General Relativity and Quantum Cosmology
The Fifth RIT Catalog of Binary Black Hole Simulations: Multiple-Resolution Studies of Eccentric Orbits
Giuseppe Ficarra, James Healy and Carlos O. Lousto
This fifth release of the RIT public catalog of numerical relativity binary black hole waveforms http://ccrg.rit.edu/~RITCatalog introduces an additional 248 configurations, prioritizing 197 newly simulated eccentric orbits. This update brings the catalog to a total of 2129 cases. All waveforms are corrected for center-of-mass drift and extrapolated to future null infinity. To rigorously estimate waveform errors, we conduct multiple-resolution convergence studies on 10 eccentric simulations (up to 33 orbits to merger) using three global resolutions increasing by factors of 1.2, plus a comprehensive six-resolution study for a single 18-orbit configuration. We evaluate waveform accuracy by computing mismatches against theoretical infinite-resolution extrapolations. Additionally, we analyze the convergence properties of key physical observables: merger times, number of orbits, final masses, final
spins,
recoil velocities, and the peak amplitude, frequency, and luminosity of the gravitational radiation.
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Chemical Physics
Minimization of disorder as a key design principle for natural sizes of light harvesting 2 complexes
Kwang Hyun Cho, Seogjoo J. Jang and Young Min Rhee
The light harvesting 2 (LH2) complex of purple bacteria has excellent energy conversion efficiency. Clarifying the design principle behind such efficiency at the atomistic level is crucial for understanding its structure-function relationship, and can be utilized for the design of artificial light harvesting systems. To this end, we conducted comprehensive computational investigation of the dynamical and statistical nature of electronic excited states of pigment molecules in a natural LH2 complex with 9-fold
symmetry and its two non-natural in silico analogues with 6- and 12-fold
symmetries. To ensure reliable and efficient all-atomistic molecular dynamics simulations, we combined a well established interpolation approach for the construction of the potential energy surface with a neural network machine learning approach. Outcomes of these calculations clarify that non-natural forms of LH2-type complexes have significantly larger quasistatic disorder than those for the natural one. In addition, non-natural systems have more disruptions of the hydrogen bonding, underscoring its crucial role for reducing the disorder. On the other hand, local environmental dynamics are relatively insensitive to the structural changes although there is moderate enhancement in the anharmonic or interatomic components for the synthetic ones. These findings based on all-atomistic simulations provide direct computational evidence that the structure and sizes of natural LH2 complexes are designed to minimize the energetic disorder. We analyze quantitative implications of these for the energy transferring capability of the LH2 complex.
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Strongly Correlated Electrons
Correlation-driven phonon renormalisation and the equation of state of $\gamma$-cerium
Yao Wei, Siyu Chen, Evgeny Plekhanov et al. (+3 more)
We investigate the thermodynamic properties of elemental cerium by assessing the crucial role of
phonon free energy within the framework of dynamical mean-field theory (DMFT). While conventional density functional theory (DFT) often fails to capture the intricate energy landscape of $f$-electron materials, our approach integrates many-body electronic correlations with
lattice dynamics to achieve a more rigorous description of the equation of state. We calculate the total energy as a function of the
lattice constant at both the DFT and DFT+DMFT levels, subsequently incorporating the vibrational free energy derived from the
phonon density of states. Our findings reveal that electronic renormalisation of the force constants significantly alters the
phonon spectra, particularly in the strongly correlated $\gamma$-phase. By applying these
phonon corrections to the energy profiles, we observe a substantial refinement in the predicted
equilibrium volumes. Using principal-component-based machine learning, we interpolate
phonon dispersions continuously from a finite set of first-principles calculations and compare them to experiment, finding significantly closer agreement compared to conventional DFT and DFT+U calculations that neglect dynamical many-body correlations. This study underlines the necessity of accounting for both electronic and vibrational
entropy when evaluating the phase stability and structural transitions of lanthanide systems under varying pressures and temperatures.
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All authors Yao Wei, Siyu Chen, Evgeny Plekhanov, Ivan Stich, Cedric Weber, Jan M. Tomczak
General Relativity and Quantum Cosmology
Static Spherically Symmetric Chaplygin and Polytropic Fluid Solutions in Teleparallel $F(T)$ Gravity
Alexandre Landry
We investigate static, spherically symmetric (SS) spacetimes in covariant teleparallel $F(T)$
gravity sourced by nonlinear Chaplygin and polytropic fluids. Using the covariant coframe/
spin-connection (CSC) formalism, we derive the corresponding field equations and conservation laws governing admissible matter distributions and nonlinear torsion sectors. A general reconstruction procedure is developed, allowing the systematic determination of teleparallel $F(T)$ models for arbitrary coframe ansätze and fluid equations of state. Focusing on power-law configurations, we obtain several classes of reconstructed solution branches, including constant-radius, compact-object-like, and wormhole-like (WH-like) branches. The Chaplygin sector naturally leads to effective dark-energy-like and exotic-matter candidate solution branches within the reconstruction framework, which may provide admissible sectors for wormhole-like reconstructed geometries, while the polytropic sector provides reconstructed branches that may serve as physically motivated candidates for future
stellar-interior and compact-object models. We discuss the associated candidate horizon and throat conditions, torsion singularities, energy conditions, and local viability properties of the reconstructed branches. The resulting geometries are organized within a teleparallel invariant classification framework, highlighting the role of nonlinear torsion corrections in shaping the solution space. Overall, this work provides a unified covariant reconstruction framework for nonlinear-fluid sectors in teleparallel $F(T)$
gravity, identifying solution branches that may serve as candidates for future compact-object,
stellar-interior, and wormhole studies.
