strong deviation from simple phase slip models, hinting at a complex interaction between the electrostatic field and the phase slip centers. Surprisingly, $\Gamma$ is not invariant under reversal of the gate-voltage polarity. Our work establishes a clear and nontrivial connection between gate voltage and $\Gamma$, guiding future research into the origins of the effect.

Low surface brightness galaxies (LSB-galaxies) and the outer regions of disks of "normal" surface brightness galaxies (HSB-galaxies) are compared in terms of the radial distributions of star formation rates and efficiencies, as well as the Toomre stability parameter $Q_T$, using data from several samples of galaxies with high $HI$ content. It is shown that the dependences of the star formation rate $SFR$ on the $HI$ surface density and the star formation efficiency $SFE$ on the disk optical brightness $\mu_g$ for LSB- and HSB-galaxies have a similar character, suggesting similarity in the conditions that determine the star formation rate in low gas density regions. The considered dependences persist out to distances corresponding to brightnesses of 26-27 mag/arcsec$^2$, where the expected volume density of the equilibrium gas layer should be very low. It is suggested that the disk density at large distances from the center may be significantly underestimated.

A previous work [H. Yamase and M. Zafur, Phys. Rev. B 103, 224527 (2021)] showed that the longitudinal spin susceptibility exhibits a jump when the superconductivity develops continuously inside a magnetic phase. That analysis employed a minimal model containing magnetic and superconducting interactions. However, in correlated-electron systems, both magnetic and bond-charge interactions originate from the same underlying spin-spin exchange interaction. We therefore extend the model by including the uniform bond-charge order to provide a more realistic description of the system. We find that the jump of the longitudinal spin susceptibility remains robust even in the presence of uniform bond-charge order, but the uniform bond-charge order quantitatively enhances the longitudinal spin susceptibility and the size of the jump at $T_c$.

The Color-of-Money (CoM) problem is a financial optimization challenge in which enterprises must determine how to allocate and route funds across multiple accounts, currencies, and time periods while satisfying regulatory, operational, and liquidity constraints. As the number of assets, obligations, and planning periods increases, the decision space grows rapidly, making large-scale optimization increasingly challenging for classical approaches. In this work, we present a proof-of-concept quantum implementation of the CoM problem using IBM Quantum hardware. The original optimization problem is formulated as a constrained Mixed-Integer Linear Programming (MILP) problem and transformed into a Quadratic Unconstrained Binary Optimization (QUBO) representation suitable for quantum execution. We employ a Variational Quantum Algorithm (VQA) with Pauli Correlation Encoding (PCE), a qubit efficient encoding technique and apply error-mitigation technique to improve solution fidelity on noisy quantum hardware. A prototype instance consisting of 3 assets, 3 obligations, and 2 time periods was executed on real IBM quantum hardware and benchmarked against classical exact solver SCIP. The quantum approach successfully reproduced the same optimal solution obtained classically, validating the correctness and feasibility of the proposed methodology. While current noisy quantum hardware does not outperform classical optimization on the evaluated small instance, the results demonstrate the feasibility of executing treasury optimization workloads on current quantum hardware and provide a foundation for future investigations.

Oblivious transfer (OT) is a fundamental cryptographic primitive that is useful for realizing any two-party computation. Since information-theoretically secure perfect OT is impossible classically and quantumly, research has focused on imperfect protocols, exploring how close to perfect one can get against unbounded dishonest parties. While current approaches often make use of pure quantum states, recent work suggests that mixed quantum states may improve performance. In this paper, we investigate the use of mixed quantum states in Rabin oblivious transfer, where a sender holds one bit and a receiver learns its value with a certain probability while the sender remains ignorant of whether the receiver learned it. We present three mixed-state protocols constructed with two distinct methods, extending an existing pure-state scheme and employing a probabilistic approach, and demonstrate improved performance compared to classical and quantum pure-state protocols across varying parameters.

