Statistical Mechanics · Cross-listed from q-fin.ST
Analysis of the Principal Components of Correlation Matrices of S&P 500 Financial Data from an Econophysics Perspective
Javier Gómez Morales
This thesis analyzes the collective dynamics of the S&P 500 from an econophysics perspective, treating the financial
market as a complex system. Using daily logarithmic returns of 430 companies, time-dependent Pearson correlation
matrices are constructed over sliding windows and their spectral structure is studied through the leading
eigenvalues and eigenvectors.
Market States (MS) are identified by applying k-Means clustering to several spectral quantities: the largest
eigenvalue (interpreted as the State of the
Market), the squared entries of the dominant eigenvector (read as a relative participation of each stock), and truncated
matrix reconstructions C^l built from the l largest eigenpairs and normalized to retain a correlation-
matrix interpretation. The stability of the resulting clusters is assessed, transition
matrices and their stationary vectors are computed, and the inverse participation ratio is used to quantify how participation spreads across assets. The COVID-19 episode emerges as an atypical state in the full correlation
matrices; reconstructing it requires more than one principal component, and the C^2 and C^3 constructions reproduce it, particularly for window length q=40 and k=5. During crisis periods the relative participation distributes over a larger number of assets, while the 2017-2018 interval contributes to the dynamics without appearing as an isolated regime. The analysis is descriptive rather than predictive, and provides conceptual and methodological tools relevant to portfolio design and trading strategies, with natural extensions to other international exchanges.
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Fluid Dynamics
The near-wall cycle for skin-friction generation revealed through explainable deep learning
Andres Cremades, Sergio Hoyas and Ricardo Vinuesa
Skin friction in wall-bounded
turbulence is produced by intermittent near-wall motions, yet conventional coherent-structure definitions do not identify which individual events generate wall-shear stress, and thus friction. We train neural networks to predict the future velocity field and wall-shear-stress distribution in turbulent channel flow, and use SHAP-derived importance maps to identify the the input regions most influential for each prediction. The dominant events appear as paired objects: an upstream velocity-relevant region is associated with high-momentum motion toward the wall, while a downstream friction-relevant region marks the enhanced wall-shear-stress left in its wake. Tracking these pairs reveals a recurrent cycle of growth, streamwise elongation, decay, and occasional splitting into new wall-shear-producing events. These results redefine near-wall coherent structures not by what the flow looks like, but by what they do to wall-shear stress.
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Mathematical Physics · Cross-listed from math.AP
Anisotropic Mixed Fractional Landau Inequalities for Rotating Compressible Flows
Rômulo Damasclin Chaves dos Santos and Delvonei Alves de Andrade
We develop a rigorous theory of anisotropic mixed fractional Landau inequalities for rotating compressible fluid flows at high Mach numbers, incorporating Coriolis and centrifugal forces. We introduce rotating fractional Sobolev spaces $\mathcal{W}^{\nu,p}_{\alpha,\Omega}(\mathbb{R}^k)$, which encode directional scaling, fractional dissipation and rotational effects. We prove sharp fractional Landau inequalities with explicit dependence on the Mach number, the rotation rate $|\Omega|$ and the anisotropy vector $\alpha$. Key tools are a rotating Littlewood–Paley decomposition, anisotropic maximal estimates with rotational corrections, and commutator estimates for the Coriolis term. As applications, we establish stability bounds for neural operators approximating rotating compressible flows and derive optimal approximation rates of order $N^{-\nu/d_{\alpha,\Omega}}$, where $d_{\alpha,\Omega}=\sum_i\alpha_i^{-1}+\kappa|\Omega|^{2/\nu}$ is the effective anisotropic–rotational dimension. Our results provide a mathematical foundation for analysing high–Mach rotating flows and for designing physically informed neural architectures.
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Biological Physics · Cross-listed from cs.RO
Reinforcement Learning Enables Autonomous Microrobot Navigation and Intervention in Simulated Blood Capillaries
Jannik Drotleff, Samuel Tovey, Paul Hohenberger et al. (+4 more)
Autonomous microrobots navigating biological vasculature could enable targeted drug delivery and thrombolysis, yet training control policies for realistic environments remains an open challenge. Prior reinforcement learning (RL) studies of microrobotic
navigation have been limited to idealized geometries that omit complex hydrodynamic flow fields, confined branching structures, and dense cellular obstacles found in vivo. Here, we develop a physically grounded simulation of a blood capillary network, incorporating realistic hydrodynamic flow fields, explicit red blood
cell dynamics, and anatomically derived branching geometry, and train deep RL
agents to navigate it via chemotaxis. We systematically map the physical limits of
navigation across
robot size and swimming speed, revealing a forbidden regime where Brownian motion and flow overcome propulsion. Successful
agents independently discover multiple universal strategy types, including run-and-rotate and energy-efficient search-and-sit policies, regardless of
robot parameters. Without retraining, these
agents perform targeted blocking and unblocking of capillary flow, restoring throughput to healthy baseline levels. These results establish RL as a viable framework for developing autonomous microrobotic intervention strategies in complex biological environments.