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Quantum Physics · Cross-listed from cs.CE
VQA for Dynamic Portfolio Optimization: Sampling Strategies, Optimizer Scheduling, and Hardware-Aware Ansatz Design
Mohammad Kashfi Haghighi
Variational
quantum algorithms are increasingly explored for optimization problems at scales relevant to near-term
quantum devices. Their practical performance depends strongly on design choices such as the sampling objective, classical optimizer, and ansatz layout before and after hardware transpilation. We study these factors for dynamic portfolio optimization, a multi-period financial problem balancing return, risk, transaction costs, cash-interest effects, and constraints. Using a sampling-based VQA framework on a 150-
qubit dynamic portfolio instance, we evaluate several components of the optimization workflow. We propose a specific adaptive CVaR schedule that gradually tightens the sampled tail used for optimization, together with a two-stage optimizer combining global exploration with Particle Swarm Optimization and local refinement with the Nakanishi-Fujii-Todo optimizer. We also study ansatz depth and sequential growth strategies. Finally, we introduce two hardware-aware ansatz-layout modifications: a data-guided colored layout that assigns correlated variables to
qubits connected by entangling gates, and a heavy-hex-native deep-chain layout designed to increase native two-
qubit interaction depth without additional routing overhead after transpilation. Simulator studies select CVaR, optimizer, and depth configurations, while the ansatz comparison is performed on the ibm_quebec QPU. The results show that sampling strategy, optimizer scheduling, and hardware-aware layout design materially affect performance. In the reported QPU layout comparison, the proposed heavy-hex-native deep-chain layout achieves the best final objective value and CVaR-tail performance among the tested layouts. Although we do not observe
quantum advantage over a state-of-the-art exact classical solver, our results provide practical guidance for improving VQA performance on near-term hardware.
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Nuclear Theory
Thermodynamic versus Dynamical Description of the Neutron-Star Crust-Core Instability: Implications for Crustal Observables
Athul Kunjipurayil and J. Piekarewicz
We investigate the crust-core transition in
neutron stars using both thermodynamic and dynamical descriptions of the instability. In the thermodynamic approach, the transition is identified through the vanishing of a generalized incompressibility coefficient signaling the onset of a bulk spinodal instability. In contrast, the dynamical approach based on the relativistic random-phase approximation (RPA) incorporates Coulomb screening and finite-size effects that determine the instability at finite wavelength. Using a family of covariant energy density functionals spanning a broad range of
symmetry-energy slopes, we show that the dynamical treatment systematically predicts lower transition densities and pressures compared to the thermodynamic approach. We further demonstrate that the RPA instability develops at a characteristic length scale set by the competition among bulk, Coulomb, and surface effects. Most importantly, we show that these differences propagate directly into
neutron-
star observables. Because the thermodynamic approach predicts larger transition pressures, it generates thicker crusts and significantly larger crustal fractions of the
stellar moment of inertia than the dynamical-RPA framework – with important implications for the interpretation of
pulsar glitches and other crust-sensitive
neutron-
star observables.
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High Energy Physics (Phenomenology)
The Scattering Algebra of Physical Space: Wigner-Covariance and Fields
Moab Croft and Neil Christensen
Following previous work, the
Algebra of Physical Space (APS) is used to explore Wigner-covariance and
spin/helicity fields within the Constructive Standard Model (CSM) of Particle Physics. The spinor formalism of the APS is used to derive explicit Wigner-covariance of Lorentz spinors, and equivalencies with the CSM are demonstrated via the Scattering
Algebra (SA). Constructive fields for
spin-1/2 and
spin-1 are given in the APS and the necessary maps for Wigner-covariance are proposed. The forms of these
spin fields are equivalent to Pauli spinors, thereby serving as a new bridge between the CSM and the study of
Quantum Information. It is further seen that
spin fields of the APS are equivalent to the
spin fields in the CSM. Sample Lagrangian densities of the CSM are analyzed using the methods herein, are given
geometric interpretations, and are connected to traditional Pauli Theory. Finally, the hff (
Higgs and two massive
fermions) Lagrangian density is used to determine the first constructive scattering amplitude that is defined purely in terms of the APS. Concerningly, this leads to an anti-Hermitian action term, and this surprise is later confirmed using traditional CSM techniques. Throughout this paper, the illuminating power of
Geometric Algebra is clear: Everything has a
geometric interpretation, and results can be accomplished
matrix-free.
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Strongly Correlated Electrons
Atomic-scale visualization of the toroidal order in a trimeric Dy(III) single-molecule toroic
Michael J. Jenkins, Madalynn G. Marshall, Jie Xing et al. (+8 more)
Single-molecule toroics (SMTs) offer a unique platform for next-generation
quantum devices utilizing head-to-tail
spin alignments in the compounds. Presence of toroidal moments in SMTs has been essentially based on magnetometry and ab initio calculations. Here, we report observation and probe of the toroidal moment in [Dy3(OH)(teaH2)3(paa)3]Cl(OMe) [teaH3: triethanolamine; paaH: N-(2-pyridyl)-acetoacetamide] from mapping of Dy3+
magnetic susceptibility tensors by polarized
neutron diffraction (PND).
Neutron diffraction under variable
magnetic fields demonstrates field-induced magnetization along the c-axis with toroidal moments anti-parallelly stacked, providing definite proof of the toroidal moment. Magnetometry studies confirm the toroidal ground state. For the first time, the combined use of PND, variable-field
neutron diffraction, ab initio calculations, and magnetometry is introduced as a robust and quantitative methodology to probe molecular-scale toroidal magnetism. This integrated approach overcomes limitations of earlier indirect methods, establishes a
benchmark framework for investigating SMTs, and provides valuable insights for the design of molecular
quantum materials.
