General Relativity and Quantum Cosmology
The Quantum Boundary of Black Hole Interiors: Signature Failure and the Termination of Mass Inflation
Edward J. Shaya
Classical general relativity predicts a singularity at the center of every black hole. We argue that it is never reached. We adopt the
conjecture of Shaya (2026) that a metric element of non-Lorentzian signature is inadmissible: it cannot enter the Feynman sum over geometries, and so cannot belong to the physical
manifold. Nothing beyond standard
quantum mechanics is invoked. Signature is the only pointwise diffeomorphism-invariant content of the metric, so the criterion is local and coordinate independent. Transverse-traceless graviton
vacuum fluctuations grow as $\Delta_g = \sqrt{8/\pi}\,\ell_P/q$ on a scale $q$, and any finite-scale metric stress driving an
eigenvalue through zero removes that element. When the surviving elements can no longer sustain connected, differentiable, causally propagating support, the
manifold terminates on a
quantum boundary $\mathcal{B}_Q$ at finite radius. For the
vacuum Schwarzschild interior the
tidal Weyl stress gives $r_{\rm qb} \simeq 1.0\times10^{-22}(M/M_\odot)^{1/3}$~m for the adopted
curvature response $C_W=0.15$. For a spinning hole, the boundary forms much farther out: mass inflation at the inner horizon $r_{-}$ concentrates an exponentially growing interior mass into a thin layer whose thickness is set by the
accretion rate and floored at one spatial
quantum, and the counter-streaming null fluxes supply a trace-free
Ricci stress along the radial axis alone. This caps the factor $n_{\rm qb}$ by which mass inflation can amplify the interior mass function, at between $10^{38}$ and $10^{69}$ for a $10\,M_\odot$ hole depending on its
accretion history, and leaves the Cauchy horizon, the ring, and all deeper extensions outside the physical
manifold. The Gibbons–Hawking–York term over this terminal slice yields a finite interior action, $S_{GHY}^{qb} \approx \frac{3}{2} n_{\rm qb} Mc^2\,\Delta t$.
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Quantum Physics
Scheme for Transport-based Global Entanglement Distribution using Quantum Processors
Erik Lundblad, Mira Abu Yahia, Antonius Johannes Renders et al. (+3 more)
We propose a scheme for distributing
entanglement over global distances in a heralded manner by using satellites to physically transport entangled processor nodes with rare-earth-ion
qubits. A full analysis of channel losses, errors and background light is performed to determine the fidelity and number of entangled pairs that can be distributed between two ground stations. We show that the scheme works already with a single satellite and can distribute close to the theoretical maximum number of entangled pairs that can be generated in a satellite overpass. In addition, we argue that in theory transportation-based schemes outperform other satellite-based schemes and can be scaled up to a constellation without additional channel losses. Daytime operation seems feasible as long as the sky is clear, with an EPR pair fidelity ranging from 99.3% at shorter network lengths to 93.9% with global coverage and can be further improved by active error correction or
entanglement purification.
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All authors Erik Lundblad, Mira Abu Yahia, Antonius Johannes Renders, Andreas Walther, Adam Kinos, Lars Rippe
Soft Condensed Matter
Kinetic Criticality in Linker-Mediated Colloidal Aggregation
Alexei V. Tkachenko, Soojung Lee, Zohar A. Arnon et al. (+1 more)
Linker-mediated aggregation plays an important role in modern nanoscience. We demonstrate that it departs sharply from classical Smoluchowski kinetics because cluster reactivity evolves during growth. Combining theory with DNA-linked gold-nanoparticle experiments, we establish kinetic critical point controlled by linker abundance. Below threshold, active linkers are depleted and growth arrests; above threshold, clusters accumulate reactive sites, self-accelerate, and cross over to
diffusion-limited coarsening. Experiments verify the predicted arrest, accelerated growth, and scaling collapse.
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All authors Alexei V. Tkachenko, Soojung Lee, Zohar A. Arnon, Oleg Gang
Disordered Systems and Neural Networks
Cluster-based Message-Passing (CluMP) Optimization for Complex QUBO Problems
Paolo Rissone, Stefan Boettcher, Alfonso Amendola et al. (+2 more)
Quadratic Unconstrained Boolean Optimization (QUBO) problems are widespread in both industrial applications and scientific studies. A QUBO problem corresponds to the optimization of a system of Ising
spins defined on a generally sparse and heterogeneous graph. When the QUBO problem contains conflicting requests, the corresponding Ising system is frustrated, generating a complex energy landscape, which is hard to explore and optimize. Despite extensive algorithmic and hardware developments, finding low-energy configurations in these systems remains challenging (e.g., local-update heuristics typically become trapped in metastable states), especially when the (possibly frustrated) interactions generate extended correlated domains. We introduce CluMP (Cluster-based Message-Passing), an
algorithm that performs collective updates on connected clusters of
spins using information from Belief Propagation (BP). By controlling the amount of frustration within clusters, CluMP enables BP convergence on large subgraphs and proposes nonlocal rearrangements involving up to hundreds of
spins in a single move. We
benchmark CluMP against state-of-the-art local-update heuristics on
spin-glass models defined on several graph
topologies, including random regular graphs and
lattice regular graphs in two and three dimensions. Cluster moves consistently bypass local trapping and reach lower energies with fewer effective operations than single-
spin dynamics. These results demonstrate that frustration-tolerant cluster updates can be implemented efficiently on sparse graphs. The CluMP framework provides a scalable strategy for large-scale combinatorial optimization and inference problems, where exploiting medium- and long-range correlations is key to navigating complex energy landscapes.
