Papers

Scalable quantum computing is limited by the dense network of electrical interconnects linking cryogenic quantum processors to room-temperature control electronics. To overcome this bottleneck, considerable effort has focused on cryogenic CMOS electronics and microwave-to-optical transduction, aiming to reduce wiring complexity and thermal loading. Wireless interconnects have recently emerged as a promising complementary approach, yet their compatibility with superconducting quantum hardware remains largely unexplored. Here, we demonstrate the wireless excitation of a superconducting microwave resonator of the type routinely employed for qubit readout, operating at millikelvin temperatures inside a dilution refrigerator. By directly comparing wired and wireless operation within the same cryogenic environment, we show that wireless coupling preserves the intrinsic resonator response while revealing parasitic electromagnetic pathways arising from stray radiation within the cryostat enclosure. These results establish a framework for the co-design of wireless interconnects, cryogenic packaging and superconducting quantum hardware.

In this work, we numerically studied the cooling process of a Fermi–Pasta–Ulam system, which occurs when the FPU system is placed in contact with a gas whose temperature $T$ is reduced with a certain cooling rate $\xi$. It was found that the existence of a weak stochastic threshold has a significant impact on the cooling process, because below such a stochastic threshold the specific FPU energy is larger than its temperature, i.e., the FPU system falls out of equilibrium. The difference remains finite in the limit $T \to 0$, so that the FPU system maintains a residual amount of energy $E_0$ at vanishing temperature. Our numerical simulations reveal that this energy exhibits a power–law dependence on both the system size and the cooling rate, scaling approximately as $E_{0} \sim (\xi N)^{2/3}$.

The field of quantum machine learning (QML) evolved to value models believed to most directly rival those providing utility in classical ML, namely large-scale neural networks. This pursuit of quantum neural-network analogues has produced important theoretical insights for expressivity and trainability at scale; however, due to our inability to conduct large-scale empirical studies, this direction has contributed to skepticism that QML will provide a compelling application for quantum computers. In the meantime, classical ML has been learning a hard lesson with respect to deploying un-interpretable neural networks in the wild: model interpretability matters for human adoption. We adopt this broader ML perspective to encourage a research direction in QML that prioritizes discovering and understanding tools from quantum information theory that applied ML researchers can use to construct inherently interpretable models: models with intentional mathematical structure that guarantees domain-aligned behavior. We first exemplify this research direction through a thread of work in a neighboring area—Bayesian ML. Specifically, we discuss an efficient mathematical tool that emerged from a connection between Gaussian processes and Bayesian linear models, which has since been widely studied and used by applied researchers for problem-specific model design. We then discuss how prior QML research can be reframed as progress towards this direction, despite having been pursued with different goals in mind. Finally, we propose an initial sketch of future work in this direction, with the broader aim of better supporting the needs of applied ML researchers.

In this work we formulate a horizon-microstructure description of four-dimensional AdS black holes in which a horizon of area $A$ is resolved into $\mathcal{N}=A/a_p$ microscopic sites and $N$ occupied horizon sites. The central result is that the combinatorics of this partially occupied horizon sector yields the entropy directly: in the finite-filling regime the leading term is proportional to the area, and the maximal-entropy filling reproduces the Bekenstein–Hawking law with $a_p=4\ln 2\ \ell_{p}^{2}$. Subleading corrections include a subtractive logarithmic term and an inverse-area expansion. We then show that this partially occupied regime admits a thermodynamic justification from an extended first law with chemical potential $\mu$, a Smarr-consistent excitation enthalpy $\delta M(A,P,N)$, and an AdS control parameter $u=PS$. In this interpretation, the combinatorics provides the dominant horizon entropy, while the thermodynamic sector supplies a dressing that selects the equilibrium filling and assigns a finite excitation cost to departures from a reference partially occupied configuration.

