Optics
Chosen-Plaintext Attacks of Double Random Phase Encryption with Nonlinear Optical Media
Yan Cheng, Yiwei Chen, Kui Ren et al. (+1 more)
This paper studies an inverse problem in nonlinear optical encryption. We examine chosen-plaintext attacks (CPA) on a nonlinear optical encryption strategy that integrates double random phase encryption (DRPE) into a nonlinear optical propagation model to enhance the security of the combined system. We first demonstrate that the system's phase information can be decoded from carefully designed differential CPA data. We then demonstrate that the strength of the optical device's nonlinearity can also be recovered from CPA data, indicating that including this parameter as an additional security key does not enhance protection against CPA attacks, although numerical simulations show that strong nonlinearity still poses significant challenges for CPA attacks. Finally, we provide a stability analysis to demonstrate that small errors in decoded security keys result in only small errors in the decrypted text, even though the encryption process is nonlinear.
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All authors Yan Cheng, Yiwei Chen, Kui Ren, Nathan Soedjak
High Energy Physics (Phenomenology)
A Model-Independent Approach to First-Order Phase Transitions, Gravitational Waves, and Primordial Magnetic Fields
Fayez Abu-Ajamieh and Nobuchika Okada
We employ a model-independent Effective Field Theory (EFT) to analyze the possibility of a strong First-Order Phase Transition (FOPT) in extensions Beyond the Standard Model (BSM). We find that sizable deviations in the
Higgs cubic and quartic interactions that are still allowed experimentally could lead to a strong FOPT, whereas the
Higgs interactions to the top
quark yield a weak FOPT. We also study the Gravitational Wave (GW) power spectra corresponding to the strong FOPT and find that they could be detectable in future experiments. In particular, we find that deformations of the
Higgs quartic coupling have the dominant impact on the FOPT, with a GW signal that could be probed by a number of future experiments, such as LISA, BBO, and DECIGO. We also study the
magnetic field produced by the corresponding FOPT and find that it could explain the
primordial magnetic field puzzle. We find that for the size of deformations that could induce a strong FOPT, a scale of NP can be as low as $\sim 4\text{--}5~\text{TeV}$ for deformations in the
Higgs cubic coupling, and $\sim 9\text{--}11~\text{TeV}$ for deformations in the
Higgs quartic coupling. This highlights the synergy between
collider searches and GW experiments in probing the
Higgs couplings, specifically the
Higgs quartic coupling.
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Cosmology and Nongalactic Astrophysics
Controlling instrumental systematics for the BICEP inflation survey
C. Vergès, P. A. R. Ade, Z. Ahmed et al. (+92 more)
The BICEP series of experiments has been observing CMB polarisation from the South Pole for over 20 years, with the goal of constraining inflationary gravitational waves. The upcoming data release, using data taken through 2024, is forecasted to constrain the tensor-to-scalar ratio $r$ at the level of $\sigma(r) \sim 0.005$ (including delensing), with the longer-term goal of reaching $\sigma(r) \sim 0.001$ by 2034. As the survey sensitivity increases, it is crucial to control instrumental systematics to unprecedented levels, and our goal is to limit dominant sources of systematics to 20% of $\sigma(r)$ or lower. Achieving this requires careful instrumental characterisation and dedicated end-to-end studies to evaluate the impact of each systematic on cosmological parameters. We first present the BICEP calibration program, which characterises the optical, spectral, and polarisation response of the receivers. We then describe the analysis strategies implemented to identify and mitigate systematic contamination, and we detail simulations used to evaluate the impact of residual effects. We focus in particular on beam systematics, the dominant source of systematics for BICEP receivers. Finally, we report preliminary estimates of the expected level of systematic contamination for upcoming BICEP results, and we discuss approaches to evaluate and mitigate instrumental systematics for future surveys.