The main result of the paper states that if $0\neq v\in\mathbb C^m\otimes\mathbb C^n$, $d=\min\{m,n\}$, and $p=SR(v)$, then for every $1\le q\le d$, \begin{equation*} \min\left\{OSR(\mathbf U): \begin{array}{l} \mathbf U\in\mathbb M_m\otimes\mathbb M_n\text{ is unitary}, SR(\mathbf Uv)=q \end{array}\right\} = \left\lceil\max\left\{\frac pq,\frac qp\right\}\right\rceil . \end{equation*} Here $OSR(\mathbf U)$ denotes the operator Schmidt rank of $\mathbf U$. Furthermore, if $\mathbf U\in\mathbb M_m\otimes\mathbb M_n$ is unitary and $OSR(\mathbf U)\le k$, then, for every unit vector $x\in\mathbb C^m\otimes\mathbb C^n$ and every $1\le r\le d$, \begin{equation*} F_{\min\{kr,d\}}(\mathbf Ux)\ge F_r(x) \quad\text{and}\quad F_{\min\{kr,d\}}(x)\ge F_r(\mathbf Ux), \end{equation*} where $F_r(x)$ denotes the sum of the $r$ largest squared Schmidt coefficients of $x$. This result is stronger than rank reachability as it controls the entire cumulative Schmidt profile. We also establish a majorization relation and use it to obtain sharp bounds on Schatten-norm distortion and on the change of Rényi entropies under unitaries with bounded operator Schmidt rank.

Cooperative behavior can improve environmental quality, whereas selfish defection can degrade shared resources. In a recent agent-based study of the Aksum civilization (Vasellini et al., 2025), a population of agents moving over a reconstructed landscape and playing a local Public Goods Game grew faster and peaked higher when the game was enabled, but settled, in the long run, at the same population level as when it was not. Here we show that this behavior does not depend on the many rules of that model. We develop a theoretical ecological model of three coupled discrete-time equations, in which two sub-populations grow logistically and share a carrying capacity that rises when cooperators are sufficiently numerous and decays otherwise. Without fitting any parameter to the simulation, the equations reproduce its qualitative behavior: an initial boom, damped oscillations, and stabilization; a higher peak when the cooperative mechanism is active; and a final equilibrium that does not depend on it. Cooperation can be self-sustained for a transient period, but in the absence of measures that mitigate free-riding it collapses, and the environmental gains it produced are lost with it.

Accurate prediction of the electronic properties of extended $\pi$-conjugated systems with radical character remains a major theoretical challenge. To overcome this challenge, thermally-assisted-occupation density functional theory (TAO-DFT) has been developed in recent years. In this study, we employ TAO-DFT to systematically explore the electronic properties of ladder-type phenylenes ($n$-LPs), containing $n$ linearly fused four-membered carbon rings. Our calculations reveal that all investigated $n$-LPs (with $n$ = 1 ~ 40) possess singlet ground states. With increasing $n$-LP length, we observe a transition from the nonradical character of shorter $n$-LPs to the polyradical character of longer $n$-LPs. Notably, we identify a distinct damped periodic oscillation in the radical character of $n$-LPs, featuring highly correlated hotspots at specific lengths ($n = 3k - 1$, where $k$ are positive integers). The real-space representation of active orbitals confirms this global electronic behavior is governed by the intrinsic structural periodicity and completely delocalized nature of the active orbitals along the central ladder framework. These findings provide fundamental insights into the size-dependent electronic properties of $n$-LPs, guiding their rational design for future nanomaterial applications.

This work is devoted to a theoretical study of the interaction of a quantum three-level ladder system with a continuous electromagnetic field in a one-dimensional open waveguide. We consider a situation closely resembling stimulated emission - the scattering of a single-photon exponential pulse by an excited three-level emitter. Using the real-space formalism, we obtain an analytical expression for the wavefunction of our system. We show that, for the low anharmonicity of a three-level system inherent to a transmon (the most common type of artificial atom), the influence of the third level can have a significant effect on the system's behavior. Namely, the presence of the third level largely suppresses the stimulated emission effect if the relative anharmonicity is lower than $| \alpha_r | < 4\%$. However, for a three-level system, it is possible to obtain correlation effects such as photon bunching in the reflected field, which can also be 'switched off' by tuning the incident photon parameters.