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All authors Jannik Drotleff, Samuel Tovey, Paul Hohenberger, Christoph Lohrmann, Julian Hoßbach, Konstantin Nikolaou, Christian Holm
General Relativity and Quantum Cosmology
Observable strong field effects of extra spacetime dimension in the braneworld black hole
K. K. Nandi, R. N. Izmailov, R. Kh. Karimov et al. (+1 more)
Inspired by the string theory, the braneworld picture introduces extra dimensions beyond the four that may have observable non-trivial effects in short distance (strong field)
gravity experiments. A case in point is the Randall-Sundrum braneworld picture that projects the $5d$ bulk Weyl tensor onto the $3d$ brane providing a stress tensor in the effective Einstein field equations on the brane. Dadhich, Maartens, Papadopoulos and Rezania (DMPR) derived an exact braneworld black hole solution of the brane
vacuum field equations. The solution formally resembles that of Reissner-Nordström but is physically different from it since the "
tidal charge" $\Upsilon$ in the solution is not the electric charge but an imprint from the fifth dimension allowing both signs in the power law modification $\pm \frac{\Upsilon ^{2}}{r^{2}}$ to the Schwarzschild metric $\left( \Upsilon = 0\right)$. The corresponding black holes are designated as DMPR$\pm$. We study here the effect of $\Upsilon$ on strong field
lensing observables and compare in the eikonal limit the ring down quasinormal mode (QNM) frequencies of DMPR$-$ with those of DMPR$+$, the two variants of
tidal charge modified Schwarzschild black hole ($\Upsilon = 0$). It turns out that the
tidal charge can significantly modify the Schwarzschild
lensing observables and QNM frequencies. In particular, we find that the Pretorius-Khurana critical exponent $\gamma$ of circular null orbits in the DMPR$-$ black hole has a lower value than that for the Schwarzschild black hole, which indicates a stronger Lyapunov instability suggesting that the
accretion disks of DMPR$-$ black holes would appear brighter. The case of the SgrA* black hole is considered for a possible constraint on $\Upsilon$ from the EHT observation of its shadow size.
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All authors K. K. Nandi, R. N. Izmailov, R. Kh. Karimov, A. A. Potapov
Mathematical Physics
On Support Cardinality for the Discrete Schrödinger Equation
Linjun Li
How sparse can a nontrivial solution of a discrete Schrödinger equation be? In this note we study Dirichlet solutions on a finite $d$-dimensional
lattice box, allowing an arbitrary real potential, and measure sparsity by the number of
lattice sites at which the solution is nonzero (assuming it is nonzero at the origin). Our main result is a dimension-reduction principle: the minimal possible support size cannot decrease when the dimension increases. Consequently, any lower bound proved in dimension $d-1$ automatically yields the same lower bound in dimension $d$. As an application, we obtain a nearly sharp lower bound in four dimensions, matching the best-known two-dimensional constructions up to a logarithmic factor.
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Solar and Stellar Astrophysics
Can Asteroseismic Structure Inversions Be Performed in Structure-Dependent Coordinates?
J. M. Joel Ong, Sarbani Basu, Willem Hoogendam et al. (+1 more)
Yes. Unlike other applications of observational asteroseismology, "structure inversions" constrain the physical properties of
stellar interiors in a model-independent fashion. However, existing techniques – which parameterise these quantities as functions of the physical radial or mass coordinate – break down when applied to
stars which differ substantially from the Sun. These difficulties may be overcome by operating in coordinate systems that have long been known to more naturally suit the physical characteristics of the measured normal modes. We derive expressions for transforming inversion kernels in the acoustic and buoyancy radial coordinates, rather than in the physical radius, and make available a numerically performant implementation. These modified inversions directly address several specific known shortcomings of existing inversion procedures. Using the buoyancy radius in
gravity-mode and mixed-mode pulsators permits meaningful comparisons of
stars and models with differently-sized convective and radiative zones, which defeat standard inversions. Even in pressure-mode oscillators, inversions in the acoustic radial coordinate eliminate the methodological requirement for the mass and radius of the true
star being needed to be known in advance.