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All authors C. Vergès, P. A. R. Ade, Z. Ahmed, M. Amiri, D. Barkats, R. Basu Thakur, C. A. Bischoff, D. Beck, J. J. Bock, H. Boenish, V. Buza, B. Cantrall, J. R. Cheshire IV, J. Connors, J. Cornelison, M. Crumrine, A. J. Cukierman, E. Denison, L. Duband, M. A. Echter, M. Eiben, B. D. Elwood, S. Fatigoni, J. P. Filippini, A. Fortes, M. Gao, C. Giannakopoulos, N. Goeckner-Wald, D. C. Goldfinger, S. Gratton, J. A. Grayson, A. Greathouse, P. K. Grimes, G. Halal, M. Halpern, E. Hand, S. A. Harrison, S. Henderson, T. D. Hoang, J. Hubmayr, H. Hui, K. D. Irwin, M. Izquierdo Poza, J. H. Kang, K. S. Karkare, S. Kefeli, J. M. Kovac, C. L. Kuo, K. Lasko, K. Lau, M. Lautzenhiser, T. Liu, S. C. Mackey, N. Maher, K. G. Megerian, L. Minutolo, L. Moncelsi, Y. Nakato, H. T. Nguyen, R. O'Brient, S. N. Paine, A. Patel, M. A. Petroff, A. R. Polish, T. Prouve, C. Pryke, C. Reintsema, S. Richter, T. Romand, M. Salatino, A. Schillaci, B. Schmitt, R. Schwartz, C. D. Sheehy, B. Singari, A. Soliman, T. St. Germaine, A. Steiger, B. Steinbach, R. Sudiwala, G. Teply, K. L. Thompson, C. Tucker, A. D. Turner, A. G. Vieregg, A. Wandui, A. C. Weber, J. Willmert, C. L. Wong, W. L. K. Wu, H. Yang, C. Yu, L. Zheng, C. Zhang, S. Zhang
General Relativity and Quantum Cosmology
Binary Black Hole Parameter Estimation with Hybrid CNN-Transformer Neural Networks
Panagiotis N. Sakellariou, Spiros V. Georgakopoulos, Sotiris Tasoulis et al. (+1 more)
The detection of gravitational waves has revolutionized our ability to explore fundamental aspects of the Universe. Traditionally, modeled gravitational-wave signals have been identified using template-based matched filtering, followed by coincidence analysis across multiple detectors in the signal-to-noise ratio time series. Recent advances in Machine Learning and Deep Learning have sparked growing interest in their application to both signal detection and parameter estimation. In this study, a hybrid Deep Learning strategy is proposed that leverages the effectiveness of
Transformer encoders alongside well-established Convolutional Neural Network architectures in an attempt to estimate the intrinsic and extrinsic parameters of non-precessing binary black hole systems. The primary focus of this work is point estimation, producing single best-fit values for each parameter rather than full posterior distributions. This method is evaluated on both simulated signals embedded in Gaussian noise and real gravitational-wave events, and it demonstrates strong predictive performance and robustness across key astrophysical parameters.
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All authors Panagiotis N. Sakellariou, Spiros V. Georgakopoulos, Sotiris Tasoulis, Vassilis P. Plagianakos
Plasma Physics
Suppressed Stiffness of energetic particle transport due to thermal plasma nonlinearity in tokamak plasmas
Guo Meng, Zhixin Lu and Gengxian Li
Energetic particle (EP) transport stiffness plays a crucial role in determining EP confinement in tokamak
plasmas. This work investigates the impact of nonlinear thermal
plasma dynamics on EP transport using global gyrokinetic simulations with the TRIMEG code. Simulations are performed for the ITPA toroidal Alfv'en eigenmode (TAE)
benchmark, and extended to beta-induced (BAE) and reversed shear Alfven eigenmodes (RSAE). Two models are compared: a fully nonlinear treatment of all species and a reduced model with only nonlinear EP. For TAE simulations, while linear properties of the instability are identical in both cases, significant differences arise in the nonlinear regime. Including thermal
plasma nonlinearity reduces the saturation level following an overshoot phase and modifies the radial mode structure, including mode broadening and poloidal harmonic splitting. These changes significantly affect EP transport. Specifically, the dependence of EP flux on the EP drive becomes weaker when nonlinear thermal
plasma dynamics are included. The saturation level changes from an approximately quadratic scaling to a weaker, nearly linear dependence, reducing the scaling of EP flux with the EP gradient from quartic to quadratic. Zonal flow generation is observed but plays a minor role in regulating the instability. Without accounting for thermal nonlinearity, the EP flux can be overestimated by an order of magnitude. Simulations of BAEs and RSAEs demonstrate similar effects of thermal
plasma nonlinearity on mitigating the saturation level. These results demonstrate that nonlinear thermal
plasma effects provide an important feedback mechanism that reduces EP transport stiffness and regulates Alfvenic mode saturation, which is essential for predictive modeling of EP confinement in burning
plasmas such as ITER.
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Cosmology and Nongalactic Astrophysics
The baryonic Tully-Fisher relation as an independent direct probe of cosmology and of the nature of dark matter
Francesco Sinigaglia
The baryonic Tully-Fisher relation (BTFR), a well-established
galaxy scaling relation linking the dynamical mass of rotation-supported
galaxies through their maximum circular velocity to the baryonic luminous mass, has emerged over the decades as a fundamental scaling relation and as a robust calibrated distance indicator, thereby providing a robust
benchmark to test
galaxy formation and
evolution theories as well as an independent probe of the expansion of the Universe. In this paper, we show for the first time that the BTFR is also simultaneously directly sensitive to the cosmological parameters $\Omega_m$ and $\sigma_8$, the astrophysical feedback from
supernovae (SNe) and active
galactic nuclei (AGN), and the mass of warm dark matter particles $M_{\rm wdm}$, and can therefore be used as novel, direct probe of cosmology and fundamental physics. We perform simulation-based inference on the large DREAMS cosmological magneto-hydrodynamic simulations suite and train deep neural networks in the form of normalizing flows to estimate the posterior distributions of $\Omega_m$, $\sigma_8$, $M_{\rm wdm}$ and the three astrophysical free parameters, given a BTFR measurement. Our framework is able to recover unbiased values for $\Omega_m$ and $\sigma_8$, with subpercent deviations accuracy and a $\sim 2.6\%$ and $\sim 3.9\%$ median precision, respectively, to capture the warm dark matter particle mass $M_{\rm wdm}$ within a $\sim 30-35\%$ precision, as well as to constrain the SN feedback parameters (but not the one regulating AGN feedback). We conclude that, beyond its usage as a distance indicator, the BTFR constitutes a direct independent probe of cosmology and fundamental physics and opens new promising avenues, such as constraining the
cosmic growth rate and testing
gravity theories, to be explored with the future Square Kilometer Array.
