Papers

Physics has traditionally advanced through two interrelated activities: inferring the laws of nature from observations and testing theoretical predictions. This Perspective proposes a new research paradigm – adversarial physics – that subjects physical limits regarded as insurmountable to active stress testing. We introduce the heuristic concept of a "cosmic bug" to denote an exploitable physical anomaly: a reproducibly realizable physical configuration that grants an observer new capabilities previously considered outside the set of achievable physical operations. The proposed paradigm currently encompasses at least three levels: (1) actively constructing complex systems under established physical laws to seek and exploit unforeseen loopholes in specific configurations and combinations of operations; (2) actively seeking, testing, and exploiting anomalous mechanisms beyond the explanatory scope of currently known theories, prompting revisions to our understanding of physical laws or the discovery of new physics; and (3) exploring how loopholes might be exploited to control or modify local physical rules. We further argue that traditional searches centered on the energy, intensity, and precision frontiers may have comparatively neglected another dimension – the configuration frontier: the vast space of physical configurations comprising complex temporal sequences, phase correlations, coherent and entangled states, feedback protocols, topological structures, multiscale organization, and engineered spacetime or vacuum conditions. Artificial intelligence provides an important tool for exploring this high-dimensional configuration space. The ultimate aim is not merely to map nature's capability boundaries, but to discover and exploit possible loopholes in the laws governing it – including physically realizable routes to controlling or modifying local physical rules.

We present a covariant modified gravity theory which reproduces all the galactic phenomenology usually attributed to dark matter in the low acceleration regime, including the flat rotation curves of massive tracers, and the deflection angles of photons as inferred through gravitational lensing. We first derive a fully covariant description of galactic space-times under a spherically symmetric and static approximation. This description accounts for flat rotation curves, observed gravitational lensing phenomenology and the Tully-Fisher mass scalings of the above. The resulting covariant description is then used to constrain the parameters of a minimally coupled gravitational action using power laws for both the Ricci scalar and the matter Lagrangian. The action presented hence leads to field equations whose trace, under the approximations taken, has as solutions metric coefficients which exactly reproduce flat rotation curves, gravitational lensing observations and observationally determined Tully-Fisher galactic mass scalings of any required index. This last allowing for an accurate fitting of observational dynamics up to galaxy cluster scales.

The answer is "Yes". As it has been shown in the Ref.[1] (22 Sep.2017, see also the comments), useing a new definite mathematical axiomatic-algebraic matrix approach, all the fundamental laws of nature could be derived uniquely (where the axiom of "no zero divisors" of the ring of integers has been generilzed and written in a new definite formulation, then basically assuming that all the physical quantities could only and only take the rational values). Based on this new mathematical approach along with the C, P and T symmetries of the derived field equations, it is concluded that the universe could be realized solely with the (2+1) and (3+1)-dimensional space-times. Moreover it is shown that the (3+1) dimensional cases of the directly determinated general covariant field equations (including two definite classes: a two indexes and a four indexes tensor fields), respectively, represent two new massive forms of the bispinor fields of spin-1and spin-2 particles; and the (2+1)-dimensional cases of the drived equations (including: a two indexes and a four indexes tensor fields), represent (asymptotically) two new massive forms of the bispinor fields of spin-3/2 and spin-1/2 particles, respectively. As a particular result, based on the formulation of the derived Electromagnetic Maxwell equations (representing by the bispinor fields of spin-1 particles, including new field equations - corresponding to the YangMills equations - compatible with two specified forms of the gauge symmetry groups), it has been concluded that magnetic monopoles could not exist in the nature to any extend. Furthermore, as the only elementary particles that could be existed in nature, along with the all discovered particles, eight new particles, including four charge-less right-handed spin-1/2 fermions (two leptons and two quarks), and a spin-3/2 fermion, and also three spin-1 massive bosons are also solely predicted.

