Papers

Higgsino dark matter remains one of the most convincing dark matter candidates. It can exist in a “quasi-Dirac" regime, when the splitting between two Majorana components is on the order of $O(\rm few~\,MeV)$ or less. Owing to the strong gravitational pull of the Sun, the DM particles accelerate to up to $\sim 1400$\,km/sec in the solar core, which allows for inelastic scattering on heavy elements and very effective capture onto solar-bound trajectories. We evaluate the expected flux of the neutrinos from the expected $\chi\chi \to W^+W^-,ZZ$ annihilation for the cosmologically preferred mass, $m_\chi \simeq 1.08$\,TeV while keeping the mass splitting $\delta$ as a free parameter. Confronting it with the non-observation of high-energy neutrinos from the Sun by the IceCube experiment, we obtain a robust limit, $\delta>566$\,keV. These limits exclude the interpretation of the recent LZ event in terms of endothermic inelastic scattering of Higgsino dark matter on xenon nuclei.

Altermagnetic materials exhibit spin splitting in their electronic band structures while maintaining zero net magnetization. However, conventional high-symmetry k-paths generally hide this splitting because they follow symmetry lines that in most cases enforce spin degeneracy. We present AlterSeeK-Path, an open-source Python tool that systematically constructs generalized band-structure paths for collinear altermagnets. The method selects the centroid of the conventional irreducible wedge used in routine band-structure calculations as the representative general k-point, maps it to a spin-flip-related partner, and inserts paired segments through these points into the standard high-symmetry path; these segments systematically sample the interior of the irreducible wedge. We demonstrate the construction for all 54 three-dimensional combinations of extended Bravais lattice type and spin Laue group across the six crystal systems that support collinear altermagnetism, and for the 12 two-dimensional cases spanning the four compatible two-dimensional Bravais lattices. Representative band structures are shown for the distinct lattice/path cases. With AlterSeeK-Path, these band structures can be constructed with essentially the same effort as conventional band structures.

Magnetic multipoles have attracted growing interest as order parameters and dynamical degrees of freedom in unconventional magnets, yet it remains unclear how broadly they can emerge as active electronic degrees of freedom. Here, we show that spin-orbit-entangled multiorbital states can host magnetic octupole (MO) degrees of freedom. In Rashba systems, this gives rise to an MO Rashba texture accompanying the J-Rashba texture. Remarkably, spin-orbital entanglement can realize a pure-MO limit in which the spin and orbital-angular-momentum textures vanish while the MO texture remains finite. An applied electric field converts this texture into a nonequilibrium MO polarization through an MO Rashba-Edelstein effect. Around the pure-MO regime, the MO Edelstein response dominates over the conventional spin response, showing that multipolar responses need not be small corrections to dipolar spin physics. Our results establish an interface-based route for electrically generating nonequilibrium multipolar magnetic polarization in spin-orbit-coupled systems.

In this work we demonstrate a novel approach to exhibit the unique spin splitting that is typical of collinear altermagnets. This approach is to plot band structures on Brillouin zone paths that sample general k-points to show a representative picture that corresponds to Brillouin zone averages. This is in contrast to conventional band structure plotting which plots band structures on the highest-symmetry points and lines, and thus in many cases can fail to show any altermagnetic spin splitting at all. Our investigation compares the new approach with the band structures of collinear altermagnets using conventional band structure plotting. We report the band structure and symmetry analysis for MnTe, CrSb, SmFeO3, ScCrO3, LaMnO3, TlCrO3, HoFeO3, InCrO3 and DyFeO3. This result clearly demonstrates the advantage of this novel method for displaying the spin splitting of collinear altermagnets.

Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text — and tables are arguably the format in which most physical measurement arrives. Did they learn any physics in the process? They are Bayesian by construction, so the question is what their prior contains. We probe it directly, evaluating four of them ($\texttt{TabPFN-3}$, $\texttt{TabICLv2}$, $\texttt{TabDPT}$ and $\texttt{Real-TabPFN-2.5}$) against six baselines on datasets sampled from 316 physical equations, in and out of domain. TFMs dominate, out of the box and after tuning. But they struggle to represent noiseless deterministic mechanisms in their uncertainty, and show no sign of exploiting physical units: they interpolate physics without yet being able to act as physical models.

