Papers

Superluminous supernovae (SLSNe) are often modeled as being powered either by a central engine or by strong interaction with dense circumstellar material (CSM). These two mechanisms may be dynamically coupled if the ejecta interact with dense CSM while being energized by a newborn magnetar. We develop a semi-analytical hybrid model that follows the coupled dynamics, energy conversion, and radiative output of such systems. A rapidly rotating magnetar injects energy through a relativistic wind, inflating a hot bubble inside the expanding ejecta. Part of the injected energy is stored as radiation, while the rest is converted into bulk kinetic energy of the swept-up ejecta. At the same time, the outer ejecta collide with the surrounding CSM and form a circumstellar interaction (CSI) region. As the shock driven by the magnetar accelerates through the ejecta, it can catch up with the CSI region and take over the subsequent interaction with the unshocked CSM. The emergent light curves are therefore governed by the coupled effects of magnetar energy injection, shock heating, and radiative diffusion. We show that this hybrid model can produce diverse SLSN light-curve morphologies, including luminous interaction-powered peaks, asymmetric post-peak declines, and late-time emission sustained by delayed leakage of magnetar-powered radiation. The model provides a plausible way to reduce the extreme nickel-mass or initial explosion-energy requirements often encountered in purely radioactive or purely interaction-powered interpretations.

Understanding adhesion is essential for describing stability, friction, and interfacial dynamics. Here, we investigate the adhesion force dynamics between a rigid sphere and a soft surface without direct contact, mediated by a viscous fluid. By combining controlled experiments, a first-principles visco-elastohydrodynamic theory, and numerical simulations, we demonstrate that viscoelastic relaxation fundamentally modifies elastohydrodynamic adhesion. Rather than simply dissipating energy, viscoelasticity causes the substrate to behave transiently as a stiffer solid, enhancing the maximum adhesive force, changing the early-time force growth for $t^{2/3}$ to $t^{1/3}$, shortening the interaction time, and giving rise to new scaling laws governed by the Deborah number. The two proposed dimensionless parameters, the softness parameter and the Deborah number, define a unified phase diagram connecting three distinct adhesion regimes: classical Reynolds lubrication, elastohydrodynamic adhesion, and the newly identified visco-elastohydrodynamic regime.

Diagonal gates are ubiquitous primitives in quantum algorithms, from phase oracles, hypergraph-state preparation, and multi-control logic to Hamiltonian simulation of spin models and digitized lattice field theories, where Ising interactions and local potential terms are diagonal in the encoded basis. Standard compilers, however, often lower diagonal structure into one- and two-qubit gates before neutral-atom hardware can exploit native Rydberg-mediated multiqubit controlled-phase operations. We propose a Möbius-guided compiler that maps a diagonal phase function to a phase hypergraph via subset-lattice Möbius inversion. The hypergraph retains the support and angle of each many-body phase term, allowing sparse or local high-order structure to be routed as native multiqubit controlled-phase candidates when feasible and decomposed otherwise. The neutral-atom scheduler accounts for atom motion, interaction-zone constraints, blockade feasibility, and error costs, enabling a direct comparison between native high-order execution and decomposed alternatives. Benchmarks against routed ZAP and ZX-calculus baselines show improved estimated success for algorithmic instances with exploitable three- and four-body phase terms, and comparable performance on predominantly two-body instances. These results provide a feasible compilation strategy for more fully exploiting the native capabilities of neutral-atom hardware, using atom reconfigurability and Rydberg-mediated multiqubit phase operations as practical resources for more efficient quantum computation.

We investigate the interaction of O$_{2}$ with an X-ray Free Electron laser (XFEL) pulse of short duration. We consider a photon energy of 570 eV, which allows for the formation of molecular states with up to two core holes. We compute the sum of the final kinetic energies, i.e. the kinetic energy release (KER) of the atomic fragments for different fragmentation channels. We demonstrate that with the knowledge of the potential energy curves the equilibrium inter-nuclear distance of O$_{2}$ is best extracted from the O$^{+}$+O$^{+}$ channel and not from higher-charged channels such as O$^{2+}$+O$^{2+}$. This challenges our current understanding of Coulomb explosion imaging, where from just applying quasi-classical dynamics one expects that the equilibrium inter-nuclear distance of molecules is best extracted from higher-charged fragmentation channels. On the other hand, we show that the KER of the O$^{+}$+O$^{+}$ channel is inconsistent with the one obtained by just calculating the Coulomb repulsion of the atomic fragments resulting from molecular dissociation.