Liquid droplets deform from spherical shape due to aerodynamic variation of pressure along the surface as the droplet moves through a gas. The deformation is predicted for axisymmetric droplets translating through a gas with low Weber numbers, We < 1, and Reynolds number Re = O(10). That deformation analysis is based on the relations between local pressure jump and the two radii of curvature. A thin boundary layer on both sides of the gas-liquid interface is considered with a surface-velocity jump due to pressure-gradient-driven flow with a large density jump and a pressure jump due to surface tension. A near-ellipsoidal shape is predicted using $We$ as a perturbation parameter. Then, the quasi-steady internal liquid-phase stream function and velocity field are predicted, describing internal circulation and a vortex ring structure with vorticity distributed through an inviscid liquid. The gas-phase flow over the oblate droplet is described using a ring doublet as an image within the droplet. The ring-doublet radius is related to We. Gas potential flow results are presented and compared using both the exact analytical solution and a perturbation analysis based on the square root of We. The perturbation analysis provides a lower computational cost. Three analyses for local curvature, liquid circulation, and gas potential flow are matched to yield the velocity and pressure fields. The appropriate radius for the image ring doublet is matched to the square root of We. Liquid-phase stream function, two velocity components in each fluid, and gas potential field are predicted. S Some comments on droplet drag are presented.

Background and Objectives: Spatial mapping retains the spatial distribution of radiomic features, but computational cost and fragmented software limit its use. We developed Flash-Radiomics with scalar extraction and spatial mapping, a central processing unit (CPU) backend, a hybrid Compute Unified Device Architecture (CUDA) backend, consistent feature names, and Hierarchical Data Format version 5 (HDF5) storage. Methods: We evaluated Image Biomarker Standardisation Initiative (IBSI) compliance, CPU-CUDA concordance, and end-to-end processing time. Compliance testing included 825 chapter 1 (IBSI-1) tests covering 165 high-consensus features and 323 chapter 2 (IBSI-2) tests with numerical references. Concordance testing included 1,148 scalar pairs and 93 spatial-map pairs. End-to-end processing time was measured five times per input volume of interest (VOI) size. Comparisons included the Medical Image Radiomics Processor (MIRP) and PyRadiomics for 102 shared scalar features and PyRadiomics for 93 shared spatial maps. Results: Both backends passed all 1,148 IBSI tests, and all paired results were concordant. At the largest scalar input, CPU required 76.343 s and hybrid CUDA 81.915 s; CPU was 4.7 times faster than MIRP and 190.7 times faster than PyRadiomics. At the largest spatial input completed by both backends, hybrid CUDA reduced processing time by 68.6% relative to CPU (79.280 versus 252.791 s). At PyRadiomics' largest completed spatial input, hybrid CUDA was 84.9 times faster. Conclusions: Flash-Radiomics unified standardized scalar extraction, spatial mapping, concordant CPU-CUDA results, and HDF5 storage. CPU processing time was similar or shorter for scalar extraction, whereas hybrid CUDA was faster for spatial mapping under the tested conditions.

We study the effects of conductivity variation on the Ponomarenko dynamo. Taking monotonically increasing/decreasing and sinusoidally varying radial profiles, we study the kinematic dynamo problem. The threshold of the dynamo, given by the critical magnetic Reynolds number Rm$_c$, is found to strongly depend on the form of conductivity variation near the discontinuity of the velocity field where the shear is dominant. For monotonically varying profiles in the limit of sharp variation, this threshold maps to the problem of the dynamo with a jump in conductivity, while for the sinusoidal profile with large variations/wavenumbers, the threshold increases due to effective diffusivity arising from the rapid changes in conductivity. Far from the threshold, it is found that the growth rate depends only on the local gradient of the conductivity near the discontinuity, with the opposite sign of shear and conductivity gradient leading to a larger growth rate, thereby aiding the dynamo instability in regenerating B$_{\phi}$ from B$_r$. We calculate the expression for the growth rate in the limit of large Rm$(\gg 1)$ and find that the conductivity variation leads to a modification proportional to the local gradient of conductivity times Rm$^{-1/2}$. This correction is found to depend only on the local gradient of the conductivity at the discontinuity. Similar dependencies are found for realistic, smooth velocity profiles and for different magnetic boundary conditions.