Liquid interfaces are both ubiquitous and also critically important for many commercial products, modern technologies, biological processes, and environmental phenomena. The properties of these interfaces can depend quite sensitively upon the composition of the bulk liquid phase. In this work, we develop a dilute solution theory (DST) for the influence of dilute cosolutes upon the interface between coexisting liquid and vapor phases. We employ a grand canonical perturbation theory to rigorously relate the interfacial free energy to the concentration of the liquid solution. We leverage a corresponding Gibbs ensemble to treat liquid-vapor coexistence and to eliminate the contribution of the bulk phases from this free energy. We express the coefficients of the resulting expansion in terms of microscopic partition functions. By treating solute-solute interactions to lowest order, we distinguish between the intrinsic and effective interfacial preferences of solutes. While the former reflects only solute-solvent interactions, the latter depends upon the solution composition and reflects the influence of solute-solute interactions. We assess this DST with molecular dynamics simulations of binary and ternary mixtures of Lennard-Jones spheres. These simulations demonstrate that DST accurately models the interfacial properties of these systems up to relatively high concentrations. Moreover, the simulations illustrate the impact of attractive solute-solute interactions in converting weak intrinsic surfactants into weak effective depletants.

We compute the next-to-leading order (NLO) QCD corrections to the light hadron decays of fully charm tetraquarks within the nonrelativistic QCD (NRQCD) factorization framework. The short-distance coefficients for the $gg$ and $q\bar{q}$ final states from fully charm tetraquarks are obtained analytically. The NLO corrections are found to be significant, altering the LO predictions by about $170\%$ for the $0^{++}$ state and $30\%$ for the $2^{++}$ state. The resulting $\mathcal{R}_{\mathrm{LH}}$ values are of order $10^{-5}$ to $10^{-4}$ MeV, about three orders of magnitude larger than the diphoton channel, as expected for strong-interaction decays. Our results provide updated theoretical predictions for future experimental studies of fully charm tetraquark decays.

Magnetoelectric phase transitions have been experimentally studied, but no macroscopic theory has been proposed to explain their dynamical origin. In this work, we assume that the axion quasiparticle with frequency undergoes a condensation like process. We show that these magnetoelectric phase transitions can be described within a Ginzbur Landau framework by introducing a coupled dynamic parameter, the axion angle, which is proportional to the magnetoelectric coeffcient. We derive relations between the static axion angle, the axion frequency, and the phase transition temperature for different magnetoelectric materials, respectively, and compare these calculations with existing experimental results. We also connect the artificially designed Dzyaloshinskii Moriya interaction with the axion condensate like process, so that the relation between the static axion angle and the experimentally measured frequency shift can be obtained.

We present the results of a detailed simulation study of Higgs boson production via vector boson fusion (VBF) at the Large Hadron Collider (LHC) in the presence of anomalous couplings. The analysis utilizes the Herwig event generator interfaced with VBFNLO, employing a multi-jet merging scheme that combines NLO accurate matrix elements for Higgs plus 2- and 3-jet multiplicities with LO accurate matrix elements for Higgs plus 4-jet multiplicities. We investigate both matching and merging setups to consistently combine these hard scattering processes with QCD parton showers. Finally, we demonstrate the robustness of azimuthal angle observables against QCD radiative corrections across these frameworks.

Black holes of primordial or astrophysical origin immersed in axion dark matter provide a natural laboratory for exploring the interplay between compact objects and ultralight scalar fields. While previous studies have primarily focused on superradiance and horizon-scale phenomena, the gravitational response of the surrounding axion distribution has received comparatively little attention. We investigate the dynamics of particles orbiting Schwarzschild and Kerr primordial black holes embedded in scalar-field dark matter halos. Using first-order perturbation theory, we show that the ambient halo redistributes the gravitationally bound axion cloud, shifting the characteristic radius of the gravitational atom. Numerical integrations of timelike geodesics demonstrate that the maximum orbital response consistently occurs at this perturbed radius, establishing a direct correspondence between the microscopic structure of the axion wavefunction and the macroscopic dynamics of orbiting particles. Our results identify a new purely gravitational signature of scalar-field dark matter around primordial black holes and provide a framework for probing mixed axion–primordial black hole dark matter scenarios.