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All authors J. M. Joel Ong, Sarbani Basu, Willem Hoogendam, Vincent Vanlaer
Strongly Correlated Electrons
Intrinsic Magnetic Excitations and Heavy-Fermion Formation in the Frustrated Mn Pyrochlore System YMn$_{2+\delta}$Zn$_{20-x}X_x$ ($X$ = In and Al) Revealed by Nuclear Magnetic Resonance and Nuclear Quadrupole Resonance Measurements
Shunsaku Kitagawa, Kenji Ishida, Yoshihiko Okamoto et al. (+1 more)
We performed
nuclear magnetic resonance (NMR) and
nuclear quadrupole resonance (NQR) measurements to investigate the microscopic electronic states of the $d$-electron heavy-
fermion candidates $\mathrm{YMn_{2+\delta}Zn_{20-x}In_x}$ and $\mathrm{YMn_{2+\delta}Zn_{20-x}Al_x}$. In these compounds,
magnetic fluctuations of the Mn pyrochlore
lattice are expected to play an important role in heavy-
fermion formation; however, excess Mn atoms complicate the interpretation of the physical properties. Our spectral analysis reveals that In substitution exhibits much higher site selectivity and introduces significantly less disorder in local structure than Al substitution. The temperature dependence of the
nuclear spin-
lattice relaxation rate divided by temperature $1/T_1T$ measured by $^{55}$Mn-NQR shows a clear enhancement at low temperatures, indicating the development of low-energy excitations associated with heavy-
fermion formation. However, its absolute magnitude is approximately 20 times smaller than that in the related compound YMn$_2$, which hosts stronger
antiferromagnetic correlations, indicating that the
magnetic interactions are substantially weakened by the enlarged Mn-Mn distance. These results demonstrate that the heavy-
fermion state in this system arises from the Mn pyrochlore network and is more closely associated with frustration-induced
magnetic excitations with low energy than with conventional
antiferromagnetic quantum-critical fluctuations.
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All authors Shunsaku Kitagawa, Kenji Ishida, Yoshihiko Okamoto, Zenji Hiroi
Strongly Correlated Electrons
The SU(N) Holstein Model
Chunhan Feng, Linh Pham, George Batrouni et al. (+1 more)
From the condensed matter physics perspective, the most natural single orbital tight-binding
Hamiltonians, and hence the most widely studied, contain two fermionic species, corresponding to
spin up and
spin down electrons. In cold atom systems, however, SU(N)
symmetry, in which $N > 2$ fermionic species reside within a single band, also occurs. In order to understand such experiments, the SU(N) Hubbard model has been increasingly studied. Here we present determinant
Quantum Monte Carlo simulations of the SU(N) Holstein
Hamiltonian, in which $N$ fermionic species couple to a single local
phonon mode. We show that at half filling it has an insulating charge density wave phase (CDW) at low temperatures, in which empty sites alternate with sites with $N$ particles. We determine the $N=3$ CDW phase diagram in the temperature, $T$, versus electron-
phonon coupling, $\alpha$, plane at fixed
phonon frequency $\omega_0$ and half-filling $\rho=1.5$. The critical temperature $T_c$ for $N=3$ can be as high as twice the maximum attainable for $N=2$. We also obtain the $N$ dependence of $T_c$ for a representative, fixed, $\omega_0$ and $\alpha$.
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All authors Chunhan Feng, Linh Pham, George Batrouni, Richard Scalettar
Instrumentation and Methods for Astrophysics
Analysis of Laser-Satellite Deconfliction for Astronomical Observatories
Christoph Baranec, Reed Riddle, Yuhei Takagi et al. (+1 more)
We present an analysis of
laser-satellite deconfliction across three astronomical
laser observatories for right ascension and declination targets and fixed azimuth and elevation ranges. This study uses new visualization tools to evaluate how different science exposure durations impact the total percentage of available open-time during observing nights. We further assess the operational efficiency of
laser keep-out-cone half-angles from the default 2.5 degrees down to the 0.1-degree minimum. We also directly compare the open-time differences of right ascension and declination targets vs. fixed azimuth and elevation ranges. Finally, we analyze historical trends to quantify the growing effect of satellite mega-constellations and the efficacy of specific waiver protocols on ground-based
laser astronomy.
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All authors Christoph Baranec, Reed Riddle, Yuhei Takagi, Jim Lyke
Mesoscale and Nanoscale Physics
Defect Engineered 2D MoS2 Materials for ML-enabled Neurotransmitter SERS Detection
Md Arifur R. Khan, Besan Khader, Nicholas Trainor et al. (+4 more)
An attachment of catechol-containing neurotransmitter molecules is demonstrated on defect-engineered two-dimensional MoS2 platform, leading to activation of SERS due to molecular charge transfer. Mechanisms of neurotransmitters' bio-detection are discussed and Machine Learning methods are applied to distinguish spectra of structurally similar analytes. The SERS effect and selective docking of biomolecules are achieved through an optimized approach for defect engineering: namely, introducing the sulfur vacancies in MoS2 monolayer films via soft
plasma etching led to molecular attachment driven by catechol functional groups. The quality of the sensor material was controlled by Raman, photoluminescence, and XPS characterization, thus allowing for optimization of the process of defect formation and achieving sensing selectivity. The sensor material showed no response to serotonin, confirming the specificity of attachment/SERS due to S-vacancies that regulate the strength of catechol-specific molecular adsorption. Defect-engineered MoS2 has enabled SERS detection of dopamine and epinephrine down to the sub-nanomolar range ($5\times10^{-10}$ M), with strong calibration reliability ($R^2$ = 0.95 and 0.99 for pure samples). PCA-LDA achieved 100$\%$ accuracy in distinguishing dopamine and epinephrine, which establishes defect-engineered MoS2 as a tunable, low-cost SERS platform for future sensing applications.
