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Physics

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Monday 22 June

Instrumentation and Detectors

Multi-scale reconstruction of single-ion damage tracks in diamond via nitrogen-vacancy centers

Daniel G. Ang, Jiashen Tang, Maximilian Shen et al. (+9 more)

Understanding particle-induced damage tracks in solid-state materials underpins emerging applications in rare-event detection and quantum defect engineering. Resolving these tracks requires multi-scale readout, from event localization at the millimeter scale to track-morphology reconstruction at the nanoscale. Nitrogen-vacancy (NV) centers in diamond provide such a platform, combining optical localization with quantum sensing of track morphology. Here, we implant sub-MeV carbon ions into nitrogen-rich diamond and detect individual recoil events via spatially localized NV formation. We develop a simulation framework that explains the observed NV yield and predicts that directional information is retained in the NV distribution after annealing. Machine learning further recovers much of the information lost to defect diffusion and limited NV yield, improving head-tail classification to a level comparable to pre-annealed vacancy tracks. Measurements of NV spin coherence indicate compatibility with nanoscale track reconstruction via NV strain mapping and magnetic gradient-based techniques. These results identify promising pathways toward NV-diamond directional detectors for rare events, while the track-modeling framework has broader implications for paleodetection and quantum material synthesis.
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All authors Daniel G. Ang, Jiashen Tang, Maximilian Shen, Michael Titze, Gavishta Liyanage, Jordan Chapman, Chinmay Bharathulwar, Andrew T. Gilpin, Tanguy Terlier, Edward S. Bielejec, Vsevolod Ivanov, Ronald L. Walsworth

High Energy Physics (Phenomenology)

Observables and conformal properties of dark matter admixed isentropic neutron stars

Arijit Das, Prashanth Jaikumar, Adarsh Karekkat et al. (+1 more)

We construct an equation of state for isentropic dark-matter-admixed neutron stars (DMANS) with a hot core and relatively cold crust incorporating self-consistent temperature and DM density profiles for GeV-scale fermionic DM. We show that the enhancement of central stellar density due to DM accumulation, previously reported for cold neutron stars, remains robust. Substantial observable effects of DM accumulation arise only for sufficiently massive stellar configurations. Similar to earlier studies of cold NS, the speed of sound profile is shown to exhibit non-monotonic behavior for sufficiently large DM density in the core. We identify a competition between thermal effects due to nonzero values of entropy per baryon and softening effects of the dark sector which drive macroscopic properties and conformality indicators in opposite directions. This competition determines the onset of conformality near the stellar core and indicates that conformality signatures attributed to quark-matter in cold NS could be mimicked by DM admixture in isentropic stars.
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All authors Arijit Das, Prashanth Jaikumar, Adarsh Karekkat, Tanumoy Mandal

Statistical Mechanics

Thermodynamic inference from noisy single-molecule time series

Todd R. Gingrich, Oleg A. Igoshin, Anatoly B. Kolomeisky et al. (+1 more)

Single-molecule or single-particle tracking measurements inherently yield noisy microscopic trajectories, often significantly constrained by the diffraction limit and by the finite rate at which photons are emitted and counted. Here we study systematically the resulting effects of finite spatial and temporal resolution on one's ability to discern and quantify the arrow of time in microscopic trajectories. Given an experimental time series Y(t) degraded by noise, we consider the problem of estimating the entropy production associated with the corresponding microscopic variable X(t) using two strategies. The first attempts to infer the statistical properties of X(t) from those of Y(t) before estimating the entropy production. The second uses the experimental observable as a proxy for the true microscopic observable, with the entropy production estimator applied directly to Y(t). We prove that both strategies result in lower bounds on the true entropy production. Importantly, noise-degraded observables Y(t) undergo non-Markovian dynamics even when X(t) are Markovian, and non-Markovian entropy production estimators are advantageous. We further note nontrivial interplay between spatial and temporal resolution: in the presence of detection noise, improving the temporal resolution alone may lead to poorer rather than better entropy production estimates.
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All authors Todd R. Gingrich, Oleg A. Igoshin, Anatoly B. Kolomeisky, Dmitrii E. Makarov

Physics and Society

One country, multiple portraits: representativeness in GPS-based mobility data is source-specific and spatially dependent

Carmen Cabrera, Francisco Rowe, Miguel González-Leonardo et al. (+3 more)

Anonymised GPS-based mobile phone data are increasingly used to estimate population distribution and human mobility, supporting applications across disaster response, public health, urban planning and migration research. Yet whether these data fairly represent the populations they describe, particularly outside high-income countries, remains poorly understood. We quantify coverage bias for 2,478 municipalities in Mexico by comparing population estimates from a single-platform source (Facebook) and a multi-app aggregator (Veraset) against the 2020 Mexican Population Census. We find that the magnitude and spatial distribution of coverage bias differ substantially across sources. Facebook provides higher and more evenly distributed coverage, whereas the multi-app data concentrate users in larger, wealthier and more digitally connected places. Coverage bias is also spatially structured, with neighbouring municipalities showing similar levels of over- or under-coverage. Using explainable machine learning, we show that digital access and material resources are the dominant drivers of bias for the multi-app data, while demographic and population structure dominate for Facebook. Explicitly modelling spatial dependence improves the performance of statistical models for explaining bias and reveals that an appreciable share of spatial variation remains unexplained by observed covariates. These findings show that coverage bias is source-specific and spatially dependent, and provide a foundation for adjustments that improve the representativeness of mobile phone data in unequal, data-scarce settings.
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All authors Carmen Cabrera, Francisco Rowe, Miguel González-Leonardo, Juan Ignacio Vilchis-García, Elisa Omodei, Maribel Hernández-Rosales