Characterizing intermediate quantum chaos in systems with mixed phase spaces requires probing spectral correlations across multiple scales. Here, we present a multi-scale statistical analysis of the resonance spectra of ultracold 166Er and 168Er atoms using higher-order spacing ratios, spacing increments, and the accumulated power spectral density of decimated level sequences. Our analysis reveals that while the spectra exhibit clear level repulsion, they are consistently better described by semi-Poisson than by standard Wigner-Dyson ensembles, with this intermediate character persisting across higher-order correlations. The accumulated power spectrum reveals an intermediate 1/f^alpha regime, with alpha approximately 1.5 at full spectral resolution and a tendency toward the integrable random-walk limit alpha = 2 at intermediate decimation scales, indicating a scale-dependent loss of spectral rigidity. Furthermore, the spacing-increment distributions independently reveal statistics intermediate between Laplace and Gaussian limits. Together, these complementary diagnostics show that the semi-Poisson character reflects persistent non-Wigner-Dyson correlations beyond the nearest-neighbor scale, providing a consistent picture of intermediate quantum chaos and a possible connection to hierarchical trapping in the underlying collision dynamics.

Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models across nowcasting, medium-range, and subseasonal-to-seasonal lead times, producing well-calibrated ensemble forecasts at reduced cost. We review these advances and consider their extension to climate horizons, where the challenge shifts from initial-condition skill to producing reliable statistical responses under altered forcings. AI-powered climate prediction systems must produce credible forced responses to drivers (e.g., greenhouse gases, land-use change) typically outside the observed record. We propose two minimum requirements for AI in climate modeling: (i) external forcing agents must enter explicitly enough to support interventions in which they vary independently; and (ii) robustness must be stress-tested in out-of-distribution regimes, including extremes and counterfactual trajectories. Using leading AI autoregressive emulators and hybrid physics-AI models, we identify development and coupling challenges. Comparing the reported throughput of these models with that of GPU-ported dynamical models highlights how AI can reduce time-to-solution by advancing only the target variables at the required resolution and using longer time steps, rather than integrating a full high-frequency, multivariate state. Diverse AI downscaling strategies can partially substitute for explicit fine-scale resolution, paving the way toward inexpensive local hazard assessment across prediction horizons.

The increasing diversity of high performance computing systems makes separate, architecture specific implementations of lattice gauge theory algorithms costly to maintain. We present kwqft, a performance portable Kokkos implementation of Wilson pure gauge Monte Carlo simulation for $\mathrm{SU}(N)$ Yang-Mills theory in an arbitrary number of space-time dimensions. The gauge group order $N$ and the dimension $D$ are compile time parameters. A single source targets the Serial, OpenMP, CUDA, HIP, and SYCL execution spaces, with MPI halo exchange overlapped with interior updates. The implementation reproduces the exact two-dimensional plaquette and published three and four dimensional values for gauge groups up to $\mathrm{SU}(17)$. On an NVIDIA A100 the Kokkos CUDA backend is competitive with a native CUDA code, SIMD acceleration improves the OpenMP path on Armv9 processors, and a large scale speedup is demonstrated for an $\mathrm{SU}(4)$ lattice on the LineShine supercomputer, currently ranked first on the TOP500 list.

A nuclear recoil measures dark matter (DM) scattering on nucleons, but usually cannot reveal the nature of the halo DM. An interchange of the ground and excited states of the DM can preserve an inelastic recoil spectrum while changing ground-state annihilation by several orders of magnitude. Solar neutrinos can then provide information that nuclear recoils leave unresolved. Motivated by the high-energy LUX-ZEPLIN candidate, we investigate a possible way to resolve the composition of singlino-Higgsino DM in the next-to-minimal supersymmetric standard model (NMSSM) by using nuclear recoils and solar neutrinos. Our analysis identifies solar-compatible singlino ground states and Higgsino ground states with weak inelastic transitions, whereas Higgsino-pair inelastic LZ fits predict excessive solar signals. An elastic Higgsino scattering alternative can suppress solar capture by closing the inelastic transition. Recoil spectra, solar evolution and target complementarity can therefore probe distinct aspects of the singlino-Higgsino DM composition, with residual degeneracies set by annihilation, halo and detector assumptions.

We study Standard Model Effective Field Theory (SMEFT) extensions in portal-mediated scattering processes from the perspective of quantum entanglement. Quantum information metrics maintain phase-sensitive spin and momentum correlations, whereas conventional collider and direct detection observables mainly depend on unpolarized cross-sections and event rates, which often suppress dimension-six interference terms or average over internal degrees of freedom. We assess linear and Von Neumann entropy fluctuations induced by higher-dimensional operator insertions by building final-state density matrices using helicity amplitudes. By avoiding conventional kinematic degeneracies, our formulation shows that entanglement measures capture interference contributions linearly in $1/\Lambda^2$, offering improved sensitivity to new physics scales. A theoretical framework for SMEFT Wilson coefficients is established by this information-theoretic method, creating new opportunities for accurate tests of fundamental interactions in high-energy and astroparticle physics.