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Mathematical Physics
Krein Space Quantization and a Spectral Interpretation of the Riemann $\xi$-Function
M.V. Takook
The invariant two-point function of a scalar field in de Sitter spacetime can be expressed in terms of Legendre functions via Lorentzian harmonic analysis. Using this structure together with the Mehler–Fock transform, we obtain an integral representation of the completed Riemann $\xi$-function in which the Legendre kernel appears naturally. Motivated by this correspondence, we introduce a retarded propagator whose spectral weight is given by the $\xi$-function and analyze it within the framework of Krein space quantization, where sign-indefinite spectral measures are admissible. This construction yields a
geometric and spectral interpretation of the $\xi$-function restricted to the critical line and relates the asymptotic spacing of its zeros to a mass–time scaling in de Sitter geometry. The results provide a novel interpretive framework linking de Sitter
quantum field theory, harmonic analysis, and analytic number theory.
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Quantum Physics
Quantum Simulation of Spin-Dependent Electron Transfer in a Synthetic Chiral Lattice with a Trapped Ion
Yi Li, Chuyuan Chen, Xingyu Zhao et al. (+8 more)
Electron transfer through
chiral structures can exhibit
spin asymmetry, known as the
chiral-induced
spin selectivity effect, whose microscopic origin remains an open question. While path-interference within the
chiral moiety has been proposed as a key mechanism, its experimental validation requires precise and versatile tunability of system parameters. Here we implement a programmable
quantum simulation of
spin-dependent electron transfer in a donor–
chiral-bridge–acceptor model using a trapped ion. The bridge is encoded in internal states of the ion with tunable nearest- and next-nearest-neighbor couplings, while donor and acceptor states are coupled via a spectator bosonic motional mode. We observe
spin-dependent interference within the bridge, and further reveal
spin-dependence in donor-to-acceptor transfer dynamics, controlled by amplitude and phase of the coupling parameter. Our results identify interference among
spin-dependent pathways as a microscopic origin of
spin-dependent transfer, and open a route toward
quantum simulations of complex
chiral lattices with multi-level and bosonic degrees of freedom.
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All authors Yi Li, Chuyuan Chen, Xingyu Zhao, Zihan Xie, Min Jiang, Xinhua Peng, Han Pu, Lyuzhou Ye, Yao Wang, Guozhen Zhang, Yiheng Lin
Quantum Physics
Pedro Baptista, Gabriel Coutinho, Chris Godsil et al. (+1 more)
Compact graphs are graphs for which the fractional
automorphism polytope has no genuinely fractional vertices. This paper proposes a
quantum analogue of this idea by evaluating the fundamental magic
unitary of the
quantum automorphism group on states, which we show to produce a closed convex set of doubly
stochastic matrices sitting between the classical
automorphism polytope and the full fractional
automorphism polytope. Our main result is that the natural
quantum analogue of compactness is classical, that is, a
quantum compact graph is classically compact. We also relate this set to the
quantum orbital
algebra and obtain a hierarchy of classical and
quantum compactness pseudo notions. The framework recovers familiar consequences of compactness through commutants and suggests
quantum analogues of generous transitivity and distance-transitivity. We also isolate examples and open problems indicating where
quantum symmetries may strictly refine the classical compactness theory.
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All authors Pedro Baptista, Gabriel Coutinho, Chris Godsil, Simon Schmidt
General Relativity and Quantum Cosmology
Black hole physics within $f(R)$ gravity: Quasi-normal spectra and greybody factors
Ángel Rincón and Grigoris Panotopoulos
We investigate several astrophysical motivated properties of a four-dimensional black hole solution in the framework of $f(R)$
gravity. The model is characterized by a single additional parameter, $\alpha$, which encodes nontrivial deviations from General Relativity. Using this black hole spacetime as the background geometry, we analyze: (i) the quasinormal modes of massless scalar perturbations (employing several complementary methods), and (ii) the greybody factors associated to the propagation of massless test scalar fields. Regarding quasinormal modes, we study the response of black holes to massless scalar perturbations using three independent approaches: the well-established sixth-order WKB semi-analytic method, analytic expressions, and the analytical expression in the eikonal limit. We examine the behavior of both the real and imaginary parts of the quasinormal frequencies as functions of the parameter $\alpha$, the overtone number $n$, and the multipole number $\ell$. In addition to that, we compute the greybody factors within the WKB approximation for various combinations of the relevant parameters. In particular, we focus on the propagation of test massless scalar fields and investigate how the greybody factors depend on the multipole number $\ell$, and the free parameter $\alpha$. The impact of the aforementioned parameters on the absorption cross-section and the reflection and transmission coefficients is studied in detail.