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All authors Md Arifur R. Khan, Besan Khader, Nicholas Trainor, Chen Chen, Joan M Redwing, Slava V Rotkin, Tetyana Ignatova
High Energy Physics (Phenomenology)
Hyun Min Lee and Rojalin Padhan
We regard the weak isospin of the
Higgs doublet as a
qubit and classify the
entanglement measures for the
Higgs scattering in the Standard Model Effective Field Theories (SMEFT) and their Ultra-Violet complete models. We consider
Higgs scattering in the unbroken phase for electroweak
symmetry. Treating the final state as a momentum-isospin bipartite system, we obtain von Neumann and linear
entropies to quantify momentum-isospin correlation. From the momentum reduced state, we calculate the concurrence, which measures the
entanglement between the two isospins. Both quantities are set by the isospin singlet and triplet scattering amplitudes, and hence by the Wilson coefficients of the dimension-6 and dimension-8
Higgs operators. We find that the von Neumann
entropy grows as a function of the total energy in SMEFT as compared to the SM case, but it undergoes a cancellation in the medium energy below the cut-off scale due to the interference effects between the dimension-4 and dimension-8 operators, in particular, when the effective interactions stem dominantly from a massive graviton. Assuming the dominance of dimension-8 operators, we find the conditions for
entanglement suppression in the forward or backward scatterings or across all the kinematics. We also show the correlations between the
entanglement suppression and the positivity bounds in the forward limit.
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Statistical Mechanics
Accelerating Chemical Potential Calculations with Minimal Normalizing Flows
Philippe Baron and Athanassios Z. Panagiotopoulos
Chemical potentials are among the most important properties that can be obtained from a molecular simulation since they define many technologically relevant collective properties. The chemical potential of a species in solution is obtained by computing the free energy change of adding that species into a bulk system, a calculation typically very expensive for systems such as electrolytes, due to the lack of phase space overlap between "not-inserted" and "inserted" states. Recently, normalizing flows have been introduced as a way to accelerate free energy computations by learning a bijective function, constructed to be as expressive as possible, that maps the configuration space of one Boltzmann distribution onto another. This expressivity makes them difficult to train, limiting their ability to be generated "on-the-fly" for any new system, and in practice these mappings have shown only modest sampling improvements for
liquids. We address these issues by introducing a "minimal" normalizing flow (MNF). This is a trainable bijective mapping that is intentionally limited in expressivity, and instead applies low-dimensional, physically informed transformations. Useful MNFs can be trained in 1 minute of GPU time due to their simplicity and our introduction of a novel training strategy. We show how calculations of chemical potentials of Lennard-Jones particle systems can be accelerated by at least 10 times with a simple radial mapping. We also apply a radial and orientational mapping to ion solvation in water, showing that MNFs can increase the effective sample size by 3 times for charging free energy calculations and 8 times for calculating free energy changes due to force field perturbations. This provides the foundation for the development of physically-informed mappings that can accelerate complex free energy calculations while retaining low training costs.
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Astrophysics of Galaxies
The new era of Lyman alpha emitters (LAEs): Efficiency in the selection criteria
P. Layana-Astudillo, I. Laferte-Urrutia, L. Guaita et al. (+6 more)
The ODIN survey has detected thousands of Lyman-alpha emitting
galaxies across seven sky fields, covering nearly one hundred square degrees. One of these regions is the SHELA field, observed with DECam on the Blanco
Telescope, reaching depths of approximately 25.3 AB mag in the N501 and N419 narrowbands and approximately 26.3 AB mag in the g and r broadbands over fifteen square degrees. In this work, we analyze the efficiency of the dual-continuum selection criterion as a function of broadband depth. Applied to the N501/N419 observations, we find that when the broadband data are roughly one magnitude deeper than the narrowband, nearly 80% of the LAEs are recovered, compared to only approximately 20% when both reach the same depth. This result shows that, for a fixed observing budget, the optimal strategy is to obtain broadband images approximately one magnitude deeper than the narrowband, since deeper exposures yield progressively smaller gains in the recovery fraction.