A central challenge in the analysis of first-order phase transitions is the identification of optimal reaction coordinates. In principle, the committor is the ideal choice; however, its computational cost has historically made it intractable. Here, we train a convolutional neural network ($p_B$-NN) as a proxy for the committor on brute-force committor labels and use it directly as the coordinate of a Markov state model. Applied to magnetisation reversal in the two-dimensional Ising model, $p_B$-NN reproduces brute-force nucleation rates across a range of thermodynamic conditions. The largest geometric cluster size also recovers accurate rates despite providing a poor pointwise predictor of the committor. These results demonstrate that an effective reaction coordinate for nucleation rate calculation must reliably separate the metastable and stable basins, but need not preserve the committor pointwise for every microstate. We stress that this distinction has direct implications for the choice of collective variable in rare-event simulations of nucleation more broadly.

We present the development of a silicon-based ultra-fast X-ray beam size monitor (SiXRM) for SuperKEKB. The system enables, for the first time at SuperKEKB, bunch-by-bunch measurements of the vertical beam size using synchrotron radiation. The detector combines a silicon strip sensor board, amplifier boards, and fast waveform readout electronics. Beam measurements demonstrate clear reconstruction of the bunch structure and X-ray images for individual bunches. The measured beam sizes show good agreement with those obtained from the existing CMOS-based XRM system. The measurement precision is estimated to be better than 6.4 $\mu$m. This system provides a powerful tool for studying beam dynamics and optimizing luminosity in high-luminosity colliders.

Circuit synthesis of multi-controlled gates is crucial for qudit ($d$-level) quantum computing. This paper presents efficient synthesis schemes that reduce the elementary gate count for multi-controlled single-qudit gates. For synthesizing general $(n-1)$-controlled unitaries on $n$ qudits, we reduce the controlled-increment (CINC) and generalized controlled-$X$ (GCX) gate counts to $O(n^2)$, improving upon existing $O(n^{2+\log_2 d})$ CINC and $O(n^3)$ GCX bounds. For $(n-1)$-controlled special unitaries, this complexity is further reduced to $O(n)$. Furthermore, we present a method for approximately synthesizing multi-controlled unitary gates with a linear complexity in the number of control qudits. By utilizing the proposed circuit, we present qudit-based circuit constructions for isometries and quantum channels from $n$ to $m$ qudits. Moreover, for the first time, we present a circuit synthesis scheme for single-controlled gates using SUM gates and single-qudit gates when $d$ is prime. This enables all CINC-based circuits for various quantum operations to be converted into SUM-gate circuits while preserving the same asymptotic complexity. Finally, we establish a theoretical lower bound on the number of SUM and CINC gates required to synthesize general $n$-qudit unitaries.

While the direct simulation Monte Carlo (DSMC) is a mainstream stochastic particle method for simulating rarefied gas flows, it incurs excessively high computational costs in the near continuum regime. As a hybrid acceleration approach coupling DSMC with macroscopic synthetic equations, the direct intermittent general synthetic iterative scheme (DIG) delivers fast convergence and asymptotic-preserving characteristics, which effectively alleviate the kinetic scale limitations inherent to standard DSMC. In this study, we develop a parallel DIG augmented DSMC solver for three dimensional rarefied gas flow simulations on unstructured meshes. On top of the standard DSMC algorithms for particle transport and collisions, a reliable intermittent coupling framework is constructed to exchange macroscopic flow data between the stochastic DSMC module and deterministic macroscopic synthetic equations. For parallel execution on unstructured grids, we employ a hybrid MPI architecture equipped with ghost cells to enable local particle tracking and batch inter-rank particle migration. A graph partitioning based dynamic load balancing strategy is also integrated to mitigate uneven particle distribution over computational domains. Numerical results demonstrate that the proposed solver achieves satisfactory agreement with the SPARTA DSMC. Leveraging the fast convergence and asymptotic-preserving properties of the DIG method, the required number of spatial cells and statistical sampling steps are drastically decreased, leading to substantial reductions in computational memory and runtime. This work presents an efficient high-performance numerical tool for high-fidelity simulations of rarefied flows over complex geometries. The code is available in the developer repository at the github link.