(Suzuki-)Trotter decompositions, splitting methods, (Lie) product formulae... The most common numerical methods for the time evolution of quantum systems come with many names. And they are used practically everywhere with applications ranging from the solution of classical equations of motion and various Monte Carlo simulations to the real and imaginary time evolution on classical as well as quantum computers. Here we review the state of the art of said methods, focussing especially on the progress made over the last few years. We highlight recently discovered efficient time evolution algorithms and explain how best to use them in practice. A central part of this work is the estimation of error bounds that has improved greatly within the past decade. The relevance of time evolution methods for quantum computing is discussed with a focus on noisy hardware. Finally, a comprehensive overview of generalisations, related methods and alternatives to Trotterization is provided. This includes time-dependent Hamiltonian dynamics, processed methods, multi-product formulae, symplectic integrators, TDVP for tensor networks, quantum signal processing, Crouch-Grossman methods and more. The overall perspective in this work is that of a theoretical physicist. All mathematical proofs as well as some technical details are omitted for easier readability. Instead, this review serves as a hands-on guide and, of course, as a starting point for references that provide further details.

Whether human or large language model (LLM), an agent in a discussion reads only a few of the others' contributions, bounded by cognition, context, or cost. LLM collectives can settle on a wrong consensus even when a majority starts out correct; we ask how far that reading bound alone decides the outcome. We model the bound with one number, the message capacity, which sets how many of the others' messages an agent reads, and generate the communication network from it. Over 31,824 randomized queries, we found that an 8-billion-parameter model's judgment of a claim effectively reduces to a logistic function of a weighted sum of its inbox, the update rule of a stochastic binary neuron with divisively normalized weights. From these weights and the network's degree statistics alone, the wrong consensus should become unreachable from any start once agents read, on average, fewer than 6.4 of their 31 sources. In 1,414 episodes with assigned starts the prediction failed: the correct side won in fewer than 50% of episodes from every start, and in only 28-45% when 75% of agents started correct. The failure traces to the field, the threshold that a claim's wording sets for the agent's answer before any message is read: the experimental claims' fields lay below the calibration mean, and with each claim's own field the same weights reproduce the outcomes. Reversing the wording showed that the threshold follows what a claim asserts, not whether it is true. On a second 8B model the pipeline predicts claim-dependent bistability; transition points appeared where computed, and an eight-claim calibration matched in 15 of 16 conditions. At 70B the assertion bias is not detected. Thus a collective's fate is largely set by two single-agent measurements: the threshold a claim's wording sets, and the message capacity that sets the transition point.

The classic theory of Landau damping requires the velocity distribution function (VDF) to be analytically continued into the complex plane, implicitly requiring analyticity, which imposes constraints far more severe than infinite smoothness. Yet physical plasmas—encountered in discrete simulations, noisy spacecraft measurements, or truncated fusion distributions—are inherently non-analytic. This discrepancy poses a foundational “smoothness paradox”: why does Landau damping robustly persist in systems where the mathematical prerequisite of analyticity is profoundly violated? Here we resolve this paradox by demonstrating that wave-particle interaction is governed by a time-dependent resonance width $\Delta v_\mathrm{res}\sim 1/kt$. Using a dispersion-free Lagrangian time-domain solver, we show that this finite width kinematically coarse-grains microscopic VDF defects at early times, acting as a natural low-pass filter that validates smooth analytical proxies—explaining the observed robustness. However, as $t\to\infty$ the resonance width narrows, inevitably forcing the wave to resolve exact topological non-smoothness. This late-time resolution triggers three distinct breakdowns: VDF truncation arrests the resonant phase transition to yield undamped discrete Van Kampen modes; observational noise induces transient algebraic spikes via linear phase-space aliasing; and step-like gradients drive anomalously violent reactive instability growth. We establish the breakdown timescale $t_b\sim 1/k\delta v$, where $\delta v$ is the characteristic scale of the non-smooth defect, providing a quantitative criterion that redefines the validity boundaries of analytic continuation in kinetic theory.

Posture control in slender bodies such as snakes and eels arises from the interplay between passive deformation, active internal actuation, and task-level constraints. We formulate a general framework for the selection of stable postures in active elastic filaments subject to distributed forcing from gravity and fluid drag, by combining the constraints of mechanical equilibrium with optimal control theory. Our theory leads to a minimal description in terms of parameters governing the competition between hydrodynamic and gravitational loading, elasticity, and activity. We show that posture selection reflects a trade-off between control cost, function and dynamical stability, leading to the coexistence of distinct solution branches and abrupt transitions between them. Applying the theory to sessile eels in flow, we recover the experimentally observed transition from upright to reclining postures and predict scaling laws for body shape and exposed length. More generally, our results provide a unified perspective on how active filaments can regulate geometry to maintain function in external fields, with implications for biological and artificial systems.