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All authors P. Layana-Astudillo, I. Laferte-Urrutia, L. Guaita, C. Artale, J. Magaña, E. Gawiser, P. Troncoso-Iribarren, K. Lee, N. Firestone
Optics · Cross-listed from eess.IV
Dimension expansion for simulation-efficient nanophotonic neural networks
Shuo Huang, Mahsa Torfeh, Lujia Zhong et al. (+3 more)
Inverse design of nanophotonic structures is challenging due to the large design space, nonlinear structure-response relationships, and the high computational cost of iterative electromagnetic simulations. Existing deep-learning approaches typically rely on large precomputed
datasets or libraries of optimized structures, which limits scalability to continuous and complex inverse-design tasks. We introduce a Dimension Expansion Network (DEN), a fully unsupervised, simulation-efficient framework for nanophotonic inverse design. DEN addresses the mismatch between low-dimensional design objectives and high-dimensional nanophotonic structures by transforming compact target parameters into structured, high-dimensional conditioning representations before inverse design. This improves target expressivity and conditioning quality for structure generation. The model is trained end-to-end using differentiable electromagnetic simulations, removing the need for any pre-generated
dataset. We validate DEN on free-form metalens and asymmetric Y-splitter design problems. For metalens design, DEN achieves focal intensities comparable to adjoint-based optimization while reducing simulation cost by approximately 50% and generalizing across tens to thousands of focal targets within a shared focal region. For Y-splitter design, DEN accurately produces arbitrary power-splitting ratios using only 21 training targets and demonstrates robust broadband performance. Ablation studies and representation analyses show that dimension expansion enhances sensitivity to target variations, increases structural diversity, and reduces mode-collapse-like behavior. Overall, DEN provides a scalable conditioning strategy for inverse design with low-dimensional objectives, enabling efficient photonic design across large continuous target spaces.
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All authors Shuo Huang, Mahsa Torfeh, Lujia Zhong, Michelle L. Povinelli, Owen D. Miller, Chia Wei Hsu
High Energy Astrophysical Phenomena
Supernovae with the Square Kilometre Array
Poonam Chandra, Yuhei Iwata, A. J. Nayana et al. (+2 more)
This chapter presents the science potential of the Square Kilometre Array (SKA) for studying all classes of
supernovae and their environments. It substantially updates and extends the earlier work of Perez-Torres et al. (2015), originally published in the 2015 Advancing Astrophysics with the SKA (AASKA14) volume, reflecting the dramatic progress in time-domain astronomy and
radio instrumentation over the past decade. We outline how SKA1 and its pathfinders will transform the
radio study of core-collapse
supernovae (CCSNe) through sensitive, commensal wide-field surveys capable of discovering hundreds of events per year, providing a
dust-unbiased census of massive-
star deaths and direct measurements of the volumetric CCSN rate. The same data will probe ejecta-circumstellar medium (CSM) interaction, shock microphysics, and progenitor mass-loss histories. Deep, triggered observations of thermonuclear
supernovae (SNe Ia) will allow the SKA to test competing progenitor scenarios by detecting – or definitively excluding – the
prompt radio emission expected from single-degenerate systems. The chapter further explores superluminous
supernovae (SLSNe), delayed interaction
supernovae and synergies with facilities such as ALMA, ngVLA, CTA, IceCube-Gen2, and ULTRASAT. Collectively, these studies will turn
radio supernova astrophysics from a discovery-limited field into one governed by population statistics.
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All authors Poonam Chandra, Yuhei Iwata, A. J. Nayana, Miguel Pérez-Torres, Kovi Rose
Medical Physics
Generation of synthetic CT images from optical scanning for superficial mold brachytherapy
Scott B. Crowe, Emily Simpson-Page, Jenna Luscombe et al. (+2 more)
Optical 3D scanning systems allow the acquisition of accurate models of patient anatomy, suitable for use in the design of simple 3D-printable patient-matched medical devices with 3D modelling software. This study developed and demonstrated the use of superficial brachytherapy surface mold design workflow that utilizes data from optical 3D surface scanning and enables a commercial brachytherapy treatment planning system to be used for catheter positioning and dose optimization steps. Synthetic CT images were generated from 14 optically scanned anatomical models of human participants. Models and skin textures ac-quired from the optical scans were imported into Autodesk Meshmixer, where the treatment area was delineated, and treatment and device volumes produced. 3D Slicer was used to convert the body, treatment and device volumes to DICOM CT and RTSTRUCT data. The synthetic CT data and contoured volumes were imported into Varian Eclipse, where catheters were designed, and dwell positions and times optimised for dose coverage of the treatment volume. The lack of in-ternal anatomy did not compromise dose calculations, due to clinical use of a TG43 based
algorithm. Once 3D printed, molds can be imaged in-situ during CT simulation, and reconstructed, for clinical dose calculation and plan approval.
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All authors Scott B. Crowe, Emily Simpson-Page, Jenna Luscombe, Rachael Wilks, Tanya Kairn
Computational Physics
A Scalable Time-Based Molecular Dynamics Approach for Simulating Single-Bubble Sonoluminescence
Shihan Cheng and David A. B. Hyde
We present a scalable time-based molecular dynamics (TBMD) framework for simulating single-bubble sonoluminescence within a hybrid continuum-MD formulation. Unlike prior event-based approaches, which model gas dynamics through instantaneous hard-sphere collisions, the present method integrates continuous Lennard-Jones and damped shifted force Coulomb interactions at each timestep, enabling self-consistent tracking of ionization state and long-range electrostatics throughout the collapse. To bridge the gap between the physical particle count ($N_\mathrm{real}\sim 10^{10}$) and computationally tractable ensemble sizes, we introduce an ensemble particle (EP) scaling formalism that preserves temperature, pressure, and ionization statistics while reducing the simulated particle count by up to four orders of magnitude. Applying the framework to argon under standard single-bubble sonoluminescence driving conditions, we perform a systematic sweep over the ionization model and thermal accommodation coefficient $\alpha_t$, with ensemble sizes up to $N_\mathrm{ensem} = 10^8$ particles. The results establish that ionization is the dominant regulator of peak temperature, reducing $T_\mathrm{max}$ by approximately a factor of two relative to the non-ionizing baseline, while $\alpha_t$ primarily controls the spatially averaged temperature at the collapse minimum. Scalar observables at $N_\mathrm{ensem} = 10^8$, including peak temperature, minimum bubble radius, and maximum wall velocity, are assessed against prior studies to help validate the EP scaling formalism and our hybrid continuum-MD framework.