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All authors Michael J. Jenkins, Madalynn G. Marshall, Jie Xing, Muthu Satheeshkumar, Brandon D. Watson-Sanders, Xiaoping Wang, Christina M. Hoffmann, Gopalan Rajaraman, Huibo Cao, Rongying Jin, Zi-Ling Xue
Instrumentation and Methods for Astrophysics
Method to get Better Sky Maps in a GstLAL Low-Latency Analysis
Prathamesh Joshi, Becca Ewing, Chad Hanna et al. (+40 more)
Modeled gravitational wave searches correlate the strain data with a bank of gravitational wave template waveforms to make detections of gravitational wave candidates, and these results are processed by downstream tools to calculate the likely sky location and distance of the source of the candidates. This is crucial for multi-messenger efforts, since it informs astronomers where to point their
telescopes to facilitate electromagnetic follow-up of the gravitational wave candidates. We present a novel method to improve the low-latency results of the GstLAL gravitational wave search pipeline, and thus improving sky location estimates of low-latency candidates. This method involves ingesting the GstLAL low-latency results, and performing a small targeted hierarchical search to recover the candidates with more accurate parameters, in a medium-latency timescale (few seconds to five minutes). To test our method, we perform a GstLAL low-latency analysis on forty days of data from the third observing run of LIGO, Virgo, and KAGRA, and show that our method improves the GstLAL results by 5.38% and the subsequent sky location results by 16.75% on average. In addition to this increase in precision, we also show that these results are more accurate as compared to the GstLAL results. This method has been adopted by GstLAL for the fourth observing run.
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All authors Prathamesh Joshi, Becca Ewing, Chad Hanna, Zach Yarbrough, Jolien D. E. Creighton, Shomik Adhicary, Pratyusava Baral, Amanda Baylor, Kipp Cannon, Sarah Caudill, Michael W. Coughlin, Bryce Cousins, Heather Fong, Richard N. George, Shaon Ghosh, Patrick Godwin, Reiko Harada, Yun-Jing Huang, Rachael Huxford, James Kennington, Soichiro Kuwahara, Alvin K. Y. Li, Ryan Magee, Duncan Meacher, Cody Messick, Soichiro Morisaki, Debnandini Mukherjee, Wanting Niu, Alexander Pace, Cort Posnansky, Anarya Ray, Surabhi Sachdev, Shio Sakon, Stefano Schmidt, Urja Shah, Divya Singh, Ron Tapia, Leo Tsukada, Koh Ueno, Aaron Viets, Leslie Wade, Madeline Wade, Noah Zhang
Geophysics · Cross-listed from cs.LG
Using Seismic Statistical Features and VQ-VAE to Improve Spatiotemporal Seismicity Predictability
Wei Quan and Denise Gorse
In this paper we build upon a previous study in which we demonstrated, using XGBoost and earthquake catalogue data from Japan and Chile, that a set of 60 seismic statistical features (SSFs) had much greater predictive value than a set of 428 generic time series features from the tsfresh package. We here extend this previous work in two key ways, focusing on data from Japan as a large
dataset is necessary in order to allow for the training of a deep learning (autoencoder) model. First, we move from whole-region prediction (considering, for each candidate event, the likelihood of an event M $\geq$ 5.0 anywhere in the region in the next 15 days) to localised predictions in which both the region of feature computation and the region of prediction are restricted to a circle of radius 24 km around the candidate event, and we show that performance remains excellent, similar to our previous whole-region study for the same area. Second, we here couple this proven set of SSFs, based on one-dimensional (catalogue) data, with a novel feature based on magnitude-stratified two-dimensional seismic maps, obtained by training a VQ-VAE model to reproduce such maps as output and identifying a measure of its error in doing so with anomalies in magnitude distribution reflecting a localised build-up of crustal stress. We show that while localised prediction based only on a set of SSFs can be effective, with test AUC values as high as those obtained in the case of Japan in our previous whole-region study, the inclusion of the new natively-spatial VQ-VAE-derived feature, top-ranked by SHAP analysis, both improves prediction and points toward a new approach that might allow computationally time-demanding traditional seismic features to be entirely set aside.
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Disordered Systems and Neural Networks
Jittery Quantum Boomerang Effect
Pedro Dornelas and Gerson J. Ferreira
We study the dynamics of a
spin-polarized wave packet in a disordered Rashba two-dimensional electron gas and identify a jittery
quantum boomerang effect in which longitudinal and transverse motion return to the origin through fundamentally distinct mechanisms. Starting from an initial state with finite momentum along $x$ and
spin polarized along $z$, we calculate the time
evolution by combining a Chebyshev expansion of the time-
evolution operator with a disorder ensemble average. In the weak-scattering regime, equations of motion derived from the
quantum kinetic equation reproduce the numerical trends and show that
impurity scattering acts as a viscous damping mechanism that suppresses the transient Zitterbewegung and drives the transverse displacement back to $y=0$ at long times. In contrast, the longitudinal dynamics show a Drude-like saturation at weak disorder. These results are consistent with the vanishing intrinsic
spin Hall conductivity in the disordered Rashba model and with experimental observations of a transient intrinsic
spin Hall effect in the time-domain. As disorder increases, the longitudinal dynamics evolve to a partial return toward the origin, which signals a transition from weak antilocalization to Anderson localization in 2D.