Quantum Physics

Log-concavity and tunneling: adiabatic quantum optimization for convex functions (with a spike)

Arthur Braida, Elie Bermot and Simon Apers

Quantum tunneling is expected to provide a computational speedup in quantum computing, a phenomenon that Adiabatic Quantum Optimization (AQO) aims to leverage. While some academic proofs of concept have been studied, such as the "Hamming weight with a spike" (HWS) problem, the algorithmic gains of this effect remain underexplored. In this work we extend the analysis underlying HWS to more general potentials. In the first half of the work, we establish (discrete) log-concavity of the ground state as a key structural property in this context. We devise a framework for establishing log-concavity of the ground state for a large family of discrete, 1-dimensional Schrödinger operators. The family includes convex potentials, but also certain potentials with local minima. In the convex case, this provides a discrete version of a continuous result by Brascamp and Lieb ('76). We demonstrate the utility of our result by establishing new spectral gap bounds, going beyond related results by Jarret and Jordan ('14) for convex potentials. In the second half of the work, we use our results on log-concavity to extend the perturbative analysis of HWS by Reichardt ('04) to the larger family of potentials with log-concave ground state. As a concrete instantiation, we use our result to extend the HWS analysis from a linear potential (which is exactly solvable) to a quadratic potential (which is no longer solvable). Our result strongly suggests the broader applicability of tunneling to convex potentials with spikes
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Quantum Physics

A quantum algorithm for one-shot signatures

Gopikrishnan Muraleedharan, Minh Thuy Truc Pham, Vir Pathak et al. (+10 more)

We provide a pre-obfuscation circuit-level implementation of an efficient one shot signature scheme, which has known applications to delegated signatures, secure token transfer, and publicly verifiable randomness. The algorithm consists of two stages: a key generation stage where a classical public key/quantum secret key pair is produced, and a signing stage where the quantum secret key is processed with a message string to produce a classical signature. There is no algorithmic error in the construction and the signed message can be efficiently checked by a classical verifier. Our scheme works by preparing a superposition over elements of a random affine coset determined by the output of a puncturable pseudorandom function, together with a circuit that tests coset membership. The logical qubit number scales like $\Theta( \kappa\log(r) + n + l)$ and the gate complexity scales like $\Theta(n^3 + nl)$, where $r$ is the public key size, $n+l$ is the signature size, $l$ is the message size, and $\kappa = \Omega(n)$ is the cryptographic security parameter. We provide explicit qubit and gate counts before obfuscation. A secure instantiation additionally requires modified key generation and a security proof for the resulting obfuscated construction.
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All authors Gopikrishnan Muraleedharan, Minh Thuy Truc Pham, Vir Pathak, Thomas Gardner, Chuanqi Zhang, Samuel Crew, Tom Hartweg, Adrian Aasen, Guido Masella, Vase Moeini, Asier Piñeiro Orioli, Hugo Perrin, Gavin K. Brennen

Materials Science

Data analysis methods for powder x-ray diffraction intensity under laser-driven dynamic compression at Omega and NIF laser facilities

Marius Millot, Federica Coppari, Amy Lazicki et al. (+1 more)

Powder x-ray diffraction (PXRD) under laser-driven dynamic compression is a powerful tool to investigate material response to extreme pressure, temperature and strain rates. Robust PXRD platforms have been developed at kJ and MJ laser facilities worldwide including the Powder X-Ray Diffraction Image Plate (PXRDIP) at the Omega Laser Facility at the Laboratory for Laser Energetics (LLE) and the TARget Diffraction In Situ (TARDIS) at the National Ignition Facility (NIF). Here we present further developments of data analysis methods focused towards improving the fidelity of the PXRD intensity determination for these platforms. We illustrate these methods by discussing how they can be implemented in a data analysis package and applied to shock compression data on diamond near 1 TPa. We discuss using the XRD signal from the collimating pinhole or a layer of un-compressed material in the sample package as in-situ references for XRD intensity. We detail how to compare data collected with different x-ray sources and how to account for thermal damping of XRD signal when comparing XRD from a shock-compressed, hot material with the reference material at ambient.
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All authors Marius Millot, Federica Coppari, Amy Lazicki, Jon H. Eggert

Mesoscale and Nanoscale Physics

Helical Domain-Wall-Ring Networks Reshape Superconducting Correlations

Yi-Chun Hung and Arun Bansil

Extended domain-wall networks that emerge in moiré materials provide a distinct platform for quasi-one-dimensional electronic states. However, the interaction-driven orders in confined networks remain largely unexplored. Here, we discuss superconducting (SC) correlations in interacting helical domain-wall-ring networks in the closed topological domains formed within the moiré patterns of an underlying twisted bilayer honeycomb lattice. We first analyze the system within the framework of an infinite-size theory and show that inter-ring SC-pair tunneling is renormalization-group relevant in an appropriate interaction regime, favoring enhanced SC correlations through inter-ring phase locking. To address finite-size effects resulting from the ring-network geometry, we present a self-consistent variational approach. Our analysis shows that even in the regime where the infinite-size theory predicts strongly coupled pair tunneling, the induced phase-locking scale remains strongly suppressed. In contrast, the SC scaling dimension is governed mainly by density-density interactions and ring geometry, decreasing modestly with decreasing twist angle while remaining insensitive to the pair-tunneling strength. This discrepancy demonstrates that ring networks cannot generally be understood as simple finite-size truncations of their infinite-size counterparts but can exhibit qualitatively distinct collective behavior. Our study highlights how the interplay of confinement effects and ring-network geometry can reshape SC correlations.
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Mesoscale and Nanoscale Physics