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Solar and Stellar Astrophysics
Standing oscillations in a resonant sunspot atmosphere captured by integral field spectroscopy
Glen Chambers, David B. Jess, Shahin Jafarzadeh et al. (+8 more)
The
solar atmosphere is replete with magnetohydrodynamic wave activity, with
magnetic structures such as sunspots channelling wave energy flux efficiently into the outer atmosphere. Steep density and temperature gradients between the photosphere and chromosphere provide ideal conditions for magnetoacoustic resonance cavities, amplifying $\sim 5$ mHz oscillatory power in sunspot atmospheres. However, diagnosis of such cavities has largely been limited to lines such as Ca II H/K and He I 10830 Å, with no evidence yet from layers probed by the Na I D$_1$/D$_2$ doublet. Here we use the newly commissioned integral field unit FRANCIS to examine oscillations spanning the formation heights of the Na I D$_1$/D$_2$ lines and determine whether propagating and/or standing modes are present within a sunspot umbra. The RH1.5D code estimated formation heights for three windows: the Na I D$_1$ wing (core $-300$ mÅ; $\approx 355$ km), the Na I D$_1$ core ($\approx 750$ km), and the Na I D$_2$ core ($\approx 850$ km). Wavelet cross-correlation of line-core and bisector Doppler velocities yielded phase spectra versus height, classifying the dominant $\sim 5.5$ mHz oscillations as propagating or standing-like. At the umbra-penumbra boundary we find propagating modes with energy fluxes of $\sim 1.3 \times 10^{4}$ W m$^{-2}$ in the upper photosphere, falling to $\sim 3.1 \times 10^{3}$ W m$^{-2}$ in the lower chromosphere, implying a damping length $L_d \approx 363$ km, comparable to the local density scale height. In contrast, near-zero phase differences dominate regions of enhanced chromospheric power at the umbral centre, evidencing standing-wave behaviour and resonance-cavity dynamics. These results demonstrate the suitability of
solar integral field units for mapping sunspot wave properties, with the Na I D$_1$/D$_2$ lines offering a novel diagnostic of resonance cavities and energy flux.
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All authors Glen Chambers, David B. Jess, Shahin Jafarzadeh, Michele Berretti, Samuel D. T. Grant, Marco Stangalini, H. N. Smitha, Damian J. Christian, Luís E. A. Vieira, Alisson Dal Lago, Fernando L. Guarnieri
Astrophysics of Galaxies
Fast Radio Bursts probe Galaxy Evolution: Evidence and implications of a redshift-dependent FRB host DM
Lluis Mas-Ribas
The
redshift evolution of ionized gas in the full
galaxy-
halo system is a central open question in
galaxy formation, because no existing observable is simultaneously sensitive to all ionized phases. Here we explore fast
radio bursts (FRBs) as a probe of the density
evolution of this gas through the
redshift dependence of the FRB host dispersion measure, ${\rm DM_{host}}(z) \propto (1+z)^{n_z}$. The host DM denotes the electron column density of all ionized gas in the host along the FRB sightline, providing a unified tracer that complements existing phase-specific diagnostics. We apply a forward-modeling framework that accounts for instrumental effects to 90 localized FRBs (69 with confirmed host
redshifts) from the DSA and ASKAP/CRAFT ICS surveys. Our inference yields $n_z = 1.62^{+1.48}_{-1.57}$, ruling out the non-evolving scenario ($n_z = 0$) at $1\,\sigma$, with both
datasets independently favoring $n_z > 0$. The main $n_z$ degeneracy is with the mean host DM and parameters such as $H_0$, highlighting the need to account for a host
evolution in inference analyses and DM-based host
redshift estimates; overestimating
redshifts by up to $\Delta z \approx 0.3$ for DM$_{\rm EG} \sim 1000 - 2000\,{\rm pc\,cm^{-3}}$ otherwise. About 100 ($300-350$) localized hosts from MeerTRAP in coherent mode (DSA/CRAFT) will yield $n_z$ uncertainties of $\sim0.7$. Precise $n_z$ measurements compared with the
evolution of individual phases and
galaxy scaling relations will shed light on ionized gas
evolution in
galaxies and
halos, informing the dominant phase, the driver of the overall
evolution, and FRB progenitor channels.