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Earth and Planetary Astrophysics
A coupled-oscillator model for the formation of planetary rings
Ruoming Gong, Theodore Broeren, Eryn M. Cangi et al. (+1 more)
We study the dichotomy between compact satellite and ring formation in proto-planetary disks. Specifically, we examine the behavior of a model system of $N$ identical particles locked into circular, gravitationally-bound orbits around a central body. We treat interactions as dominated by inter-particle collisions, and extract an effective two-particle interaction function based on both theory and simulations. We then demonstrate that the expected dynamics are equivalent to a variant of the Kuramoto model, which undergoes a phase transition as parameters vary. This offers a novel potential explanation for the transition between formation of rings versus moons.
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All authors Ruoming Gong, Theodore Broeren, Eryn M. Cangi, Daniel M. Abrams
Materials Science
Machine Learning Accelerated SSNEB for Efficient Minimum Energy Pathway Calculations
Yu Zhang, Guanzhi Li, Minkyung Han et al. (+4 more)
Metastable states and their minimum energy pathways (MEPs) are central to understanding transformations and phase stability in complex materials, yet mapping transition pathways between competing states remains computationally demanding and experimentally challenging. Here, we introduce a hybrid solid-state nudged elastic band (SSNEB) framework that integrates two pretrained machine learning models, EquiformerV2 (eqV2) and the equivariant Smooth Energy Network (eSEN), with DFT for energy, force, and stress evaluations. Applied to three solid-state systems, CsPbI$_3$, GaN, and TiO$_2$, our framework achieves up to a 7-fold speedup while converging to the same pathways predicted by first-principles calculations. Moreover, the hybrid SSNEB framework enables systematic benchmarking of existing ML models, providing both efficiency and reliability for predicting MEPs across various materials.
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All authors Yu Zhang, Guanzhi Li, Minkyung Han, Sean Gasiorowski, Daniel Ratner, Chunjing Jia, Yu Lin
Instrumentation and Methods for Astrophysics
Autonomous AI-Cosmoindustry and the Quiet Expansion Filter: A Threshold-Based Resolution of the Fermi Paradox
Sergey Ivliev
The
Fermi paradox is sharpened, not weakened, by plausible extrapolations of artificial intelligence, autonomous robotics, in-situ resource utilization, orbital manufacturing, space-based computing, and uncrewed interstellar probes. Once a civilization can design, launch, and maintain autonomous industrial systems beyond its home
planet, interstellar expansion no longer requires biological starships or a human-like empire. It can proceed through low-mass probes, robotic seed factories, archival payloads, biological repositories, local computation, and slow replication across nearby
stellar systems. This paper proposes the quiet expansion filter: old, stable civilizations that reached autonomous AI-cosmoindustry probably did not arise in the part of the
Galaxy capable of reaching the
Solar System, because after that threshold interstellar expansion becomes too useful, inexpensive, and rational for all civilizations to refuse; however, successful expansion would be machine-mediated, distributed, low-noise, and partly biological rather than Kardashev-like or imperial. Order-of-magnitude estimates indicate that a single post-threshold civilization could saturate its reachable
stellar neighborhood within ~10^7 yr – less than 0.1% of
Galactic age – at modest energy cost per probe. The novelty of the proposal lies not in any new mechanism but in extending the AI-filter literature toward post-threshold observability predictions. The hypothesis predicts that successful advanced expansion, if present, is more likely to appear as weak artifacts, local probes, small-scale resource processing, exoplanetary anomaly clusters, or techno-biological preservation systems than as
galaxy-scale energy harvesting.
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Disordered Systems and Neural Networks
Low-variance estimators overcome the phase-gradient bottleneck in complex-valued neural quantum states
Yi-Ran Xue, Rui Wang, Baigeng Wang et al. (+1 more)
Complex neural
quantum states are difficult to optimize when their wavefunction phase carries gauge,
chiral, fermionic, or topological structure. We show that the major failure mode is not only ansatz expressivity, but the Monte Carlo
estimator used to learn this phase. For separated amplitude-phase states, differentiating the local energy at fixed samples gives a different unbiased
estimator of the same variational Monte Carlo phase force, without changing the objective. We further extend the construction to coupled two-head networks by keeping the amplitude-gradient contribution and applying the direct derivative only to the phase path. An adaptive minimum-variance mixture interpolates between standard and direct
estimators during training. Across flux ladders,
chiral chains, two-dimensional flux cylinders, an interacting
fermion ladder, shared-network controls, and a fractional
quantum Hall benchmark, the resulting
estimators reduce phase-gradient variance, suppress seed failures, and often move multi-percent standard-gradient plateaus to sub-percent accuracy.