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Materials Science
Dominant in-plane anomalous Hall effect in a monoclinic room-temperature ferromagnet
Guoxin Zheng, Arjyama Bordoloi, Mingjun Fan et al. (+6 more)
Ferromagnetic metals are characterized by enhanced dissipationless transverse transport responses via the anomalous
Hall effect, offering a route towards
magnetic sensing and spintronic readout functionalities. In most ferromagnets, the anomalous
Hall current is constrained to lie in the plane perpendicular to the magnetization (or applied
magnetic field). Recently, it has been recognized that selected
symmetries can also permit a
Hall response in a traditionally forbidden configuration, where the
Hall current lies in the same plane as the magnetization, realizing an in-plane anomalous
Hall effect. Reported realizations of this effect, however, are typically much weaker than the conventional
Hall response in the same material. Here, through engineering specific crystallographic mirror
symmetry-breaking, we realize a strongly enhanced in-plane anomalous
Hall response in monoclinic Cr3Te4 with room-temperature ferromagnetism. Remarkably, the in-plane anomalous
Hall signal exceeds the out-of-plane response by a factor of five, with which we demonstrate a unique in-plane field and current sensing functionality. Combined with density functional theory calculations, our results establish low-crystalline-
symmetry ferromagnets with near-
Fermi-level Weyl points as a practical platform for
symmetry-engineered
Hall responses, and point to a route towards room-temperature, geometry-flexible sensing devices.
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All authors Guoxin Zheng, Arjyama Bordoloi, Mingjun Fan, Shunsuke Kitou, Hiraku Saito, Taro Nakajima, Sobhit Singh, Takashi Kurumaji, Linda Ye
General Physics
New sum rules of the Koide type
Alejandro Rivero
We report a mass rule of Koide type with inverse shape, \[m_i=M^{(d)} (w_0+w_i)^{-2}.\] It applies to the down-
quark sector with numerical precision comparable to that of the direct charged-
lepton sum rule $m_i=M^{(l)} (z_0+z_i)^{2}$. For central mass values, Koide ratio reaches exactly $2/3$ near 280 TeV under Standard Model renormalisation-group running. We also review other rules of the direct kind involving
quarks.
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Quantum Physics
Identical Bosons, large occupation numbers and classical field description
Gaurav Goswami
For a system with a large number of identical
Bosons, it is common to claim, often without any additional justifications, that, when the mean occupation number in a single particle state is sufficiently large, classical field description will be applicable. This is why e.g. for ultra-light dark matter, the classical field equations are used to compute its dynamics. In this work, we test the validity and robustness of this assumption based on the criterion $2 \sigma_\varphi < |\langle \varphi \rangle| $ for classical field behaviour and applying it to aribtrary
quantum states. We find that an arbitrary state with large occupation number doesn't behave classically while imposing some restrictions on the state vectors can improve the classical behavior. Since coherent states are known to have quasi-classical behaviour, we also ask how much deviation from coherent state can spoil the classical behaviour. Based on this analysis, we find that it is the proximity of the state to a large occupation coherent state rather than large occupation number itself which ensures validity of classical description. Implications of this for ultra light dark matter are discussed.
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Quantum Physics
Scaling law of asymptotic freedom in collective charging of quantum batteries
Gentaro Watanabe, Chunlin Chen and B. Prasanna Venkatesh
We establish a universal scaling law for collective charging of
quantum batteries, independent of microscopic details. We prove that the ergotropy-to-energy ratio approaches unity at least as fast as $\sim N^{-1}$ with the number of batteries $N$, implying generic asymptotic freedom. We further show how the universal $1/N$ scaling can be overcome: when the battery state becomes asymptotically pure, the convergence can be substantially faster, including $\sim N^{-b}$ with $b>1$ and even exponential scaling in $N^2$. Rigorous finite-$N$ upper and lower bounds on the ergotropy-to-energy ratio are further derived, providing nonasymptotic guarantees for the universal $1/N$ scaling.
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Lattice Field Theory
Momentum Dependence of Heavy Quark Diffusion in a Thermal Gluonic Plasma on the Lattice
Harshit Pandey and Sayantan Sharma
We study the dynamics of a heavy
quark in a thermal
plasma consisting of non-perturbatively interacting soft momentum
gluons at high temperatures, described in terms of an effective theory of QCD. Discretizing this effective field theory on a three-dimensional
lattice, we propose a numerical strategy that allows us to simulate the dynamics of a heavy
quark for different values of initial momenta and for a wide temperature range, higher than $480$ MeV. This allows us, for the first time, to extract the momentum dependence of the heavy
quark drag and
diffusion coefficients in a non-perturbatively interacting thermal, non-Abelian
plasma.
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Superconductivity
Distribution of Majorana modes in the extended-range Kitaev chain
Pedro B. Widniczck and Gerardo Martínez
The topological properties of the Kitaev chain model with extended-range interactions are investigated, focusing on cases where the topological winding number is preserved. We assume that the pairing and hopping terms decay algebraically in space with exponents $\alpha$ and $\beta$, respectively. We show that in the truncated-range scenario, there are as many distinct topological phases as the number of coupled neighboring sites. In addition, an explicit analytical formulation is provided to evaluate the topological invariant and the phase transitions that emerge in these systems. Besides the analytical description, we introduce a new physical insight into the topological excitations of the ground-state by measuring the spatial distribution of the edge modes with the Majorana average position. Taking the next-nearest neighbor Kitaev chains as a probe, various numerical calculations of Majorana edge states were performed in finite-size clusters to determine the sensitivity of the topological zero energy modes to the parameters of interest. The occupation of edge-to-edge non-local
fermion states is computed and defined as an effective parity. Such an effective parity exhibits new interesting features beyond the energetic exchange from the ground-state
fermion parity switches, which are related to the distribution of the respective edge modes. Our calculations show a direct correlation between the ground-state
fermion parity and the edge occupation numbers, which are translated into localization and delocalization of the Majorana average position.