To make full use of the HL-LHC, especially in the search for BSM physics, all Standard Model backgrounds have to be understood with increased precision. This is especially difficult for Double Parton Interactions (DPIs) and more generally Multi Parton Interactions (MPIs), which are very difficult to isolate precisely in experiment. DPIs are parameterized by Double Parton Distributions (DPDs) and the lattice determination of the latter is, therefore, especially attractive. In our previous work on DPDs on the lattice, we focused on the results obtained from one gauge ensemble with higher than physical pion mass. In this work, we extend our efforts by investigating artifacts introduced by finite volume and the dependence on the lattice spacing. Moreover, we consider the dependence on the mass parameters. This study is carried out by employing the Wilson-Clover fermion gauge ensembles generated by the CLS collaboration.

Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made significant advances in materials discovery, the hierarchical structure of polymers across multiple length scales makes them inherently difficult to represent in a unified and physically meaningful way. Here we introduce HiPoly, a polymer-native AI framework that processes complete polymer descriptions through a three-level hierarchical graph architecture built on the G2RINS representation. HiPoly encodes stochastic inter-monomer connectivity, composition, and molecular weight directly within its architecture, using physically motivated design principles that mirror the multi-scale nature of polymeric systems. The framework establishes an end-to-end AI-driven workflow from experimental formulation data to property prediction, generative molecular design, and physics-based validation through molecular simulations, all unified by a single polymer representation. We demonstrate state-of-the-art prediction accuracy for thermophysical properties of multi-component polymer systems, with ablation studies confirming that each hierarchical design choice contributes independently to model performance. As an example, the generative design pathway is applied here to the discovery of sustainable alternatives to persistent fluorinated polymers, where it is possible to identify and independently validate PFAS-free candidates with target surface-energy properties. This work demonstrates how polymer-native AI can accelerate discovery by linking representation, prediction, and design across complex polymer chemistries.

Graphene-derivatives are widely employed materials to improve bulk and interface properties of metal-halide perovskite devices. Yet the implications of their flake chemistry and interactions with the perovskite precursors remain unclear. Here, we show that pristine graphene flakes (GF) and more conventional graphene oxide flakes (GOF) are not interchangeable. Density functional theory calculations reveal that GOF interacts more strongly with the perovskite lattice but induces larger structural distortions, stronger interfacial polarisation, and localised gap states. In contrast, GF forms comparatively non-disruptive contacts, a response retained across a wide compositional range. Machine-learning atomistic simulations further show that GF contacts both Pb- and I-containing regions of solvated perovskite nanocrystals, with a strong solvent dependency. Solution spectroscopic characterization indicates that GF additives serve as scaffold for preorganised Pb/I-containing precursors, favouring film crystallisation. In this sense, GF enhances solar cell performance across perovskite compositions, but particularly those facing a more challenging crystallisation. In mixed Sn-Pb perovskite solar cells, GF raises the champion power-conversion efficiency from 21.5% to 23.7% with improved storage stability. These results establish pristine GF as a chemically defined additive and connect its atomic-scale interactions with precursor organisation, crystallisation, device performance, and stability.

We study fixed-temperature logarithmic and Riesz gases after subtracting the leading mean-field contribution relative to a prescribed background law. For repulsive interactions in the Hilbert–Schmidt regime, we prove $N$-uniform bounds and quantitative convergence of the resulting modulated partition function to a normalization expressed by the Carleman–Fredholm determinant of the centered interaction operator. We show that the Hilbert–Schmidt threshold is sharp and obtain explicit lower bounds on the rate of divergence at and above it; these rates are expected to be nonoptimal. The proof combines positive-definite truncations and a low/high-frequency decomposition with exponential inequalities and Gaussian-chaos asymptotics for canonical degree-two $U$-statistics. As consequences, we establish entropic commutator estimates with the sharp $O(N^{-1})$ additive scale in the modulated-free-energy method, a static joint linear-statistics central limit theorem, and a dynamical central limit theorem for joint linear statistics at finitely many times. This extends the logarithmic partition-function estimates of the first two authors to the full Riesz Hilbert–Schmidt range and identifies the limiting determinant normalization. For the attractive logarithmic interaction at sufficiently small inverse temperature, we also prove analogous results.