The Elliptic Curve Discrete Logarithm Problem (ECDLP) is a fundamental problem in cryptography, and reducing the resource requirements of quantum algorithms for solving ECDLP is an important goal. In this work, we present a space-efficient quantum algorithm for solving the ECDLP over prime fields, achieving an implementation with only $3n+6\lfloor \log_2 n \rfloor+O(1)$ logical qubits and $1056n^3/\log_2 n+O(n^2)$ Toffoli gates, where $n$ is the bit-length of the prime. For a 256-bit prime-field curve, our construction requires only 835 logical qubits, reducing the previous best estimates of 1098 and 1175 logical qubits by Chevignard et al. [EUROCRYPT 2026] and Babbush et al. [ArXiv Preprint 2026], respectively. The key to our improvement is a new space-efficient reversible modular inversion circuit, which addresses the dominant space bottleneck in affine-coordinate point addition. Starting from the extended Euclidean algorithm (EEA), we refine the register-sharing technique of Proos and Zalka by introducing length registers and location-controlled arithmetic to compactly store and update intermediate variables. We further optimize the reversible update procedures and construct the corresponding controlled arithmetic circuits, resulting in a modular inversion circuit implemented by only $2n+6\lfloor \log_2 n \rfloor+O(1)$ logical qubits and $229n^2+O(n\log_2 n)$ Toffoli gates. This modular inversion circuit together with mid-circuit measurements and classical feed-forward operations provides a space-efficient controlled affine point-addition circuit and a complete implementation of Shor's algorithm for ECDLP.

The Markovian dynamics of open quantum many-body systems are typically governed by the Lindblad master equation, yet obtaining the reduced density matrix for bosonic and fermionic systems remains a formidable numerical challenge due to the exponential growth of the Hilbert space. Here, we introduce a computationally efficient framework for constructing the reduced density matrix by modeling the environment as a copy of the primary system with a monotonically decaying coupling that enforces unidirectional energy flow. Our method directly yields exact solutions that rigorously satisfy the Lindblad master equation for both bosonic and fermionic cases, bypassing the need for costly Liouvillian diagonalization. We validate our approach through applications to paradigmatic models, demonstrating accurate reproduction of dissipative dynamics across a broad parameter regime. This work provides a straightforward and powerful tool for simulating Markovian open-system evolution, with immediate applicability to quantum transport and control problems in many-body physics.

We study strongly correlated many-body states in alternating twisted trilayer and tetralayer MoTe$_{2}$. By sliding the top layer with respect to others and applying a perpendicular electric field, a variety of band structures can be realized. In many cases, the topmost hole band has unity Chern number and its quantum geometric properties can be tuned to some extent. Exact diagonalizations suggest that fractional Chern insulators are stabilized in certain parameter regimes but not in some regimes even when the band is topological. This contrast is attributed primarily to different quantum geometries as quantified by the trace condition. Our results demonstrate that sliding can serve as a useful knob for probing many-body states in moiré systems.

The production rates of $\Xi^{-}/\bar{\Xi}^{+}$ baryons in energy-ranked jets produced in $Z\to\text{hadrons}$ decays are measured using $3.2$ million hadronic $Z$ events recorded by the DELPHI experiment. Jets are reconstructed using the Durham algorithm with $y_{\text{cut}}=0.005$. Quark- and gluon-enriched jet samples are obtained by ranking the jet energies in three-jet events. The softest jet are found to produce fewer $\Xi^{-}/\bar{\Xi}^{+}$ and less energetic baryons than the other jets. The ratio of $\Xi^{-}/\bar{\Xi}^{+}$ production rates in gluon and quark jets, each normalized to the corresponding mean charged-particle multiplicity, is measured to be $1.21 \pm 0.18~\mathrm{(stat.)} \pm 0.26~\mathrm{(syst.)}$. The result is consistent with the JETSET expectation and the OPAL measurements of $K_S^0$ and $\Lambda$ productions in $Z$ decays. This study presents the first measurement of the gluon-to-quark production ratio for baryons containing two $s$ quarks, providing new insights into strange-quark production and hadronization. Future $e^{+}e^{-}$ colliders such as CEPC and FCCee will provide much larger $Z$-boson samples and will allow far more precise studies of the subject.

We demonstrate that the redox-sensitivity of mantle outgassing can trigger transient episodes of atmospheric re-inflation in highly irradiated and geochemically-reduced super-Earths, a mechanism we term reflation. Mantle redox governs the outgassing and speciation of CHONS volatiles, setting the background secondary atmospheric composition during extended photoevaporation at highly irradiated conditions. Using simulations of the coupled atmosphere-interior evolution of irradiated super-Earths, we illustrate that reduced mantles close to the iron-wustite buffer initially produce CO-dominated atmospheres. Hydrodynamic escape continuously removes volatiles while outgassing from the melt replenishes the atmosphere with H2, converted from H2O dissolved in the underlying magma ocean. This leads to a late-stage transition from C- to H-dominated gas that transiently re-inflates super-Earth atmospheres and decreases their bulk densities by up to $\sim$60$\%$ between several hundreds of Myr to Gyr after their formation, prior to complete atmospheric erosion by photoevaporation. In contrast, oxidised mantles, closer to Earth-like geochemistry, strongly buffer their atmospheric composition while exposed to hydrodynamic escape, producing monotonic radius deflation. Reflation events are triggered by geochemically-reduced mantles, intermediate escape efficiencies, high irradiation, and initial water inventories $\gtrsim$ 5 Earth oceans. This redox-dependent evolutionary divergence hinges on the sensitive feedback between interior and atmospheric evolution serving as a potential tracer of historical geochemical state. Population-level reflation signatures of close-in super-Earths may thus serve as tracers of interior geochemistry and formation conditions.