We present an automated method for reducing fault-tolerant circuits through fault-equivalent rewrites. Starting from a known fault-tolerant circuit, the search applies non-reducing enabling rules to expose Bell-pair reductions, each of which removes an ancilla preparation and a CNOT gate. Because every search transition preserves fault equivalence, the resulting circuits inherit the fault-tolerance properties of the input circuit. Candidate circuits are evaluated using circuit-level Monte Carlo simulation. For Shor-style syndrome extraction with the $[[7,1,3]]$ code, our method reduces one syndrome-measurement round from 30 to 18 ancilla preparations and from 54 to 42 CNOT gates. At a physical two-qubit error rate of $p = 10^{-3}$, the optimized circuit lowers the logical error rate by approximately 21% for both logical basis states. The reduction ranges from 13% to 23% over a range of $p$ spanning two orders of magnitude. We also apply the method to Steane-based dynamic syndrome extraction constructed from Goto's verified logical-$\lvert 0 \rangle$ preparation, in which the verification qubit serves as a flag. The search selects a circuit using four ancillas and 14 CNOT gates, matching the resource counts of the previous design but with an improved CNOT depth. Under depolarizing idle noise at $3p/10$ the selected circuit lowers the logical error rate by approximately 15% for both logical basis states, and by approximately 10% at $p/10$. These results demonstrate that automated fault-equivalent rewriting can identify circuits with lower resource costs or improved logical performance without separately verifying the fault tolerance of every candidate.

Cosmic birefringence, the rotation of the polarization plane of CMB photons, provides an intriguing probe of physics beyond the Standard Model. In this paper, we investigate a vector Chern-Simons coupling between the neutrino current and photons as a possible origin of isotropic cosmic birefringence. Firstly, we perform the first analysis of anisotropic cosmic birefringence induced by the neutrino current. We find that the anisotropic signal sourced by lepton-number isocurvature fluctuations can be important on large scales, whereas on small scales, the anisotropic signal induced by gravitational effects becomes dominant comparing with the axion-like particle (ALP) scenario. Secondly, we show that a large lepton asymmetry generated through the Affleck-Dine mechanism can successfully account for the observed isotropic birefringence, and discuss its possible connection to the recently reported low helium-4 abundances in Subaru EMPRESS and Atacama Cosmology Telescope (ACT).

Standard quantum mechanics takes the complex numbers as its scalar algebra. We ask whether this complex structure is algebraically fundamental or may instead form a distinguished embedded sector of a larger commutative and associative scalar algebra. Requiring the ordinary complex sector to remain intact while admitting an additional stable complex-like analytic sector turns the latter into a proper ideal, makes zero divisors unavoidable in finite dimension, and implies a lower bound of four real dimensions. The bicomplex algebra realizes this minimum, and under an additional compatibility assumption the four-dimensional realization is unique up to isomorphism. The resulting algebra exhibits two distinct decompositions: the canonical decomposition into orthogonal idempotent ideals and a decomposition adapted to the embedded complex sector and the additional ideal-valued sector. The ordinary complex scalars therefore lie diagonally across the canonical idempotent decomposition. The ideal sector supports Taylor series, oscillatory exponentials, Fourier-type kernels, and Schrödinger-type expressions, and carries a formal ideal-valued eigenvalue structure. Restricting the Born rule to the embedded complex sector recovers its standard form. Whether this dual scalar architecture has physical significance beyond the algebraic framework remains an open question.

Multimode entangled states of light are key resources for high-dimensional photonic quantum technologies, particularly for continuous-variable quantum computing and quantum information processing. Exploiting their full capabilities requires detection strategies that can efficiently and simultaneously access a large number of modes and their quantum correlations. Multimode optical parametric amplification (MOPA) provides a promising approach by amplifying multiple quadratures prior to detection, rendering the measurement robust against subsequent optical losses while enabling broadband operation. Here, we demonstrate the spectral multimode capability of MOPA by simultaneously characterizing a broadband 60-node dual-rail continuous-variable cluster state. We reconstruct the cluster-state nullifiers across the spectral modes and observe nearly uniform squeezing ranging from -7.2 to -6.5 dB. Furthermore, by evaluating the van Loock-Furusawa criterion across all relevant bipartitions, we verify genuine multipartite entanglement throughout the 60-node state. These results establish MOPA as a promising platform for scalable high-dimensional quantum information processing in the spectral domain.

