Computational Physics
SIREN: A nonlinear Rankine-source boundary element solver for the stationary motion of a marine vehicle in calm water
Daniele Peri
SIREN (Ship Inviscid Resistance and Elevation eNgine) is a Rankine-source panel solver for the steady wave resistance of a ship, in the tradition of Dawson's method. The free-surface condition is linearised about a base flow, and the linearisation is iterated. In the present formulation the base flow is the solution of a Neumann problem on the actual boundary: sources on the entire hull, wet and dry, and on the free surface panels, with impermeability imposed on both, so that the free surface acts as a rigid lid at the position it currently occupies. This replaces the classical double-body flow, whose image about z=0 is meaningful only for a flat surface and a hull cut at z=0, and it removes the need for desingularised free-surface panels. In the non-linear iteration the free-surface panels are moved rigidly in the vertical to the relaxed wave elevation at their centroid, the hull panels are marked wet or dry against the moved surface, and the base flow is recomputed on the moved geometry; impermeability applies to the whole hull regardless of this marking, which is used only to select which panels enter the force integral, and under-relaxation is confined to the passes where the non-linear correction accumulates without being reset. The radiation condition is imposed by a one-row upstream shift of the collocation points, and the wave resistance is obtained by pressure integration and, independently, by transverse wave-cut analysis.
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Cellular Automata and Lattice Gases
Towards New Parity Rules with Asynchronous Updating Inspired by Fatès's Rule
Rolf Hoffmann
The parity problem in 1D Cellular Automata is a classifier based on a local rule. If the number of ones in a ring of binary
cells is odd then the automaton shall converge to all-one (11...11) else to all-zero (00...00). The objective is to find rules that are related to Fatès's Balanced Rule F but use less active neighborhoods (actions). The method is to analyze the effect of each actions and to find a functioning subset of the 12 actions used in rule F. New rules called HA, HB, HC, HF are defined with 10, 6, 4, 8 actions. Rule HC and HF need only three inputs whereas all others need four. The classification time of the rules was determined by averaging over many simulation runs with random initial configurations. It is almost the same for the rules HA and F, and is longer for the rules HB, HC, HF. In addition, the rule HD is defined, which updates three
cells in parallel and works faster. In future work, the functioning and performance of the proposed rules should be treated in a more formal way, and related rules (also with different update schemes) could be considered.
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General Physics
Shadow signatures and near-horizon energy accumulation in coherent quantum sine-integral black holes
A. Errehymy, Y. Khedif, M. Daoud et al. (+4 more)
Quantum modifications of black hole spacetimes can lead to observable departures from the predictions of classical general relativity, particularly in the strong-
gravity regime near the event horizon. In this context, the coherent
quantum black hole model introduces a sine-integral correction to the gravitational potential, characterized by a coherence scale \(R_s\), which softens the central singularity and alters the near-horizon geometry. Motivated by the growing precision of black hole imaging and strong-field observations, we explore how these
quantum-induced effects influence
photon motion and the resulting shadow structure. Considering representative values within the interval \(R_s \in [0.5M, 1.2M]\), we show that the
photon sphere shifts inward while the critical impact parameter decreases, reaching values such as \(b_{\rm crit}\approx 4.764M\) for \(R_s=0.5M\). Consequently, the shadow radius becomes systematically smaller and develops a more intricate structure than in the Schwarzschild case (\(b_{\rm crit}=3\sqrt{3}M \approx 5.196M\)). The analysis of the corresponding intensity distributions also reveals a pronounced enhancement of radiation near the shadow boundary, especially for intermediate coherence scales. This feature can be attributed to
photons remaining longer within the modified near-horizon region before escaping toward distant observers. Such an increase in brightness may therefore provide a possible observational signature of
quantum corrections at horizon scales. Furthermore, although the geometry allows radiation and energy to accumulate around an effective horizon surface, its response to perturbations differs from that expected for compact objects with stable light rings. Instead of contracting under backreaction effects, the accumulation surface shifts outward.
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All authors A. Errehymy, Y. Khedif, M. Daoud, B. Turimov, S. Usanov, Z. Yasakov, F. Turaev
Fluid Dynamics
Impact of bubble nucleation on the functioning of the pulsating heat pipe: numerical simulation study
Vadim Nikolayev and Iaroslav Nekrashevych
In this communication, we discuss results obtained with the numerical in-house PHP simulation code CASCO (French abbreviation for Advanced PHP simulation code). The aim is to study the impact of bubble generation (boiling) on the established oscillation of a PHP with a high turn number (10-turn water-copper tubular PHP with independently heated turns in the evaporator region). We vary the nucleation barrier value, i.e. the local superheating $\Delta$Tnucl at which the nucleation occurs and the heat load Pe; other simulation parameters are kept constant. The PHP heat transfer performance is evaluated with the PHP thermal resistance Rth for both horizontal and vertical favorable PHP orientation. Since the bubble generation plays a positive role for the PHP functioning, one expects that the function Rth($\Delta$Tnucl) monotonously increases. This is true for high $\Delta$Tnucl. For small $\Delta$Tnucl, the Rth($\Delta$Tnucl) function is decreasing, thus a minimum occurs. It appears because of a transition between the regimes of stable PHP functioning. The regimes strongly differ by the average penetration of
liquid plugs into the evaporator. For horizontal PHP, these regimes correspond to the intermittent and continuous oscillations. The regimes are discussed and the regime map in the coordinates Pe -$\Delta$Tnucl is obtained.