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Quantum Physics
Quantum Non-Gaussian State Preparation of Levitated Particles via Time-Dependent Control of Weakly Nonharmonic Hybrid Potentials
Piotr T. Grochowski and Oriol Romero-Isart
Levitated high-mass
quantum systems provide access to unprecedented regimes in both fundamental science and technological applications. However, deterministic generation and manipulation of
quantum non-Gaussian states, which are central to many continuous-variable
quantum advantages, remain elusive in such platforms. In this work, we propose a theoretical protocol for preparing a continuous-variable degree of freedom of a levitated massive object in a variety of
quantum states, including Fock and Schrödinger cat states, without coupling to auxiliary two-level systems. Our approach enhances otherwise weak nonharmonic effects by transient wave-function delocalization and combines this with optimal control of the potential. Specifically, time-dependent modulation of the linear component of the potential, in the presence of a static cubic nonharmonicity, provides a route to universal control of the mode. We analyze
quantum state preparation under such control and estimate the required nonharmonicity, motional delocalization, and maximum tolerable decoherence for generating target non-Gaussian states. The proposed optimal-control scheme can also be readily extended beyond single-particle state preparation, for example, to
unitary transformations and nonlinear measurements. As a concrete example, we demonstrate mechanical Bell-state preparation for two interacting particles using only local modulation of weakly nonharmonic potentials, while the interparticle interaction remains effectively linear. We emphasize that the protocols presented here apply to different mechanical degrees of freedom, such as center-of-mass motion and libration, and can also be implemented in other weakly nonharmonic systems with a leading cubic nonharmonicity.
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Cosmology and Nongalactic Astrophysics
Learning the Universe with the 2nd Generation of CAMELS: Varying 35 parameters of the IllustrisTNG model in (50Mpc/h)^3 boxes
Shy Genel, Yongseok Jo, Boon Kiat Oh et al. (+10 more)
We present a new set of 1,192 cosmological simulations as part of the CAMELS project, in which a space of 35 cosmological, astrophysical, and numerical parameters is explored around the fiducial IllustrisTNG model. The volume of each of these simulations is (50Mpc/h)^3, eight times larger than that of previous CAMELS simulations. This provides lower sample variance as well as access to more massive
halos and more diverse environments. We focus this work on exploring the advantages these differences provide for parameter inference powered by neural networks. We generate training sets based on the matter power spectra, projected maps of the volumes, graphs representing
galaxy spatial distributions, and thermodynamical properties of massive
halos. We employ multilayer perceptrons, convolutional neural networks, graph neural networks, and Gaussian processes, respectively, to extract information on the simulation parameters from these inputs while comparing systematically to analogous results from our previous generation of (25Mpc/h)^3 simulations. We generally find that the new, larger volumes produce tighter marginal constraints on the parameters, to degrees that vary between the different inputs. The improvements, however, scale more weakly than with the square root of the increase in the amount of data (i.e., physical volume). We interpret this as originating either from information loss due to mode coupling or from complex degeneracies in parameter space. We also discuss the effects on statistics of the intergalactic medium temperature from four new parameters that are varied in these simulations, which control the amplitude and timing of the ionizing background radiation. We publicly release the simulation outputs and ancillary data at https://camels.readthedocs.io.
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All authors Shy Genel, Yongseok Jo, Boon Kiat Oh, Megan Taylor Tillman, Max E. Lee, Jun-Young Lee, Elena Hernández-Martínez, Christopher C. Lovell, Xavier Sims, Blakesley Burkhart, Kentaro Nagamine, Daniel Anglés-Alcázar, Francisco Villaescusa-Navarro
Exactly Solvable and Integrable Systems
Noncommutative NLS systems: Darboux–Bäcklund transformations and integrable discretisations
Sotiris Konstantinou-Rizos
We study noncommutative analogues and integrable discretisations of nonlinear Schrödinger (NLS)-type systems associated with reduction groups. In particular, we consider the Ablowitz–Kaup–Newell–Segur (AKNS) system, the Kaup–Newell derivative NLS system, and the Mikhailov–Shabat–Yamilov deformation of the derivative NLS system together with their Darboux–Bäcklund transformations and associated
lattice equations. We derive the continuum limits of previously constructed integrable
lattice systems and recover the corresponding NLS-type partial differential equations. We then construct a noncommutative deformation of the Mikhailov–Shabat–Yamilov system and show that, unlike the AKNS and Kaup–Newell cases, its Lax representation requires the introduction of nonlocal variables. Furthermore, we derive Darboux–Bäcklund transformations and integrable discretisations for the noncommutative derivative NLS and deformation derivative NLS systems in the form of vertex–bond
lattice equations. We also construct explicit solutions for a six-point derivative NLS-type
lattice equation and for its noncommutative analogue.
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Astrophysics of Galaxies
Learning the Universe at High Redshifts: Impact of Accretion Modeling on Early Black Hole Growth
Jonathan Kho, Aklant K. Bhowmick, Rainer Weinberger et al. (+8 more)
JWST discoveries of the earliest ($z \gtrsim 9$) supermassive black holes (BHs, $M_\bullet \gtrsim 10^6\,\rm{M}_\odot$) challenge the BH seeding and
accretion models of most cosmological simulations. In this work, we compare early BH growth arising from three different
accretion prescriptions characterized by distinct scalings between the
accretion rate ($\dot{M}_{\rm \bullet}$) and the BH mass ($M_{\rm \bullet}$): the commonly used Bondi-Hoyle model ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^2$), and two free-fall models with shallower scalings ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^{1/2}$ and $M_{\rm \bullet}$). Bondi
accretion tends to produce stronger runaway growth than the free-fall models when using heavy ($\sim10^5\,\rm{M}_\odot$) seeds in extreme environments owing to the steeper $M_\bullet$ scaling, but its sensitivity to the local gas sound speed makes it more susceptible to suppression from temperature increases due to AGN and
stellar feedback. The free-fall models tend to produce stronger growth for lower-mass seeds ($\sim10^{3-4}\,\rm{M}_\odot$) in moderate environments as they are less dependent on the BH's mass to accrete effectively, however in this regime BH growth remains negligible for all
accretion models in the presence of fiducial
stellar feedback. Enhancing early BH growth via many BH-BH mergers disproportionately enhances subsequent
accretion-driven growth for Bondi due to the steeper $M_{\rm \bullet}$ dependence. Our simulations can thus assemble BHs with masses of $\sim10^6-10^7~M_{\odot}$ at $z\gtrsim9$, as inferred by JWST, under two circumstances: 1) abundant heavy-seed formation that drives BH-BH mergers, or 2) Bondi
accretion with weak feedback.