Using the recently published global census of the biomass of wild terrestrial mammals, we perform a detailed mathematical statistical analysis of its distribution over $N_s=4795$ species, drawing on tools developed in economics to characterize wealth inequality. We show that the Lorenz curve of the mammal biomass distribution is characterized by a large Gini coefficient $G=0.944$ exceeding the inequality reported for wealth distribution among world countries. This distribution is compared to the predictions of the Wealth Thermalization Hypothesis (WTH), in which species biomass values are treated as energy levels populated according to a Rayleigh-Jeans (RJ) steady-state distribution. We show that an RJ extended spectral model reproduces the real Lorenz and Pareto curves over four orders of magnitude of biomass variation, capturing the strong condensation of biomass among the rare, heavy-bodied species and its near-absence among the vast majority of light-bodied ones. These results extend the WTH framework, previously validated on distributions of human economic origin, to a biological distribution shaped by ecological and evolutionary constraints, and place the extreme rarity of large-bodied mammal species within the same statistical mathematical description as the oligarchic concentration of wealth in human societies. We finally discuss possible ecological mechanisms that may contribute to the observed distribution, including interspecific interactions, food availability, and competition.

The Tibet AS$\gamma$ experiment observes cosmic gamma rays from several teraelectron volts to the petaelectron volt range using an array of ground-based surface air-shower detectors (Tibet-III), which is composed of plastic scintillators. The arrival direction is conventionally reconstructed by fitting the shower front to detector hit-timing data, and the resulting angular resolution is approximately 0.5$^\circ$ to 0.2$^\circ$ in the energy range from 10 to 100 TeV. In this study, to further improve the directional reconstruction accuracy, we developed a new arrival-direction reconstruction method that integrates a convolutional neural network (CNN) with the conventional method. Evaluations using gamma-ray events generated by Monte Carlo simulations show that the angular resolution is improved by approximately 10\,%–15\,% compared with that achieved with the conventional method. In addition, this performance improvement shows little dependence on the zenith angle up to 40$^\circ$. The proposed method provides a performance gain equivalent to increasing the Tibet-III array, which consists of approximately 600 detectors, by roughly 150 to 200 detectors.

We prove global rigidity of smooth asymptotically flat stationary vacuum black holes with sufficiently small ADM angular momentum, under global regularity, bifurcation, and maximal-hypersurface assumptions, with a threshold depending on fixed geometric bounds. This answers the question of Alexakis, Ionescu, and Klainerman concerning replacement of their smallness assumption on the stationary field at the bifurcation sphere by smallness of the angular momentum at infinity. The main step establishes Kerr rigidity near infinity for arbitrary angular momentum. We transform the vacuum metric into an Einstein–Maxwell family and compare null focusing at its limiting end with the area–charge inequality on compact maximal hypersurfaces, constructed by continuation through the family. Equality determines both the transformed metric and its stationary field, from which the inverse transformation recovers Kerr. Two Kerr identities then give the horizon estimate required for the global conclusion.

The non-collinear antiferromagnet (AFM), Mn3Sn, exhibits ultrafast spin dynamics and negligible stray fields, making it a promising candidate for fast and energy-efficient spintronic devices. However, its practical applications remain limited by the relatively small Hall response compared with ferromagnets. Here, we demonstrate through both first-principles calculations and experiments that Cr-doping is a promising strategy to enhance the anomalous Hall transport in Mn3Sn without breaking the antiferromagnetic order. Our first-principles calculations reveal an effective Cr-doping window that enhances the anomalous Hall conductivity while largely preserving the host coplanar inverse triangular AFM order. Berry curvature and Wannier Hamiltonian analyses further reveal that Cr substitution amplifies the pre-existing Berry curvature hotspots through coordinated changes in the energy alignment, local interband gap, and Mn-derived orbital weight of the relevant bands. Experimentally, we have found that Cr doping not only supports our computational predictions (enhancement of the anomalous Hall conductivity), but also suppresses the transition to helical or spin-glass phases at low temperatures. These findings demonstrate that Cr-doping is an effective strategy for stabilizing the AFM order while simultaneously improving the anomalous Hall transport properties over a wide temperature range in Mn3Sn.