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Statistical Mechanics
Information Entropy and Dissipation Potential in Stochastic Nambu Nonequilibrium Thermodynamics
So Katagiri and Tatsuaki Wada
We investigate the relationship between the dissipation potential $S_{\mathrm{NB}}$ and information
entropy in
stochastic Nambu nonequilibrium thermodynamics (NNET). Starting from pure
diffusion, gradient-flow systems, and systems with
Hamiltonian rotational currents, we derive the stationary distribution of the Fokker–Planck equation including a Nambu flow. We show that, when the Nambu flow preserves the dissipation potential and an Einstein-type relation holds between the
diffusion matrix and the transport tensor, the stationary distribution is governed by an exponential weight determined by $S_{\mathrm{NB}}$. Consequently, the local self-information is directly related to the dissipation potential, demonstrating that $S_{\mathrm{NB}}$ should not be identified with the Shannon
entropy itself but instead serves as the stationary quasipotential governing the nonequilibrium steady-state distribution. Using the distinction between the thermodynamic
entropy and the dissipation potential established for an open gas–piston system coupled to a thermal bath and an external-pressure reservoir, we further clarify the Massieu interpretation of $S_{\mathrm{NB}}$, introduce a Nambu canonical distribution, and derive the covariance of fluctuations within the saddle-point approximation. These results provide a statistical interpretation of the NNET dissipation potential by identifying it as the stationary quasipotential underlying nonequilibrium steady states.
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Quantum Physics
The Quantum Sphere: A Physically Realizable Optimization Benchmark with Provable Linear Convergence in White- and Black-Box Settings
Ofer M. Shir
We revisit an established
Quantum Control objective, characterize its exact local metric geometry, and reposition it as a rigorous
benchmark for Search and Optimization. The trap-free
topology of the landscape, established two decades ago, guarantees unhindered optimal pathways, but global
topology alone does not govern convergence speed. Although the so-called
Quantum Sphere is defined by the fourth power of the control field, we show that its yield gap admits an exact representation as a nonnegative linear combination of $\sin^2$ terms. From this single identity, we derive a two-sided quadratic sandwich with ratio $4/\pi^2$ on a certified, worst-case quarter-wave region, proving the optimal peak nondegenerate modulo its affine gauge and well-conditioned. For white-box optimization, on a halved (eighth-wave) region, the objective satisfies a Polyak-Łojasiewicz inequality with an explicit constant, granting Gradient Descent a linear rate of $1 - 16/(\pi^4\kappa_r)$, where $\kappa_r$ is the condition number of the relevant Hessian block. For black-box optimization, we prove that the elitist single-parent
Evolution Strategy converges linearly, almost surely and in expected hitting time, from a certified sublevel set, despite the landscape's continuous gauge
symmetry and its
lattice of periodic optima; the certified level is explicit whenever the landscape is trap-free, and near the optimum the strategy provably sees only the quadratic tangent of the peak. Systematic numerical simulations corroborate the theory. Finally, we show that additive input (actuator) noise reweights each term of the representation by a Debye-Waller factor without disrupting the landscape's structure, and outline open challenges: output (signal) noise, far-field plateau escape, angular-synchronization certificates, and another physically scalable
benchmark (SHG with Glass).
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Chaotic Dynamics
Automated discovery of dimensional reductions in coupled oscillators
Dishant Sisodia and Sarika Jalan
There have been persistent efforts to uncover low-dimensional macroscopic dynamics in large systems of interacting microscopic units, in which underlying physical principles govern their collapse onto low-dimensional
manifolds. Here, focusing on interacting phase oscillator systems, we show that an unsupervised autoencoder framework can determine their intrinsic dimensionality, in agreement with the predictions of Watanabe-Strogatz theory. Systematic sweeps over the latent dimensions identify the analytically predicted reduced dimensions, while supervised regression confirms that the learned latent variables capture the full information contained in the theoretical Watanabe-Strogatz coordinates. We demonstrate this capability for two prototype systems: Kuramoto oscillators and resistively loaded Josephson junctions. We further establish the diagnostic specificity of the framework by showing that systems lacking such reducible dynamics do not exhibit a sharp dimensional reduction.
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Soft Condensed Matter
Predicting and extending the bubble-free operating limit of capillary-fed water electrolysis
Farkhondeh Khodabandeh and Zhengmao Lu
Gas bubbles impose large penalties in water electrolysis at industrially relevant rates. Capillary-fed electrolyzers greatly mitigate them by wicking electrolyte to electrodes and venting gas from the backside, but only below a threshold current density. We show that the separator pore size sets this threshold through two opposing effects: smaller pores raise the supersaturation required for nucleation but reduce the permeability for electrolyte replenishment. A coupled electrochemical-transport model, anchored to a single measured onset, quantifies both mechanisms across 0.1-8 $\mu$m pores. Experimentally, reducing pore size from 8 to 1.2 ${\mu}$m raises the bubble onset limit from 0.18 to 1.73 A cm$^{-2}$ and lowers
cell voltage by 0.11 V at 1 A cm$^{-2}$, primarily by suppressing bubble-induced overpotential. At 0.45 ${\mu}$m and below, the replenishment limit takes over and the
cells dry out before bubbles form. Our findings establish the bubble-free operation limit as designable rather than purely empirical.