The density profiles of dense molecular cores are important indicators of their physical and evolutionary states. Multi-wavelength dust continuum data offers excellent constraints on the density profile of cores. Here we introduce CARPP (Core Analysis via Radiative Transfer and Profile Parameters), a publicly available fitting package that generates optimized core density and temperature profiles based on parameterized radiative transfer calculations. CARPP assumes spherical symmetry and adopts physically motivated parametric forms for the density and temperature profiles, and uses dust continuum data for fitting. Tests on synthetic data show that CARPP achieves high accuracy, namely averaged relative errors of CARPP's seven parameters being $<20\%$, when the data quality satisfies $\frac{\rm RMS \,\, noise}{[\rm peak \,\, flux]} < 0.025\times \frac{[r_0]}{\rm resolution} +0.05$, where $r_0$ is the core's characteristic radius. We select the low-mass core TMC-1C and the high-mass core Ori2-2 to demonstrate CARPP's performance on real data. It classifies TMC-1C as a Bonnor-Ebert sphere in near-hydrostatic equilibrium, while Ori2-2 exhibits a power-law-dominated profile indicative of a collapsing envelope. This capability establishes CARPP as a powerful and versatile tool to classify the dynamical states of individual cores. It offers an optimal balance between physical fidelity and computational efficiency, serving as a practical, standardized alternative to both over-simplified SED analyses and complex, time-intensive 3D radiative-transfer modeling.

The effect of a moving impurity in a dilute Bose-Einstein condensate is investigated by means of the one-dimensional Gross-Pitaevskii model (GP) with non-zero boundary conditions at infinity. The impurity is modeled as a localized external potential, that travels at constant speed $v \in \mathbf{R}$. In a co-moving reference frame, we study the existence and stability of time-independent solutions. The latter are of physical relevance, being associated with the superfluid behavior of the condensate. For every non-zero velocity $v$ in the subsonic regime, we show the existence of a family of time-independent solutions which bifurcates from a (displaced) gray soliton $\phi_{0,v}(x-s_0)$, with $s_0 \in \mathbf{R}$, of the GP equation. The position $s_0$ is determined as an extremal point of an effective potential explicitly defined. Moreover, we study the spectral stability of these states. For small values of the potential strength, we show that the families originating from the maxima of the effective potential are spectrally unstable. For this last result, we employ an Evans function approach. Finally, we formally apply the instability result to the case of a repulsive delta potential.

The thermal radioactivity of beta-decay photons, described by a 1D Planck distribution, can be modeled as classical radiation emitted by an accelerated electron. Here, we present the basics of the out-of-equilibrium computation to illustrate acceleration thermality. Suitable for advanced undergraduate calculations, we demonstrate that an exactly soluble non-uniformly accelerated trajectory enables spectral analysis of the emitted photons, facilitates time evolution, and reveals Planckian radiation.

Surveys of Galactic halo stars have revealed numerous streams and substructures tracing stellar populations accreted by the Milky Way. Among these, Gaia-Sausage-Enceladus (GSE) and Sequoia are the most prominent, both associated with dwarf galaxies accreted about 10 Gyr ago. We aim to measure beryllium abundances in nine stars associated with Thamnos, a substructure possibly linked to Sequoia, following the discovery of a Be-rich star BPM3066 by Monaco et al (2025). We used Gaia photometry and parallaxes to compute ATLAS9 model atmospheres. Synthetic spectra were generated with Turbospectrum and used with MyGIsFOS in single-model mode to analyze UVES high resolution spectra. Four new stars exhibit a significant beryllium overabundance. Moreover, the two known Be-rich stars, HD 106038 and HD 132475, are also found consistent with Thamnos membership. Thus, all currently known Be-rich stars appear associated with the Thamnos-2 structure. The Be enhancement is accompanied by elevated Si abundances, and we detect a correlation between Be and neutron-capture elements. No comparable Be-rich population is known elsewhere in the Galaxy, pointing to a rare enrichment event. The measured A(Be)/A(Li) excess ratio bears the imprint of spallation reactions, pointing to a highly energetic event in which fast CNO nuclei fragmented upon collision with the surrounding medium. The silicon overabundance is also consistent with a hypernova origin. Such an event may have rapidly enriched the surrounding gas to [Fe/H] about -1.5 explaining the relatively high metallicities of stars formed from this material despite their old ages (about 13 Gyr).