Schottky spectra provide key beam diagnostics, with betatron sidebands encoding the fractional tune. Reliable tune measurement is particularly important for third-order resonance slow extraction in compact medical proton synchrotrons, where low signal-to-noise ratios and limited frequency resolution can compromise conventional peak-detection and curve-fitting methods. This work develops two complementary tune estimators with a shared spectral front-end but different temporal representations. The classical estimator coherently pools motion-compensated spectra, detects the sideband using a multi-width matched-filter bank, and performs sub-bin estimation through local argmax and an adaptive MAD-gated centroid. The deep-learning estimator converts each spectrum into a tune-likelihood map using a convolutional neural network with FFT-based global convolutions, then propagates the posterior with a discrete two-dimensional (q,v) Bayesian tracker under a Gaussian motion model while also reporting posterior uncertainty. On a synthetic dynamic-tune benchmark, the deep-learning estimator outperforms published baselines across the operating range, while the classical estimator exceeds the latency-compensated baseline and requires neither training data nor GPU acceleration. On near-stationary SAPT beam data, both methods operate end-to-end, with the deep-learning model requiring no retraining. Median per-frame latency remains below 1 ms on commodity hardware, supporting real-time-capable tune measurement in compact medical synchrotrons.

In this work, we introduce a complementary optimization method for progressive and adaptive state search (COMPASS) based on biorthogonal adaptive recurrent neural quantum states. Our approach combines an adaptive autoregressive architecture with a biorthogonal variational Monte Carlo scheme as well as a complementary optimization scheme that alternates between energy and variance minimization. This enables the stable convergence to ground-state eigenpairs, while avoiding Markov chain sampling through exact autoregressive generation. We demonstrate that for parity-time(PT)-symmetric Hamiltonians, unconstrained complex ansatze can spontaneously break PT symmetry during optimization, even in the unbroken phase, leading to spurious imaginary energies. Real-valued ansatze, on the other hand, naturally constrain the optimization to the correct physical manifold. Conversely, for generic non-Hermitian (NH) Hamiltonians without symmetry protection and complex spectra, complex ansatze are essential for capturing complex ground-state properties. Our results establish that physically-informed ansatz selection is crucial for reliable NH simulations. By combining adaptive architectures, biorthogonal optimization, and symmetry-aware modeling, this framework enables a direct study of 1D and 2D NH many-body systems without Hermitian embeddings or adiabatic continuation. Applying this framework to systems with frustrated magnetism, we show that gap frustration provides a quantitative shield against NH spectral instability, with the frustration gap setting a critical threshold for PT-symmetry breaking. Also, complexifying the frustration coupling itself generates a new topologically nontrivial network of diabolic level crossings, controlled by the phase of the complex coupling, that has no Hermitian analog. We term this novel spectral topology in NH frustrated systems the diabolic ring.

Merging supermassive black holes (SMBHs) in low- and intermediate-mass galaxies are important sources for future millihertz gravitational-wave observatories such as LISA. Predicting the delay between galaxy coalescence and SMBH merger is therefore critical for modelling the observable SMBH merger population. Using the KETJU code, we perform 16 equal-mass galaxy merger simulations as part of the Resolving supermAssive Black hole Binaries In galacTic hydrodynamical Simulations (RABBITS) series to investigate SMBH binary evolution in galaxies with stellar masses below $M_{\star}\lesssim10^{10}\,{\rm M}_{\odot}$. We systematically vary the strength of stellar feedback by altering the supernova outflow velocity by a factor of $\sim4$, while still producing galaxies consistent with observed scaling relations. We find post-hardening SMBH merger time-scales spanning $\sim30$-$500\,{\rm Myr}$, with stronger stellar feedback producing systematically longer merger delays through its impact on the central stellar density of the merger remnants. Across our suite, merging time-scales vary by more than an order of magnitude, demonstrating that uncertainties in stellar feedback alone can translate into large uncertainties in SMBH merger delays. At the onset of hardening, the binary evolution remains consistent with stellar-dynamical hardening models based on the local stellar density and velocity dispersion near the binary sphere of influence. Using KETJU as a benchmark, we show that merging time-scales can be recovered with useful accuracy when these nuclear stellar properties are extrapolated from scales up to $\sim 100\,R_{\rm infl}$. These results provide a promising route for modelling SMBH mergers in cosmological simulations.