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Atmospheric and Oceanic Physics
OceanMind: A multi-agent AI system for ocean diagnosis
Fan Zhang, Weicong Cheng, Yuheng Chen et al. (+6 more)
Time-dependent, three-dimensional (3D) oceanic multi-variables define coherent states of the evolving ocean to facilitate ocean diagnosis and advance ocean science to better inform environmental and hazard management. However, extracting quantitative evidence from these variables requires substantial and complex analytical effort. We introduce OceanMind, a multi-
agent AI system that directly couples large
language models (LLMs) with comprehensive time-dependent 3D ocean states for swift and effective diagnosis. OceanMind organizes the analytical process into four coordinated complexity stages: Query Routing, Skill-based Planning, Tool Execution, and Evidence-based Summary Generation. Specialized
agents interpret user requests, construct and execute multi-step computational workflows, and synthesize quantitative evidence. To ensure reliable workflow construction, 63 reusable ocean-specific analysis skills serve as procedural manuals that guide the LLM
agent in selecting data, conducting diagnostics, and applying analytical tools. With reflection and replanning mechanisms that use execution feedback to repair invalid plans, OceanMind ensures reliable analysis workflows across diverse needs. On a
benchmark of 240 computational-workflow queries spanning the four stages, OceanMind outperformed general ReAct
agents with the same registered tool pool, achieving relative improvements of 41.2% in effectiveness and 21.5% in efficiency. Beyond the
benchmark, OceanMind reproduced published oceanic diagnostics, validated hypotheses, and supported environmental decision-making over global oceans. Overall, OceanMind advances LLMs by integrating them with time-dependent 3D ocean analysis, enabling scientific interpretation and enhancing formulation of environmental policies based on quantitative ocean evidence.
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All authors Fan Zhang, Weicong Cheng, Yuheng Chen, Hiuseut Kung, Ying Zhang, Aixi Han, Quanjia Zhong, Can Yang, Jianping Gan
General Relativity and Quantum Cosmology
Nonlinear completions of the Ricci coupling in black-hole scalarization
Subrat Parida
We study spontaneous scalarization of static, spherically symmetric black holes in scalar–Gauss–Bonnet
gravity with a
Ricci coupling $F=1 \beta\phi^{2}/4+\gamma\beta^{2}\phi^{4}+O(\phi^{6})$ that nonlinearly completes the quadratic one. For arbitrary couplings and potential, we derive the near-horizon regularity condition and horizon
curvature invariants in closed form; scalarized branches terminate where this condition degenerates, at finite horizon
curvature. A weakly nonlinear expansion fixes the bifurcation direction exactly: for a massless scalar, its governing coefficient is quadratic in $\beta$, changes sign at $\beta=1.1156$, and depends linearly on a quartic self-interaction. At equal horizon values of the scalar, completions differ in mass, to leading order, in proportion to $\gamma$. A radial-perturbation master equation for arbitrary couplings confirms the exchange of stability at the bifurcation and turning points. Consequently, the domain of radially stable black holes shrinks as $\gamma$ increases over the range studied; it is smaller for the exponential completion than for the quadratic truncation.
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Statistical Mechanics
Harnessing Measurement Error as a Thermodynamic Resource in Two-Reservoir Information Engines
Yang Xiao, Qian Zeng and Jin Wang
In general, measurement error constrains the performance of information engines. However, this may not hold universally. In this work, we propose a class of two-reservoirs information engines (TRIEs) with a two-level system and demonstrate that the monotonic relationships between the work output, the efficiency, as well as the work fluctuations of the TRIEs and measurement error are determined by the demon's control parameters. Utilizing this, we establish the conditions that allow the TRIEs to generate useful work under any level of measurement error, and identify the regimes in which these performance parameters can be optimized simultaneously by the measurement error. Furthermore, we demonstrate that when the demon's energy cost is supplied solely by the cold reservoir, the efficiency that accounts for this cost can surpass the standard Carnot bound without violating the second law. Finally, we design a dual Otto cycles TRIE and provide an experimental scheme for its implementation based on a trapped $^{40}\mathrm{Ca}^+$ ion. Significantly, our results can be applied to the multi-level system information engines.
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High Energy Astrophysical Phenomena
Generation of UL-Axions by a Kerr Black Hole. Part III: The fate of its Axion Wind
Guy Pelletier
In two previous articles, we have explained how super-massive Kerr Black Holes in the
nucleus of an active
galaxy or
quasar can generate a large amount of
axion particles in their magnetosphere. In that third part, we explore the possibility of observable dynamics resulting from some interaction of an
axion wind with the baryonic matter and the axionic Dark Matter in the surroundings of the closest AGNs. The
axions that we have considered are the same as those Ultra Light
Axions favored in cosmology as the main content of Dark Matter and which form Bose-Einstein Condensates, supporting a gigantic Schrödinger wave. In the paper we investigate what can be the nature of the interaction of the
axion wind with the
plasma and the hydrogen gas in the host
galaxy and its
halo. Despite the intriguing nature of a possible interaction, we show that only a kind of gravitational Tcherenkov-Vavilov effect can be efficiently operating with acoustic waves through a streaming instability. The instability is fast enough to operate efficiently in the central region of the host
galaxy up to parsec scales and makes Lyman-alpha diagnostics of the acoustic waves of hydrogen gas and
plasma possible, as well as the detection its hyperfine emission at 21 cm. However it turns out that scattering of the
axion wind is very long and thus these winds could travel over very large distances and cross other
galaxies. And then the wind travels without significant loss along its
halo and even beyond up to
quantum thermalization, which makes possible direct detection of these
axions by conversion into gamma-rays on Earth, opening a possible
axion astronomy in the local Universe. The parameters of Messier 87 indicate that it is a good candidate for developing these investigations both through the conversion of
axions into gamma-rays and Lyman alpha diagnosis in the bulge.