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All authors Paolo Rissone, Stefan Boettcher, Alfonso Amendola, Simone Sala, Federico Ricci-Tersenghi
Astrophysics of Galaxies
Consistency between X-ray and UV-Optical reverberation measurements in NGC 5548
Amit Kumar Mandal, Bożena Czerny, Michal Dovčiak et al. (+2 more)
The hard X-ray$-$emitting hot corona is a key component of active
galaxies. Constraints on the hot corona height can be derived from reverberation studies in both the X-ray and optical bands. X-ray reverberation (X-ray$-$RM) studies often imply a very low corona height, whereas UV/optical reverberation mapping (photometrcic continuum$-$RM) typically points to a much larger one. To reconcile this discrepancy, we examine the constraints provided by both methods for the same source. We adopt a uniform methodology using the KYNSED and KYNXiltr codes within a consistent modeling framework for reverberation mapping, applicable across both the X-ray and UV-optical spectral and time domains. We select the source NGC 5548, for which the necessary observational data are available in the literature. We carry out our analysis for NGC 5548, a source with extensive reverberation mapping data obtained independently in the X-ray and UV-optical bands across different epochs. Our results hint for a substantial discrepancy between the global parameters required to reproduce the X-ray and those needed to fit the UV-optical reverberation signals. In particular, the mismatch in the inferred black hole mass and
accretion rate presents a significant challenge for interpreting the observed time delays within a unified reflection-based framework. Our unified reflection-based modeling sheds light on X-ray and UV-optical variability of NGC 5548, but discrepancies in black hole mass,
accretion rate, and corona properties might imply fundamental challenges to a self-consistent model. However, future analyses leveraging extended X-ray
dataset with improved treatment of absorption and variability coherence are crucial to obtaining more robust constraints.
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All authors Amit Kumar Mandal, Bożena Czerny, Michal Dovčiak, Elias Kammoun, Iossif Papadakis
Soft Condensed Matter
Cobalt-Catalysed Chain Transfer Polymerisation Enables Soft Methacrylate Nematic Elastomers for Switchable Pressure-Sensitive Adhesion
Noboru Koshimizu and Mohand O. Saed
Liquid crystal elastomers (LCEs) exhibit unique viscoelastic behavior arising from reversible
liquid-crystalline ordering, making them attractive candidates for switchable pressure-sensitive adhesives (PSAs). However, methacrylate-based LCEs are typically highly crosslinked, leading to elevated glass-transition temperatures ($T_g$) and storage
moduli ($E'$) that limit adhesive performance. Here, we demonstrate that catalytic chain-transfer polymerization provides an effective strategy for engineering soft methacrylate nematic elastomers through systematic control of network architecture. Incorporation of parts-per-million concentrations of bis(boron difluorodimethylglyoximate)cobalt(II) (CoBF) during photopolymerization reduced the effective crosslink density and increased the molecular weight between crosslinks, producing substantial decreases in $T_g$ and $E'$ while preserving nematic order. Dynamic mechanical analysis revealed that increasing CoBF concentration enhanced viscoelastic dissipation and broadened the accessible nematic temperature window. To further optimize rheological properties for pressure-sensitive adhesion, monofunctional methacrylates and flexible poly(ethylene glycol) dimethacrylate (PEGDMA) were incorporated into the network. The optimized formulation exhibited a $T_g$ near 0~$^\circ$C, a room-temperature storage modulus of approximately 0.3 MPa, and high damping behavior, approaching the Dahlquist criterion for pressure-sensitive adhesion. As a result, the resulting nematic elastomers displayed strong tack, peel, and lap-shear adhesion in the nematic state, together with rapid, reversible, and residue-free debonding upon heating above the nematic-to-isotropic transition temperature.
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Fluid Dynamics
Filtering effects on entropy transport and entropy-production structure in a supersonic reacting shear layer
Sriram P. Kalathoor and Joseph C. Oefelein
Spatial filtering is examined in time-resolved mid-plane DNS fields of a supersonic reacting shear layer using a sequence of box filters. The analysis tracks a nondimensional
entropy-like scalar $s^\ast$, its in-plane material derivative $D s^\ast / D t^\ast$, a residual $\Pi_s^\ast$, and viscous and conductive
entropy-production diagnostics, $\sigma_\mu^\ast$ and $\sigma_k^\ast$. Filtering changes $s^\ast$ only weakly, attenuates $D s^\ast / D t^\ast$ and the strongest tails of $\sigma_\mu^\ast$ and $\sigma_k^\ast$, but broadens the residual distribution and increases the residual RMS with filter width. The residual remains concentrated in the layer core that carries the largest mechanical and thermal activity. Conditional statistics show that $|\Pi_s^\ast|$ rises with both
entropy-production intensity and
entropy-gradient strength. Spectral and structural diagnostics show that increasing filter width removes high-wavenumber content and simplifies the geometry of the high-$|\Pi_s^\ast|$ sets. Coarser filtering therefore increasingly distorts
entropy transport preferentially through the most dynamically and thermally active structures, rather than uniformly across the plane.