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All authors Yi-Ran Xue, Rui Wang, Baigeng Wang, Chenan Wei
High Energy Physics (Phenomenology)
Probing the $G(3900)$ State in Heavy-Ion Collisions
Luciano M. Abreu, Pedro Brandão, Rodrigo O. Magalhães et al. (+1 more)
We investigate the interactions of the recently confirmed exotic
hadron $G(3900)$ with the hadronic medium composed of light
mesons produced in heavy-ion collisions. Using an effective Lagrangian approach, we compute both
vacuum and thermally averaged cross sections for processes such as $G(3900) + \pi \to D^{(\ast)} + \bar{D}^{(\ast)}$ and their inverse reactions. Following recent proposals, the $G(3900)$ is interpreted as a $P$-wave $D\bar{D}^*/D^*\bar{D}$ molecular state. The resulting thermally averaged cross sections are employed in a rate equation to determine the time
evolution of the $G(3900)$ multiplicity, with initial conditions provided by statistical and coalescence hadronization models. We compute the number of $G(3900)$'s produced in central Pb-Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV and compare it with the number of produced $Z_c(3900)$'s . We obtain a considerably smaller final yield of $G(3900)$ compared to $Z_c(3900)$.
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All authors Luciano M. Abreu, Pedro Brandão, Rodrigo O. Magalhães, Fernando S. Navarra
High Energy Physics (Phenomenology)
Anomalies, Topology, and Hadron Structure in QCD
Ismail Zahed
Quantum Chromodynamics (QCD) provides a remarkable realization of how
quantum effects reshape the
symmetries of a classical field theory. The axial anomaly links chirality to gauge-field
topology and underlies the resolution of the $U(1)_A$ problem, while the trace anomaly generates the intrinsic QCD scale through dimensional transmutation and accounts for most of the mass of
hadrons and hence visible matter. Together, these
quantum effects reveal the central role of gluonic dynamics and
vacuum structure in strong-interaction physics. In this review, we discuss the theoretical foundations and physical consequences of anomalous
symmetry breaking in QCD. We examine anomalous Ward identities, the topological structure of gauge fields, instantons, topological susceptibility, and the realization of
chiral and scale
symmetries in the QCD
vacuum. We review their role in the generation of
hadron masses, the $\eta'$ mass, and the resolution of the $U(1)_A$ problem, and discuss their manifestations in polarized deep inelastic scattering, nucleon
spin structure, and modern studies of
hadron structure. Particular emphasis is placed on recent developments connecting
vacuum topology, the
flavor-singlet axial charge, topological screening, and the
proton spin problem. Our aim is to provide a unified perspective on how
quantum anomalies connect
vacuum structure,
hadron properties, and partonic observables, bridging nonperturbative dynamics and perturbative QCD.
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Materials Science
Molecular Beam Epitaxy of Mn2In2Se5 van der Waals Layers Using Mn Intercalation
Qihua Zhang, Ke Wang, Wesley Auker et al. (+2 more)
The weak van der Waals (vdW) force in layered chalcogenide materials has enabled the growth of ternary chalcogenide layers using unconventional approaches. Here, we report the molecular beam epitaxy (MBE) growth of Mn2In2Se5, a
spin glass material with high level of
magnetic frustration, through the heterointegration of MnSe on In2Se3. Directly depositing {\alpha}-MnSe on the vdW In2Se3 layers results in Mn intercalation, transforming the In2Se3 layer into Mn2In2Se5. Large growth windows, including substrate temperatures from 250-450 {\deg}C and Se:Mn flux ratio of 1.1-3.1, have been identified for the intercalation process. With an optimized MnSe deposition time, smooth, single-crystalline, and (0001)-oriented Mn2In2Se5 layers with a root-mean-square (RMS) roughness of 1.5 nm can be synthesized. Further extending the MnSe deposition time results in the growth of uniform rock-salt structured {\alpha}-MnSe (111) layers with a thickness of up to 8 nm and a narrow full-width-at-half-maximum (FWHM) of 0.35{\deg} in MnSe (222) XRD rocking curves. This report presents a unique approach for the growths of uniform and single-crystalline Mn2In2Se5 vdW layers using MBE, and potentially opens a pathway for synthesis of ternary vdW chalcogenides by intercalation of new atomic species in binary vdW chalcogenides.
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All authors Qihua Zhang, Ke Wang, Wesley Auker, Maria Hilse, Stephanie Law
Materials Science
Multi-modal machine learning analysis of GaSe molecular beam epitaxy growth conditions
Mingyu Yu, Isaiah A. Moses, Wesley F. Reinhart et al. (+1 more)
Autonomous synthesis platforms integrating machine learning with in situ diagnostics have the potential to revolutionize thin-film growth by enabling real-time process optimization and reducing the need for manual tuning. However, their application to molecular beam epitaxy (MBE) remains underdeveloped. Here, we present a machine learning-guided framework for MBE growth of GaSe films, leveraging reflection high-energy electron diffraction (RHEED) as an in situ diagnostic alongside ex situ characterization via X-ray diffraction and atomic force microscopy. Unsupervised learning on RHEED patterns reveals a well-defined boundary between high- and low-quality samples, capturing physically meaningful features. Mutual information analysis shows a strong correlation between RHEED
embeddings and rocking curve full-width at half-maximum (fwhm), while the correlation with AFM root-mean-square (RMS) roughness is weak. Among key growth conditions, growth rate most strongly influences fwhm, whereas the Se/Ga flux ratio primarily affects RMS roughness and the RHEED
embeddings. Supervised learning models trained to predict fwhm and RMS roughness demonstrate moderate accuracy, with significant improvement achieved by incorporating RHEED
embeddings. Furthermore, anomaly detection via residual analysis in supervised learning aligns well with unsupervised classification from RHEED, reinforcing the reliability of the predictive models. This study establishes a data-driven framework for machine learning-assisted MBE, paving the way for real-time process control and accelerated optimization of thin-film synthesis.