In this work, we have systematically investigated the structural stability, electronic properties, and photocatalytic performance of the 2D h-Be3N2 monolayer for water splitting application, utilizing a first-principles density functional theory. Electronic structure calculations based on the PBE functional reveal that h-Be3N2 is a direct band-gap semiconductor with a band gap value of 1.74 eV, making it well suited for visible-light-driven photocatalysis. Furthermore, the alignment of band-edges illustrates that h-Be3N2 has suitable redox potential that facilitate overall photocatalytic water splitting in neutral and alkaline environment. Conversely, in acidic condition, the position of valence band is an adequate to enable the OER, thereby leading to photocathodic behavior. At neutral pH, the HER process is still possible with the application of an external potential of 0.77 V. For the OER process, it is thermodynamically favourable only under strongly alkaline conditions, while an external potential of 0.43 V is needed to promote the reaction at neutral pH. These results clearly underscore the significant impact of solution pH and photogenerated charge carriers on the photocatalytic effectiveness of the h-Be3N2 monolayer. Furthermore, the study of H coverage indicates that the amount of H that adheres to the surface has a considerable impact on the efficiency of the HER in h-Be3N2. The favourable photocatalytic capabilities of the h-Be3N2 monolayer imply that it might be a viable option for upcoming solar-powered green hydrogen generation and may assist in realizing the goals of the National Green Hydrogen Mission by facilitating effective and sustainable hydrogen production.

Quantum kernel methods are leading candidates for a practical quantum advantage in machine learning, but assessing that potential requires two quantities usually reported separately: how well a kernel performs on the task, and how far its geometry departs from the classical kernels available for the same problem. We introduce a fully unsupervised, multi-objective protocol that optimises simultaneously the normalised pseudo discrepancy (NPD), a label-free proxy for anomaly detection quality, and the geometric difference (GD) to a tuned classical reference kernel, selecting models from the resulting Pareto front. We apply it to malware beaconing detection in real network traffic, using a one-class support vector machine with fidelity and projected quantum kernels over four data encodings, on simulators and on IQM's 20-qubit Garnet processor. NPD-guided selection alone finds a fidelity kernel that beats the tuned classical baseline, but with a geometric difference too small to certify the gain as quantum. Projected kernels reach far larger geometric differences; the Pareto-selected one only marginally exceeds the baseline (AUC $0.782$ versus $0.765$, $g_{C\to Q}\approx 89>\sqrt{N}$ relative to that reference kernel), still below the NPD-selected fidelity kernel ($0.840$).

Quantum emitters in hexagonal boron nitride (hBN) are promising building blocks for solid-state quantum photonics because of their bright room-temperature emission. These emitters strongly interact with lattice vibrations, which partially underpins their excitation efficiency. Here, using complementary cathodoluminescence (CL) and photoluminescence (PL) spectroscopy, we demonstrate cavity-mediated interactions between hBN quantum emitters coupled to the same plasmonic Au void cavity at the room temperature. Cathodoluminescence measurements reveal that a vibronic transition of the 443 nm emitter hybridizes with the cavity mode, giving rise to a spectrally resolved splitting, while the neighboring 537 nm emitter remains in the weak-coupling regime despite spectral overlap. The energy split of the CL peak is at the order of 36.2 meV, whereas the PL-resolved peak is approximately 24.1 meV, which is due to the collective excitations of multiple emitters per electron excitation and their mutual interactions. Maxwell-Bloch simulations reproduce the experimental spectra and identify the observed splitting as the result of cavity-induced hybridization. Excitation-dependent PL further shows that the hybridized state can be accessed through phonon-assisted excitations below the zero-phonon transition. These results demonstrate that vibronic transitions provide an effective pathway for controlling interactions between multiple quantum emitters in hybrid plasmonic nanophotonic systems.

We introduce EC-EarthFlow, a generative flow matching model that emulates simulations from the physical climate model EC-Earth3. The model is trained on transient simulations from EC-Earth3 (1950-2166, SSP2-4.5) to predict the day ahead temperature field from the previous days temperature as well as annual mean temperature. Predictions are made auto-regressively with rollout periods of between a month and an extended season. Using only this variable of interest, we are able to reproduce the daily variability, spatial patterns, annual cycle and long-term trend from EC-Earth3 at a substantially lower computational cost than the physical model. We demonstrate that EC-EarthFlow is stable for long inference periods, and that it can learn the physical relationships as simulated in EC-Earth3.