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All authors Jonathan Kho, Aklant K. Bhowmick, Rainer Weinberger, Paul Torrey, Laura Blecha, Lars Hernquist, Greg L. Bryan, Alex M. Garcia, Niusha Ahvazi, Alejandro Saravia, Boon Kiat Oh
Chemical Physics
Electron Paramagnetic Resonance Study of Radical Species on NaNbO3@CeO2-Modified Carbon Vulcan XC72 Gas Diffusion Electrode for Electrochemical Degradation of Paracetamol via Electro-Fenton
Caio Machado Fernandes, Joao Paulo C. Moura, Aline B. Trench et al. (+4 more)
While electrochemical oxidation is a promising technology for water treatment, a fundamental understanding of the specific radical mechanisms involved in pharmaceutical degradation has remained limited. This study addresses this gap by employing Electron Paramagnetic Resonance (EPR) spectroscopy to directly quantify the radical species generated during the degradation of paracetamol using a novel gas
diffusion electrode (GDE) modified with NaNbO3 nanocubes and CeO2 nanorods. This approach provides a critical advancement beyond prior literature by moving from indirect inference to direct, quantitative analysis of reactive species. Results demonstrated that a boron-doped diamond (BDD) anode (65% OH radical, 35% aryl radicals) drastically outperformed a Platinum (Pt) anode (74% OH radical, 26% aryl radicals), achieving complete degradation in 15 minutes versus 45 minutes and 81.6% versus 67.8% mineralization. Consequently, this work provides a foundational mechanistic framework that fundamentally advances the field, offering not just a more effective material system (BDD/NaNbO3@CeO2-GDE) but also a validated methodology for rationally designing and optimizing electrochemical water treatment processes based on quantifiable radical pathways.
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All authors Caio Machado Fernandes, Joao Paulo C. Moura, Aline B. Trench, Rafael Sotana, Ana Maria P. Neto, Willy G. Santos, Mauro C. Santos
Adaptation and Self-Organizing Systems
Collective drift and pinning in active rotator networks with Kuramoto coupling and mixed-sign feedback disorder
Arpan Dey
Active rotator models provide a minimal phase description of excitable and oscillatory systems and have long been used to study mutual entrainment, synchronization, and collective transitions. In this paper, we investigate fully connected active rotator networks with Kuramoto coupling, where a common positive intrinsic drive competes with local feedback amplitudes drawn from a zero-mean Gaussian distribution. We characterize the dynamics using the mean absolute late-time drift, the polar and nematic order parameters, and the fractions of positive and negative drifting oscillators. The model with an even mixed-sign feedback ensemble has an exact discrete
symmetry under a simultaneous phase shift by $\pi$ and reversal of the feedback amplitudes. This exposes two physically distinct low-drift states: at weak coupling and strong disorder, local pinning produces an approximately antipodal, nematically ordered population, whereas at strong coupling the system can form a polar, coherently pinned state. A self-consistent stationary mean-field theory determines the existence edge of a nonzero coherent branch, provides quantitative predictions for the polar and nematic order, and shows that the coherent branch followed here is fully pinned. Sustained negative drift is impossible in a stationary mean field; the negative-drift population observed is instead localized to an intermediate-coupling regime characterized by a non-stationary mean field. Finally, finite-size extrapolations show persistent coupling-induced drift recovery and are compatible with vanishing strong-coupling drift at large disorder in the thermodynamic limit. These results show that even with a homogeneous intrinsic drive, mixed-sign local feedback can generate distinct regimes of drift, pinning, and collective phase organization.
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Cosmology and Nongalactic Astrophysics
Learning the Universe: Constrained simulations of the Coma galaxy cluster – I. Radial X-ray and Compton-y signatures
Ulrich P. Steinwandel, Stuart McAlpine, Richard Stiskalek et al. (+7 more)
We present a suite of 50 high-fidelity simulations of Coma cluster analogues constructed from BORG/MANTICORE constrained initial conditions and evolved with the IllustrisTNG
galaxy formation model. Regions predicted to form massive clusters comparable to Coma in mass and environment are selected and followed through
cosmic time, producing realistic
galaxy populations and intracluster medium properties. The ensemble captures both
cosmic variance and uncertainties in the local initial conditions, providing a statistically robust framework for interpreting Coma in a cosmological context. We focus on direct comparisons with observed thermodynamical profiles of the intracluster medium. Specifically, we extract X-ray surface brightness profiles from the simulated clusters and confront them with measurements from eROSITA, as well as compute the thermal Sunyaev–Zel'dovich effect via integrated Compton-$y$ profiles for comparison with Planck satellite data. The simulations reproduce the broad shape and normalisation of both observables, while also highlighting the range of scatter expected from environmental and assembly history differences. This enables us to assess how feedback processes, merger activity, and large-scale environment shape observable cluster properties. Our results demonstrate that combining constrained cosmological initial conditions with state-of-the-art
galaxy formation physics provides an effective strategy for generating targeted, observation-driven analogues of specific clusters. The resulting
dataset offers a valuable resource for testing models of intracluster medium physics, calibrating scaling relations, and interpreting upcoming joint X-ray and Sunyaev–Zel'dovich observations of nearby massive clusters.