Quantum Geometry Driven Finite-Momentum Exciton Fluctuations in Flat-Band Systems

Yi-Chun Hung, Xiaoting Zhou and Arun Bansil

Quantum geometry is instrumental in stabilizing exotic phenomena in systems ranging from topological insulators to superconductors. In dispersionless flat bands, where the kinetic energy is quenched, the quantum metric emerges as the fundamental driver of macroscopic collective phenomena. Here, we theoretically demonstrate that lattice-geometry-induced flat bands, such as those in kagome and Lieb lattices, provide a fertile platform for realizing a purely quantum-geometry-driven excitonic insulator (EI) phase. By applying an out-of-plane Zeeman field to lift spin degeneracy without spin-orbit coupling, we establish a Ginzburg-Landau framework in which the electron-hole wavefunction-overlap directly maps the flat-band quantum metric onto the macroscopic free energy. This mapping plays a key role in both the EI and the associated superfluid phases, with the coherence length and phase stiffness emerging directly from the quantum metric. Our analysis reveals that under strong interactions, the quantum metric induces a negative effective kinetic coefficient for the amplitude mode. Rather than destabilizing the uniform condensate, this softens the amplitude fluctuations at a finite momentum, giving rise to a finite-momentum superfluid density fluctuation (FMSDF) state. This state is observable as a periodically modulated magnitude of in-plane magnetization fluctuations. Our findings establish a rigorous link between flat-band quantum geometry and dynamic collective excitonic states, with promising pathways for realization in covalent-organic frameworks (COFs).
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High Energy Physics (Phenomenology)

Next-to-next-to-leading-order QCD corrections to ${}^3S_1^{(8)}$ gluon fragmentation function for quarkonium

Feng Feng, Yu Jia and Wen-Long Sang

We present the first computation of the next-to-next-to-leading-order (NNLO) QCD corrections to the ${}^3S_1^{(8)}$ gluon fragmentation function for quarkonium within the nonrelativistic QCD (NRQCD) factorization framework, accurate to the lowest order in the velocity expansion. The calculation is performed with high numerical precision and encompasses both polarized and unpolarized cases. We find that the NNLO corrections are positive and substantial across most of the $z$ region. Furthermore, the logarithmic singularities near the endpoint $z\to 1$ are fully reconstructed, providing essential inputs for future threshold resummation beyond leading-logarithmic accuracy. Combined with threshold-resummed formulas in the large-$z$ region, our results yield phenomenologically viable inputs for the $^3S_1^{(8)}$ gluon fragmentation function. This enables a more reliable description of large-$p_T$ $J/\psi$ ($\psi'$) and $\chi_{cJ}$ production and polarization at hadron colliders, representing a crucial step toward a definitive test of the color-octet mechanism.
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Quantum Physics

Random dimension reduction and learning symmetric properties of quantum states

Angus Lowe and Xinyu Tan

We describe a procedure that simultaneously reduces the dimensions of many, potentially distinct quantum states while preserving properties invariant under the tensor power action of an isometry. This serves as a black-box method to replace the dimension with the maximum rank in the sample complexity of learning symmetric properties, even those depending on multiple input states. Combined with full state tomography, random dimension reduction yields improved upper bounds for estimating distances, fidelities, and relative entropies between pairs of states. Expressing the action of this procedure through the Choi–Jamiołkowski isomorphism reveals an intimate connection with the recently introduced random purification channel by Tang, Wright, and Zhandry. With this new perspective, we obtain a simple description of the rank-dependent version of the random purification channel and give an end-to-end analysis of sample-optimal tomography without requiring a reference to the Schur transform or Schur polynomials. Finally, we prove that there does not exist a random purification channel that simultaneously purifies copies of multiple, potentially different input states. Hence, the procedure is related to, but distinct from, random purification.
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Cellular Automata and Lattice Gases · Cross-listed from cs.LG

It's Much Easier for Neural Networks to learn Game of Life Dynamics with the Right Activation Function: Polynomial Kolmogorov-Arnold Networks

Tashin Ahmed and Q. Tyrell Davis

Previous work has found a gap between the scale of neural networks that reliably learn Conway's Game of Life, and minimal networks capable of representing the classic cellular automaton with hard-coded parameter values. Viewing neural network learning as a search process suggests a dependence on networks large enough to contain sub-networks with lucky initializations (sometimes known as 'winning tickets') that actually learn the task. In this work, we reorient our perspective from discovering Life rules as a search problem back to a learning problem, and reason that with fitting inductive biases, the problem should be much more amenable to minimal networks. We find that network variants with several alternative activation functions meaningfully outperform the default choice of Rectified Linear Units, and in particular, that a 2nd degree polynomial activation function consistently learns Life dynamics with or without the benefit of learning neural weights. Our results provide an informative demonstration of the benefits of matching learning to the task at hand and challenge the easy default choice of scale for all problems. In particular, we advocate for the use of cellular automata as simple test domains for developing strategies that can benefit machine learning for science, physics-based deep learning, and interpretable machine learning.
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Superconductivity