We present a framework for foliating any Pauli-based quantum error-correcting code over prime-dimensional qudits. For any such code, we obtain a qudit graph state that can be measured to perform fault-tolerant measurement-based quantum computing. Such a paradigm is of interest in platforms such as photonics, where measurement-based protocols are natural and high-dimensional states are readily available. We discuss several examples for arbitrary prime dimension $d$, such as the qudit toric code (stabilizer, CSS), the $d$-dimensional perfect $[[5,1,3]]$ code (stabilizer, non-CSS), and a straightforward $d$-dimensional generalization of the CSS honeycomb code (dynamical, CSS). Under a simple error model, we numerically calculate thresholds for the foliated qudit toric code and demonstrate that they are comparable to the non-foliated version.

We present jQMC, a Python-based computational package for ab initio Quantum Monte Carlo (QMC) simulations, designed for modern GPU-accelerated computing environments. jQMC implements two well-established QMC algorithms: Variational Monte Carlo (VMC) and the lattice-regularized variant of Diffusion Monte Carlo (LRDMC). The employed wave function is a Jastrow factor combined with the antisymmetrized geminal power with spin-singlet and spin-triplet pairings, which contains the single Slater determinant as its special lowest-rank case. The wave function can be initialized from external Hartree-Fock/Density Functional Theory calculations through the TREX-IO library (a common wave-function format across electronic-structure packages) and optimized by stochastic reconfiguration and linear-method energy minimization. One of the prominent features of jQMC is its use of JAX, which enables automatic differentiation for wave function optimization and atomic force calculations, and allows the main QMC algorithms to be Just-In-Time (JIT) compiled and portable across CPU and GPU. jQMC is vectorized over walkers at the top level of the QMC algorithms, providing efficient intra-GPU~(CPU) vectorization. The multi-GPU~(CPU) parallelization is also supported through MPI and JAX sharding. To assess the practical performance of this implementation, we benchmarked jQMC performance on NVIDIA GPUs (A100 and H100) and analyzed CUDA kernels. For the test cases analyzed here, with system sizes up to 160 electrons, the current version of jQMC is faster than TurboRVB, a Fortran90 code implementing the same algorithms and wave functions, once jQMC is run on GPUs. In terms of wall-time, the gain can reach an order of magnitude for VMC, while it is more moderate for LRDMC.

We present space-time lensing by synthetic accelerated interfaces in dispersive media. Frequency-dependent group velocities map spectral components of a pulse onto distinct trajectories in the longitudinal space-time plane, while an accelerated interface reshapes their frequencies through time-dependent Doppler shifts. We develop an inverse-design procedure for the interface trajectory that focuses a quasi-monochromatic wave packet at a prescribed space-time event for an arbitrary dispersion relation, then extend the construction to polychromatic pulses. In its time-reversed form, the operation collimates a broadband pulse into a narrow-band wave. Moreover, cascading the forward and reverse operations enables a broadband pulse to propagate through an otherwise dispersive channel in a spectrally compressed state before being refocused. Full-wave simulations validate the focusing construction and demonstrate dispersion suppression.

Recrystallization in disordered solids proceeds through a sequence of local structural rearrangements that are difficult to resolve using conventional diffraction analysis. In amorphous and partially ordered materials, subtle variations in diffuse scattering, short-range order, and defect-mediated symmetry emergence encode the pathways through which ordering initiates and propagates. Here, we introduce a latent space framework for mapping these pathways directly from in situ 4D-STEM diffraction data. A convolutional autoencoder provides a compact representation of structural motifs, and unsupervised clustering identifies recurring microstructural states, including amorphous, paracrystalline, crystalline, twinned, and hybrid intermediates. By tracking these states across temperature, we construct phase trajectory models that reveal the topology of the recrystallization landscape, including metastable basins, branching pathways, hybrid states, and temperature-dependent reorganizations of accessible states. Applied to ion irradiated GaAs, this approach uncovers two distinct recrystallization regimes separated by a transition near 250\textdegree{}C. At low temperature, recrystallization is growth-dominated and dominated by the persistence of amorphous and crystalline states. At high temperature, the transformation landscape reorganizes: hybrid and faulted states become metastable precursors to twinning, polycrystalline regions stabilize, and twinned structures emerge as dominant end states. The latent space representation also identifies amorphous patterns with weak symmetry signatures that precede recrystallization. This reveals structural precursors to ordering that are not captured by conventional descriptors give new insights into how recrystallization is initiated.