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All authors Ulrich P. Steinwandel, Stuart McAlpine, Richard Stiskalek, Rüdiger Pakmor, Volker Springel, Eugene Churazov, Ildar Khabibullin, Jens Jasche, Guilhem Lavaux, Greg L. Bryan
Astrophysics of Galaxies
Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations
Laura Sommovigo, Deaglan J. Bartlett, Rachel K. Cochrane et al. (+3 more)
Dust attenuation is a major source of systematic uncertainty in both SED fitting and forward modeling of
galaxy populations, yet the functional form used to parameterize attenuation curves has received surprisingly little systematic scrutiny. Particular unanswered questions include: how many free parameters are genuinely needed, and which analytic expression best captures the full diversity of attenuation curve shapes in
galaxies across
cosmic time? Using a large library of synthetic attenuation curves from TNG50 and TNG100
galaxies post-processed with the SKIRT radiative transfer code using three
dust mixtures (Milky Way, SMC, and
stellar dust), we show via Information-Ordered Bottleneck analysis that exactly four parameters are needed to capture the diversity of attenuation curves. Guided by this result, we use symbolic regression to derive a new, interpretable four-parameter attenuation model that outperforms existing parameterizations in recovering both attenuation curves and emergent fluxes across all
dust mixtures explored. The four parameters of this model have clear physical interpretations: UV bump strength, FUV slope, UV-bump transition
curvature, and large-scale optical slope. Their correlations with
galaxy properties are primarily regulated by
star-formation rate surface density,
metallicity, and
stellar-
dust geometry, and are largely preserved across
dust mixtures – except for the bump-sensitive parameters, which retain a stronger dependence on grain composition. We further provide symbolic-regression scaling relations linking all four parameters to quasi-observable
galaxy properties, offering a physically motivated route to assign realistic attenuation curves in SED fitting and forward modeling without radiative-transfer calculations.
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All authors Laura Sommovigo, Deaglan J. Bartlett, Rachel K. Cochrane, Matthew Ho, Christopher C. Lovell, Rachel S. Somerville
Astrophysics of Galaxies
Pressure-regulated feedback-modulated star formation as a subgrid model for galaxy formation simulations
Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim et al. (+1 more)
We present a new subgrid model for interstellar gas
evolution in cosmological simulations of
galaxy formation, based on the pressure-regulated, feedback-modulated (PRFM) theory of
star formation. In contrast to the empirically pegged
star formation prescriptions employed in current cosmological simulations, the PRFM model links the local
star formation rate to the dynamic balance achieved in
galactic interstellar gas between
gravity and
stellar feedback effects. With this formulation, both the
star formation efficiency and the effective equation of state may be directly calibrated using numerical simulations, such as TIGRESS, which resolve physics of the interstellar medium and
star formation at parsec scales. We develop, and implement in the Arepo moving-mesh code, two complementary classes of the subgrid model: a volumetric version (PRFM-vol) applicable when the gas disk scale height of a
galaxy is numerically resolved in a simulation, and an integrated version (PRFM-int) that reconstructs the mid-plane density and pressure from vertical
equilibrium considerations when the true gas scale height cannot be numerically resolved. Using isolated Milky-Way-like disk simulations across mass resolutions $10^5$-$10^7~{\rm M}_\odot$, we show that both implementations yield shorter gas depletion times than the IllustrisTNG prescription, especially in regions where pressure and density are large. At high resolution, PRFM-vol and PRFM-int agree closely with each other and with TIGRESS for the
star formation rate; PRFM-int remains robust at all resolutions tested. These results demonstrate that PRFM-derived subgrid prescriptions provide a physically grounded and numerically stable framework for
star formation across the dynamic range of
galaxy formation simulations, paving the way for future cosmological applications.
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All authors Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jan Burger
Cosmology and Nongalactic Astrophysics
Learning the Universe with cosmological rescaling of merger trees and semi-analytic galaxy formation models
Richard Stiskalek, Lucia A. Perez, Shy Genel et al. (+3 more)
Learning cosmology from
galaxy surveys requires large suites of simulations spanning the cosmological and astrophysical parameter space, yet hydrodynamical simulations of
galaxy formation remain prohibitively expensive. Semi-analytic models offer an inexpensive, physically grounded alternative, but still require
halo merger trees from $N$-body simulations, and densely sampling cosmological parameters in sufficient volume remains expensive. We address this by extending cosmological rescaling to operate directly on merger trees and applying it in the $\Omega_{\rm m}$-$\sigma_8$ plane, running the Santa Cruz semi-analytic model for
galaxy formation on the rescaled trees to produce
galaxy populations across new cosmological and astrophysical parameters at negligible additional cost. A novel
halo-profile-based correction, controlled by a single free parameter, suppresses systematic bias in rescaled
halo masses to below the per cent level. We apply the method to parameter estimation of $\Omega_{\rm m}$ and $\sigma_8$ given either the
stellar mass function or the two-point correlation function, finding that as few as 64, and potentially fewer, base $N$-body simulations, rescaled to $\sim1000$ training samples, match the accuracy of 750 dedicated $N$-body simulations; rescaling to 3200 realisations improves the prediction of $\Omega_{\rm m}$ by $\sim25\%$. Rescaling all merger trees from a single CAMELS-SAM $N$-body simulation costs $\sim0.1$ CPUh, compared to several thousand CPUh to run the simulation itself. We demonstrate a practical route to obtaining predictions of
galaxy summary statistics across cosmological and astrophysical parameters, even with a relatively small number of base $N$-body simulations.