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Data Analysis and Statistics
Developing Multi-Dimensional, Sequential sWeighting Routines for Reaction Selection with Emphasis on Kaon Identification at CLAS12
A. Acar, M. Bashkanov, D.P. Watts et al. (+1 more)
In
nuclear and particle physics experiments, event selection is often a multidimensional classification problem which involves several correlated observables. The widely used sWeight technique provides a statistically rigorous means of separating signal and background using discriminating variables, but its conventional formulation is generally applied to a single discriminating variable or a simultaneous multidimensional fit. In this paper we present a novel extension of the widely used sWeight technique, in which an arbitrary number of discriminating variables can be used to construct a multidimensional sequential framework. This method allows the extraction of signal distributions in controlled variables in a rigorous way. Particular
attention is given to the treatment of signal and background correlations, as well as the propagation of statistical uncertainties through successive weighting stages. The method yields high-purity signal samples even in the presence of large and correlated backgrounds. As a
benchmark application, the validity of this technique is demonstrated on kaon identification in a
dataset collected with the CLAS12 detector at the Thomas Jefferson National Laboratory for cascade
baryon searches. The final workflow is shown to be robust and consistent across different run periods and beam/detector conditions, demonstrating minimal systematical uncertainties associated with the method. Statistical uncertainties are proved to be evaluable using a bootstrap-based procedure. The method provides a general framework for multidimensional event weighting and is intended for application in complex analyses requiring robust signal selection in the presence of complex correlated backgrounds.
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All authors A. Acar, M. Bashkanov, D.P. Watts, M. Nicol
Instrumentation and Methods for Astrophysics
A Missing Latent, Not a Missing Simulator: Radius-Augmented Inference for Real JWST Retrieval
Angshuman Chakravertty and P V V Raj
Amortized simulation-based inference (SBI), which is trained on radiative-transfer simulators, recovers
exoplanet atmospheres accurately on synthetic James Webb Space
Telescope (JWST) spectra but collapses when it comes to real reduced spectra. The flow posterior collapsed on real WASP-39b (importance-sampling effective sample size (ESS) = 1, best-fit ḩi}2/N = 301), and such a failure is usually blamed on missing the forward-model physics, but ruling these levers out with nested sampling first (a temperature gradient, SO2 opacity, and a high-fidelity opacity set) leaves the fit unchanged, meaning the collapse is not from the simulator misspecification but instead from a missing latent, the
planet radius. To fix this, we build MIRAGE, a radius-augmented flow-matching posterior calibrated against an independent nested-sampling reference with importance sampling and an optimal-transport map, which yields a physical and literature-consistent
retrieval of real WASP-39b (with ḩi}2/N from 301 to 0.06). This same method transfers unchanged across two instruments and three real JWST targets, including one spectrum self-reduced end-to-end from raw Mikulski Archive for Space
Telescopes(MAST) data. The lesson is cross-domain, as a latent the simulator encodes but the inference omits can masquerade as misspecification.
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Applied Physics
Finite Element Simulation of Microwave Technologies for PowderBased Volumetric Additive Manufacturing Processes
Brendan Mackey, Levi Smith and Bosco Yu
Volumetric additive manufacturing (VAM) is a promising field of advanced manufacturing which reduces production times of conventional 3D printing while retaining application to complex geometries. Current VAM systems are limited to photo-polymerizing resins, which reduces the general applicability across industry. This work presents exploratory finite element simulations of microwave-based VAM systems compatible with ceramic, metal, or composite powder feedstock. The simulations explore three devices – a linear resonator, a cross interferometer, and a boundary heater – each with potential uses in manufacturing processes for one or multiple of the considered feedstock materials. We find that with precise control of input frequency, power, and waveguide transverse modes, thermal
lattices can be engineered to selectively heat regions of the feedstock, allowing direct application to VAM. Resultant
lattices have cellular dimensions on the order of 1 mm, and require input powers on the order of 100 kW. With advances in microwave technologies allowing for this precision, such devices could open pathways to VAM with materials currently outside the scope of optical methods.
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Quantum Physics
Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks
Oliver Knitter, Jonathan Mei, Sang Hyub Kim et al. (+3 more)
For
quantum machine learning, the exact boundary between classical and
quantum advantage is still poorly understood. Direct comparison between
quantum neural networks (QNNs) and existing classical models, which encompass fundamentally different function classes, often fails to provide broader insight into the difference between the two. Inspired by the techniques of Neural
Quantum States and Random
Fourier Features, this work introduces Neural
Fourier Surrogates (NFS), a
stochastic classical neural network architecture for efficiently learning coefficients over the same finite
Fourier series support as
quantum neural networks. Testing on a selection of tabular
benchmark datasets, we find that NFS is an effective classifier architecture broadly competitive with established classical baselines, including a comparable Random
Fourier Features model, and possessing comparable performance to data-reuploading QNNs; combined with additional analysis comparing the learned
Fourier spectra of QNNs and NFS on synthetic data, these results establish NFS as a natural classical baseline for evaluating QNN performance.