Supercritical CO$_2$ is a highly efficient solvent for the development of more environmentally benign chemical processes. It is crucial to predict its solvation properties – the solvation free energy and the solvation structure – both accurately and at low computational cost. We show here that classical density functional theory (cDFT) can reproduce the solvation properties obtained from conventional molecular simulations, while requiring a computational effort that is several orders of magnitude lower. This excellent agreement is achieved using a molecular cDFT formalism based on a density that depends on both the positions and orientations of CO$_2$ molecules in the vicinity of the solute. We further examine several levels of approximation for the excess free-energy functional in cDFT and demonstrate that the homogeneous reference fluid approximation is sufficient to recover the molecular dynamics (MD) benchmark results. These findings open the way to extending molecular cDFT to other thermodynamic conditions.

We study a nonlinear tensorial wave-Dirac system on $(1+3)$-dimensional asymptotically flat spacetimes as a semilinear model motivated by the Maxwell-Dirac and Einstein-Dirac systems. The purpose of this model is to isolate the interaction between the null geometry of antisymmetric tensor fields and the intrinsic first-order geometry of the Dirac equation while avoiding the derivative loss mechanism of the Einstein equations and the gauge structure of the Maxwell equations. Our analysis preserves the first-order nature of the Dirac equation throughout the nonlinear argument. The Dirac current provides the fundamental energy identity, while quantitative spacetime estimates are obtained from the wave equation arising from the squared Dirac operator. Combining these ingredients with integrated local energy decay estimates and $r^p$-weighted energy hierarchies, we establish a coupled energy method for the tensorial and spinorial components. A key observation is that the Clifford algebra is compatible with the null decomposition of antisymmetric tensor fields and excludes the most singular nonlinear interactions. As a consequence, we establish the global existence of small-data solutions together with quantitative weighted energy and decay estimates. Remarkably, combining the null structure with dyadic argument, weak decay such as $t^{-\frac12-\delta}$ is sufficient to obtain nonlinear stability of the system, in the spirit of \cite{DHRT}. We expect that the geometric ideas developed in this paper provide a useful starting point for the study of more general nonlinear Dirac systems, including the Maxwell-Dirac and Einstein-Dirac equations.

Gigena et al. [npj Quantum Inf. 11, 82 (2025)] proved the exact quantum maximum of the doubly-tilted CHSH functional $B_{\alpha\beta}=\alpha\langle A_0\rangle+\beta\langle B_0\rangle+\mathrm{CHSH}$ and observed that the NPA level required to reach it grows without evident bound toward the critical line $\alpha+\beta=2$. We quantify the mechanism on the symmetric slice $s=2-\alpha-\beta$: (i) the quantum value leaves the local bound cubically, $c_Q=4-s+s^3/6-s^4/36+O(s^5)$; (ii) each NPA level overshoots quadratically, $c_k(s)=4-s+a_k s^2+O(s^3)$, with the almost-quantum coefficient computed exactly, $a_{1+AB}=3/64$; (iii) the divergence of the required exact level is equivalent to positivity of the single sequence $(a_k)$ - proven for every $k$ in the companion paper. We prove the supercritical side completely: for all $\alpha,\beta\ge 1$ and every level the hierarchy is exact, via three explicit rational certificates realizing an affine identity. The hierarchy's exactness thus undergoes a phase transition at the critical line. On the subcritical side we certify the first four levels in exact arithmetic (rational pseudo-moments beating $c_Q$, confirmed by Sturm's theorem). We identify the exact mechanism: rescaled to the critical corner, the limiting obstruction is the Motzkin polynomial, the classical nonnegative-but-not-sum-of-squares form, so the finite-level failure sits in the restricted-certificate regime. The phase boundary has a precise geometric reading via Nie's finite-convergence theorem and Marshall's boundary Hessian condition: a self-tested optimum is finitely NPA-certifiable whenever its boundary Hessian is nondegenerate (contact order two), which holds for the single tilt and fails exactly at the doubly-tilted cubic touch. Three verified errata in the published polynomial system of Gigena et al. are documented.