Influence of Harris disorder on quantum-critical superconductivity

Serhii Kryhin, Peter Lunts, Aavishkar A. Patel et al. (+2 more)

In the Hertz theory, a quantum critical metal is described by the coupling of a Fermi surface to fluctuations of a Landau-damped bosonic field $\phi$, which may represent either an order parameter or a Higgs field for a transition without symmetry breaking. Scattering from $\phi$ produces non-Fermi-liquid behavior in the normal state, while the same fluctuations mediate enhanced Cooper pairing. By the Harris criterion, symmetry-preserving disorder couples most strongly to the coefficient of the $\phi^2$ term, locally tuning the system toward or away from criticality. This random mass (“Harris disorder”) leads to a finite density of localized low-energy $\phi$ modes even when the fermionic states remain extended and continue to provide Landau damping. We study the onset of pairing mediated by these localized overdamped bosonic modes. Starting from a real-space linearized Usadel equation for the two-particle propagator, we show that the localized bosonic wave functions generate both a spatially random pairing vertex and an effective random potential for Cooper pairs. Numerical solution, a self-consistent Born approximation, and Lifshitz-tail analysis reveal two regimes of the pairing instability. At high temperatures, pairing nucleates compact superconducting puddles on the most localized bosonic modes. At lower temperatures, an extended pairing eigenstate appears, but its transition scale and spatial structure remain strongly affected by mesoscopic correlation effects and enhanced probability of returns to favorable regions of the localized bosonic glue. The resulting distribution of local pairing scales has a power-law tail, in contrast to the stretched-exponential tails of disordered BCS superconductors. This mechanism provides a route to broad gap inhomogeneity and superconducting puddles in quantum-critical metals, and offers an interpretation of STM measurements of the cuprates.
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All authors Serhii Kryhin, Peter Lunts, Aavishkar A. Patel, Subir Sachdev, Pavel A. Nosov

High Energy Physics (Phenomenology)

Quantification of the Flavor Diagonal Hadronic CP Violation

Nodoka Yamanaka

The flavor diagonal CP violation of elementary particle physics contributes to the atomic, nuclear, and nucleon electric dipole moments (EDMs), T-violating neutron optics, and to the angular correlations of beta decay. In this contribution, we review the basics and the importance of CP violation in the search for new physics beyond the standard model, the recent progress in the quantification of the hadron level CP violation contributing to the aforementioned observables, and finally the current attempt to solve the strong CP problem without additional interactions and fields.
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High Energy Physics (Phenomenology)

Irrelevance of Anomalous Breaking of Axial U(1) Symmetry and the U(1) Problem

Nodoka Yamanaka

The eta and eta' mesons are conventionally known to receive contribution from the anomalous breaking of axial U(1) symmetry, and they are considered to not be the Nambu-Goldstone (NG) bosons of the spontaneous chiral SU(3)_L x SU(3)_R symmetry breaking of QCD. However, it has recently been shown that this axial U(1) anomaly is not actually physical. In this contribution, we first review this statement and then propose a mechanism in which eta and eta' mesons are indeed NG bosons while being consistent with the axial U(1) problem.
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Quantum Physics

Genuine Global Kochen-Specker Contextuality as Classical Coordination Cost

Ming Yang

We formulate classical simulation of quantum correlations as coordination across a spacetime separator. All past-dependent information capable of influencing the future must cross the separator either through communicated messages or through a persistent classical state. We prove a general lower bound on this classical coordination cost in terms of the nonnegative rank of the separator correlation matrix, with approximate and amortized extensions governed by approximate nonnegative rank and Wyner common information. For sequential processes, we introduce a causal positive-realization rank that enforces consistent response and state-update maps, and we explain how bounded local computation and support-covering models arise as restricted cases. We apply the framework to genuine global Kochen–Specker contextuality, in which local subsystems are noncontextual and the tested multipartite blocks are generalized-Bell-local, while the complete empirical model has no global noncontextual explanation. At the symmetric point of a polarization–path Hardy construction, exact classical simulation requires two coordination bits, whereas the corresponding quantum separator requires one qubit. Under exact repetition, the classical lower bound is the base-two logarithm of three bits per copy; with asymptotically vanishing error, it becomes one and a half classical bits per copy, compared with one qubit per copy. We further construct a finite stabilizer–Peres–Mermin family for which the exact classical coordination cost grows quadratically with system size, while the quantum boundary cost grows only linearly. The separation applies to arbitrary finite-state causal online simulators. Establishing a constant-error quadratic separation and an intrinsic construction without flag conditioning remain open.
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Solar and Stellar Astrophysics