Precision measurements with molecules require molecular beams with high flux and narrow divergence. Here we present the design, implementation, and characterization of an electrostatic quadrupole lens (EQL) for focusing a cryogenic beam of $^{205}$TlF molecules. The EQL consists of four electrodes operated at spatially alternating potentials up to $\pm 30$ kV. This configuration generates a transverse restoring force that focuses molecules prepared in selected manifold of hyperfine states. At the optimal applied voltage, the EQL increases the detected molecular signal by a factor of $14.4(4)$ at the current detection position. The measured lens gain, transverse Doppler spectra, and transverse spatial profiles are all reproduced by trajectory simulations using independently measured beam parameters as input. Based on this agreement, we project a gain of $16.5(8)$ for the full $7.9~\mathrm{m}$ CeNTREX beamline. These results establish the EQL as a key component for increasing sensitivity in precision experiments using cryogenic beams of polar molecules.

We present a theoretical study of a semiconductor photon-pair source based on a radiative cascade enabled by a permanent exciton dipole. The source consists of a GaAs quantum dot placed between a metal nanoparticle and a mirror. The dot exciton and the localized electromagnetic mode mix to form upper and lower polaritons. Without a permanent dipole, a symmetry separating states with even and odd excitation numbers forbids photon emission between the polaritons. Separation of the mean electron and hole positions gives the exciton a permanent dipole and breaks this symmetry. The upper polariton can then emit an idler photon as it decays to the lower polariton. The lower polariton can emit a signal photon as the system returns to its ground state. Using an effective model, we calculate the probability that a prepared upper polariton emits both photons through the metal antenna. We also analyse fluctuations in the emitted photon counts and correlations between the two emission channels. The calculation establishes an operating principle for assumed emitter properties and optical loss rates. Whether the device can be built and its photon correlations measured remains open.

Many proteins function through transitions between conformational states, yet rare states are rarely sampled by diffusion models trained on an equilibrium ensemble, demanding better sampling methods. We introduce METALICA, which implements Metadynamics on a pretrained diffusion model via Replica Exchange. It accumulates a bias potential along a Collective Variable, repels new samples from previous ones through biased sampling, and reweights samples onto the unbiased distribution. METALICA holds one replica per diffusion level, forming a Markov Chain that evolves through inter-replica communication and is refined in place as the bias grows. METALICA is the dual of sequential control, in which Sequential Monte Carlo parallelizes the sampler over a batch of particles. Parallelism over the levels of the diffusion-time schedule instead allows METALICA to generate samples from long chains, essential for the discovery of rare events, with accuracy set by run length rather than by the memory available. We validate on a bimodal target with known free energies, then apply METALICA to the unfolding of a protein. At a budget for which sequential control yields no unfolded structure, METALICA populates the basin and resolves a second free energy minimum.

Bolometers transduce incident electromagnetic radiation into measurable electrical signals via radiation-induced heating in thermo-resistive materials. They are uniquely capable of detecting low-energy photons without cryogenic cooling, and are widely deployed for uncooled long-wave infrared (LWIR) radiation detection and thermal imaging. Although their fundamental detection limit is set by the thermodynamic fluctuations, state-of-the-art uncooled bolometers still operate well above this limit due to the presence of Johnson noise, 1/f noise and noises from the readout circuits. Here, we address this challenge by introducing a new uncooled LWIR bolometer concept—the silicon avalanche transition edge (SATE) bolometer. Operating near the steep current transition edge associated with avalanche breakdown, the device exhibits an ultra-high, positive temperature coefficient of resistance (TCR) of 330 %/K, greatly suppressing the impacts of other noise sources. Even without any thermal insulation structures, the SATE bolometer delivers a high room-temperature responsivity up to 160 mA/W for 9.5 $\mu$m radiation, a noise equivalent power of 370 pW/$\sqrt{\mathrm{Hz}}$, and a strong electro-thermal feedback enlarged bandwidth of 77 kHz—performance unattainable with conventional bolometer materials with a TCR of $-1\sim-3\%$/K. Our work establishes a promising thermo-electric transduction mechanism toward high-sensitivity, high-speed room-temperature thermal imaging and infrared spectroscopy using CMOS technology.