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Quantum Physics
Watching a Superconducting Coplanar Waveguide Heat Up with a Single Color Center
Ioannis Karapatzakis, Jeremias Resch, David Hunger et al. (+1 more)
Single color centers in diamond offer a local probe of their cryogenic environment, providing a direct way to quantify heating in
spin-control hardware. Here, we establish a single spectrally stable tin-vacancy (SnV) center as an on-chip thermometer for a diamond membrane and use it to characterize microwave- and
radio-frequency-induced heating in a superconducting coplanar waveguide patterned on the same chip. We first calibrate the temperature dependence of the optical C-transition frequency and linewidth from $20\,\mathrm{K}$ down to the few-kelvin regime. At lower temperatures, where the optical response becomes weakly temperature dependent, we use the
spin-
lattice relaxation time $T_1$ as a complementary thermometer and tune its sensitivity with the transverse
magnetic-field component. Applying this local thermometer to a niobium coplanar waveguide, we observe
magnetic-field-dependent superconducting breakdown under GHz drive, accompanied by abrupt heating of the diamond. In contrast, at $20\,\mathrm{MHz}$ and $400\,\mathrm{mT}$, relevant for
nuclear-
spin control, we detect no measurable heating up to the breakdown threshold of $9.4\,\mathrm{dBm}$, corresponding to $B_\mathrm{ac}\sim1.2\,\mathrm{mT}$. These results define a safe operating window for superconducting microwave and RF control structures in diamond-based
quantum nodes.
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All authors Ioannis Karapatzakis, Jeremias Resch, David Hunger, Wolfgang Wernsdorfer
High Energy Astrophysical Phenomena
Constraining hydrodynamic model of nearby type IIP SN 2023ixf
V. P. Utrobin and N. N. Chugai
Despite proximity of SN 2023ixf and a wealth of observational data, the released hydrodynamic models leave too broad range of the derived explosion energy and the ejected mass. We revisit the hydrodynamic modeling based on a broader set of observables than have been previously used. Among those of top priority is the early maximum ejecta velocity that is crucial in removing parameter degeneracy. The inferred parameters of SN 2023ixf are the explosion energy of 2.8x10^{51} erg, ejecta mass of 13.2 Msun, presupernova radius of 1540 Rsun, and Ni-56 mass of 0.07 Msun. The circumstellar matter is composed by the dense circumstellar shell with the mass of 0.01 Msun and radius of 5x10^{14} cm, as well as the external rarefied wind. Both circumstellar components are consistent with the early H-alpha broad wings caused by the Thomson scattering and the intrinsic column density provided by X-ray data. Based on the radiation hydrodynamics we, for the first time, simulate the SN 2023ixf phenomenon from the explosion to the emergence of the hard X-ray radiation.
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Optics
Multi-channel high-speed flip-chip packaging platform for thin-film lithium niobate photonic circuits
Zhenzheng Wang, Xiangzhi Xie, Yikun Chen et al. (+11 more)
To address the urgent need for multi-channel high-speed electrical interfacing of thin-film lithium niobate (TFLN) photonic
circuits, we realize a flip-chip packaging platform capable of simultaneously delivering 13 high-speed and 32 low-speed electronic signals to a centimeter-sized TFLN chip. The platform exhibits low flip-chip bonding loss and low inter-channel crosstalk over a broad bandwidth up to 50 GHz. Leveraging this packaging platform, we demonstrate high-speed electrical interfacing with two proof-of-concept TFLN photonic
circuits, namely a 2x8 optical switch and an electro-optic comb-based transmitter. The switch achieves arbitrary 8-channel routing with ~3 dB insertion loss, < -20 dB crosstalk, and an equipment-limited switching time of <= 34 ps. The transmitter
circuit includes a 50 GHz electro-optic comb generator with 2.8-dB flatness, a tunable microring to arbitrarily filter one comb line, and a modulator for data transmission at 20 Gbit/s. The packaging platform could significantly advance large-scale TFLN
circuits in optical communications, microwave photonics, and photonic computing.
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All authors Zhenzheng Wang, Xiangzhi Xie, Yikun Chen, Yifan Wu, Zeyu Luo, Hanke Feng, Yulong Chen, Zengyi Xu, Zixi Wang, Yuansong Zeng, Mandie Huang, Ke Zhang, Yingxia Liu, Cheng Wang
High Energy Astrophysical Phenomena
Comparison of X-ray Emission Properties of TDEs and Soft Flares from AGNs
Samaresh Mondal, K. Decker French and Jason T. Hinkle
X-ray flaring activity from active
galactic nuclei (AGNs) may mimic the expected emission from
tidal disruption events (TDEs), thus contaminating TDE searches. To compare X-ray emission properties between TDEs and AGNs, we cross-match publicly available XMM-Newton and Swift-XRT point source catalogs with the Million
Quasars Catalog and optically selected TDEs. We find that AGNs tend to become softer with a similar hardness ratio (HR) value as TDEs during their flaring events. The soft HRs during flaring events in these AGNs are driven by the emergence of a blackbody-like component below $\sim$2 keV, likely associated with the soft X-ray excess, as well as the continuum emission becoming steeper with the increase of
accretion rate. We find 2.5% in XMM-Newton (23 out of 920) and 4.4% in Swift-XRT (179 out of 4089) AGNs display
flares with peak count rate $>$$2\sigma$ from the median count rate and peak HR$<$$-0.75$. The rate of such
flares in XMM-Newton and Swift-XRT is (1.1-2.5)$\times10^{-3}\rm\ galaxy^{-1}\ yr^{-1}$ and (0.9-2.0)$\times10^{-3}\rm\ galaxy^{-1}\ yr^{-1}$, respectively. We also estimate the rate of
flares with a maximum flux change (peak/min) of $>20\times$ over on a rest-frame time scale of two years or more with a HR$<$$-0.75$ at peak to be (4.7-11.0)$\times10^{-5}\rm\ galaxy^{-1}\ yr^{-1}$ and (3.1-7.1)$\times10^{-5}\rm\ galaxy^{-1}\ yr^{-1}$ in XMM-Newton and Swift-XRT, respectively. Finding an optical or infrared counterpart may help to identify these flaring AGNs. We confirm 61% and 79% of flaring sources from XMM-Newton and Swift-XRT, respectively, as AGNs through variability in ZTF light curves or a WISE $W1$$-$$W2$$>$0.8 mag color cut.