Density matrix embedding theory (DMET) provides an elegant framework in quantum chemistry to describe local properties of chemical systems that allows a high-level method being used to solve an embedded subsystem constructed based on a low-level treatment of the whole system, and therefore achieves a balance between efficiency and accuracy. However, because the embedded subspace in DMET is typically constructed from the mean-field ground state Slater determinant, the resulting bath orbitals inherently favor the ground state, leading to unbalanced descriptions of ground and excited states for local excitations. In this work, we first demonstrate the starting-point dependence of DMET in excitation energy calculations, and then generalize original ground-state based DMET by extending the starting point from the single Slater determinant to state-averaged (SA) complete active space self-consistent field (CASSCF), hence termed as SA-DMDT. In calculations of magnetic anisotropy and excitation energies of transition metal and lanthanide complexes, SA-DMET shows significant improvement in accuracy compared to the single-state DMET. Configuration-averaged Hartree-Fock (CAHF), which is equivalent to SA-CASSCF when all states in the chosen active space are equally averaged, is found to give comparable accuracy as a DMET starting point, thus offering a more efficient choice for state-averaged embedding. Finally, the recently proposed non-orthongal atomic-orbital-based DMET (AO-DMET) is tested on various systems and gives very promising results in all cases. These results establish SA-DMET, especially in combination with AO-DMET and CAHF, as a robust and efficient embedding framework for local excited states in strongly correlated metal complexes.

We investigate strongly correlated electron-phonon (e-ph) systems via a non-Gaussian matrix product state method. By combining non-Gaussian states with matrix product states, our method efficiently characterizes the intractable entanglement between strongly correlated electrons and phononic modes of unbounded Hilbert space, enabling scalable simulations across broad parameter regimes. In one-dimensional generalized Hubbard–Holstein (HH) models, we identify a pronounced tendency toward phase separation (PS), an instability relevant to recent angle-resolved photoemission spectroscopy observations on doped cuprate chain. In two-dimensional HH models, we construct the phase diagram at half-filling featuring a metallic phase emerging from the competition between non-local phonon-mediated attraction and local Hubbard repulsion. Upon doping, we elucidate the role of soft phonons in stabilizing stripe phases. In the antiferromagnet, the stabilization of the fully filled stripe is attributed to a local retardation effect, wherein the charge order is pinned by phonons, leading to a diminished response to spin fluctuations. In the doped charge-density-wave regime, a novel bipolaronic stripe phase with an enlarged unit cell is stabilized via a non-local retardation effect, where long-range phonon-mediated interactions suppress PS. Our work establishes a systematic route to decoding the e-ph interplay that is crucial for superconductivity.

Electromagnetic calorimeters provide essential information for reconstructing and selecting both Standard Model (SM) and potential beyond the SM physics events at high-energy particle colliders. The fine-grained segmentation of modern calorimeters captures rich information about the internal structure of particle showers, much of which is discarded by conventional high-level reconstruction methods. In this work, we leverage calorimeter cell-level information to classify highly collimated diphoton signatures, arising from the decay of light axion-like particles, from isolated single-photon showers. We systematically compare a range of machine learning architectures, spanning high-level, shower shape variable-based approaches and direct cell-level methods. Cell-level machine learning shows significantly superior classification ability, with a Transformer in particular representing the best performance among six different architectures studied, and an MLP Mixer representing a resource-constrained alternative for potential real-time, trigger-level applications. Beyond classification, the Transformer model developed enables direct invariant mass regression from calorimeter cells, improving the characterization of light resonances and providing an additional handle in reducing the $\pi^0$ and $\eta$ fake photon backgrounds. These results demonstrate that cell-level machine learning methods can extend calorimeter-based particle identification and performance well beyond the capabilities of current conventional techniques.

Quantum computing has emerged as a promising framework for addressing computationally demanding problems in collider physics. In recent years, a growing number of quantum algorithms have been proposed for applications ranging from event generation and parton shower simulation to the evaluation of scattering amplitudes, loop and phase-space integration, and optimization problems relevant to experimental analysis. We provide a concise overview of the main ideas behind these developments, with emphasis on the potential advantages of quantum approaches in comparison with classical methods, as well as on the current limitations imposed by noisy intermediate-scale quantum hardware.