We study wetting on a doubly periodic rough surface in three dimensions. Although the liquid-vapor interface meets the solid at the local Young's angle, microscale roughness can cause the macroscopic apparent angle to differ substantially from this value. We formulate the directional contact angle hysteresis (CAH) interval in terms of apparent angles associated with pinned microscopic configurations. To approximate its receding and advancing endpoints, we evolve capillary mean curvature flow (CMCF) toward extremal stationary states. Computing these states is difficult because the pinning that produces hysteresis is generated at the scale of the roughness, whereas the apparent angle is only meaningful at the macroscopic scale, so a single uniform grid must resolve both. We therefore introduce a two-scale alternating (TSA) method based on a Schwarz decomposition: a Merriman-Bence-Osher (MBO) diffusion-generated scheme resolves the contact-line near region, while a linearized minimal-surface problem updates the far region. For an idealized reference iteration, we prove decay of an approximate interfacial energy. Numerical experiments on a representative doubly periodic surface show a strongly anisotropic CAH interval whose width varies by more than a factor of three with contact-line orientation and changes sharply near the diagonal directions. Because a stationary droplet must meet the solid at an apparent angle inside this interval, the computed anisotropy constrains which macroscopic wetted regions the surface can support; it is consistent with a square-like stationary droplet whose sides align with the diagonal directions.

Motivated by the Planckian thermalization rate $\Gamma \sim T$ observed in the two-body interacting SYK model, we study thermalization in the $q/2$-body case. Previous studies of such systems have established the notion of instantaneous thermalization to leading order in $1/q$. It was conjectured that the thermalization may still be Planckian but with a divergent rate $\Gamma \sim T q$, explaining the “instantaneous” part. For an analytically and numerically tractable system, we calculate the effective temperatures after a quench at time $t = 0$ and indeed find a Planckian rate, albeit with the unexpected decaying behavior $\Gamma \sim T q^{-1} $. This is contrasted with the behavior of the causal Green's function $\mathcal{G}(t_1, t_2)$, which instantly acquires a thermal form in the two-time plane block $t_1, t_2 > 0$. The resulting picture is that instant thermalization is a meaningful concept only for this block, while the off-diagonal blocks $t_1 \cdot t_2 < 0$ are inherently non-thermal at any $q$. Since the effective temperature is obtained from correlations spanning all blocks, it inherits a finite rate set by the off-diagonal. We illustrate this directly by studying the non-thermal correlations' time dependence.

This study aims to improve the directional sensitivity of magnetic resonance hydrophone (MRH) methods and allow for detection and quantification of waves traveling at any angle relative to the MRI bore-axis. Doing so may better integrate MRH technology into transcranial focused ultrasound neuromodulation therapies. Existing MRH implementations only encode acoustic waves propagating along the MRI bore-axis, precluding use with wide aperture transducers or temporal skull windows. This study expands the MRH technique into a MR-based Omni-directional Hydrophone (MRbOH) that can quantify the magnitude pressure and phase of waves propagating at any angle. The MRbOH method formulates a system of equations around uniquely sensitized images that, when solved, introduce sensitivity to oblique acoustic waves. The method was tested experimentally in a gel phantom that was insonated at $0^o$, $45^o$, and $90^o$ relative to the MRI bore-axis. The method reconstructed pressure maps at all three angles of propagation, including features such as peak pressure, partial reflections, and beamwidth. The MRbOH method measured an average beamwidth of 16.2 mm while the hydrophone measured a beamwidth of 14.5 mm. Average hydrophone-measured pressure within a region of interest was 416.19 $\boldsymbol{\pm}$ 78.07 kPa. Average MRbOH measured pressure in the same region at $0^o$, $45^o$, and $90^o$, respectively, were: 285.5 $\boldsymbol{\pm}$ 49.5 kPa, 193.13 $\boldsymbol{\pm}$ 43.55 kPa, 194.7 $\boldsymbol{\pm}$ 47.38 kPa. In addition, the study presents and experimentally verifies a statistical noise model that predicted the mean with $R^2 = 0.85$, and standard deviation with $R^2 = 0.83$.