For fifty years the Blandford–Znajek mechanism has been a mechanism and not an exact solution: force-free electrodynamics on a prescribed metric, with the jet's own field carrying no weight. Here that field gravitates. A split monopole weighs as much as a magnetic monopole, so its self-gravity is the magnetic Reissner–Nordström geometry; two copies glued across an equatorial current sheet put hole, disk and jet-driving flux into one spacetime, and force-free plasma makes a magnetosphere of it. Three things then follow that no test-field calculation can see. First, a steady jet is impossible. A stationary horizon cannot be heated but a slipping magnetosphere necessarily heats it, so the only stationary state is a dead one corotating with the hole, and a working jet is a black hole in decay at rates the field equations fix rather than assume. Second, flux enters the laws of black-hole mechanics as a charge, sharing one extremality budget with spin. That budget caps the jet power at $c^5/48G$ whatever the mass. Third, the lifetime output is finite: a maximally spinning hole delivers $1-e^{1/4}/\sqrt2=9.2\%$ of its mass and grows its horizon area by exactly $\sqrt e$. The horizon's own moment of inertia vanishes with the irrational exponent $(\sqrt{17}-1)/2$ set by the near-horizon throat, and what is left is a rotating hole whose angular momentum has passed to its own field.

We show that vacuum Rabi oscillations can directly generate spin squeezing through geometric focusing on the Bloch sphere. Starting from a coherent spin state resonantly coupled to a cavity initially in the vacuum state, quantum fluctuations are focused by the curvature of the Bloch sphere as the collective spin approaches the atomic ground state, producing squeezing transverse to the direction of motion. The squeezing timescale is set by the collective Rabi frequency $t_s\sim 1/(g\sqrt{N})$. The optimal Wineland squeezing parameter scales as $\xi_{\rm opt}^2\propto N^{-1/3}$, which is an outcome of the competition between the geometric focusing effects and the cavity-field vacuum fluctuations. The squeezing remains robust against realistic dissipation. In the end, an application example of $^{171}$Yb is briefly discussed to show the feasibility of our protocol.

Semiconductor quantum-dot arrays are a compelling platform for scalable quantum technologies, yet their practical operation is hindered by the complexity of tuning large-scale devices. Existing automation tools rely on simplified physical models—such as constant-capacitance approximations and equilibrium Hubbard models—which assume instantaneous relaxation to a steady state. These frameworks fail in experimentally critical regimes where measurement rates exceed tunneling dynamics, necessitating more sophisticated non-equilibrium control strategies. To bridge this gap, we introduce QArray+, an extension of the QArray framework that incorporates gate-dependent tunnel coupling and a quantum open-system description of dissipative processes. This approach enables the unified simulation of coherent interdot charge-state hybridization and the non-equilibrium latching dynamics essential for training robust machine-learning models for automated device operation. Implemented in JAX with GPU acceleration, QArray+ scales across GPUs and multi-node systems. For example, a charge stability diagram for a 100X100 grid of gate voltages over 64 dots can be computed in $\sim0.17\,\mathrm{s}$ on multiple GPUs. Since interdot interactions are short-ranged and the corresponding tuning corrections are local, simulations at these scales capture the physics relevant to even larger devices. These capabilities support high-throughput dataset generation for automated device tuning.

Optical computing offers a promising route to high-speed, energy-efficient information processing. However, implementing nonlinear operations typically requires strong light-matter interactions. Here, we introduce structural nonlinearity into an optical reservoir computing architecture, using only linear components. A digital micromirror device acts as a reconfigurable scattering potential, while the propagation of light through a scattering medium provides the high-dimensional mode mixing. By enforcing a second interaction with the wavefront shaper, we obtain a quadratic mapping of the input within the reservoir. A single experimental apparatus simultaneously implements conventional and structurally nonlinear reservoir architectures, enabling a direct comparison on forecasting of the chaotic Mackey-Glass time series. We demonstrate that the structurally nonlinear reservoir improves short-term prediction accuracy and better preserves the long-term dynamics of the chaotic system, demonstrating the potential of structural nonlinearity for low-power optical computing.