Corotating Interaction Regions (CIRs): evolution over a solar lifetime

Rose F. P. Waugh and Moira Jardine

Corotating Interaction Regions (CIRs) are persistent structures in stellar winds that arise from the interaction between fast and slow wind streams. They are known to generate shocks and high-energy particles, potentially influencing the erosion of planetary atmospheres and space weather conditions. Although extensively studied for the present-day Sun, their evolution over a star's lifetime and implications for planetary environments remain less explored. We model the evolution of CIRs around a solar-mass star using a rotational evolution framework and assess how their location, shape, and particle distributions vary with stellar age. We find that CIRs form closer to the star during early spin-up phases and migrate outward during spin down, with the minimum CIR radius inversely related to rotation rate. We show that the distribution of high-energy particles produced in CIR shocks varies significantly with age. During the Hadean period, when Earth's atmosphere evolved significantly, CIRs may have generated a number of energetic particles that is \(10^3\) to \(10^7\) times greater than for the present-day Sun. The frequency and strength of CIR-planet interactions also peak during early rapid rotation phases. Furthermore, we demonstrate from this preliminary study that, for stars with mass less than 1.4 Msun, whilst CIRs can form within the habitable zone, their shocks always form beyond it. This suggests that energetic particle impacts may rain inward from more distant regions, as with the present-day Sun. These findings have implications for habitability and the evolution of atmospheres since these particles can alter the chemistry and escape rate of atmospheres.
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Materials Science

INCARBench: A Benchmark for Scientific Configuration in VASP INCAR by Large Language Models

Bin Shao, Jixiang Li, Xinyue Zhang et al. (+3 more)

Large language models (LLMs) are increasingly being integrated into first-principles computational workflows, yet their ability to configure scientific calculations remains poorly understood. Here, we introduce INCARBench, a benchmark for evaluating LLMs on input configuration for the Vienna Ab initio Simulation Package (VASP) through both configuration generation and repair tasks. Evaluating 19 model configurations reveals substantial capability differences among current frontier models. While several models achieve high semantic and policy accuracy, task-critical correctness remains substantially lower, demonstrating that parameter-level correctness does not necessarily imply scientifically valid configurations. Failure analysis shows that errors concentrate in physically coupled settings involving DFT+$U$, magnetism, and correlated materials, where multiple constraints must be satisfied simultaneously. Repair evaluation further reveals that correcting incorrect settings and preserving already-valid configurations are distinct capabilities, with configuration preservation remaining a major challenge. These findings establish scientific configuration as a measurable capability of large language models and provide a foundation for developing more reliable AI systems for computational materials science.
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All authors Bin Shao, Jixiang Li, Xinyue Zhang, Baishun Yang, Zhiyang Liu, Weichao Wang

Astrophysics of Galaxies

Detection of Variability in Seyfert 2 Galaxies and Measurement of the Optical Scattering Region Size

Natalie Kovacevic, Xinyu Dai, Heechan Yuk et al. (+5 more)

One main theme of the Unification Model of active galactic nuclei is that there is an obscuring torus structure blocking the direct view of the central engine for Seyfert 2 galaxies. Here, we present the detection of long-term optical variability for a sample of nearby Seyfert 2s. We found that Seyfert 2s exhibit a relatively low but significant level of variability beyond the constant fluxes established by galaxies over month to year time scales. The variability is also detected in the structure functions of Seyfert 2s. Assuming a simple variability suppression model by the scattering region and dilution due to host starlight, where the region smooths the unobscured photon packets from the central engine as the light scatters over the torus, we estimate AGN scattering region sizes by matching the variability amplitudes of Seyfert 1s to 2s. Our measured scattering sizes are largely consistent with the torus size measured using their emission properties, suggesting that the scattering region is of a similar size as the torus. Our results pave the way towards variability as a powerful and independent test for AGN unification models.
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All authors Natalie Kovacevic, Xinyu Dai, Heechan Yuk, Emilia Jaervelae, Tingfeng Yi, Patrick J. Vallely, Benjamin J. Shappee, Francesco Shankar

Cosmology and Nongalactic Astrophysics

Unifying the Dark Sector with the New Generalized Chaplygin Gas: Observational Constraints

Abdulla Al Mamon, Andronikos Paliathanasis and Subhajit Saha

In light of recent cosmological observations, we examine a generalized Chaplygin gas model with a redshift-dependent exponent as a framework for describing the dark energy and dark matter content of the Universe. Specifically, we treat this fluid as a single unified component and test it against late-time background observational data. We employ Type Ia supernova data, cosmic chronometers, and baryon acoustic oscillations from the second data release of the Dark Energy Spectroscopic Instrument. We perform a Bayesian analysis for parameter estimation and compare the model with $\Lambda$CDM. We find that the generalized Chaplygin gas provides systematically higher values of the combined likelihood; nevertheless, once the larger number of free parameters is taken into account, both the Bayesian evidence and the Akaike Information Criterion suggest that the model is statistically indistinguishable from $\Lambda$CDM.
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Biological Physics

Electrochemical DNA Hairpin Sensors for Differentiating Small Molecule Intercalation from Minor Groove Binding

Kiara Thompson, Kian Barnes, Saron Yoseph et al. (+5 more)

Small molecule double-stranded DNA intercalators have significant potential for therapeutic applications. However, screening for and confirming a drug candidate's intercalative behavior remains labor-intensive and costly. To address this, we investigated the sequence and biophysical parameters that affect the performance of electrochemical DNA hairpin sensors for streamlined identification of structural intercalators. These sensors utilize oligonucleotide (oligo) sequences that form hairpins upon intercalator binding. The 3prime end of the oligo is modified with alkylthiol linkers for gold electrode surface monolayer self-assembly, while the 5prime end carries a methylene blue redox reporter. Hairpin formation enhances electron transfer between methylene blue and the gold electrode, which can be detected via voltammetry. We tested seven hairpin structures varying in stem length and sequence. Our optimal oligo, HP4, features a four-base-pair stem and responds to five DNA intercalators over a broad detection range, with EC50 in close agreement with published affinity (KD) values for these interactions. We further demonstrate HP4s ability to discriminate intercalator binding from a series of minor groove binders through significant differences in signal gain upon incubation. Altogether, our strategy establishes a platform for identifying intercalative compounds that should support the development of DNA-targeting therapeutics.
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All authors Kiara Thompson, Kian Barnes, Saron Yoseph, Vincent Clark, J.D. Mahlum, Ananya Majumdar, Philip S Lukeman, Netzahualcóyotl Arroyo-Currás