Quantum machine learning offers a compelling representational perspective: angle-encoded states inhabit Hilbert spaces in which periodic similarities and interactions can be expressed naturally. Realizing this perspective for visual recognition remains difficult, however, because present quantum neural networks are constrained by limited qubit counts, costly circuit simulation and measurement, noise, and unstable optimization on noisy intermediate-scale quantum devices. We investigate whether useful structural ideas from quantum models can instead be realized as scalable classical Transformer operations. We introduce QiT, a Quantum-inspired Transformer for vision tasks with three components: (i) angle-inspired encoding that maps image tokens to learned trigonometric Hilbert-space features analogous to quantum rotation-based state encoding; (ii) self-attention over these periodic features, inducing a classical cosine kernel approximated to quantum fidelity kernels; and (iii) gated multiplicative emulation, a trainable classical surrogate for interaction terms found in variational circuits. All components are differentiable tensor operations, so QiT claims neither quantum computation nor quantum speedup and retains the $\mathcal{O}(N^2D)$ attention complexity of a standard Vision Transformer. Across image-classification benchmarks, QiT is competitive with a matched classical Transformer while avoiding the severe runtime cost observed for a small simulated quantum Transformer. QiT-B reaches 78.3% ImageNet-1K top-1 accuracy with 45.7M parameters and 11.5 GFLOPs. These results position QiT as a scalable baseline for isolating and evaluating quantum-motivated inductive biases in visual recognition.

We combine the Briegel–Englert damping basis of a lossy cavity mode with the permutation-invariant Liouville basis of \(N\) identical, incoherently pumped two-level emitters. The resulting Liouvillian is exactly block tridiagonal in a single radial field index, with atomic blocks of dimension \(\binom{N+3}{3}\). The stationary state follows from a matrix continued fraction whose asymptotic closure is a linear matrix equation that we prove to be uniquely solvable throughout the dissipative regime \(A>0\), and the same construction in the coherence-one sector yields the emission spectrum. The method is validated against direct diagonalization, weak-pump perturbation theory, and closed-system spectra, reaches \(N=16\) in tens of seconds in the few-quanta regime, and has a quantified precision limit at large photon number. We use it to derive an exact two-atom photon-balance identity that isolates the cavity-induced pair coherence and relates it to a singlet–triplet population difference; to establish an exact pump-order hierarchy of connected correlations for a zero-temperature cavity and a parity property of the minimal collective-spin sector; and to benchmark the second-order cumulant closure used in few-emitter laser theory, which we find to be semi-quantitative for the photon number but to predict the wrong sign of the inter-emitter coherence above inversion. In a good-cavity regime the exact solution shows near-Poissonian statistics and strong line narrowing for two and three emitters.

Labor strikes do not necessarily lead to complete institutional disruption, particularly when non-striking sectors maintain part of normal activities. We propose a minimal dynamical model to investigate how such residual activity affects the persistence of labor conflicts. The model couples strike participation, institutional response, and overall functionality through two competing mechanisms: a direct suppressive effect of residual activity on strike participation and an indirect effect arising from the reduced institutional pressure to resolve the conflict. Analytical calculations reveal a counterintuitive regime in which increasing residual activity increases, rather than decreases, stationary strike participation. We characterize this behavior through a strike-response susceptibility and derive an exact compensation threshold separating the conventional regime from a resilience-paradox regime. At the threshold, the two mechanisms exactly balance, making stationary strike participation independent of residual activity. Numerical results confirm the analytical predictions and illustrate the underlying mechanism. Our results show that institutional resilience can have an unintended dynamical consequence: by absorbing part of the disruption generated by a strike, continued operation may reduce the urgency of institutional response and thereby favor conflict persistence. This provides a simple example of how individually stabilizing processes can collectively generate counterintuitive outcomes in complex social systems.

A continuous cryogenic-pellet injector has been used to realize long-pulse high-performance plasmas in Wendelstein 7-X (W7-X). A hydrogen ice pellet deposits particles directly in the confined region. If the particles are deposited sufficiently far inside the plasma, they produce a density gradient that suppresses ion-temperature-gradient turbulence and improves plasma confinement. However, after multiple pellets have been injected and the plasma density and temperature have increased, the plasma performance begins to saturate. In this work, we analyze multiple pellet-injection experiments conducted in 2024 and 2025, during which the injected pellet sizes varied unintentionally. This analysis reveals a positive correlation between pellet size and the quasi-steady-state stored energy of W7-X plasmas. Although this pellet-size dependence can be understood qualitatively from pellet-ablation physics, the measured deposition position differs quantitatively from the neutral-gas-shielding (NGS) model prediction. This discrepancy suggests significant inward transport of the pellet cloud. The trend identified here suggests that injection of even larger pellets could further improve plasma performance.