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High Energy Astrophysical Phenomena
Mapping Domain-Wall Bayesian Reconstruction with LISA
Satyabrata Datta and Rome Samanta
We study the
Bayesian reconstruction of peaked domain-wall gravitational-wave signals with LISA and construct reconstruction maps over the signal-parameter plane. These maps identify regions where the signal can be probed with minimal posterior uncertainty and parameter degeneracy. Our analysis employs a two-parameter domain-wall spectral template and includes astrophysical foregrounds from
Galactic double-white-
dwarf binaries and extragalactic compact binaries, together with LISA instrumental noise.
Bayesian inference is performed for 64 injections using nested sampling, and the resulting posterior quantities are interpolated with the Clough–Tocher method to generate smooth maps across parameter space. Under the adopted instrumental-noise and foreground assumptions, we find that LISA reconstructs domain-wall signals most effectively for annihilation temperatures $T_*\sim10^3\!-\!10^6\,\mathrm{GeV}$. In this regime, posteriors become tighter and less degenerate, enabling reliable two-parameter reconstruction. The most favorable region corresponds to signals with ${\rm SNR}\gtrsim50$, while signals with ${\rm SNR}\sim10$ remain reconstructable near $T_*\sim10^{5-6}\,\mathrm{GeV}$. This weaker-signal region corresponds approximately to $4\times10^{-12}\lesssim\Omega_{\rm GW}^{\rm peak}h^2\lesssim4\times10^{-11}$ and $30\,\mathrm{mHz}\lesssim f_p\lesssim100\,\mathrm{mHz}$. Our results provide a quantitative reconstruction forecast for peaked domain-wall signals in the LISA band and a guide for particle-physics models predicting milli-Hz gravitational-wave spectra.
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Quantum Physics
Quantum optimal control of steady orbits
Shebha Anandhi Jegadeesan, Yujie Zhao, Robert Hunter et al. (+6 more)
Periodically driven dissipative systems can settle into steady orbits - fixed loops on their dynamical
manifolds. In
quantum mechanics, steady orbits occur in cooling engines (used to initialise
quantum devices), coherent oscillators (such as
lasers and masers), precision metrology devices (atomic clocks, optical and
spin magnetometers), and
magnetic resonance (steady state free precession, dynamic
nuclear polarisation). Steady orbits and stroboscopic steady states are a promising target for
quantum optimal control, but the numerical complexity is prohibitive: the infinite loop defeats gradient ascent pulse engineering (GRAPE) which relies on explicit numerical propagation in the time domain. Here we propose an efficient
quantum control strategy for stroboscopic steady states and limit cycles that are approached asymptotically when a control sequence is repeated infinitely many times. The formalism is different from Floquet-Lindblad state engineering and effective
Hamiltonian theories: it finds control sequences that drive a dissipative
quantum system towards a steady orbit passing through user-specified waypoints. The software implementation (same numerical complexity scaling as GRAPE) is done for the Spinach library.
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All authors Shebha Anandhi Jegadeesan, Yujie Zhao, Robert Hunter, Hassane El Mkami, Maximilian Keitel, Callum Musselwhite, Graham Smith, Guinevere Mathies, Ilya Kuprov
Quantum Physics
Single-Image Entanglement Verification with Spatially Encoded Measurement Contexts
Nazanin Dehghan, Alessio D'Errico, Yingwen Zhang et al. (+3 more)
Entangled
photon pairs produced by spontaneous parametric down-conversion exhibit rich spatial
entanglement structure that is often difficult to probe with conventional measurements. Here, we show that
spin-orbit optical elements can convert this spatial structure into directly observable
quantum interference patterns. Using a $q$-plate, we demonstrate that the relative wavefront
curvature of biphoton states generated by a pair of nonlinear
crystals can be retrieved from the spatial modulation of coincidence images. Building on this principle, we introduce a
liquid-
crystal metasurface that performs spatially multiplexed Bell measurements across the transverse profile of the
photon field. The device, which we call a Clauser-Horne-Shimony-Holt (CHSH) plate, assigns different polarization projections to different azimuthal sectors of the beam, allowing the sixteen joint measurements required for a CHSH test to be realized simultaneously in a single acquisition. In this architecture, the spatial coordinate acts as a classical register selecting the measurement context, while
photon pairs sample these contexts according to their emission directions. We further demonstrate that the same measurement concept can be implemented using a programmable spatial light modulator, providing a dynamically reconfigurable realization of the scheme. Our results show that spatially structured optical elements can transform Bell tests into parallel measurements distributed across the transverse plane, enabling rapid characterization of spatially varying
entanglement. This approach opens new possibilities for structured-light
quantum measurements, Bell-inequality-based imaging, and the study of spatially engineered entangled
photon sources.