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All authors Oliver Knitter, Jonathan Mei, Sang Hyub Kim, Chi Chen, Masako Yamada, Martin Roetteler
High Energy Astrophysical Phenomena
Optimal Pulsar Timing Array Strategies with the Deep Synoptic Array
Tyler Cohen, Paul B. Demorest, Jeremy G. Baier et al. (+50 more)
Pulsar timing array (PTA) experiments have seen evidence for a nanohertz-frequency gravitational wave background (GWB) through coordinated
radio timing observations of millisecond
pulsars. The significance of this evidence is expected to grow and the GWB's progenitor(s) uncovered with continued observations, especially as the next generation of
radio telescopes comes online. We present a framework for simulating timing observations of a set of
pulsars with a set of
telescopes to predict the per-
pulsar optimal instrument, observing frequency, and integration time. We apply this methodology to the NANOGrav source list of 85
pulsars observed with the Green Bank
Telescope, Very Large Array, Canadian Hydrogen Intensity Mapping Experiment (CHIME), and the Deep Synoptic Array (DSA), a
radio dish array under construction in Nevada. We discuss the dominant noise contributions to the timing precision of these
pulsars and show that most are not dominated by intrinsic pulse phase jitter noise. We also determine which
pulsars should be timed with DSA and CHIME or only DSA and show that an ab initio DSA PTA is more sensitive than one which uses current instruments. Finally, we solve for the optimal integration time per
pulsar, subject to a fixed time budget, that maximizes the GWB signal-to-noise. We show that there is little benefit to optimizing over integration time for these
pulsars observed with DSA. Through Monte Carlo realizations of the PTA, we show that the GWB sensitivity improves by $\sim 5\%$ for time-optimized observations compared to the equal-time-per-source scenario with an early-science, fixed source list.
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All authors Tyler Cohen, Paul B. Demorest, Jeremy G. Baier, Ryan S. Lynch, Scott M. Ransom, Michael T. Lam, Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Ava L. Battaglia, Paul R. Brook, Anabelle L. Brueggemann, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Timothy Dolch, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Jeffrey S. Hazboun, Ross J. Jennings, Megan L. Jones, David L. Kaplan, Matthew Kerr, Duncan R. Lorimer, Jing Luo, Hugo E. Marquis, Alexander McEwen, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Cherry Ng, David J. Nice, Timothy T. Pennucci, Benetge B. P. Perera, Nihan S. Pol, Henri A. Radovan, Paul S. Ray, Ann Schmiedekamp, Carl Schmiedekamp, Brent J. Shapiro-Albert, Ingrid H. Stairs, Kevin Stovall, Abhimanyu Susobhanan, Joseph K. Swiggum, Haley M. Wahl
Quantum Physics
Remote state preparation of a single-spin state via hybrid spin-photon entanglement
Yunge Jiang, Yehan Yu, Lili Song et al. (+3 more)
Remote state preparation is a fundamental
quantum-information protocol that exploits prior knowledge of a target state to reduce the communication resources required for
quantum-state distribution. Here, we propose a remote-state-preparation protocol for a stationary electron-
spin qubit using hybrid
entanglement between the electron
spin and a coherent-state light pulse, generated by
spin-dependent reflection from a
spin-cavity system. Unlike single-
photon encodings, the coherent-state encoding is naturally tolerant of
photon loss: a loss channel attenuates the coherent-state amplitude, leading to a gradual reduction in preparation fidelity rather than probabilistic protocol failure. The central difficulty—implementing the projection onto superpositions of nonorthogonal coherent states required in the conventional protocol—is circumvented by coupling the transmitted pulse to an auxiliary
spin, followed by homodyne detection and a
spin projective measurement. The protocol therefore avoids direct coherent-state-superposition measurements and
photon-number-resolving detection. In the ideal limit, deterministic preparation of a particular class of target states can be achieved using only one bit of classical communication. We analytically quantify the effects of coherent-state nonorthogonality, fiber loss, and
spin dephasing on the preparation fidelity. Increasing the coherent-state amplitude improves state distinguishability and hence the preparation fidelity, but also enhances which-branch information leakage caused by
photon loss, resulting in an optimal amplitude at each transmission distance. For experimentally relevant parameters, the optimized average fidelity remains well above the classical
benchmark over distances of tens of kilometers. We also discuss a possible implementation using diamond nitrogen-vacancy centers.