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All authors Mingyu Yu, Isaiah A. Moses, Wesley F. Reinhart, Stephanie Law
Instrumentation and Detectors
Fast Timing and TCT Measurement Results of CNM Double-Sided 3D Sensors
Fabian Lex, Alexander Dierlamm, Teresa Hasler et al. (+12 more)
Sensors with fast timing capabilities (on the order of tens of picoseconds) are a critical component of future HEP tracking detectors, providing the ability to disentangle high multiplicity events. Silicon 3D sensors are capable of delivering this temporal resolution and additionally display an excellent radiation hardness, suitable for the harsh environments expected in future
hadron colliders (e.g. FCC-hh). In the course of the RD50 project "3D detectors optimized for timing applications", double-sided 3D sensors with two different column layouts, hexagonal and orthogonal, and different column counts were designed and produced by CNM. In this study, results of IV, top-TCT and source timing measurements of unirradiated as well as
proton irradiated sensor structures are presented. The IV characterisation shows a strong decrease of the overall high leakage current of the sensors after irradiation. Top-TCT measurements with both an infrared and red
laser reveal a mostly homogenous charge collection in the sensor bulk, while higher signals are observed in the outermost columns for surface charge injection. The time resolution of sensors irradiated up to a $1 \, \mathrm{MeV}$
neutron equivalent fluence of $3\times10^{15} \, \mathrm{cm^{-2}}$ reaches down to ca. $65\,\mathrm{ps}$, showing only a slight degradation compared to unirradiated sensors.
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All authors Fabian Lex, Alexander Dierlamm, Teresa Hasler, Lorena Hahn, Marc Hauser, Karl Jakobs, Roland Koppenhöfer, Ole Kreyscher, Ulrich Parzefall, Niyathikrishna Meenamthuruthil Radhakrishnan, Brendan Regnery, Yannik Sibold, Dennis Sperlich, Lea Stockmeier, Iveta Zatocilova
Fluid Dynamics
On the Geometry of Spreading Puddles
David Darrow
We develop a
geometric model for the spreading of shallow, viscous puddles of arbitrary shape, building on the recent 'capillary current' model for axisymmetric droplets. In short, we assume that a spreading puddle remains close to instantaneous mechanical
equilibrium as it spreads, with hydrostatic pressure balanced by surface
curvature. In turn, its contact line advances so as to maximize the rate of energy loss subject to viscous dissipation. The resulting system yields a natural
geometric evolution equation for both the two-dimensional footprint and the three-dimensional depth profile of a spreading puddle. In appropriate limits, it recovers the classical spreading laws for axisymmetric droplets, a local version of the Hoffman-Voinov-Tanner law for small non-axisymmetric puddles, and a nonlocal Hele-Shaw-like description for large, relatively regular puddles. We show that the model rationalizes new observations of silicone oil spreading over smooth borosilicate glass.
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Statistical Mechanics · Cross-listed from q-bio.CB
Mean First Passage Time for Persistent Random Walks in Annular Search Domains
Fatemeh Saghafifar and Daniel Coombs
We study the mean first-passage time of a random walker to a small absorbing target at the center of a two-dimensional annulus with a specularly reflecting outer boundary. The problem is motivated by natural killer
cell migration toward a target cancer
cell, where the goal is to quantify how long it takes immune
cells to reach the target and how search efficiency depends on directional persistence and chemotactic bias.
Cell motion is modeled as a velocity-jump process. We first consider a correlated random walk with a von Mises turning kernel, with a concentration parameter controlling directional persistence. We then extend the model to a biased correlated random walk using a phase-shifted turning kernel that represents preferential motion, for example following a concentration gradient. Our analysis combines closed-form
benchmarks for simple and biased random walks,
Fourier-mode reductions of the transport equations for the correlated and biased correlated models, and a fast-turning perturbation expansion that gives an analytical correction to the
diffusion-limit mean first-passage time for the random walker. Our analytical results are supported by numerical methods that include a semi-Lagrangian solver in radial and angular coordinates, a stationary discretisation designed to handle biased transport, and an event-driven Monte Carlo simulator for cross-validation. Together, our results provide a framework relating persistent and biased immune-
cell motion to target-search times in confined two-dimensional domains.
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High Energy Physics (Theory)
Flat Space Entanglement: A Coulomb Branch Perspective
Eivind Jørstad, Robert C. Myers and Sabrina Pasterski
We study
holographic entanglement entropy in Coulomb-branch solutions describing spherical shells of D$p$-branes. The corresponding throat geometries contain a flat-space bubble in the infrared region, providing a concrete top-down framework for exploring
holographic entanglement of flat space. We find that the flat-space region is associated with a reduction of
entanglement and of the effective infrared degrees of freedom in the dual boundary state relative to the standard
vacuum. We also examine internal RT surfaces and
holographic complexity, and show that they exhibit similar qualitative behavior. Finally, we comment on the broader implications of our results for flat space holography.