KIC~8462852 (Boyajian's star) shows deep, asymmetric, and highly irregular dimming events with no simple repetition pattern. A symmetric 1.1% transit detected by TESS in 2019 has been interpreted as a possible giant planet or brown dwarf, while the irregular dips are generally attributed to transiting dust from exocomets or planetesimal fragments. We test whether the broader dip families may nevertheless recur orbitally. Our scenario assumes a major disruption that produced fragments with slightly different periods, causing successive returns to spread progressively in orbital phase. We compare this recurrent model with a null hypothesis of chronologically independent family centers, accounting for the observing window, and marginalize over the recurrence period $P$ and dispersion scale $\sigma_P$. We obtain $B_{10}=44.9$ in favor of recurrence, corresponding to “very strong” evidence on the Jeffreys scale. The maximum-likelihood solution is $P_{\rm ML}=781.6$~d and $\sigma_{P,\rm ML}=80.0$~d, close to the 776.1-d timescale obtained if D800 and the 2019 TESS event are separated by four revolutions. Independently of the timing fit, this period predicts a transit duration of about 20.5~h for the published stellar and transit parameters, in close agreement with the observed $\sim21$~h. The result is conditional on the adopted topology, priors, family definition, and observing selection function, and does not prove orbital recurrence. Nevertheless, the family timings strongly favor this specific recurrent-fragment model over independent occurrence, making progressive orbital phase dispersion a viable and physically motivated interpretation.

Open quantum many-body systems are commonly described by Lindblad master equations, yet the treatment of Lindbladian operators in the thermodynamic limit remains a major challenge. We develop a framework for constructing effective quasiparticle-conserving Lindbladian operators directly in the thermodynamic limit. Our approach extends continuous similarity transformations to non-Hermitian open quantum systems and enables the systematic block diagonalization of Lindbladians with respect to the quasiparticle (qp) number. We formulate two complementary methods. The first, projective continuous similarity transformations (pcst++), generalizes perturbative continuous unitary transformations to Lindblad operators so that a linked-cluster expansion allows us to obtain high-order series expansions of the infinite system. The second, deepCST, extends directly evaluated enhanced perturbative continuous unitary transformations by combining the same qp-conserving generator with a perturbative truncation scheme that yields non-perturbative effective Lindbladian operators directly in thermodynamic limit. We apply pcst++ and deepCST to the dissipative transverse-field Ising chain with local dissipation. We focus on the low-Ising regime. We purify the Lindbladian by splitting each spin into two sites. A spin flip then corresponds to two qps. We derive and analyze the effective, qp-conserving Lindbladian in the sectors with zero to two qps. We show how the Ising interaction renormalizes the decay rates of elementary spin-flip excitations and provides the microscopic mechanism for a competition between coherent interactions and dissipation. Our work establishes perturbative and non-perturbative continuous similarity transformations as a versatile tool for deriving effective qp pictures of open quantum many-body systems in the thermodynamic limit.

Twistronics of layered materials has emerged as a highly active field due to its profound implications for quantum electronics and materials engineering. However, the controllable manipulation of interlayer stacking remains a significant experimental challenge. Here, the homogeneous contact between hexagonal boron nitride layers is shown to be reproducibly switched between two distinct stable stacking configurations via an externally applied torque. Combining experiments and computational modelling, we identify the stacking order of these stable states as the commensurate AA and AB modes. These two states are associated with different rotational torque maxima, exhibiting an asymmetry ratio of 0.7, and distinct dynamics as a function of the twist angle. Moreover, the peak torque values scale linearly with contact area, highlighting the dominant role of edge elasticity in the twisting process. Given that the AA and AB stacking modes correspond to different out-of-plane electric polarization states, our findings offer a pathway for reconfigurable nano- and micro-electromechanical devices.

We study the minimum-work feedback control of particles subject to active fluctuations. Considering an active Ornstein-Uhlenbeck particle confined by a moving harmonic trap, we derive exact optimal protocols following an initial position measurement. Our results show that nonequilibrium correlations between position and active fluctuations allow work extraction from the activity based on positional information only, i.e., without directly measuring the active degree of freedom, which was the focus of earlier literature. We find that depending on the persistence time, activity can either facilitate or impede transport relative to passive systems. Surprisingly, unlike feedback schemes based on direct measurements of the active fluctuations, positional feedback remains energetically advantageous even in the limit of infinitely persistent activity. Our results provide design principles for information engines and optimal control strategies operating in active environments.