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All authors Yunge Jiang, Yehan Yu, Lili Song, Yan Mu, Chaoyun Peng, Mingfeng Wang
Statistical Mechanics
Thermal entanglement transitions from strong $\textrm{SU}(2)$ symmetry
Siqi Mo, Ehud Altman and Samuel J. Garratt
We study mixed-state
entanglement in Gibbs states with strong $\mathrm{SU}(2)$
symmetry, focusing on locally interacting
spin systems with
ferromagnetic interactions. Our main result is to show that finite-temperature ordering transitions are associated with
entanglement transitions, and therefore the steady state of strongly symmetric Lindbladians can exhibit
entanglement transitions. While in the paramagnetic phase it is known that the distillable
entanglement and logarithmic
entanglement negativity between two halves of a large system grow logarithmically with the square root of the number of
spins, we show that in
ferromagnetic phases these quantities grow parametrically faster with system size. To arrive at this result we first establish relations between these mixed-state
entanglement measures and
spin correlations in states that are singlets under global $\rm{SU}(2)$
symmetry transformations. We then introduce a semiclassical theory for $\rm{SU}(2)$ singlet thermal states. While the global singlet constraint generally enters this theory as a complicated function of the full semiclassical
spin configuration, we show that in large $S$ limit it simplifies drastically to a Gaussian suppression of total magnetization in disordered phases as well as in ordered phases in the vicinity of continuous thermal phase transitions. This leads us to a field theory describing
spin correlations in the singlet sector. Using this we determine the behavior of various probes of mixed-state
entanglement at low and at high temperatures, supporting our analytical results using numerical Monte Carlo simulations of a three-dimensional
lattice realization of our semiclassical theory. We also use exact numerics in one-dimensional
spin-$1/2$ systems to confirm our predictions for the scaling of mixed-state
entanglement with correlation length and system size in the paramagnetic phase.
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Instrumentation and Detectors
Impact of Gain Layer Doping Concentration on the Performance of 4H-SiC LGADs
Tao Yang, Ben J. Sekely, Yashas Satapathy et al. (+12 more)
Gain layer doping concentration determines the electric field profile in a low gain avalanche detector (LGAD) and is therefore the primary design parameter. This work reports its influence on the charge collection and timing behavior of 4H-SiC LGADs. Two mesa-isolated devices with cold He ion implanted termination differ only in gain layer doping, $4\times10^{17}$~$cm^{-3}$ and $5\times10^{17}$~$cm^{-3}$, and are characterized together with a PIN diode from the same wafer using the ultraviolet transient current technique (UV-TCT). The 25% doping difference produces a gain difference of about two orders of magnitude at the same applied bias, representing a gain range of 3.7 to 216. Under UV-TCT excitation, the higher-doped device exhibits time-resolution minima within a gain range of about 20–80 across the investigated
laser intensities, consistent with the transition from electronic-noise-dominated jitter to multiplication shot noise. The non-monotonic timing response is also observed under a $^{90}Sr$ beta source with a Si LGAD reference: the higher-doped device reaches 51.7 ps at 280 V and then degrades, while the lower-doped device requires more than 450 V. This measured gain window provides an experimental reference for further optimization of the gain-layer design.
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All authors Tao Yang, Ben J. Sekely, Yashas Satapathy, Abraham Tishelman-Charny, Greg Allion, Gil Atar, Philip Barletta, Gabriele Giacomini, Carl Haber, Steve Holland, John F. Muth, Spyridon Pavlidis, Chengxi Yang, Haichen Wang, Stefania Stucci
Earth and Planetary Astrophysics
Correlations between the Carbon-to-Oxygen Ratio and the Orbital and Physical Properties of Exoplanets
Noah Ferich, Robert Royer III, Cody Shakespeare et al. (+1 more)
Studies suggest that protoplanetary disks around
stars with high carbon-to-oxygen (C/O) ratios can produce terrestrial
planets with carbon-dominated compositions instead of silicon-dominated ones. While previous work studied the
evolution of these disks and the
planets that form within them, none analyze in detail how the differences in the surface density profiles of these disks could affect the architectures and iron and siderophile contents of exoplanetary systems. Here, we present a new study that uses the N-body integrator REBOUND and data from a sequential
dust condensation model to simulate the formation of
planets in systems with varying C/O ratios. We find that bulk density could be used to distinguish between silicon-rich and carbon-rich
planets, though it may not be a reliable metric on its own.
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All authors Noah Ferich, Robert Royer III, Cody Shakespeare, Jason H. Steffen
Strongly Correlated Electrons
Local geometry of the Fermi surface and its effect on the electronic characteristics of normal metals
N. A. Zimbovskaya
Fine features in the
Fermi surface geometry, such as nearly cylindrical or nearly paraboloidal strips or local flattenings, are examined as regards their effect on the electronic, mainly galvanomagnetic, properties of metals. It is shown that under certain conditions, these features may significantly change the way a conventional normal metal or a layered structure with metallic conductivity responds to high- frequency external disturbances. All of the effects considered appear to be very sensitive to the disturbance propagation direction and/or to that of the external
magnetic field. Experimental possibilities of observing the described effects are discussed.
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High Energy Physics (Theory)
Antipodal Self-Duality for Generalized Fishnets from Integrability
Lance J. Dixon, Claude Duhr, Francesca C. Fernandes et al. (+1 more)
Antipodal self-duality (ASD) is a remarkable property that relates an amplitude to itself, after performing a suitable kinematic map and reversing the letters of the symbol (more precisely, acting with the antipode of the
Hopf algebra of multiple polylogarithms). ASD has been seen in only one process in planar $\mathcal{N}=4$ super-Yang-Mills theory, and its physical origin is unknown, motivating a search for ASD in other contexts. Recently, ASD was found to hold for square fishnet integrals in a strongly-deformed version of planar $\mathcal{N}=4$. In this paper, we investigate the properties of
polynomials in ladder integrals under the ASD transformation that leaves the square fishnet invariant. Our basic building blocks are determinants of certain
matrices of ladder integrals, that are labeled by partitions or Young diagrams, and automatically obey the Steinmann relations. We employ integrability-based representations of such determinants, which are essentially
matrix-model integrals, and the theory of symmetric
polynomials to find many more ASD quantities – linear combinations of determinants whose coefficients are expressed using the combinatorics of partitions. As a byproduct, we provide an alternate proof that square fishnet integrals obey ASD.