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All authors Richard Stiskalek, Lucia A. Perez, Shy Genel, Rachel S. Somerville, Raul E. Angulo, Sergio Contreras
Cosmology and Nongalactic Astrophysics
Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions
Ludvig Doeser and Jens Jasche
Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data. While Markov chain Monte Carlo methods provide asymptotic convergence guarantees, they are computationally demanding in high-dimensional settings. Neural network-based generative models for entire discretized 3D fields enable fast amortized inference but often lack convergence guarantees and principled accuracy assessment. Using
Hamiltonian Monte Carlo to obtain reference posterior samples, we conduct a controlled field-level evaluation of an implicit generative model (
Stochastic Interpolants) and an explicit likelihood-based model (GLOW normalizing flows). This comparison, unavailable in typical applications, enables the detection of posterior geometry failures that standard metrics cannot capture. As a case study, we consider the cosmological inverse problem of inferring
cosmic initial conditions from present-day large-scale structure. To match the precision of modern cosmological data, this problem increasingly relies on complex, non-linear, and non-differentiable simulators, which are incompatible with gradient-based inference frameworks. Generative models offer a route to address these challenges, provided their inferred posteriors are reliable. In this work, we show that matching posterior means, marginal distributions, or achieving high cross-correlation does not imply correct uncertainty structure, as revealed by posterior variance fields and sample-based evaluations. Through this work, we aim to raise awareness of the challenges of uncertainty estimation in high-dimensional field-level settings, highlighting the importance of careful design and validation of neural generative approaches for scientific applications.
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Astrophysics of Galaxies
Learning the Universe with PRFM-vol: Introducing a new subgrid model for star formation in cosmological simulations
Jan D. Burger, Volker Springel, Eve C. Ostriker et al. (+7 more)
We introduce PRFM-vol, a new subgrid model for
star formation in cosmological simulations that aims to increase the physical realism of cosmological simulations by leveraging results obtained with focused ISM simulations. We deploy a modified effective equation of state and calculate the
star formation rate for each gas
cell as a function of the ambient densities of gas, dark matter, and
stars, based on the pressure-regulated feedback-modulated (PRFM) theory of
star formation. Test simulations of our model in isolated
galaxies show that we match PRFM predictions and TIGRESS scaling relations remarkably well, provided sufficiently high resolution is available. In particular, we are able to clearly demonstrate the impact of the
stellar potential on the
star formation rate, thereby retaining an important prediction of PRFM. We then apply our new model to cosmological multizoom simulations and find, compared to our previous TIGRESS/Schmidt model, a significant increase in the
stellar scale heights and a slight increase in
stellar mass. We demonstrate that modifying the effective equation of state significantly affects the morphology of simulated
galaxies. Pronounced
stellar clumps appear if the effective pressure at low hydrogen number densities is low, and disappear for higher pressure. We show that the formation of clumps is a result of Toomre instabilities, and conclude that simulated
galaxy morphologies can be used to constrain effective equation of state models. Overall, our results establish PRFM-vol as a new self-consistent, physics-motivated subgrid model for
star formation in high-resolution cosmological simulations.
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All authors Jan D. Burger, Volker Springel, Eve C. Ostriker, Chang-Goo Kim, Ulrich Steinwandel, Matthew C. Smith, Lars Hernquist, Greg L. Bryan, Rachel S. Somerville, Alon Gurman
Cosmology and Nongalactic Astrophysics
The Manticore Project II: Bayesian digital twins of cosmic structure across the SDSS and BOSS volumes
Stuart McAlpine, Jens Jasche, Guilhem Lavaux et al. (+2 more)
We present Manticore-Deep, a high-resolution
Bayesian field-level reconstruction of
cosmic large-scale structure over a comoving volume of $(4~h^{-1}\mathrm{Gpc})^{3}$ to $z\approx0.7$ at ${\sim}4$~Mpc/h resolution. Extending the companion Manticore-Local analysis (Paper~I), Manticore-Deep jointly constrains five
galaxy redshift surveys within a single hierarchical
Bayesian framework using the BORG
algorithm. The inference reconstructs
primordial initial conditions evolved under
gravity, yielding a posterior ensemble of three-dimensional density and velocity fields that causally reproduce the observed large-scale structure. A novel tiled inference strategy extends the reconstructed volume by more than an order of magnitude beyond Paper~I. Posterior realisations are consistent with LCDM, reproducing Gaussian isotropic initial conditions and the expected $z=0$ matter power spectrum, bispectrum, and
halo mass function over the resolved scales. We validate the reconstruction using two independent template-free posterior-predictive tests against observations excluded from the inference. Cross-correlation with the Planck PR3 CMB
lensing map yields a cumulative detection significance of 7.4 $\sigma$, while velocity-weighted stacking of $64{,}750$
galaxy clusters on the Planck 217~GHz map detects the kinetic Sunyaev–Zel'dovich effect at $3.5\sigma$, with a model-independent approach–recession split confirming the inferred velocities. Together, these tests validate both the projected-density and three-dimensional velocity fields recovered by Manticore-Deep. The BOSS Great Wall is recovered as a ${\sim}3\sigma$ overdensity consistent with LCDM across the posterior ensemble. Manticore-Deep establishes a
benchmark for survey-depth constrained cosmological digital twins and reproducible field-level validation of large-scale structure reconstructions.
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All authors Stuart McAlpine, Jens Jasche, Guilhem Lavaux, Ludvig Doeser, Arthur Loureiro