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All authors Nazanin Dehghan, Alessio D'Errico, Yingwen Zhang, Hugo Defienne, Daniele Faccio, Ebrahim Karimi
General Relativity and Quantum Cosmology
EMRI Dephasing from a Torsion-Inspired Near-Zone Kerr Deformation: Motivated by Spin-Polarized Dark Matter
Jingxu Wu, Liangyu Luo, Daniil Stepanenko et al. (+1 more)
Extreme-mass-ratio inspirals (EMRIs) are sensitive probes of weak conservative perturbations in the strong-field region of massive black holes. We study a phenomenological EMRI model motivated by Einstein–Cartan
gravity in which a
spin-polarized dark-matter spike is described by a Weyssenhoff fluid. After torsion is eliminated algebraically, the local
spin contribution contains a repulsive exterior source $U_{tt}^{\rm spin}\propto-\sigma_0^2/r^3$. Solving the corresponding static linearized field equation, however, does not produce a global $1/r^3$ metric perturbation; the response contains a mass renormalization, a logarithmic $r^{-1}$ tail, and an $M/r^2$ term. We therefore introduce $g_{\mu\nu}^{\rm eff}=g_{\mu\nu}^{\rm Kerr}+\alpha h_{\mu\nu}^{\rm eff}$ only as a local near-zone matching ansatz, not as a complete rotating Einstein–Cartan black-hole solution. Within this torsion-inspired deformation we compute circular equatorial inspirals and analytic-kludge waveforms. The fiducial model can produce large phase shifts in an idealized adiabatic calculation, but the forecast is optimistic and does not include a full LISA/Taiji response, Teukolsky/self-force fluxes, eccentricity, inclination, or high-dimensional parameter degeneracies. The results should be read as constraints on an effective near-zone operator rather than as a prediction of minimally coupled Einstein–Cartan dark matter.
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All authors Jingxu Wu, Liangyu Luo, Daniil Stepanenko, Jie Shi
Geophysics · Cross-listed from cs.LG
Learning Earthquake Wave Arrival Time Picking from Labels with Inaccuracies
Sen Li, Xu Yang, S. Mostafa Mousavi et al. (+5 more)
Inaccurately labeled training data, or "label noise", poses a significant threat to the integrity of supervised machine learning models. This corruption directly degrades performance by teaching the model erroneous mappings between features and labels, which leads to poor generalization and reduced accuracy on properly labeled validation and test data. Current seismological applications mainly rely on large-scale training sets or data augmentation to reduce the label-noise impact, which can be labor-intensive and costly. Here, we introduce a Label Noise-Contrastive Robust Learning (LaNCoR) approach that can effectively handle noisy labels in seismic signal processing tasks, without requiring large-scale training
datasets. In this approach, the input waveform feature and label representation distributions are aligned in the feature space to correct mislabeling and reduce its impact on the training process. We present LaNCoR's performance on the task of P-phase arrival-time picking of real microseismic data using two baseline models and training approaches. Our results indicate that LaNCoR can improve performance by up to 28.8% across performance metrics. This approach holds great promise for model training in seismology and geosciences.
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All authors Sen Li, Xu Yang, S. Mostafa Mousavi, Anye Cao, Keting Fan, Yaoqi Liu, Changbin Wang, Qiang Niu
Mesoscale and Nanoscale Physics
Topological Surface Charge Detection via Terahertz Time-domain Spectroscopy
Tong Shen, Yiyang Xie, Yucheng Dai et al. (+4 more)
The topological magnetoelectric effect (TME) is a condensed-matter realization of the four-dimensional
quantum Hall effect (4D-QHE), manifesting as quantized surface charge accumulation proportional to an applied
magnetic field. To date, however, no optical technique has been developed to directly probe this charge accumulation. Here, we demonstrate a terahertz time-domain spectroscopy method for direct detection of surface charge accumulation—a physical quantity relevant to both the 4D-QHE and 2D-QHE, in sharp contrast to the previous optical measurements, which focused on the
Hall conductivity $\sigma_{xy}$ of the 2D-QHE. Using a chromium-doped (Bi,Sb)$_2$Te$_3$ thin film, we achieve sub-milliradian Faraday rotation precision. Extending this scheme to
axion insulators, we predict that the TME gives rise to an imaginary Faraday rotation linear in frequency, whose slope directly reflects the single-surface charge density. With further improvements in sample thickness and precision, this approach offers a viable pathway toward direct verification of the TME and 4D-QHE.