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All authors Lance J. Dixon, Claude Duhr, Francesca C. Fernandes, Victor Mishnyakov
Instrumentation and Methods for Astrophysics
Near-Noiseless Single-Photon Detection in the Infrared with a Megapixel Semiconductor Array for Low-Background Astronomy
Guillaume Huber, Pavaman Bilgi, Charles-Antoine Claveau et al. (+7 more)
Sensor noise is a fundamental barrier to low-flux astronomical imaging and spectroscopy, where the ideal sensor would unambiguously distinguish individual
photon arrivals. While optical
semiconductor arrays can reach single-
photon sensitivity, comparable performance in the infrared has largely required superconducting detectors. These must be operated at temperatures near absolute zero and require substantially more power, introducing major system-level challenges. HgCdTe avalanche photodiodes offer a
semiconductor alternative by amplifying charge before readout, but dark current and tunneling effects have limited their use in the faintest regimes. Here we demonstrate single-
photon-resolving operation in a megapixel-format HgCdTe linear-mode avalanche photodiode array operated at conventional cryogenic temperature. Avalanche gain raises
photon-induced steps in non-destructive up-the-ramp data above the readout-noise floor while leaving the dark signal largely unamplified, with a false positive rate of approximately 2 false counts per thousand reads per pixel. These results establish LmAPDs as a promising route toward infrared
photon-counting focal planes for future low-background astronomical observatories.
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All authors Guillaume Huber, Pavaman Bilgi, Charles-Antoine Claveau, Shane Jacobson, Ian Baker, Daniel Owton, Vincent Isgar, Chris Maxey, Markus Loose, Michael Bottom
Materials Science
Long-Range Machine Learning Interatomic Potentials for Defect Energetics in SrTiO$_3$
Yee Chit Wong, Marcel F. Langer, Reinhard J. Maurer et al. (+1 more)
Machine learning interatomic potentials (MLIPs) have advanced rapidly in recent years, yet the majority of models remain semilocal in nature and neglect long-range electrostatic interactions. A growing number of long-range models have emerged to address this limitation, but systematic
benchmarks comparing their performance on physically realistic systems remain scarce. In this work, we assess three long-range MLIPs – MACE-POLAR, MACE-LES, and LOREM, against a short-range baseline MACE model, on their ability to capture long-range Coulombic interactions, progressing from idealised synthetic point-charge systems to first-principles data on realistic
crystal structures. This progression allows us to isolate model's capability to learn electrostatic interactions from the many competing energy contributions, such as dielectric screening and exchange-correlation, that are present in DFT total energies. As a physically motivated
benchmark system, we focus on strontium titanate SrTiO$_3$ with Sr–O Schottky vacancy pairs, a material in which long-range charge interactions play a central role and which serves as a natural stepping stone towards the study of charged polarons and other electronic and optical properties. Building on this
benchmark, we further examine oxygen vacancy migration in the presence of the Sr–O Schottky pair, using climbing-image nudged elastic band calculations and molecular dynamics to obtain activation barriers as a function of the vacancy pair separation, providing further extrapolation test of each model's ability to capture the electrostatic effects that govern defect transport.
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All authors Yee Chit Wong, Marcel F. Langer, Reinhard J. Maurer, Nicholas D. M. Hine
Atmospheric and Oceanic Physics
Weather Jiu-Jitsu: Exploring the Feasibility of Control Paradigms in Weather Foundation Models
Prakriti Biswas, Kobi Abayomi and Upmanu Lall
Weather Jiu-Jitsu is a control paradigm for extreme climatological events, inspired by chaos theory. As a proposition, small, precise, targeted, and cost-inexpensive perturbations can redirect trajectories of a large dynamical system. This strategy has been demonstrated analytically in the Lorenz-63 system, where a naturally chaotic trajectory switching between two attractors can be confined to a single attractor, indefinitely, via arbitrarily small perturbations. This paper examines the feasibility of Microsoft's Aurora – a 1.3 billion parameter global atmospheric model – as a test bed for this strategy. This paper explores three questions: (1) Is Aurora a reliable enough simulation environment to serve as a meaningful testbed? (2) Are the perturbations required to redirect its trajectories small enough to be physically plausible? (3) Does Aurora's learned latent space (the parametric
estimators on climatological attributes) yield any apparent, structured, and/or perhaps interpretable features that can convey a geo/atmospheric response to initial conditions? We find evidence consistent with all three: Aurora's modeled trajectories respond to perturbations beyond measurement drift, the perturbation magnitudes required are small relative to the model's own forecast uncertainty, and its latent representations exhibit directional structure that responds to Jiu-Jitsu-type interventions, even though that structure does not separate extreme from normal states outright. These results should be read as feasibility diagnostics rather than a demonstration of control: we do not implement or test an actual steering intervention on Aurora, and several of our findings, particularly around the model's latent-space geometry, are exploratory.