Strong-field photoionization of molecules and molecular clusters gives rise to a rich variety of fragmentation pathways governed by charge localization and redistribution on ultrafast timescales. Here, we report a velocity-map imaging study of the strong-field photoionization and fragmentation of carbonyl sulfide (OCS) monomers and dimers driven by 150 femtosecond (fs) laser pulses at 775~nm. The images of the total kinetic-energy and angular distributions of the OCS$^{2+}$, S$^+$, and CO$^+$ fragments were interpreted with the help of electronic-structure calculations of the potential energy surfaces for OCS$^+$ and OCS$^{2+}$. We identify distinct dissociation pathways of singly and doubly ionized OCS, including two-body breakup channels of OCS$^+$ into $\mathrm{S}^+ + \mathrm{CO}$ and $\mathrm{CO}^+ + \mathrm{S}$, dissociation of OCS$^{2+}$ into $\mathrm{S}^+ + \mathrm{CO}$$^+$ as well as higher-order three-body fragmentation. In addition, the images of the OCS$^{2+}$ channel exhibit near-zero-momentum components, low-energy isotropic features, and highly anisotropic contributions at high kinetic energies that cannot be explained by monomer ionization alone. Analysis of the KER distributions and angular anisotropies indicates that these features originate from the breakup of multiply charged OCS dimers ((OCS)$_2^{2+}$, (OCS)$_2^{3+}$, and (OCS)$_2^{4+}$) through charge-separation channels. Our results illustrate how dynamic signatures of strong-field fragmentation evolve from intramolecular dissociation in isolated molecules to intermolecular charge separation in weakly bound clusters providing a unified picture of charge-driven dissociation dynamics beyond the single-molecule limit.

Classical numerical techniques for solving partial differential equations (PDEs) become computationally expensive as the dimension of the discretized differential operator increases. For PDEs giving rise to Sturm–Liouville problems, tensor network (TN) methods can be highly productive: an operator of dimension $N\times N$ can be represented as a matrix product operator (MPO) using only $n=\log_2(N)$ qubits, enabling computation of eigenvalues and eigenvectors via imaginary time evolution (ITE). However, this remains computationally challenging. First, most methods for generating MPOs of large operators without explicit tensor-product structure require prohibitively large memory. Second, the number of Trotterization steps for convergence in conventional ITE increases rapidly with $n$. We present techniques to mitigate both challenges for certain sparse, structured differential operators. To address the first, we construct the MPO by expanding the operator in the Pauli-string basis, enabled by an analytical expression for the Pauli basis coefficients that reduces the memory requirement from $\mathcal{O}(2^{n+1})$ to $\mathcal{O}(2n)$. To address the second, we propose a multistage state-refinement heuristic that accelerates ITE convergence, reducing convergence time by up to two orders of magnitude. Using this TN framework, we compute the first 32 eigenstates of a Laplacian of dimension exceeding $10^6$ with fidelity above $0.95$ using a 20-qubit MPO. We further validate the method on the 2D anharmonic oscillator and investigate disordered systems, where increasing random potential strength degrades accuracy and limits the approach.

We develop a new method for proving a weak functional inequality by first proving it for a sufficiently regular sequence of distributions approximating the stochastic localization (SL) process, and then transferring it to the desired distribution via regularity of the SL process and conductance arguments. We use this strategy to prove a weak Poincaré inequality (WPI) holds for the Gibbs measure of the Sherrington-Kirkpatrick model when $\beta < \frac{1}{2}$. A prior result of the authors [arXiv:2605.03718, 2026] proves the ASL process for the Sherrington-Kirkpatrick model satisfies the required regularity conditions. A consequence of the WPI is that a much simpler algorithm – Glauber dynamics with a warm-start – efficiently samples the Gibbs measure of the SK model at $\beta < \frac{1}{2}$. This is a significant structural step towards resolution of the conjecture that Glauber dynamics mixes fast in the replica-symmetric regime for the Sherrington-Kirkpatrick model [arXiv:2504.20539, Open-Problem 15, 2025].