Traditional theoretical treatments of ferroelectricity do not straightforwardly extend to sliding ferroelectrics, which are increasingly-studied layered materials where a switchable electrical polarization is controlled by two-dimensional relative motion of the stacked layers. Therefore, in-depth analyses of the underlying processes which dictate their polarization behavior remain challenging. In this paper, we present a comprehensive approach for identifying the symmetry-adapted microscopic parameters which are responsible for driving the emergence of this polarization. First, we outline our approach, which appeals to group theory arguments and the distortion of Wannier orbital densities to connect macroscopic symmetries to the microscopic electronic distortions which dictate the appearance of ferroelectricity. Then, we illustrate this process by using density functional theory to apply our strategy to honeycomb bilayer systems, including hexagonal boron nitride. In this way, we find that combinations of dipole-like and quadrupole-like distortions of lone pair electron orbitals control electronic reorganization, and by extension, ferroelectricity in such systems.

Most molecular transitions occur on timescales far beyond direct molecular dynamics simulations. The committor, the probability that a configuration reaches a product state before a reactant state, is a central kinetic statistic, providing a mechanism-independent reaction coordinate and a foundation for transition path theory and the calculation of rates. This review surveys modern approaches for estimating the committor and related kinetic statistics from molecular simulations, with an emphasis on self-supervised methods that learn solutions of their defining dynamical equations rather than relying on labeled shooting data. We develop a common operator viewpoint connecting generator-based partial differential equations, variational principles, Markov state models, dynamical Galerkin approximation, and neural networks. Empirical and theoretical evidence points to the efficiency of these methods. We provide theoretical and practical guidance for realizing their full potential in applications, including strategies for treating non-Markovian effects and for sampling. We conclude by identifying opportunities for further research, including connections to reinforcement learning and generative modeling.

Capillary forces are commonly regarded as an energetically closed channel in multiphase turbulence, redistributing kinetic energy across scales without net gain or loss. Here we show that this picture breaks down in bubble-laden turbulence when short-range near-contact interactions are active. A spectral analysis of the kinetic-energy budget reveals that the cumulative capillary power does not vanish at statistical stationarity, but instead retains a finite negative residual. This apparent imbalance is exactly compensated by the work of short-range repulsive forces, which is negligible at large and intermediate scales and becomes positive only at small scales. Near-contact interactions therefore open a distinct small-scale pathway in the interfacial energy transfer, rather than acting as a mere regularization of unresolved thin films. The proper scale-by-scale description is thus an extended interfacial transfer, combining capillary and near-contact work, rather than a purely capillary one.

Achieving robotic-assisted string assembly has been a longstanding objective in superconducting cavity pro-duction to improve precision, repeatability, and through-put while reducing operator-dependent variability. At Fermilab, robotic systems have been successfully deployed for the installation of individual components on SSR2 cavities inside a cleanroom environment. The single-cavity installations validated the feasibility of robotic techniques and provided confidence to extend automation to the assembly of a full prototype cavity string. Leveraging lessons learned from earlier operations, the robotic system was adapted for the string assembly. This work describes the robotic-assisted assembly process in detail, including alignment strategies for coupler flanges, torque control for bellows connections, and mitigation of particulate generation in cleanroom conditions. Performance metrics of the cryomodule are presented, together with an analysis of improvements needed for robotic assembly. The effort also represents a broader R&D initiative at Fermilab to the long-term goal of scalable SRF cryomodule production.

We present psi4-cbo, an open-source extension of the Psi4 program for simulations within the cavity Born-Oppenheimer Approximation (CBOA). By treating the cavity photon mode on the same footing as the nuclear coordinates, psi4-cbo incorporates light-matter coupling into standard electronic structure workflows. These workflows include self-consistent field calculations, response theory, analytic gradients, joint Hessians, and geometry optimization. The package is designed for reproducibility and is documented with working examples for its main workflows. To evaluate the approximations inherent to the CBOA framework, we use an exact \gls{qedfci} reference. Resolving the correlation energy into electron-electron and electron-photon channels enables us to precisely determine the point at which the CBOA becomes quantitatively sufficient. Additionally, we highlight that, since self-consistent treatments dress the cavity modes, satisfying experimental resonance conditions is method-dependent. As a practical application, we investigate the chromophore acrolein under vibrational strong coupling and detail how to locate resonances on the dressed photon modes rather than the bare molecular bands.