We obtain a family of multihump-multivalley solitons (MHMVSs) on a plane-wave background in birefringent optical fibers governed by the two-component Fokas-Lenells equations, with exact solutions derived via the Darboux transformation method. The fundamental solutions are systematically classified through their phase diagrams, and higher-order configurations are identified as well. Notably, the construction extends to solitons with arbitrary MHMV structures, a class of solutions previously unreported in two-component integrable systems. Numerical simulations confirm the robustness of these solutions under weak white noise. Furthermore, analysis of their topological structure reveals that the virtual monopole field is determined equally by the intensity zeros and poles of MHMVSs in the complex plane, a feature that has remained unrecognized in previous studies of nonlinear wave topological phases. These findings reveal a previously unknown soliton family on a plane-wave background along with a distinct topological feature within the two-component framework, thereby enriching the broader understanding of topological phases of nonlinear waves.

G6096 (Gaia DR3 609651611028044544) was recently reported as a wide ($P\sim 450$ days) and eccentric ($e\sim0.18$) binary possibly hosting a massive white dwarf or neutron star. In this work, through analyses of the projected rotational velocity between the blue and red bands, spectral disentangling, joint radial velocity and astrometric fitting, and X-ray emission, we suggest that the system contains additional visible component(s) rather than a compact object. We develop a new approach to reveal the nature of G6096 by jointly modeling the spectral energy distribution, rotational velocity, and astrometric measurements. Finally, we speculate that G6096 is a hierarchical triple main-sequence star system, comprising a primary with a mass of $\sim 0.75\,M_\odot$ orbited by an inner binary consisting of two dwarfs with masses of $\sim 0.62\,M_\odot$ and $\sim 0.40\,M_\odot$, respectively. This method may help reveal a population of triple systems when applied to Gaia astrometric data, particularly the upcoming DR4.

We report a search for dark matter (DM) produced in association with a leptonically decaying \(Z\) boson at \(\sqrt{s}=13\) TeV using CMS Run 2015D open data corresponding to an integrated luminosity of \(2.32\,\mathrm{fb}^{-1}\) together with simplified-model Monte Carlo simulation. Events are selected in the mono-\(Z\rightarrow\ell^+\ell^-\) final state in both the \(\mu\mu\) and \(ee\) channels. Forty kinematic observables are extracted from MINIAOD and MINIAODSIM, cleaned with physics-motivated selections, and reduced to a 37-dimensional feature vector. Five Neural Spline Flows are trained independently to model Standard Model background and mediator-specific DM signal densities. The per-event test statistic is constructed from the log-likelihood ratio between the signal and background density estimates, providing sensitivity across the full kinematic phase space without requiring a hard upper \(\mathrm{MET}\) threshold. A simultaneous profile-likelihood fit combining the two channels yields observed (expected) 95% confidence level upper limits on the signal-strength parameter of \(\mu<0.0177\) (\(0.0018\)) for the scalar mediator, \(\mu<0.0362\) (\(0.0039\)) for the vector mediator, and \(\mu<0.0498\) (\(0.0069\)) for the axial-vector mediator. The observed limits are weaker than expected because of a residual high-\(\mathrm{MET}\) background-modeling discrepancy rather than evidence for a DM signal. To our knowledge, this is the first application of Neural Spline Flow likelihood-ratio scoring to a mono-\(Z\) dark matter search using CMS Run 2015D open data simultaneously in the \(\mu\mu\) and \(ee\) channels.

We investigate the single-particle momentum distribution, the two-body contact and three-body tail coefficients of mass-imbalanced three-body systems at the critical dimension $D_c$, where the transition between discrete and continuous scale invariance takes place as the spatial dimension is tuned between three and two dimensions. We show that the asymptotic momentum distribution at $D_c$ is governed by a distinct logarithmic scaling structure, which differs fundamentally from both the log-periodic behavior of Efimov states and the power-law scaling of the unatomic regime. This structure contains an additional quadratic-logarithmic contribution, characterized by the asymptotic coefficient $C_3''$, which leads to a finite and well-defined description of the momentum tail at the transition. The coefficient $C_3''$ depends sensitively on the mass imbalance, changing sign across different mass configurations and vanishing for identical particles. For heavy-light-light configurations, the subleading three-body term vanishes at a characteristic momentum, leaving the leading two-body contribution at the order retained in the asymptotic expansion. The physical accessibility of this cancellation depends on the separation between the trimer size and the interaction range. We further analyze the narrow intermediate region connecting the Efimov and unatomic regimes, here identified as an intermediate scaling regime, whose extent and properties are strongly controlled by the mass ratio. These results establish the critical dimension as a regime with emergent scaling properties and provide quantitative momentum-space signatures for probing the transition between discrete and continuous scale invariance in few-body quantum systems.