The organization of interfacial water shapes the electric double layer behavior in aqueous electrolytes. Asymmetries upon charge reversal are commonly attributed to specific ion adsorption or surface chemistry. Yet it is unresolved whether interfacial water is net oriented at zero charge, and whether such orientation alone makes its response charge-asymmetric. Here, using electrochemical heterodyne-detected sum-frequency generation spectroscopy and constant-potential molecular dynamics simulations, we resolve the absolute orientation of water at a weakly interacting graphene electrode. We show that interfacial water retains a net H-down orientation, with hydrogens pointing toward the bulk, at zero net surface charge. Superimposed on this offset, the field-induced reorientation is linear and symmetric upon charge reversal, independent of how the charge is introduced or distributed. The zero-charge offset therefore shifts the potential of zero water orientation negatively relative to the potential of zero charge, making the interfacial water response intrinsically charge-asymmetric. These results establish an electrostatic baseline against which extrinsic contributions at electrified interfaces can be isolated.

Variational two-particle reduced-density-matrix methods impose hierarchies of semidefinite constraints. We ask whether a fixed level of such a hierarchy can recover even an elementary many-fermion spectrum, using the dispersion test, in which a value is accepted as an eigenvalue when the minimized dispersion vanishes. For an exactly solvable operator that counts fermions in one half of the spin orbitals, whose spectrum consists of integers, we determine the complete set of accepted values at every level of the full hierarchy of particle-hole semidefinite constraints. Besides the integers, this set contains an entire interval of noninteger values unless the hierarchy level grows linearly with the particle number, and we give the exact threshold. The proof constructs explicit pseudo reduced density matrices that are diagonal in the occupation basis, obtained by continuing the occupation probabilities of a fixed-particle-number state to a noninteger particle number. Classical semidefinite constraints on occupation correlations, supplemented by nonnegative occupation-pattern probabilities, suffice to establish fermionic positivity. For this counting model the two relaxations have the same dispersion zero set, not necessarily the same feasible states, and a converse argument shows that no other false eigenvalues occur. The limitation is specific to the hierarchy: two-body inequalities that encode the integer spectrum would remove every false value but are not generated at a fixed level. We also verify that the full semidefinite constraints and their complete projection onto two-particle reduced-density-matrix space are equivalent in finite dimensions, so that the result applies equally to the polar formulation.

Simulations of water at solid interfaces routinely disagree on basic properties, from contact angle to friction, depending on the model used, whether an empirical force field or a density functional theory (DFT) exchange-correlation (XC) approximation. Yet no accurate computational reference has been available to determine which, if any, is reliable. Here we assess XC approximations spanning the rungs of Jacob's Ladder against the random-phase approximation (RPA) at the graphene-water interface. Using machine-learned potentials (MLPs) trained on both DFT and RPA data, we achieve the extensive sampling required to characterize interfacial structure, wettability, friction, and vibrational sum-frequency generation spectra. We find that XC approximations disagree substantially with RPA and with each other. To make sense of this, we introduce a transferable, multi-observable scoring framework that distills each functional's agreement with RPA into a single measure. Six functionals emerge as reliable starting points for studies of graphene-water and other dispersion-dominated interfaces, namely B3LYP-D3(0), revPBE-D3(0), revPBE-D3(BJ), B97M-rV, r$^{2}$SCAN, and revPBE0-D3(0). Notably, this ranking follows no simple rule based on functional family or rung of Jacob's Ladder. What does hold across functionals is that dynamical and spectroscopic properties tend to be harder for DFT to reproduce than structural ones, with direct consequences for functional selection. Our framework also offers a general strategy for benchmarking any atomistic model, including the new generation of foundational MLPs, against high-accuracy references at solid–liquid interfaces. Beyond simulation, this work identifies which models can be trusted to connect measured contact angles, friction, and vibrational spectra to the molecular structure behind them.

We present initial-state corrections to $e^+\,e^-\to\mu^+\,\mu^-\,\gamma$ at next-to-next-to-leading-order in QED for several experimentally motivated scenarios up to a few GeV. We include photonic as well as vacuum-polarisation corrections into the Monte Carlo framework McMule that allows for the calculation of arbitrary infrared-safe observables. For the total cross sections, the corrections are typically below the percent level, but they can be locally larger in distributions. The vacuum-polarisation corrections are of similar size and must not be neglected, in particular for larger centre-of-mass energies.