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Plasma Physics
A toroidally spectral field solver in the X-point Gyrokinetic Code for accurate simulation of reduced magneto-hydrodynamic modes
Robert Hager, C. S. Chang, Thomas Gade et al. (+5 more)
A new field solver has been implemented in the global electromagnetic total-$f$ gyrokinetic particle-in-
cell code XGC to extend the code's capability to large-scale reduced MHD-type instabilities in tokamak
plasma. While XGC's regular field solver is accurate at typical microturbulence scales of the order of the ion Larmor radius in tokamaks with arbitrary aspect ratio, a more accurate field solver is required for large-scale (i.e., low toroidal mode number) MHD-type modes such as internal kink, tearing and peeling modes. The higher accuracy of the new field solver is achieved by dropping the (large aspect ratio) assumption that the poloidal
magnetic field is much smaller than the toroidal
magnetic field, while its numerical complexity is controlled by using a spectral discretization in the toroidal direction. To cover the entire spectrum from large-scale MHD-type modes to small-scale microturbulence, the regular and the new field solver can be run alongside each other. This work details the derivation of the new field solver, analyzes the differences between the XGC's regular and new field solvers, and verifies the new field solver against analytic predictions and the gyrokinetic code ORB5 and the MHD code NIMROD.
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All authors Robert Hager, C. S. Chang, Thomas Gade, Eric Held, Seung-Hoe Ku, Alexey Mishchenko, Aaron Scheinberg, Benjamin Sturdevant
Medical Physics
Magnetic resonance imaging assessment of the suitability and consistency of radiotherapy treatment positioning achieved using intra-oral stents
Tanya Kairn, Philip Chan, Benjamin Chua et al. (+7 more)
As head-and-neck radiotherapy treatments grow more complex and precise, it becomes increasingly important to assess the anatomical separations that can be achieved using intra-oral stents. A series of twenty T2-weighted turbo
spin echo
magnetic resonance images (MRI) were acquired of one healthy participant, with a range of different wax and 3D printed intra-oral stents in situ. The resulting measurements showed that a 3D printed modular stent containing hard polylactic acid (PLA) and flexible thermoplastic polyurethane (TPU) components made the largest and most reproducible separation between the cheeks (70.8 +/- 0.3 mm), two hard PLA stents designed to exactly fit the participant's teeth produced the poorest positioning reproducibility (standard deviations of up to 3 mm between a range of landmarks measured in repeated images). Most stents were described as “comfortable” although the wax stents left small pieces of wax attached to the teeth after use. This MRI based comparison demonstrated that the materials and designs used for intra-oral stents can have substantial effects on the level of anatomical separation and positioning reproducibility that they produce.
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All authors Tanya Kairn, Philip Chan, Benjamin Chua, Susannah Cleland, Jodi Dawes, Lizbeth Kenny, Charles Y. Lin, William R. McDowall, Tania Poroa, Scott B. Crowe
Cosmology and Nongalactic Astrophysics
A new $H_0$ measurement with SNe Requiem and Encore using $\texttt{Gravity.jl}$
L. Bazzanini, G. Di Rosa, A. Acebron et al. (+24 more)
We present a strong-
lensing (SL) analysis of the
galaxy cluster MACS J0138.0-2155 (z=0.336), the first known lens cluster discovered to host two distinct multiply imaged Type Ia
supernovae (SNe): SN Requiem and SN Encore. Both SNe are located in the massive, multiply imaged red
galaxy MRG-M0138 at z=1.949. The projected total mass of this cluster has been investigated with several independent lens models (Suyu+26; Pierel+26), using a sample of 23 spectroscopically confirmed multiple images from 8 background sources (0.767<z<3.420), identified from HST and JWST imaging data, and VLT/MUSE spectroscopy. In this work, we develop a new SL model based on a novel
Bayesian parametric lens-modelling framework $\texttt{Gravity jl}$, exploiting the same SL
dataset. Our reference mass model accurately reproduces the observed image positions, with an image-plane rms image position residual of 0.15”. Assuming H0 = 70 km/s/Mpc, we predict the future reappearances of highly delayed SNe counter-images, finding $D_t(1d,1a) = 3122_{-70}^{+75}$ d (April-August 2032) for SN Encore and $D_t(2d,2a) = 3902_{-67}^{+72}$ d (January-May 2027) for SN Requiem. By allowing H0 to vary, and using the measured time delays of SN Encore and Requiem together with their statistical uncertainties as observables, we infer the value of H0 jointly with the other lens-model free parameters, by combining the values inferred from 3 mass models. We obtain a new measurement of $H_0 = 69.2_{-8.0}^{+9.6}$ km/s/Mpc, consistent with the value inferred from independent lens models. This error is currently dominated by the large relative uncertainty on the measured time delays (>10%). The forthcoming reappearance of SN Requiem offers an immediate opportunity to significantly improve constraints on H0, provided that lens-model systematics are controlled. These results establish M0138 as a premier anchor for high-precision cluster TDC.