We formulate quantisation of gauge field theories on globally hyperbolic Lorentzian manifolds with marked hypersurfaces within the framework of perturbative algebraic quantum field theory (pAQFT) enriched by the Batalin, Fradkin, Vilkovisky formalism (BV/BFV). This allows one to incorporate some crucial aspects of the local functorial approach to gauge field theory on manifolds with boundary within the algebraic setting. In particular, we provide a pAQFT-formulation of the modified classical and quantum master equations (after Cattaneo, Mnev and Reshetikhin CMR), as well as a constructive way to build a renormalised quantum BFV operator correcting the failure of the Quantum Master Equation by means of boundary terms (in the appropriate sense). We find that the renormalised quantum homotopy dg Lie algebra arising from the Anomalous Master Ward Identity becomes curved when boundaries are considered. The failure of the quantum master equation is thus encoded by a nontrivial curvature term in an $L_\infty$ algebra. As a byproduct, we recover previous results of Hollands' on the relation between the (boundary) BRST charge and the BV operator, and we recover CMR's ansatz for the quantum BFV operator at leading perturbative order on causal cylinders in Abelian Yang–Mills theory.

Gigena, Panwar, Scala, Araujo, Farkas and Chaturvedi [npj Quantum Inf. 11, 82 (2025)] determined the quantum maximum of the doubly-tilted CHSH functionals, observed that the Navascues-Pironio-Acin level needed for exactness grows without evident bound toward the critical tilt, and asked whether any finite level suffices. We answer this in the negative. For the symmetric critical family $B_s=(1-s/2)(\langle A_0\rangle+\langle B_0\rangle)+\mathrm{CHSH}$ we prove: for every NPA level $k\ge 2$ there are an explicit rational $g_k>0$ and an $s^*_k>0$ with $c_k(s)\ge 4-s+g_k s^2$ on $(0,s^*_k]$; since the quantum value leaves the local bound only cubically, every finite level strictly overshoots on an interval: no finite level is exact on any neighbourhood of the critical point. Unconditionally $a_2>1/39$, $a_3>1/188$, $a_4>1/641$. The proof is a primal construction: an exactly feasible moment curve at each level, built from level-uniform structural laws and one level-independent signed witness – a closed-form class function $y^*$ with $N_k^T\Gamma(y^*)N_k=u_k u_k^T$ at every level. The mechanism forces the sign: for $k\ge 3$ no quantum state and no smooth curve of quantum models can realize the gain direction, so the overshoot lives strictly in the non-quantum part of the NPA tangent cone. The proof is computer-assisted in the strict sense: finite exact-integer verifications with proven degree bounds are constituent parts of the argument; the chain has been re-verified against independent implementations, including a symbolic per-regime proof of the witness identity and a clean-room implementation written from the paper text alone. The one external input is the published quantum value of Gigena et al., cross-checked to twelve digits.

Bound states of heavy quark-antiquark pairs, known as quarkonia, have long been regarded as particularly sensitive probes of the quark-gluon plasma (QGP). Comparing quarkonium yields in collisions of heavy nuclei, such as gold or lead, with a proton-proton (pp) reference reveals a characteristic pattern of sequential suppression, in which weakly-bound excited states are more strongly suppressed than the ground states. We report the first measurements of the three lowest mass $\mathrm{S}$-wave vector bottomonium resonances, the ground state $\Upsilon$(1S) and the excited states $\Upsilon$(2S) and $\Upsilon$(3S), in oxygen-oxygen collisions at a center-of-mass energy per nucleon pair of $\sqrt{s_\mathrm{NN}}$ = 5.36 TeV. Measurements of the yields of the $\Upsilon$(1S) and $\Upsilon$(2S) resonances in neon-neon collisions, at the same $\sqrt{s_\mathrm{NN}}$, are also presented. The $\Upsilon$(2S)/$\Upsilon$(1S) ratio is found to be significantly below the measured pp reference value, and the $\Upsilon$(3S)/$\Upsilon$(1S) ratio shows an even larger reduction. The significance of the relative $\Upsilon$(3S) to $\Upsilon$(2S) suppression exceeds three standard deviations. These results provide evidence for the sequential suppression of $\Upsilon$(nS) states in light ion collisions, similar to observations made in lead-lead and gold-gold collisions, generally attributed to the presence of a QGP medium.