Adjoint optimization is a cornerstone of broadband nanophotonic inverse design, but conventional time-domain implementations face a severe memory bottleneck because they retain forward-field histories at every finite-difference time-domain (FDTD) time step. Here, we show that this full time-step storage is unnecessary for broadband design objectives because the underlying fields are band-limited. By storing forward fields only at Nyquist intervals and using the resulting sparse fields during the adjoint pass, the proposed method enables on-the-fly gradient accumulation without retaining full forward-field histories. This Nyquist-sampled adjoint FDTD framework preserves the two-simulation scaling of time-domain adjoint optimization while substantially reducing the dominant field-storage. Because the broadband gradient is evaluated directly in the time domain, with no spectral discretization, the per-iteration cost is independent of the number of frequencies—in contrast to frequency-sampled adjoint formulations, whose cost grows with spectral sampling density. Gradient verification confirms that Nyquist sampling reproduces conventional full-storage adjoint gradients with negligible error, whereas undersampling beyond the Nyquist limit produces aliasing-induced gradient degradation. Across four two-dimensional broadband nanophotonic benchmarks and a fully three-dimensional metalens, the method maintains gradient fidelity and optimized device performance while reducing dominant field-storage memory by more than $100\times$ relative to full-history storage in a prototypical example. These results suggest that the principal memory barrier in broadband time-domain adjoint FDTD is not an intrinsic requirement of gradient evaluation but rather a consequence of redundant temporal field storage, thereby opening a practical route to large-scale three-dimensional nanophotonic inverse design.

Although quantum key distribution (QKD) enables information-theoretically secure key distribution, it is mainly designed for point-to-point communication and cannot directly support multi-user collaborative scenarios. To address this limitation, quantum secret sharing (QSS) has been proposed to enable secure multiparty key sharing. However, most existing QSS protocols rely on a single-input single-output (SISO) channel, which limits the achievable secret key rate (SKR) and transmission distance. This paper proposes a continuous-variable (CV) QSS protocol based on a multiple-input multiple-output (MIMO) architecture operating in the terahertz (THz) band. In the proposed scheme, transmit-receive beamforming decomposes the MIMO channel into multiple parallel SISO subchannels, thereby improving both the SKR and transmission distance. We describe the QSS transmission procedure and derive the SKR expressions for eight protocol variants under Gaussian collective attacks. Specifically, Gaussian modulation and passive modulation are considered at the transmitter, while homodyne and heterodyne detection are considered at the receiver. Both asymptotic and composable finite-size SKR formulas are derived to characterize the ideal upper-bound performance and the achievable performance under finite resources, respectively. Simulation results show that, under ideal assumptions including perfect channel state information, perfect phase synchronization, and ideal beamforming, the Gaussian-modulation protocol with a 32 x 32 antenna configuration and the passive-modulation protocol with a 1024 x 1024 antenna configuration achieve transmission distances of 14.99 m and 160 m in the atmospheric channel, respectively. These results provide an idealized theoretical benchmark for evaluating the potential performance gains of MIMO-assisted THz CV-QSS in indoor and short-range outdoor wireless networks.

Societal goals need to shift from over-reliance on gross domestic product (GDP) to broader aspects of sustainable and inclusive wellbeing (SIW). However, defining SIW and eventually measuring it with a single number is problematic because it involves many subjective and objective contributors that combine in complex, non-linear ways. Conventional approaches either use linear weighted averages or reduce SIW to subjective wellbeing alone. Neither is sufficient. This paper reviews aggregation methods for SIW against nine conditions derived from needs theory and strong sustainability: limited substitutability, penalisation of imbalances, non-linear transformations, respect for environmental ceilings, respect for lower limits, a formative measurement model, no correlation requirement, distributional sensitivity, cross-border spillovers, and intertemporal aggregation. We compare 13 methods, from simple arithmetic means to penalty-based indices, outranking multicriteria, data envelopment analysis, and insights from ecology, neuroscience, and machine learning. Our illustrative example shows that aggregation choices change significantly country rankings. Compensatory methods create similar rankings. No single method satisfies all nine conditions. We conclude that a future SIW composite indicator will require combining methods across levels: non-linear normalisation, non-compensatory aggregation, and measurement-level choices for inclusiveness and spillovers. This paper provides a step towards the headline aggregated indicator advocated by the UN High-Level Expert Group on Beyond GDP.