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Fluid Dynamics
Nested homogenization of xylem-inspired porous fluidic networks
Pier Giuseppe Ledda, Giacomo Ferrari and Giuseppe Antonio Zampogna
Fluidic networks may contain hierarchical porous structures in which transport across macroscopic interfaces is controlled by geometrical features at multiple nested length scales. Direct resolution of all these scales rapidly becomes computationally prohibitive for network-scale studies, while reduced descriptions require a priori effective hydraulic properties. Here, we develop a nested homogenization framework for rigid porous interfaces under single-phase viscous flow. The pore-scale structure is first replaced by an effective stress-jump interface law, which is then embedded as an internal interface condition within a second characteristic problem at the intermediate scale. This successive upscaling propagates the pore-scale geometry through effective tensors to obtain a closure for flow across the whole porous structure. The approach is validated against fully resolved simulations at the mesoscopic and macroscopic scales, for two xylem-inspired channel configurations, and accurately captures pressure drops and flow redistribution while strongly reducing computational cost. The framework provides a tractable bottom-up description of a network composed of nested porous membranes and a basis for extensions to deformable structures and multiphase flows.
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Mathematical Physics
A Betchov-Type Hydrodynamic Formulation of the Ivancevic Option-Pricing Equation
Sandeep Kumar
We show that, under constant-coefficient assumptions, the Ivancevic option-pricing nonlinear Schrödinger equation admits a Betchov-type hydrodynamic formulation analogous to the one arising in the context of the
vortex filament equation. Along with this structural correspondence, known Ivancevic solutions are interpreted in terms of density–velocity variables. As an illustration of the financial interpretation, we compare the normalized one-
soliton density with the Black–Scholes risk-neutral density, obtaining an explicit relation between the Ivancevic coefficient ratio and standard
market quantities. We further show that the probability current can be reconstructed from the temporal
evolution of the density and demonstrate this reconstruction for an interacting two-
soliton solution. Together, these results illustrate how the Betchov-type hydrodynamic formulation can be used to describe the
evolution and transport of the Ivancevic density, while establishing a coefficient-explicit bridge between nonlinear wave models in mathematical finance and
geometric fluid mechanics.
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Materials Science
Towards Atom-by-Atom Fabrication: Mechanosynthetic donation and abstraction
Brandon Blue, Mathieu Morin, Alex Inayeh et al. (+55 more)
Enabled by inverted-mode scanning tunneling microscopy (IM-STM) and the use of functionalized molecular tools, we demonstrate positionally-controlled mechanosynthetic addition (donation) of carbon and subtraction (abstraction) of silicon atoms on a model build site: atomically clean and crystalline Si(100). The resulting structures represent the first demonstrations of an emerging ability to manipulate radical chemistry with positional control of specific atoms and moieties in 3D. Furthermore, by comparing the behavior of molecular tools designed for atomic donation versus abstraction, we highlight general principles governing molecular tool design for selective and reliable mechanosynthetic functionality.
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All authors Brandon Blue, Mathieu Morin, Alex Inayeh, Rosemary Cranston, Cameron J. Mackie, Marc Savoie, Adam Bottomley, Christian J. Imperiale, Zehra Ahmed, Rafik Addou, Aly Asani, Eduardo Barrera-Ramirez, Jeremy Barton, Doreen Cheng, Megan Cowie, Chris Deimert, Tyler Enright, James Zhangming Fan, Robert A. Freitas Jr, Alan T.K. Godfrey, Ryan Groome, Si Yue Guo, Kareem A. Clarcia, Aru Hill, Taleana Huff, Mark Jobes, Robert J. Kirby, Sam Lilak, Hadiya Ma, Adam C. Maahs, Oliver MacLean, Steven M. Maley, Michael Marshall, Terry McCallum, Ralph Merkle, Matthew Moses, Jonathan Myall, Ryan Plumadore, Adam Powell, Henry Rodriguez, Sam Rohe, Luis Sandoval, Khalil Sayed-Akhmad, Benjamin Scheffel, Kashif Tanveer, Bheeshmon Thanabalasingam, Denis A.B. Therien, Janice L. Wong, Reid Wotton, Cristina Yu, Damian G. Allis, Michael Drew, Matthew R. Kennedy, Tait Takatani, Marco Taucer, Dušan Vobornik, Ryan Yamachika, Mathieu Durand
Materials Science
Dynamical multiferroicity in framework materials
Marek Matas and Carl P. Romao
Dynamical multiferroicity, which describes the
magnetic fields generated by circularly polarized
phonons in materials, is an established mechanism for optical control of magnetism. Here we perform ab initio calculations of dynamical multiferroicity in inorganic and organic framework materials, with the goal of identifying materials which enable the generation of large
magnetic fields by light. We find the metal–organic framework material Zn(NH$_4$)(formate)$_3$ to have modes with
magnetic moments almost twice that of SrTiO$_3$; these modes involve circular motions of NH$_4^+$ hydrogen ions with high gyromagnetic ratios. The complex structure and flexibility of framework materials can allow such angular momentum localization, and also increase the maximum light-induced magnetization permitted by the Lindemann melting criterion.