Non-adaptive quantum amplitude estimation (QAE) fixes its Grover depths in advance, so every circuit can run in parallel, but it has so far needed more queries than the best adaptive methods. We show that most of this gap comes from two conventional choices: subspace-based post-processing and power-of-two depth ladders. We replace the first by the exact maximum-likelihood estimate, one matrix multiplication per batch of estimates, and the second by a geometric ladder with ratio $r \approx 1.45$. The result is a fully parallel, deterministic-schedule estimator with total query complexity $2.8$-$3.1/\varepsilon$ at 95% confidence for target errors from $3.5\times 10^{-3}$ to $10^{-6}$. This matches the average-case complexity of chebAE, the best benchmarked adaptive method, within statistical uncertainty (with the lower point estimate at every scale tested), beats its maximum-observed complexity by $1.6\times$, and needs a maximum sequential depth of only $0.21/\varepsilon$ against chebAE's $2.9/\varepsilon$. Relative to csAE, the best non-adaptive benchmark, the constants improve by 30-35% at 95% and $1.5$-$1.7\times$ at 99% confidence. The optimal ratio has a simple origin. Doubling is the fastest depth growth at which the data can still tell neighboring candidate values apart, so power-of-two ladders sit at the edge of confusion and must buy reliability with extra shots; a slightly denser ladder checks every scale redundantly. An error-probability analysis reproduces the measured failure rates and locates the optimum. The likelihood formulation extends directly to noise-aware estimation, and uniformly scaling the capped ladder covers the depth-limited regime, realizing the optimal trade-off $M N_{\mathrm{tot}} \approx (0.4$-$0.6)/\varepsilon^2$ within $\sim 1.1\times$ of the schedule's Cramér-Rao limit.

Two-dimensional metals became a laboratory reality with the isolation of Goldene, a gold sheet one atom thick released by chemical exfoliation, which raises the question of what alloying can achieve on the same close-packed lattice. Here we combine an exhaustive enumeration of derivative superstructures with density functional theory to map the ordered Au-Ag-Cu monolayer alloys, relaxing every symmetry-inequivalent arrangement up to four atoms per cell and extending the set with larger cells selected by a fitted model. We find that the arrangement of the atoms, and not their proportion, controls the mixing energy, since the spread among the orderings of a single composition is several times the step between neighboring compositions, one composition spans more than 50~meV/atom between two arrangements of the same three atoms, and at two compositions the arrangement decides the sign. The energetics is carried by a competition between Au-Cu contacts, which bind, and Ag-Cu contacts, which do not, and bulk enthalpies computed under the same protocol show that this chemistry is not uniformly rescaled in two dimensions, since Au-Cu orders more strongly in the monolayer than in the crystal while the other two weaken. A pair model completed by an elastic size-mismatch term reproduces the computed energies to a few meV/atom and returns a composition landscape whose convex hull no balanced ternary composition reaches. One equimolar ordering, which we name Noblene, is the only structure in which every atom is surrounded exclusively by unlike species, and it is dynamically stable and metallic, and carries a Poisson's ratio above one half, higher than that of any of the three pure monolayers. Since Noblene sits on the lattice that Goldene already realizes, the route that produced Goldene is a plausible starting point for its synthesis.

Beta Pictoris is a young and nearby planetary system hosting an edge-on debris disk and at least three gas-giant planets. Their circumplanetary environments could host exomoons and rings, a detection of which would be highly informative for moon and planet formation theories. A photometric fluctuation of about 4% was seen towards Beta Pictoris in 1981, indicating the transit of dust in the system, which could be associated with the Hill spheres of the two inner planets. We search for the origin of the 1981 event by searching for an analogous event in multi-epoch photometry from 2017 to 2023, and look for signs of circumplanetary material in transits of the Hill sphere of Beta Pictoris c. Observations from the BRITE satellite, and the bRing and ASTEP observatories are fitted to a model of the 1981 event to search for a similar event, and also search for a signal consistent with a circumplanetary disk transit using a simple flat disk model. No compelling evidence for a 1981 event during a Hill sphere primary transit is found, although we do find a candidate event around 2019 July 26. Due to the uncertainty in the time of closest projected separation of Beta Pictoris c, a search for a disk during the primary transit of 2018 could not be robustly determined, but bRing photometry for the second primary transit places an upper limit on the dust content of the Hill sphere of ~ $10^{22}$ grams of material. With no compelling detection of an event similar to that seen in 1981 during the transits of Beta Pictoris c in the photometric time series, we rule out the hypothesis that this event was related to the Hill spheres of Beta Pictoris c and Beta Pictoris b. Future observations of the next Hill sphere transit in 2028 can be realised with both ground-based observatories and with PLATO, whose first long duration science pointing will include Beta Pictoris.