Detection efficiency in gated-mode single-photon avalanche detectors recovers gradually after each gate edge, limiting attainable count rates, yet quantitative recovery models exist only for free-running operation. We extract the gated recovery time constant of a free-running InGaAs/InP detector at 1550 nm by sweeping the gate frequency from 100 kHz to 1 MHz and globally fitting count rates across four dead times, requiring neither a pulsed laser nor a time-to-digital converter. The recovery time decreases linearly with detection efficiency, from 301 to 161 ns between 10 % and 25 %, at 9.3 ns per percentage point. We further resolve a periodic count-rate modulation consistent with bias-dependent capacitive gate feedthrough.

Micron-sized particles moving through a fluid are subject to viscous resistance and thermal fluctuations. Beyond steady Stokes friction, colloids also exhibit hydrodynamic memory effects arising from conservation laws of the surrounding fluid. Although fluid-flow problems in complex geometries and confinements are often highly involved, numerical or approximate solutions can be obtained; translating these solutions into closed-form equations of motion for individual colloids, however, is rarely possible. Here, we develop a theoretical framework that provides both underdamped and overdamped colloidal dynamics from the solution of an arbitrary flow problem: (i) Using the Lorentz reciprocal theorem, we express the colloidal equation of motion in terms of the geometry's Green's function and the fluid-flow profile. This formulation yields both the corresponding Stokes drag as well as a Basset-like hydrodynamic memory contribution. (ii) As colloid inertia is often negligible, we furthermore derive the corresponding overdamped (colloid-inertia-less) limit, which inherits the Stokes and Basset-like resistances and additionally gives rise to a spurious drift. We propose applications of this framework to passive and active particles subject to involved confinements and problem geometries.

Micron-sized colloid particles diffusing through a fluid experience hydrodynamic inertial and memory effects, the latter causing velocity autocorrelation to decay as a power law. At the same time, many theoretical descriptions treat colloidal diffusion in a fluid using overdamped Langevin dynamics for its convenience, eliminating velocity, omitting inertia, but also ignoring the power-law memory. In this Letter, we show that hydrodynamic memory survives in the overdamped (colloid-inertialess) limit. By identifying the dimensionless parameter controlling the crossover between early- and late-time dynamics, we derive in closed form the overdamped Langevin equation in the presence of hydrodynamic memory. This provides a theoretical framework for realistically describing colloidal dynamics in a fluid, and establishes a rigorous basis for the positional memory observed in high-resolution experiments. Our theory predicts that hydrodynamic memory becomes increasingly pronounced for smaller particles and under stronger external forcing, and offers experimental probes for the crossover from conventional exponential relaxation to memory-dominated power-law dynamics.

The proton temperature anisotropy in the solar wind is bounded by the thresholds of pressure-anisotropy-driven kinetic instabilities, and the distance at which the plasma settles from these thresholds is thought to be regulated by compressive fluctuations through the fluctuating anisotropy effect. We test whether the level of Alfvénicity is associated with this distance in the slow solar wind. Using five years of Wind/SWE bi-Maxwellian proton measurements (2004–2008), we separate slow-wind intervals into Alfvénic and non-Alfvénic populations on the basis of normalized cross helicity and residual energy. We compare their magnetic compressive fraction and normalized compressive amplitude, and measure their proximity to marginal stability in the plane of parallel proton beta and temperature anisotropy using the maximum growth rate over the scanned parallel wavenumbers, $\gamma_{\parallel,\max}$, from a Vlasov dispersion solver. At low matched parallel beta, the Alfvénic slow wind has lower normalized field-strength fluctuation amplitude and reaches the parallel-mode marginal-stability criterion more often than the non-Alfvénic slow wind. This association is consistent with a weaker fluctuating-anisotropy effect in the Alfvénic slow wind, but does not establish a causal relation.