Capturing the ultrafast structural dynamics that occur at the solid-liquid interface is key to understanding adsorption, desorption, diffusion, and aggregation processes in catalysis and interfacial chemical reactions. Hard-X-ray scattering in grazing-incidence geometry can, in principle, access interfacial structural changes with angstrom-scale structural sensitivity and ultrafast temporal resolution. However, the long optical paths of the optical pump and hard-X-ray pulses inside the liquid sample pose significant challenges to the temporal resolution, signal-to-noise ratio, and overall stability of such an experimental scheme. Here, we report a method for creating and characterizing ultrathin surface-attached free-flowing liquid sheets, whose submicrometer thickness enables ultrafast temporal resolution and reduces the bulk-liquid scattering contribution. The impinging-jet geometry produces stable micrometer-scale sheets whose morphology depends systematically on incidence angle, jet velocity, and capillary diameter. Gas-assisted shaping using a second capillary further narrows and thins the sheet, producing an extended ultrathin region and reducing the measured minimum thickness below 500~nm for acetonitrile. The resulting platform provides a reproducible, continuously flowing, surface-attached liquid geometry for grazing-incidence scattering experiments.

We investigate non-Hermitian $\mathcal{PT}$-symmetric Klein–Gordon (KG) fields in a magnetized cosmic string spacetime. A complex non-minimal scalar interaction, $\mathcal{F}_{\mu}=(0,\mathcal{F}_{r},0,0)$ with $\mathcal{F}_{r}=\omega r+ib\in\mathbb{C}$, indulged with a magnetic charge $q=ie$, is shown to introduce an effective $\mathcal{PT}$-symmetric Klein–Gordon oscillator supplemented by complex Coulombic and linear interactions. The resulting radial equation is shown to be conditionally exactly solvable using a biconfluent Heun series-to-polynomial approach. To observe non-Hermitian \(\mathcal{PT}\) symmetrization, we compare with the Hermitian counterpart by mapping $e=-i\tilde e \Rightarrow q\in \mathbb R$ and $b=-i\tilde b \Rightarrow \mathcal F_r\in \mathbb R$. In the limiting case $\omega=0$, the system is shown to reduce to an exactly solvable non-Hermitian \(\mathcal{PT}\) symmetric Coulomb-type KG equation using confluent hypergeometric series/polynomials. Hereby, for both \(\mathcal{PT}\) symmetric models considered, we show that non-Hermitian \(\mathcal{PT}\) symmetrization introduces an upper limit for the allowed energies, unlike the corresponding Hermitian cases. These results provide an analytically tractable framework for exploring non-Hermitian relativistic quantum fields in curved spacetimes and demonstrate the role of $\mathcal{PT}$-symmetry in regulating the allowed spectrum.

Direct spectroscopy is very promising approach to characterizing the atmospheres of nearby rocky exoplanets. Non-common path aberrations (NCPA) are differential aberrations between the science optical path and the adaptive optics optical path. The NCPA leak through the coronagraph and create speckles that mimic exoplanet signals. This limits the sensitivity of high-contrast imaging instruments at close angular separations - exactly the separations where we want to search for rocky exoplanets with current and future telescopes and instruments. We aim to actively remove the NCPA on-sky during observations by using focal plane wavefront sensing and control with the newly upgraded MagAO-X instrument. MagAO-X is equipped with a unique second-stage Adaptive Optics (AO) system. The second-stage AO system contains a dedicated deformable mirror (DM) for coronagraphic focal plane wavefront control. This DM is placed after the science and AO beam-splitter and is therefore not seen by the main AO loop. The DM has been recently upgraded from an ALPAO-97 to a Boston Micromachine Kilo-DM. The new Kilo-DM enables focal plane wavefront control with the implicit Electric Field Conjugation (iEFC) algorithm. We developed the necessary procedures to run iEFC with MagAO-X on-sky. We demonstrated the successful removal of NCPA on-sky with an iEFC interaction matrix that was calibrated on the MagAO-X internal source. This demonstrates the repeatability between our off-sky and on-sky alignment. The iEFC algorithm was tested on HR4796A and Alpha Centauri in 0.5" seeing conditions. We saw a reduction of the NCPA by a factor of 2 to 20. This on-sky validation confirms the robustness and efficiency of iEFC under realistic observing conditions, paving the way for its integration into next-generation AO systems for the Extremely Large Telescope and Giant Magellan Telescope.