High Energy Physics (Experiment)

Probing Nuclear Effects with Transverse Kinematic Imbalance in Muon-neutrino Induced Charged-Current $\pi^0$ Production on Argon with the MicroBooNE Detector

MicroBooNE collaboration: P. Abratenko, D. Andrade Aldana, J. Asaadi et al. (+191 more)

Neutrino-nucleus cross-section measurements are needed to improve interaction modeling and to enable precision neutrino oscillation measurements in upcoming experiments such as the Deep Underground Neutrino Experiment (DUNE), Hyper-Kamiokande, and the Short-Baseline Neutrino program. Baryon-resonance neutrino interactions constitute a dominant contribution near the peak of the DUNE neutrino energy spectrum. We present the first measurement of muon neutrino charged-current resonance-like interactions on argon using transverse kinematic imbalance variables with the MicroBooNE detector. These observables are highly sensitive to the modeling of final-state interactions. This measurement probes kinematic imbalances using the reconstructed momenta of the muon, leading proton, and neutral pion. A comprehensive characterization of the $\pi^0$-proton final state is presented; however, none of the models considered are able to simultaneously reproduce all measured observables.
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All authors MicroBooNE collaboration: P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, V. Bhelande, M. Bhattacharya, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M.B. Brunetti, L. Camilleri, D. Caratelli, F. Cavanna, G. Cerati, A. Chappell, Y. Chen, J.M. Conrad, M. Convery, L. Cooper-Troendle, J.I. Crespo-Anadon, R. Cross, M. Del Tutto, S.R. Dennis, P. Detje, R. Diurba, Z. Djurcic, K. Duffy, S. Dytman, B. Eberly, P. Englezos, A. Ereditato, J.J. Evans, C. Fang, W. Foreman, B.T. Fleming, D. Franco, A.P. Furmanski, F. Gao, D. Garcia-Gamez, S. Gardiner, G. Ge, S. Gollapinni, E. Gramellini, P. Green, H. Greenlee, L. Gu, W. Gu, R. Guenette, L. Hagaman, M.D. Handley, M. Harrison, S. Hawkins, A. Hergenhan, O. Hen, C. Hilgenberg, G.A. Horton-Smith, A. Hussain, B. Irwin, M.S. Ismail, C. James, X. Ji, J.H. Jo, A. Johnson, R.A. Johnson, D. Kalra, G. Karagiorgi, A. Kelly, W. Ketchum, M. Kirby, T. Kobilarcik, K. Kumar, N. Lane, J.-Y. Li, Y. Li, K. Lin, B.R. Littlejohn, L. Liu, S. Liu, W.C. Louis, X. Luo, T. Mahmud, N. Majeed, C. Mariani, J. Marshall, F. Martinez Lopez, D.A. Martinez Caicedo, M.G. Manuel Alves, S. Martynenko, A. Mastbaum, I. Mawby, N. McConkey, B. McConnell, L. Mellet, J. Mendez, J. Micallef, A. Mogan, T. Mohayai, M. Mooney, A.F. Moor, C.D. Moore, L. Mora Lepin, M.A. Hernandez Morquecho, M.M. Moudgalya, S. Mulleriababu, D. Naples, A. Navrer-Agasson, D. Nawarathne, N. Nayak, M. Nebot-Guinot, C. Nguyen, L. Nguyen, J. Nowak, N. Oza, O. Palamara, N. Pallat, V. Paolone, A. Papadopoulou, V. Papavassiliou, H.B. Parkinson, S.F. Pate, N. Patel, Z. Pavlovic, E. Piasetzky, K. Pletcher, I. Pophale, X. Qian, J.L. Raaf, V. Radeka, A. Rafique, M. Reggiani-Guzzo, J. Rodriguez Rondon, M. Rosenberg, M. Ross-Lonergan, I. Safa, C. Sauer, D.W. Schmitz, A. Schukraft, W. Seligman, M.H. Shaevitz, R. Sharankova, J. Shi, L. Silva, E.L. Snider, S. Soldner-Rembold, J. Spitz, M. Stancari, J. St. John, T. Strauss, A.M. Szelc, N. Taniuchi, K. Terao, C. Thorpe, D. Torbunov, D. Totani, M. Toups, A. Trettin, Y.-T. Tsai, J. Tyler, M.A. Uchida, T. Usher, B. Viren, M.L. Velazquez Fernandez, J. Wang, L. Wang, M. Weber, H. Wei, A.J. White, S. Wolbers, T. Wongjirad, K. Wresilo, W. Wu, E. Yandel, T. Yang, L.E. Yates, H.W. Yu, G.P. Zeller, J. Zennamo, S. Zhai, C. Zhang, Y. Zhang