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All authors Tong Shen, Yiyang Xie, Yucheng Dai, Yifan Zhang, Yuanze Li, Xufeng Kou, Tian Liang
Astrophysics of Galaxies
PEARLS: NuSTAR and XMM-Newton Extragalactic Survey of the JWST North Ecliptic Pole Time Domain Field VI: Multiwavelength SED Analysis
Rafael Ortiz III, Francesca Civano, Rogier A. Windhorst et al. (+27 more)
We model spectral energy distributions of 261 X-ray sources to $z \sim 5$ in the North Ecliptic Pole Time Domain Field, extending prior XMM-Newton and NuSTAR analyses. Using the
star-forming main sequence (SFMS) and black hole
accretion rate (BHAR) frameworks, we find that SFRs generally lie below the SFMS while most BHARs exceed the population average, as expected for X-ray-selected samples. There is a strong correlation ($\rho=+0.73$) between SFR relative to the SFMS and specific AGN luminosity, $L_{AGN}/M_*$;
galaxies with the highest $L_{AGN}/M_*$ exist at or above the SFMS. X-ray luminosity correlates with SFR ($\rho=+0.80$), revealing a
star-forming and X-ray luminous "cold
quasar" population consistent with dramatic, short-timescale
accretion episodes. Low-mass
galaxies show BHARs well above the population averaged value for their mass whereas high-mass
galaxies' SMBHs accrete at the population averaged BHAR, suggesting "growth spurt" and "maintenance-mode"
accretion, respectively. Traditional AGN classifications (obscured, unobscured, or
radio-loud) do not reveal these distinctions, demonstrating the X-ray perspective's unique ability to identify rare AGN phases that are critical for the instantaneous link between
galaxies and their SMBHs.
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All authors Rafael Ortiz III, Francesca Civano, Rogier A. Windhorst, S. P. Willner, Gibson B. Bowling, Timothy Carleton, Seth H. Cohen, Samantha Creech, Vicente Estrada-Carpenter, Brenda L. Frye, Norman A. Grogin, Heidi B. Hammel, Timothy Heckman, Rachel Honor, Rolf A. Jansen, Satoshi Kikuta, Anton M. Koekemoer, Madeline A. Marshall, Sylvia Mesicek, Mar Mezcua, Stefanie N. Milam, Simon D. Mork, Rosalia O'Brien, Payaswini Saikia, Ross M. Silver, Brent M. Smith, Hyewon Suh, Christopher N. A. Willmer, Haojing Yan, Xiurui Zhao
High Energy Physics (Phenomenology)
Constructing perfect spin-1 hydrodynamics from Boltzmann to Bose-Einstein statistics
Sudip Kumar Kar and Valeriya Mykhaylova
We derive thermodynamic currents for a perfect fluid of massive
spin-1 particles obeying Bose-Einstein statistics within the Wigner-function approach. Using a covariant
spin density
matrix, we construct
spin-extended
equilibrium distributions and obtain the energy-momentum and
spin tensors that match, up to second order in polarization, those of
spin-1/2 systems and the Boltzmann case. We find that the approach yields a unified description of relativistic
spin hydrodynamics independent of statistics and
spin representation. Furthermore, the framework fulfills the requirements of the divergence-type theory, with nonlinearly causal and stable dynamical equations.
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Optics
Super-Gaussian approximations for optimum far-field irradiance in intersatellite optical communications: coherent and incoherent beam shaping
Mario Badás Aldecocea, Yves van Gennip, Pierre Piron et al. (+2 more)
Intersatellite optical communication links are strongly affected by transmitter pointing jitter, which stochastically modulates the received optical power and degrades communication performance. While adjusting the divergence of a conventional Gaussian beams can partially mitigate this effect, the optimum far-field irradiance distribution for maximizing link performance has not been formally derived. In this work, we introduce a variational formalism to determine the optimum far-field irradiance for an intersatellite link affected by pointing jitter. The flat-top beam is found to be the optimum beam shape for minimizing outage probability. In particular, it requires $\sim37,8\%$ of the power needed by a conventional Gaussian beam to achieve the same outage probability. However, the flat-top profile is discontinuous and physically unrealizable. To address this, we analyze a continuous family of super-Gaussian beam shapes that approximate the flat-top as the order increases. In addition, several coherent and incoherent beam shaping techniques are evaluated to assess their ability to reproduce the optimum irradiance distribution. The results show that these techniques can reduce the required transmitted power by up to $\sim50\%$ compared with conventional Gaussian beams.
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All authors Mario Badás Aldecocea, Yves van Gennip, Pierre Piron, Jasper Bouwmeester, Jérôme Loicq
Instrumentation and Methods for Astrophysics
Spiking Neural Dedispersion: A Neuromorphic Fast Radio Burst Detection Pipeline
Alessio Magro
Real-time FRB detection at next-generation
radio telescopes is increasingly dominated in cost and footprint by the real-time dedispersion backend. We present a complete neuromorphic FRB detection pipeline built on the Spiking Neural Dedispersion (SND)
algorithm, a hierarchical delay-and-add tree that performs incoherent dedispersion on spike-encoded filterbank data, supporting arbitrary trial-DM grids and configurable branching factors. Three operating modes are evaluated, spanning a resource-sensitivity trade-off from binary thresholded accumulation to full float32 precision. Validated against Heimdall on synthetic Northern Cross filterbanks, float SND matches Heimdall at 99.3% detection completeness (244 mW per beam), graded mode achieves 89.3% at 61 mW, and binary mode reaches 59.4% overall (1.75 mW), retaining 91% sensitivity for bright, narrow events. The full pipeline fits on a single SpiNNaker 2 chip across all three modes; binary mode fits entirely within on-chip SRAM, while graded and float require external DRAM for the history buffer. On a deployed 48-chip system, total power projects to approximately 100-112 W, a reduction of order 10-40x over an equivalent GPU deployment, with 48 simultaneous beams per board.