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All authors L. Bazzanini, G. Di Rosa, A. Acebron, P. Bergamini, M. Lombardi, P. Rosati, G. Angora, G. B. Caminha, S. Ertl, G. Granata, A. M. Koekemoer, S. H. Suyu, J. Pierel, A. B. Newman, C. Grillo, S. Schuldt, M. Bulla, S. Cha, M. D'Addona, J. M. Diego, M. Fogliardi, B. L. Frye, M. J. Jee, P. S. Kamieneski, M. Meneghetti, A. Mercurio, E. Vanzella
Computational Physics
Leveraging Population Dynamics to Steer Efficient Search in Large-Scale Combinatorial Optimization
Nikhat Khan, Ridge Redding and Nikhil Shukla
Combinatorial optimization problems pose substantial computational challenges because their feasible solution spaces grow exponentially with problem size. This paper presents a GPU-accelerated augmented Population Annealing Monte Carlo (PAMC) framework for large-scale graph-partitioning problems, with emphasis on Max-Cut and Max-K-Cut. The proposed framework extends conventional PAMC by coupling population-based resampling with two stagnation-driven mechanisms: adaptive temperature control and energy-preserving nonlocal cluster moves. By using population-level optimization history as feedback, these mechanisms regulate the balance between exploration and refinement by reheating stalled populations and enabling collective transitions across locally confined regions of the solution space. Experiments on G-set
benchmark instances show that the augmented PAMC framework achieves competitive or lower time-to-solution than reported state-of-the-art baselines on several large Max-Cut instances, while matching or improving solution quality under comparable runtime budgets. The solver also discovers a new best-known solution for the G63 Max-Cut instance and scales to a fully connected 100,000-
spin Ising instance. For Max-3-Cut, the same framework establishes new best-known solutions on 36 G-set instances, demonstrating its applicability beyond binary Ising formulations. These results indicate that feedback-controlled population dynamics provide an effective and scalable strategy for steering
stochastic search in large-scale combinatorial optimization.
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Nuclear Theory
Two-Body Scattering Observables from Finite-Volume Real-Time Evolution
Lucas Platter
We study two-body scattering observables from real-time
evolution in a finite periodic box. The system consists of two distinguishable particles on a two-dimensional
lattice interacting through pointlike $s$- and $p$-wave interactions. We evolve their wave packets in real time, define detector observables through angular wedges in the relative coordinate, and attach infinite-volume labels obtained from the bound-state pole equation and the low-energy scattering amplitude. We train a convolutional neural network on this data and test its performance on held-out scattering problems and find that is able to predict the total magnitude and angular shape for previously unseen
Hamiltonians.
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Optics
Modeling and Analysis of Phase Instability in Photonic Processor
Gökhan Elmas, Igor Litvin, Paul Kohl et al. (+1 more)
Achieving both reconfigurability and stable output signals is a critical challenge in the development of integrated photonic
circuits for large-scale optical
quantum information processing. This has led to the creation of multimode photonic processors, also known as reconfigurable multimode interferometers, which have wide-ranging applications in
quantum and classical information processing. However, maintaining phase stability in multi-port input signals remains a significant hurdle, particularly due to the phase instabilities introduced by active cooling systems and temperature drifts in the photonic processor. In this study, we propose theoretical models to simulate phase instability in photonic processors and validate them against experimental results. Two distinct modeling approaches were employed: a Brownian random walk and phase reconstruction based on experimentally observed oscillating harmonics. Additionally, we verified and applied our model to a specific application for input phase correction using self-feedback control within the photonic processor.
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All authors Gökhan Elmas, Igor Litvin, Paul Kohl, Janis Nötzel
Mathematical Physics · Cross-listed from math.AT
Hodge Spectral Surrogates for Topology-Constrained Optimization
Satoshi Kanno and Yoshi-aki Shimada
Topology-constrained optimization arises in applications such as medical image
segmentation,
geometric design, and network generation, where global structural correctness matters. Yet Betti numbers and persistent homology are discrete and combinatorial, making them difficult to control directly by gradient-based optimization. We propose a differentiable framework that replaces discrete topological counting with a soft spectral relaxation of the Hodge
Laplacian. Candidate simplices are embedded in a fixed ambient complex, while simplex inclusion is represented by continuous activations, producing a smooth spectral path between different hard complexes. The soft states are used only as optimization surrogates; in the hard limit, the ordinary Hodge
Laplacian and its homological zero modes are recovered. We establish operator-norm and spectral perturbation bounds connecting hard Betti numbers to soft near-zero modes, and derive differentiable objectives using heat, resolvent, and
polynomial low-pass filters. Controlled experiments on Vietoris–Rips point clouds show more spatially distributed gradients, reduced scale-normalized derivative variation near persistence-pairing changes, and geometry-aware update directions in the tested settings. Experiments on graph clique complexes further show controllable shifts in sampled hard Betti regimes and compatibility with standard graph objectives. The framework provides a complementary Hodge-spectral approach to persistent-homology-based
topology optimization.
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