Mathematical Physics · Cross-listed from cs.DS

Computing Gaussian and exponential integrals in ${\Bbb R}^n$

Alexander Barvinok

We consider expectations of the type $E \exp \left\{\sum_{i=1}^m \phi_i \right\}$, where $\phi_i: {\Bbb R}^n \longrightarrow {\Bbb C}$ are functions, each depending on a few coordinates of a point in ${\Bbb R}^n$, and the expectation is taken with respect to the standard Gaussian or symmetric exponential probability measures. We prove sufficient conditions, in terms of the Lipschitz constants of $\phi_i$ and the combinatorics of their dependencies, for the integral to be non-zero, and, consequently, to be amenable to a computationally efficient approximation. We discuss applications to computing volumes of bodies and statistics on integer points in polyhedra in ${\Bbb R}^n$.
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Optics · Cross-listed from cs.NI

Protection Switching in Hybrid Hollow-Core and Single-Mode Fiber Networks: Challenges, Analysis, and Mitigation Strategies

Md Ghulam Saber and Zhiping Jiang

Hollow-core fibers (HCF) are transitioning from laboratory curiosities to production-deployed infrastructure, with cloud providers operating thousands of kilometers of hollow-core links. As operators upgrade their networks, working and protection paths will inevitably traverse different fiber types, creating a class of protection switching challenges absent in homogeneous single-mode fiber networks. This article provides a comprehensive overview of these challenges and presents a comparative analysis of protection switching under two architectures - 1+1 dedicated and shared backup path protection (SBPP) - in hybrid hollow-core and single-mode fiber networks. Using Monte Carlo simulation with random per-link fiber assignment across six reference topologies (1,602 node pairs), we quantify chromatic dispersion (CD) steps, generalized signal-to-noise ratio (GSNR) penalties, and modulation-format degradation for both architectures. At 50% HCF deployment mean CD steps range from 4,000 to 22,000 ps/nm, with GSNR penalties of 1.6-3.1 dB and 38-59% of node pairs requiring modulation downgrade under 1+1 protection. A complementary cross-fiber extreme analysis reveals that the two switching directions are fundamentally asymmetric: HCF-to-SMF switching doubles the CD step and inflicts about a 10 dB GSNR penalty while SMF-to-HCF switching delivers a negative GSNR penalty (the protection path is higher quality than the working path). SBPP shows up to 7% higher CD steps and 4 percentage points more downgrade in sparsely connected topologies due to its greedy shortest-first path selection. Capacity retention improves with HCF penetration for both architectures, reaching 85-99% at full HCF deployment. We present mitigation strategies including DSP pre-loading, spectral pre-equalization, and network planning guidelines, concluding that 1+1 dedicated protection is preferable to SBPP for hybrid deployments.
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Statistical Mechanics

Skewness tunes the small-drift record rate of random walks and Lévy flights

José Ricardo G. Mendonça

A random walk with small positive drift $\mu$ sets new records at a rate $\lambda(\mu)$ that vanishes as $\mu \to 0$. For Gaussian and strictly stable centered steps whose stable law $Y$ has index $1 < \alpha \leq 2$ and positivity parameter $\rho = \mathbb{P}(Y>0)$, we find $\lambda(\mu) \sim K\mu^{(1-\rho)/\nu}$ as $\mu \to 0$, where $\nu=1-1/\alpha$ and $K$ is explicit. Throughout their domains of attraction, the exponent persists, with a slowly varying factor replacing the constant $K$. The exponent is set by the asymmetry only through $\rho$, sweeping the interval $[1,\,1/(\alpha-1)]$ as the skewness varies. For centered strictly stable steps, $\rho$ also governs the driftless record growth, $\langle R_{N}\rangle \sim N^{\rho}/\Gamma(1+\rho)$, which the small-drift law meets at the crossover where the drift takes over. The formula recovers the Gaussian linear law $\lambda(\mu) \sim \sqrt{2}\mu/\sigma$ and, for symmetric heavy tails, the power $\mu^{\alpha/2(\alpha-1)}$. It follows from one Mellin transform of the harmonic sum in the Spitzer–Baxter identity, which factorizes into a kernel transform carrying the step distribution and a Riemann zeta function carrying the harmonic weights. Its poles deliver the leading law, its prefactor, and a correction ladder reproducing the known Gaussian and stable series, unifying diffusive, heavy-tailed, and skewed walks. The power law ends at the Cauchy point $\alpha=1$, where $\mu$ is a pure location shift: for the strictly Cauchy family the limiting rate vanishes and records accumulate sublinearly with a shift-dependent exponent.
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General Relativity and Quantum Cosmology

Affine quantization of the dynamical Reissner–Nordström region

Morteza Bajand and Babak Vakili

We study the quantum dynamics of the dynamical region of the Reissner–Nordström geometry using a minisuperspace reduction and affine quantization, which is naturally suited for positive-definite geometrical variables. The resulting Wheeler–DeWitt equation becomes separable, yielding Hermite-polynomial modes in one sector and Gaussian-like radial solutions in the other. Affine quantization introduces additional short-distance contributions that modify the small-radius behaviour of the wave function. By constructing normalizable semiclassical wave packets, we analyze the resulting probability distributions in minisuperspace and the role played by the electric charge in the quantum dynamics. Our results extend previous affine-quantization studies of the Schwarzschild case to the charged Reissner–Nordström geometry.
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Earth and Planetary Astrophysics

Observing a 542-day transiting giant with large TTVs: The 2025 transit of HIP 41378 f and new constraints on the outer system

Pietro Leonardi, Alexandre Santerne, Luca Borsato et al. (+27 more)