Divide-and-conquer variants of the Quantum Approximate Optimization Algorithm (QAOA) provide a promising route for executing combinatorial optimization problems beyond the qubit capacity of near-term quantum devices. However, existing approaches rely on the existence of small vertex separators and fail entirely on dense or highly connected graphs where such decompositions do not exist. We introduce Frozen Large Graph Partitioning (FrozenLGP), an adaptive decomposition framework that transforms partitionability from an assumption into an enforceable property. When standard partitioning fails, FrozenLGP identifies the minimum set of obstructing vertices through a minimum-vertex-cut computation based on max-flow and classically freezes their spin assignments. The energetic contributions of the removed interactions are rigorously preserved by folding them into linear bias terms in the Ising Hamiltonian of neighboring active qubits. Across graph sizes up to 10,000 vertices and multiple topology families, FrozenLGP achieves 100% decomposition coverage, compared with 4.6% for the standard divide-and-conquer baseline on high-connectivity instances. End-to-end MaxCut experiments demonstrate that FrozenLGP preserves approximation quality on instances already solvable by conventional divide-and-conquer QAOA while extending applicability to previously unsupported graphs, and outperforming alternative full-coverage decomposition strategies. Noise simulations further show improved robustness arising from reduced entangling-gate requirements. These results establish FrozenLGP as a topology-robust front end for distributed QAOA on near-term quantum hardware.

One of the technical anchors of JVN's research was the "action-at-a-distance" view of gravitational interaction, driven by "Mach's Principle" addressing the origin of inertia. This view exorcises the concept of a field as a mediator of force between separated "particles". However, within a quantum framework, the concept of field as a mediator transcends to field as an autonomous physical entity. Beginning with a comparison between direct action view and field theoretic view in classical framework and moving over to quantum framework, I sketch the strides made in quantum field theory including the new features brought in by gravity. This is intended as a conceptual trace rather than a review.

A central problem in quantum information theory is understanding how quantum resources can be used to communicate information more efficiently than classical resources. We introduce quantum dense network coding – a protocol that transmits the output of a non-Boolean function to a receiver using provably half as many qubits as bits for each sender by not transmitting the entirety of the function inputs. We show this advantage requires both shared entanglement and quantum communication, is robust to noise, and the gap in success probability between quantum and classical communication can be amplified exponentially in the number of senders. Finally, we show that dense network coding gives rise to a novel, information-theoretically secure, quantum cryptographic protocol, which we call measurement-device-independent quantum key growing.

We present the results of our study of Ambiguous Planetary Candidates (APCs) in data from the Transiting Exoplanet Survey Satellite (TESS) using the open-source LATTE package. LATTE provides an effective framework for distinguishing transit-like signals, including planetary candidates and eclipsing binaries, from stellar variability and instrumental noise. We performed a comprehensive analysis of TESS APCs by applying the LATTE diagnostic tools and visually inspecting the resulting light curves and diagnostic plots to identify false alarms and false positives. Our analysis confirms nine potential exoplanet candidates that warrant follow-up observations with ground-based facilities. These findings demonstrate the effectiveness of the LATTE package for the identification and vetting of exoplanet candidates in TESS data. Future analyses incorporating observations from additional TESS sectors will further improve candidate validation and may lead to the discovery of additional exoplanet candidates.

Particle physics stands at a crossroads. The discovery of the Higgs boson in 2012 completed the Standard Model, but it also opened a new set of fundamental questions about the nature of our universe. Answering these questions, from the hierarchy problem and the nature of dark matter to the origin of neutrino masses, will require a new generation of powerful and sophisticated experiments. The global community is currently engaged in a comprehensive, long-term planning process to determine the next big machine. These discussions are not merely technical. The decisions made in the coming years will shape the field until 2060 and beyond. This extended timeline has a direct and immediate impact on the lives and careers of the field's youngest members: the graduate students, postdoctoral fellows, and other early-career researchers (ECRs) who will be tasked with designing, building, and ultimately analyzing the data from these future facilities. This proceeding provides an overview of the key issues facing ECRs in particle physics today, based on a talk delivered on the subject. It begins by surveying the future collider landscape from an ECR perspective. It then delves into the critical feedback gathered directly from ECRs through large-scale surveys, focusing on their primary concerns and actionable recommendations. Following this, it presents an analysis of the academic job market, the important but often unrewarded role of science outreach, and the emerging dual-edged challenge and opportunity of artificial intelligence. The paper concludes by highlighting the indispensable support networks available to ECRs, which are vital for navigating this complex and uncertain career path.