Using the newly developed $3$d quantum trace map, we compile more evidence for the length conjecture, a refinement of the all-order volume conjecture that incorporates insertions of additional links in the skein module of the knot complement. In particular, we prove that the length conjecture holds up to first order for an infinite family of twist knots. Along the way, we form a conjecture that the $3$d quantum trace map behaves naturally with respect to Dehn filling.

Halo nuclei are exotic nuclei, which exhibit a much larger matter radius than their isobars. This unusual size is now understood as a threshold effect, in which one or two valence nucleons are loosely bound to the core of the nucleus. Thanks to this loose binding, halo nuclei exhibit a strongly clusterised structure with a diffuse neutron halo surrounding a compact core. Being short lived, halo nuclei are mostly studied through reactions, such as breakup. In this talk we show that including Halo Effective Field Theory within existing reaction codes is both effective and efficient to analyse experimental data. We first apply this idea to study the Coulomb breakup of 19C within a Bayesian approach. Second, we extend Halo-EFT to include the core's excitation to test the sensitivity of the Coulomb breakup of 11Be on spectroscopic factors.

Free-space optical neural networks offer distinct advantages for computational imaging and machine vision because they can compute directly on incident optical fields. However, conventional ONNs composed of cascaded linear optical components are bound to a general linear input-output relation with square-law detection between the input field $\mathbf{x}$ and output score $\mathbf{y}$, $\mathbf{y}=|\mathbf{T}\mathbf{x}|^2$, where at best every complex-valued element of the transmission matrix $\mathbf{T}$ is trainable. This restricts each output score to a quadratic form $\mathbf{x}^\dagger\mathbf{A}\mathbf{x}$ with rank-one decision matrix $\mathbf{A}=\mathbf{t}^\dagger\mathbf{t}$. Here, we present a random-mapped intensity optical neural network (RMI-ONN) as an all-optical two-layer computational network that lifts this rank-one limit. We numerically demonstrate that a high-dimensional feature projection by a disordered medium, a programmable nonnegative intensity mask, and segmented spatial power summation together can surpass the rank-one ceiling through the expressivity of higher-rank quadratic decision boundaries. Furthermore, exploiting the vectorial coherent wave-mixing nature of the disordered medium, we experimentally validate multimodal classification of amplitude, phase, and polarization on MNIST, Fashion-MNIST, and Quick Draw with the RMI-ONN, under a single optical configuration across all encoding domains. These results provide a practical and conceptual basis for scalable direct-field optical processors capable of exploiting amplitude, phase, and polarization information within a unified intensity-based inference framework.

Ultrasound is increasingly used to control biological cells, but its multiple physical effects, including radiation force, streaming, heating, and cavitation, require theoretical frameworks that can quantify their relative strengths. Here we develop a semi-analytical model to predict flow patterns and energy distributions of ultrasound-induced intracellular streaming. Cells are modeled as viscoelastic droplets immersed in a fluid with different viscoelastic properties. For this geometry, the momentum equation with an Oldroyd-B constitutive law is solved using a perturbation expansion commonly applied in acoustofluidics. The resulting equations for the different orders of the expansion are solved using partial wave expansion and explicit integration. We investigate our model for a range of parameters which is relevant both for synthetic polymer and for protein solutions. We find a series of flow reversals that we can connect to the distribution of energy into the different modes. We also consider density and compressibility contrasts, which shift these transitions and introduce new ones. Finally, we discuss the potential biological relevance of our mathematical results for cellular sensing and signaling.

Large-scale molecular dynamics simulations of particle systems on multi-GPU architectures are often constrained by the computational and communication costs of nonbonded force evaluation. We present RBMD 2.0, a major new release of the random batch molecular dynamics package designed for cross-node multi-GPU simulations of large-scale systems. It combines the improved random batch Ewald method with three-dimensional domain decomposition and ghost-particle communication to accelerate multi-GPU nonbonded force evaluation, while the DTK CUDA framework facilitates portability across heterogeneous accelerator architectures. Numerical experiments on multiple benchmark systems demonstrate both the accuracy and efficiency of simulations with RBMD 2.0. For simulations involving up to hundreds of millions of particles across multiple accelerator devices, one achieves speedups ranging from severalfold to approximately two orders of magnitude in nonbonded force evaluation while exhibiting over $97.5\%$ weak-scaling behavior. These results demonstrate the promising nature of RBMD 2.0 as a computational engine for future exascale molecular dynamics simulations.