Characterizing long-period transiting exoplanets is inherently challenging due to the rarity and long duration of transit events. Yet, these systems provide unique insights into planetary formation, migration, the detection of exomoons, and primordial atmospheres by occupying a sparsely populated region of the exoplanet parameter space. The complexity increases further for long-period planets near mean-motion resonances, where transit timing variations (TTVs) can reach amplitudes of several hours to days. We present a coordinated space- and ground-based observing campaign, using photometry from NEOSSat, multiple LCOGT sites, MuSCAT, MuSCAT3, Tierras and NGTS, to capture the 19-hour transit of the long-period giant exoplanet HIP 41378 f ($P$ = 542 d, $R$ = 9.5 $R_{\oplus}$) on 31 October 2025. Our transit analysis constrains the time of inferior conjunction to $T_{\mathrm{C}} = 2460980.888 \pm 0.029~\mathrm{BJD_{TDB}}$, occurring $\sim 7$ hours earlier than predicted from its linear ephemeris. This significant offset is consistent with the previously reported TTVs of HIP 41378 f, making it the longest-period exoplanet known to exhibit measurable TTVs. By combining this new precise measurement to the transit timings of the two outer planets in the system (HIP 41378 d and HIP 41378 e), we perform a dynamical modeling of the system, using the N-body integrator TRADES, refine the ephemeris of HIP 41378 f, and predict future transit events for all three outer transiting planets.
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All authors Pietro Leonardi, Alexandre Santerne, Luca Borsato, Salomé Grouffal, Christopher R. Mann, Giampaolo Piotto, Karen A. Collins, Patrick Tamburo, Yugo Kawai, Denise C. Stephens, Juliana García-Mejía, Edward M. Bryant, Krzysztof Sz. Zielinski, Daniel Bayliss, David Charbonneau, Jerome P. de Leon, Gareb Fernández-Rodríguez, Akihiko Fukui, Eric G. Hintz, Keith Horne, Keisuke Isogai, James S. Jenkins, Norio Narita, Ramotholo Sefako, Avi Shporer, Richard P. Schwarz, Gregor Srdoc, Peter Wheatley, Jamie B. Williams, Jorge Fernández Fernández

Disordered Systems and Neural Networks

Approximating velocity fields with planted point attractors via Neural-ODE for classification purposes

Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni et al. (+3 more)

In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks. The planted fixed points serve as indicators for the target classes, while the velocity field, leveraging the universal approximation capabilities of the architecture, shapes the dynamical landscape. This process defines the basins of attraction of the trained model, effectively directing each input (provided as an initial condition) toward its corresponding destination target.
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All authors Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni, Lorenzo Chicchi, Diego Febbe, Raffaele Marino

Accelerator Physics

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations

Nandana Menon and Giorgio Vallone

This paper presents SuperCond-GNN, a graph neural network-based surrogate model for predicting the voltage distribution in high-temperature superconducting (HTS) magnets. HTS magnets are modeled as lumped-element equivalent circuits and mapped onto graph representations, enabling message passing GNNs to learn the electrical response as a function of circuit topology, material properties, and operating current. As a proof of concept, tape stacks of up to 10 tapes are considered across a range of circuit topologies and operating conditions. The surrogate is trained on data generated from circuit simulations and achieves a mean MAPE of 4.3 % within the prescribed design space. The predicted nodal voltages enable fast and scalable inference of current redistribution and local operating conditions across a wide range of circuit configurations. The effect of incorporating physics-informed regularization via Kirchhoff's current law is also evaluated, and generalizability to unseen topologies is assessed through zero-shot inference and few-shot fine-tuning. While demonstrated on tape stack circuits, the graph-based framework is topology-agnostic and naturally extensible to more complex HTS cable and magnet configurations, offering a scalable alternative to conventional circuit solvers for downstream applications such as design space exploration, current sharing analysis, and real-time magnet monitoring.
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Quantum Physics

Structure-Aware Variance Reduction for Unbiased Randomized Hamiltonian Simulation

Joshua W. Dai, Fredrik Hasselgren and Chusei Kiumi

Randomized Hamiltonian simulation methods are often governed by a trade-off between systematic bias and sampling overhead. We study how classical variance-reduction techniques can be applied to such methods without changing their mean channel, and therefore without introducing additional bias. As a motivating unbiased estimator, we formulate continuous time-evolution probabilistic angle interpolation (continuous TE-PAI), a quasiprobabilistic random-circuit protocol whose remaining Monte Carlo error is purely statistical. Continuous TE-PAI removes Trotter discretization error with finite-depth random circuits, whereas deterministic Trotterization does so only in the infinite-depth limit. Further, in tensor-network simulations, we demonstrate that discretization error can cause an unphysical exponential growth in the bond dimension required for Trotterized simulations, whereas comparable-depth continuous TE-PAI circuits avoid this growth. We then show that the variance of randomized product-formula-based estimators admits a canonical decomposition into a classical counting component and a quantum ordering component such that the dominant simulation overhead results from the non-commutative parts of the Hamiltonian dynamics. Motivated by this decomposition, we achieve an $\approx70\%$ error-reduction using the counting-component for small systems whereas our tensor-network simulations of $n=30$ spin-chain dynamics use coarser statistics tailored to the observable and estimator attaining a negligible bias and a reduction of $\approx 80\%$ leading to $\approx91\%$ and $\approx96\%$ sampling-cost reductions, respectively.
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