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Data Analysis and Statistics · Cross-listed from stat.ME
Matched generating elements in maximum entropy density reconstruction
Serhii Zabolotnii
Moment-constrained maximum
entropy (MaxEnt) reconstructs a density as an exponential family whose sufficient statistics are chosen constraint functions. We study this choice separately from the numerical coordinates used to solve the dual problem. An odd-only family on a symmetric support forces f(x)f(-x) to be constant, so parity matching is necessary. A logarithmic-rational constraint produces the Student/Cauchy family and remains population-defined when required integer moments do not exist; a parity-matched one-parameter path provides a reproducible fractional-exponent alternative containing the monomials. The numerical study uses a common damped-Newton solver and audits the six-distribution
benchmark of Rajan et al. Stable parity-block divided differences, residual replay in the original constraint coordinates, and independent adaptive integration identify a raw-coordinate false convergence on D5. Under the corrected computation, the selected PATP arm is within 1.22 times the oracle on D5 but retains selected-to-oracle error ratios of 30.7, 8.88, and 3.33 on D2, D4, and D6 at n=12. These checks preserve the negative selector conclusion without treating a numerical artifact as statistical evidence. The Pearson row is reproduced, whereas the published GOPoly rows are not under the printed protocol. Matched LogRat results show family capacity; neither tested selector supports automatic choice among constraint families.
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Fluid Dynamics
ShipNet: A Geometric Deep Learning Surrogate for Real-Time Ship Hydrodynamics
Kirsten Odendaal and George Drakoulas
Accurate prediction of hydrodynamic performance is central to ship design, yet high-fidelity computational fluid dynamics remains prohibitively expensive for large-scale parametric exploration. This motivates the development of data-driven surrogate models that provide rapid approximations to hydrodynamic predictions at substantially reduced cost. We present ShipNet, a
geometric deep-learning surrogate that predicts both hull-surface pressure distributions and far-field free-surface wave patterns directly from hull geometry and speed. The network employs a regularized dynamic graph convolutional backbone on hull point clouds, with a multi-head decoder for simultaneous near-body pressure and free-surface elevation outputs. Training data consist of 420 inviscid free-surface simulations generated using a potential-flow panel method for two parent yacht hulls, each parameterized into 70 variants and evaluated at three speeds. ShipNet predicts per-point pressure coefficient and two-dimensional wave elevation map using a composite loss that combines point-wise regression and image-structure terms. On a geometry-held-out test set, ShipNet achieves R^2=0.98 for hull pressure and R^2=0.91 for wave fields. Inference requires approximately 0.15s per case, yielding over a 550x speedup relative to the potential-flow solver on conventional hardware. Limitations include the restricted geometry and speed ranges and the inviscid training data, while future work will extend the model to high-fidelity viscous simulations with physics-informed regularization.
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Instrumentation and Methods for Astrophysics
GridFire: A new, open source, nuclear network for stellar structure and evolution
Emily M. Boudreaux and Aaron Dotter
We present a novel
nuclear network implementation, GridFire, which has been developed with a focus on efficiency, ease of use, and automatic physical extension. In this first paper we provide a detailed overview of GridFire's numerics, performance characteristics, and a comparison to pre-existing
nuclear network implementations pynucastro and MESA's net module. We find that generally GridFire performs similarly to and requires significantly less user input and setup than these current generation
nuclear network codes. Further, GridFire has been developed with a flexible "view" based physics engine that allowing researchers to implement domain specific physics without modifying the underlying source code. GridFire has been released under an open-source license, GPL v3.0, and will eventually be incorporated into the forthcoming 4D-
STAR stellar structure
evolution code.
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Strongly Correlated Electrons · Cross-listed from math.NA
Linear algebra at exponential scale via tensor network dimension reduction
Chris Camaño, Ethan N. Epperly, Raphael A. Meyer et al. (+1 more)
Many problems in modern scientific computing are challenging because of a curse of dimension, where their mathematical formulation involves objects whose dimension is exponential in the nominal "size" of the problem. Tensor networks can provide a compact representation for exponentially large vectors and
matrices that arise in applications, but these representations do not always lead to reliable
algorithms. This paper develops and analyzes techniques for randomized dimension reduction of tensor network data. These techniques support a suite of efficient
algorithms for provably solving exponential-scale linear
algebra problems, including trace estimation and
eigenvalue approximation. The paper includes several stylized illustrations from
quantum many-body physics with ambient dimension up to $2^{200}$.
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All authors Chris Camaño, Ethan N. Epperly, Raphael A. Meyer, Joel A. Tropp
Disordered Systems and Neural Networks
Generative modelling powered by room-temperature polariton condensates
Yuan Wang, Marcin Muszynski, Avinash Dash et al. (+3 more)
Generative modelling requires efficient
stochastic nonlinear transformations and physical platforms that can naturally realise them. We experimentally demonstrate that nonlinear optical systems operating in the strong light-matter coupling regime can serve as physical transformation layers for conditional generative modelling. Specifically, we develop a workflow in which room-temperature
exciton-polariton condensates formed in organic dye microcavities act as a physical
stochastic transform within a generative
adversarial network and enable conditional digit-to-image translation. By using the nonlinear many-body dynamics and intrinsic stochasticity of polariton condensates, the workflow outperforms baseline approaches based on digitally injected perturbations. We find that polariton-enabled sampling via generative
adversarial network (Polariton GAN) yields improved inception score, digit preservation accuracy and structural similarity compared with both digital sampling and
laser-based systems. We further show that spatially correlated output variations can naturally regularise
adversarial training and enhance output diversity. Our results establish polariton condensation as a new computational resource for generative modelling, opening a pathway towards physics-enhanced machine learning systems.