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Materials Science
DFTB coupled with NEGF study of the structural, electronic and transport properties of goldene 2D material
Taoufik Sakhraoui and František Karlický
We report the structural, electronic, and transport properties of the goldene 2D material using the density functional tight-binding (DFTB) method. Electronic transport calculations were conducted in conjunction with the non-
equilibrium Green's functions (NEGF) technique. Our study reveals that the Au 2D material is dynamically and thermally stable, and it possesses good elastic properties. On the other hand, goldene has a linear relationship between current and voltage at low potentials, indicating its metallic character. The calculated current-potential curve correlates well with transmission functions and the electronic density of states around the
Fermi level. We also investigated the electronic structure and
magnetic properties of silicon (Si)-doped Au 2D material. Our results show that the Si atom can induce a local
magnetic state in the goldene monolayer. The resulting
magnetic moment is 0.63 $\mu_B$.
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Instrumentation and Methods for Astrophysics
Multi-Variable Stellar Parameter Estimation Using Residual Multitask Neural Networks
Bruno Santos Meneses Barreto and Marcio Eisencraft
We present an end-to-end pipeline for estimating
stellar parameters from Sloan Digital Sky Survey Data Release 12 spectra using a fully connected multitask neural network with residual blocks, whose hyperparameters are tuned via
Bayesian optimization. The preprocessing pipeline includes per-spectrum standardization, RobustScaler normalization of the target variables – effective temperature $T_{\mathrm{eff}}$,
metallicity $[\mathrm{Fe/H}]$, and surface
gravity $\log g$ – and data augmentation via Gaussian noise injection. On a held-out test set, the model achieved Mean Absolute Errors (MAE) of $59.76~\mathrm{K}$ for $T_{\mathrm{eff}}$, $0.103~\mathrm{dex}$ for $[\mathrm{Fe/H}]$, and $0.130~\mathrm{dex}$ for $\log g$. Normalized against the full-scale range of each parameter, these results represent range-normalized errors between $1\%$ and $3\%$, achieved with a highly efficient model complexity of approximately 540,000 trainable parameters. These results demonstrate that a compact residual multitask architecture, combined with principled signal preprocessing, provides a parameter-efficient solution for nonlinear parameter estimation in large-scale spectral
datasets. In particular, the proposed model achieves competitive performance with substantially lower complexity than deeper neural network baselines.
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Materials Science
Closed-loop discovery of out-of-distribution processing protocols by evolutionary search and uncertainty-aware learning
Yu Liu, Stanislav Udovenko, Ching-Che Lin et al. (+4 more)
Many materials and chemical systems exhibit history-dependent responses, where functional outcomes are governed not only by final-state variables but by the time-dependent sequence of fields, temperatures, or chemical potentials applied during operation. Discovering new processing protocols is therefore a high-dimensional search problem in which the control variable is an entire waveform or sample history, and conventional strategies either remain confined to conservative interpolative families or become prohibitively measurement intensive. Here, a closed-loop workflow is introduced that couples evolutionary search over a compact waveform representation with uncertainty-aware deep kernel learning to generate, rank, and experimentally validate candidate protocols. Applied to ferroelectric thin films, with the scanning-probe tip-bias waveform as the protocol and the nonlinear electromechanical response as the reward, the workflow discovers waveform families that enhance nonlinearity by de-aging the film. Spatially resolved before/after measurements show that the best-performing waveforms selectively activate pre-existing, weakly pinned domain-wall segments, whereas the worst drive long-range irreversible switching. This framework reframes protocol tuning as out-of-distribution discovery, generalizable to synthesis and annealing trajectories, battery formation protocols, and other high-dimensional control problems.
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All authors Yu Liu, Stanislav Udovenko, Ching-Che Lin, Jaegyu Kim, Lane W. Martin, Susan Trolier-McKinstry, Sergei V. Kalinin
Quantum Physics
Local correlations in long-range dual-unitary kicked Hamiltonian chains
Vladimir Al. Osipov, Marc Cedric Spyra, Jana Carolina Schumann et al. (+2 more)
Many-body Floquet models with exact space–time duality, such as the kicked Ising chain, provide paradigmatic examples of dual-
unitary dynamics. The requirement of exact space–time duality is, however, highly restrictive and, in its standard formulation, permits only nearest-neighbor interactions. We demonstrate that the latter constraint can be avoided, still resulting in exactly solvable models. In particular, we construct a broad class of dual-
unitary kicked
spin chains with long-range interactions. We show that, for an interaction range $r$, local two-point connected correlation functions propagate along the edges of the light cone, $|n|=r|t|$, and can be evaluated analytically for local observables. We illustrate our general statement by analytic calculation of the connected correlation function for a kicked Ising chain with next-to-next-nearest-neighbor interactions.
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All authors Vladimir Al. Osipov, Marc Cedric Spyra, Jana Carolina Schumann, Thomas Guhr, Boris Gutkin