Machine-learning interatomic potentials (MLIPs) have become a powerful tool for rare event sampling in molecular dynamics, offering near ab initio accuracy at a fraction of the computational cost. However, the uncertainty associated with these models remains a major challenge. Existing uncertainty quantification approaches have largely focused on point-wise quantities, such as energies and forces, or on equilibrium thermodynamic observables. In this work, we introduce a framework for propagating MLIP uncertainty to the averaged committor probability, a kinetic observable that enables reaction-rate calculations. Our approach combines rare event sampling methods such as Adaptive Multilevel Splitting with Girsanov reweighting to estimate the sensitivity of committor probabilities to variations in MLIP parameters, without requiring the costly resampling of reactive trajectories for each parameter realization. We derive exact and approximate Girsanov-based estimators for uncertainty propagation and validate them on several benchmark systems, including a rugged Muller-Brown potential, a dimer in a solvent, and the conformational transition of butane. The proposed framework enables the construction of uncertainty-aware probability distributions for rare event observables and successfully recovers reference rare event probabilities from uncertain surrogate models. Under mild assumptions on the accuracy of the MLIP within metastable basins, the framework can also provide uncertainty bounds on reaction rates through Hill's relation. These results demonstrate that path-space reweighting provides an efficient route for propagating MLIP uncertainty to rare event kinetics.

In this work, we consider the problem of computing a linear combination over a noiseless quantum many-to-one network. There are $k$ senders, Alice$_1$, $\ldots$, Alice$_k$, and a single receiver, Bob. Each Alice$_i$ has a data vector $W_i \in \mathbb{F}^{m_i}$, where $\mathbb{F}$ is a finite field. Bob wants to compute the linear combination $Y = V_1 W_1 + V_2 W_2 + \cdots + V_k W_k \in \mathbb{F}^m$, where $V_i$ is an $m \times m_i$ matrix over $\mathbb{F}$. The senders transmit quantum states to Bob through a noiseless many-to-one quantum network, but they are not allowed to communicate with each other. The senders share entanglement among themselves, while Bob does not share this entanglement. They encode their classical information $W_i$, $i=1,\ldots,k$, into their local subsystems and transmit them to Bob so that he can recover $Y$ through a quantum measurement and subsequent post-processing. The N-Sum Box protocol proposed by Allaix et al. (2025) considers this problem under certain constraints on the linear combination and the distribution of the data vectors among the senders. We present protocols that support the computation of a more general class of linear transformations by giving the senders access to more qudits and allowing them to judiciously precode their input symbols. The communication cost of our schemes is at most that of the best-known prior results in this area and is strictly lower in certain cases. Finally, we demonstrate that the communication cost is subadditive across instances. Specifically, we identify two linear functions for which the total cost of computing them individually is strictly larger than the cost of computing them jointly.

We investigate the production of high-energy neutrinos from microscopic black holes formed through the gravitational collapse of asymmetric dark matter accumulated inside neutron stars. When Hawking evaporation dominates over accretion, long-lived, feebly interacting particles beyond the Standard Model escape the neutron star and subsequently decay into high-energy neutrinos. We analyze the repeated cycle of dark matter capture, black hole formation, and evaporation, identifying two distinct regimes determined by the competition between the dark matter thermalization time and the collapse cycle. In particular, we identify a partially thermalized regime in which the dark matter cloud evolves toward a quasi-stationary state with a temperature significantly exceeding that of the neutron star core. We derive the time-integrated Hawking emission, the resulting secondary neutrino spectra, and the expected Galactic and diffuse extragalactic neutrino fluxes. The predicted signal exhibits two distinctive signatures: a broad neutrino spectrum with a characteristic energy scale set by the initial Hawking temperature of the evaporating black hole, whose spectral peak naturally lies above $\mathcal{O}(10)$ TeV, and an extended Galactic component strongly concentrated toward the Galactic Center. Although the predicted event rates are generally small, the resulting signal may contribute at the percent level to the observed Galactic high-energy neutrino flux under favorable microscopic and astrophysical conditions. The proposed mechanism provides a new observational window on Hawking evaporation through microscopic black holes continuously produced inside neutron stars, linking dark matter, compact objects, black hole thermodynamics and high-energy neutrino astronomy.

We review perturbative matching between the regularization-invariant symmetric MOM (RI/SMOM) and MS schemes at the symmetric subtraction point, which is relevant for lattice QCD simulations. For bilinear operators we summarize three-loop conversion factors for local quark currents and for the n=2,3 twist-two moments of structure functions. For three-quark operators we summarize two-loop RI/SMOM matching for N=0 baryonic operators and three-loop anomalous dimensions together with two-loop matching for the N=1 Mellin moment, enabling improved lattice studies of baryon distribution amplitudes. All numerical results quoted here are given in Landau gauge.