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All authors Yuan Wang, Marcin Muszynski, Avinash Dash, Rishabh Kaurav, Vinod M. Menon, Oleksandr Kyriienko
Mathematical Physics · Cross-listed from eess.SP
Generalized likelihood ratio test for magnetic anomaly detection: a geometrical approach
C. Chenevas-Paule, S. Zozor, L.-L. Rouve et al. (+3 more)
State-of-the-art approaches to
magnetic anomaly detection rely on the generalized likelihood ratio test (GLRT). These approaches are based on the formulation of a parametric model of the source to be detected, expressed in a suitable functional basis. One of the primary objectives of this study is to demonstrate that, for a given measurement configuration, the signal is constrained to evolve within a restricted subset of the space generated by these functional bases. The parametric representation of the signal is identified as a semi-algebraic space which, for the dipole model used in this article, turns out to be a cone outside of which the estimated signal does not satisfy the physical equations. Thus, a second objective is to exploit this property to constrain the signal parameters in the GLRT to belong to the semi-algebraic space, in order to improve detection performance. The performance gain of the proposed
algorithm is compared to the one of conventional approaches; numerical simulations show that the proposed approach not only outperforms state-of-the-art methods but can even provide results close to those of the clear-seeing (optimal) receiver.
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All authors C. Chenevas-Paule, S. Zozor, L.-L. Rouve, O. J. J. Michel, O. Pinaud, R. Kukla
Materials Science
A Unified Dielectric-Dependent Hybrid Functional for Accurate Band Gaps across Dimensions
Subrata Jana, Manoar Hossain, Arghya Ghosh et al. (+3 more)
Predicting fundamental band gaps across material classes and dimensionalities remains a central challenge in electronic-structure theory. Here, we show that intrinsic dielectric screening provides a unified control parameter for nonlocal exchange from bulk to low-dimensional and heterogeneous materials. We introduce a geometry-independent dielectric response and incorporate it self-consistently into a nonempirical screened-dielectric-dependent hybrid functional.
Benchmarks for 100 materials spanning bulk, two-dimensional, one-dimensional, and mixed-dimensional systems show near-GW accuracy at the computational cost of generalized Kohn-Sham theory. These results reveal a screening-exchange-gap relation in which reduced dimensionality weakens intrinsic dielectric screening, strengthens nonlocal exchange, and drives the opening of fundamental gaps.
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All authors Subrata Jana, Manoar Hossain, Arghya Ghosh, Gabriel Chirchir, Prasanjit Samal, Szymon Smiga
Materials Science
Nonlocal Orbital-Free Kinetic Energy Functional from the Jellium-with-Gap Model for Finite Systems
Abhishek Bhattacharjee, Subrata Jana, Szymon Smiga et al. (+1 more)
The quasi-linear scaling of orbital-free density functional theory (OF-DFT) with system size makes it a computationally efficient alternative to conventional Kohn–Sham density functional theory for many condensed-matter applications. However, its applicability remains limited, particularly for finite systems such as molecular clusters, due to the lack of accurate kinetic energy density functionals. In this context, the development of nonlocal kinetic energy density functionals (NL-KEDFs) has significantly advanced the practical utility of OF-DFT. Here, following an alternative formulation based on the linear-response kernel derived from the jellium-with-gap model (JGM), we develop an NL-KEDF capable of accurately describing the diverse density regimes characteristic of finite systems, including molecular clusters.
Benchmark calculations, together with an analysis of the corresponding Pauli potentials, demonstrate that the proposed functional achieves higher accuracy than state-of-the-art orbital-free approaches for finite systems. Furthermore, the optical properties computed using the present method show good agreement with reference results, highlighting its reliability. These results indicate that the proposed NL-KEDF provides a robust and efficient framework for extending OF-DFT to finite systems, with potential implications for nanomaterial design and a deeper understanding of nanoscale phenomena.
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All authors Abhishek Bhattacharjee, Subrata Jana, Szymon Smiga, Prasanjit Samal
Materials Science
Symmetry-aware generative design of flat-band materials beyond known crystal-net prototypes
Yihao Wei, Ivan Savochkin, Artem Mishchenko et al. (+2 more)
Flat electronic bands underlie a range of strongly correlated and topological phenomena, whose design in real materials has so far relied on a small catalogue of named
geometric motifs such as kagome, Lieb, and pyrochlore nets. This discrete catalogue is by no means to exhaust the geometries that support flat bands in real compounds, as band flatness is a property of network connectivity. Here we combine a continuous
geometric representation of
crystal sublattices, with a
symmetry-constrained generative model, to access a broader design space for materials hosting flat bands. The key step is to choose sublattice motifs that are outside the known
geometric clusters, ensuring the novelty of the generated structures. We then introduce SkeleGen, which pins these unconventional skeletons to
symmetry-compatible Wyckoff positions while denoising the surrounding chemistry, resulting in 9,352
crystal candidates that survive stability and flatnessscreening. Band flatness is confirmed using high throughput full DFT calculations, which agree well also with the tight-binding spectra of the isolated skeletons, supporting a
geometric origin of the band flatness. We demonstrate "out-of-distribution" motifs as a new design principle to dramatically expand
geometric repertoire for materials discovery, potentially beyond flat bands.
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All authors Yihao Wei, Ivan Savochkin, Artem Mishchenko, Xiangwen Wang, Qian Yang