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Fluid Dynamics
Scalar mixing by stagnation points on solid surfaces
Gaute Linga, Tanguy Le Borgne and Joris Heyman
Recent advances have linked mixing in porous media to the deformation of infinitesimal fluid elements. However, these Lagrangian frameworks generally neglect or simplify interactions with solid surfaces. We consider transport of thin solute blobs (strips or sheets) near single generic obstacles, in particular along separation lines (separatrices) which connect to stagnation points at solid boundaries. In this case, we demonstrate that the coupling between flow and
diffusion is analytically tractable. We provide a complete theory for scalar mixing near upstream stagnation points, which we validate by numerical simulations. We identify a mixing time scale $t_B \sim Pe^{1/3}$, where $Pe$ is the Péclet number, which controls whether scalar decay is driven by fluid stretching or by interaction with the solid boundary. Asymptotically, for times $t < t_B$, we find that the maximum concentration $c_{\rm max}$ decays as $t^{-5/2}$ and that the width $\sigma$ grows like $t^{1/2}$. For $t > t_B$, we find exponential decay of $c_{\rm max}$ and constant width $\sigma \sim s_B \sim Pe^{-1/3}$, where $s_B$ is a mixing length scale distinct from that which appears in shear flows. The asymptotic scalings of $c_{\rm max}(t)$ and $\sigma(t)$, and their dependence on $Pe$, are universal to no-slip stagnation points and qualitatively different from stagnation points in open flows.
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Quantum Physics
Real-Time Adaptive Filtering and the Boxcar Limit in Superconducting Qubit Readout
Hans Johnson, Tanay Roy, Leonardo Bove et al. (+3 more)
Control and readout systems for superconducting
quantum computing support real-time control and high-fidelity
qubit-state discrimination. We examine when additional digital processing improves readout fidelity. A common baseline for dispersive readout uses a boxcar averager to compute a uniformly weighted average over a fixed window followed by threshold-based state assignment. We evaluated an adaptive finite-impulse-response (FIR) filter trained in real time using the least-mean-squares (LMS)
algorithm on a field-programmable gate array (FPGA)
quantum controller. We also analyzed measured readout shots offline to compare the frozen filter with boxcar averaging, and evaluate per-sample weighting plus sequential detection. For the fixed FIR filters tested, summing the filtered samples gives the boxcar sum multiplied by one complex number apart from a small edge correction. We call this the kernel collapse. The multiplication scales the state separation and noise equally without improving state discrimination, and we call this the boxcar limit. The frozen LMS filter reduces trace noise, but shows no resolved improvement in readout fidelity. On a 2D transmon, optimizing the readout window accounted for much of the improvement over full-window integration. We then examined how changing the decision method could reduce calibration effort and decision time. On a higher-fidelity 3D ancilla readout, our modeled template estimation reached the same fidelity target as direct averaging with 89.8% fewer labeled shots per state. Offline sequential replay assigned most shots before the acquisition window ended. These results distinguish waveform denoising from state-discrimination improvement, and motivate direct control of decision weights and assignment time in dispersive readout.
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All authors Hans Johnson, Tanay Roy, Leonardo Bove, David van Zanten, Silvia Zorzetti, Jafar Saniie
Atmospheric and Oceanic Physics
Can we create a `race to the top' for weather forecasts to inform smallholder farmer decisions?
Colin Aitken, Michael K. Tippett, Pedram Hassanzadeh et al. (+9 more)
Artificial-intelligence weather prediction (AIWP) models have made it possible to produce high-quality tailored forecasts with limited computational resources. This advance has the potential to benefit hundreds of millions of farmers in low- and middle-income countries who lack access to forecasts of critical weather phenomena. However, it can be difficult for key stakeholders to evaluate forecast quality, risking a "race to the bottom" as cheap but low-quality forecasts crowd out forecasts that would benefit farmers. We propose a set of principles and protocols for evaluating agriculturally-relevant forecasts as a starting point for standards that would let forecasters credibly convey their forecasts' quality.
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All authors Colin Aitken, Michael K. Tippett, Pedram Hassanzadeh, Katherine Kowal, Rendani Mbuvha, John H. Marsham, Shruti Nath, Ousmane Ndiaye, Douglas J. Parker, Caroline M Wainwright, Michael Kremer, William R. Boos
Fluid Dynamics
On the spectra of strong turbulence on water surfaces
Gregory Falkovich
Here, I give a brief history of the theory, with twists and turns, and list possible predictions for the spectra of the direct cascade of
gravity waves on the water. The description of long waves is straightforward within the weak-
turbulence theory developed by Zakharov and his school. As the energy cascade proceeds to shorter scales, the mean surface steepness grows, and wave-breaking events appear with increasing frequency. Considering surface cusps, Phillips suggested a wavenumber spectrum (with a wrong magnitude, as I argue here) and a frequency spectrum whose whole form is incorrect. The right form for the frequency spectral slope due to breaking waves was suggested by Kuznetsov. Here we estimate the magnitude and argue that the frequency spectrum is expected to continue unchanged through the whole cascade. The transition from weak to strong
turbulence in the wavenumber and spatio-temporal spectra is due to spectrally nonlocal interactions and happens earlier (at larger scales) than the dimensional estimate suggests. As a result, the magnitude of the strong-
turbulence spectrum is not universal but depends on the pumping for a sufficiently long weak-
turbulence cascade. The reason for nonlocality is likely that breaking of shorter waves is determined by the magnitude of the longest wave on whose crest they are running.
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