Papers

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Physics

Friday 28 August

Mesoscale and Nanoscale Physics

Subcritical bifurcation and on-off bistability in ballistic polariton condensates

Oleg I. Utesov, Soohong Choi, Pavel Kozhevin et al. (+11 more)

Dynamics of exciton-polariton condensates under continuous-wave incoherent Gaussian optical pumping is considered. It is shown that the conventional supercritical Stuart-Landau picture is invalid in a certain domain of the parameter space. For strong polariton repulsion from the reservoir and relatively small pump spots, the dynamics is adequately described by the quintic Stuart-Landau equation. The corresponding subcritical pitchfork bifurcation leads to condensate formation, accompanied by bistability between the trivial and nontrivial states over a finite pump-power range and a one-bit memory. Further increase of the repulsion parameter or decrease of the spot size breaks down the perturbative approach and leads to a peculiar self-trapping regime with complex dynamics. Experimental evidence of the emergence of the proposed behavior is provided. Our findings can be used to design polaritonic setups that exploit the predicted memory effect.

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All authors Oleg I. Utesov, Soohong Choi, Pavel Kozhevin, Min Park, Daegwang Choi, Hyungdo Lee, Alexey N. Osipov, Alexey V. Yulin, Se Kwon Kim, Yong-Hoon Cho, Igor S. Aranson, Hyoungsoon Choi, Anton V. Nalitov, Sergei V. Koniakhin

Chemical Physics

Resolving Spin-Phonon Relaxation Pathways in Molecular Qubits via Regularized Regression

Sayan Banerjee

Designing molecular qubits requires controlling the spin-lattice relaxation pathways that fundamentally limit the coherence time. For spin-1/2 molecular qubits, significant discrepancies remain between theoretical predictions and experimental measurements of spin-phonon relaxation pathways, with theory often overestimating the role of low-frequency vibrational modes. Here, we present an alternative first-principles approach augmented with regularized regression that identifies spin-phonon relaxation pathways in an automated fashion without ad hoc mode selection. Applied to Cu porphyrins spin-1/2 molecular qubits, the method successfully reproduces experimental trends in relaxation times and predicts the curvature in the relaxation-vs-temperature profile. The g-tensor time series reveal distinct system-specific autocorrelation functions and spectral-density profiles despite the qubits' structural similarity. Further, regression between g-tensor time series and mode-projected vibrational-amplitude time series obtained from molecular dynamics yields linear and bilinear mode coupling contributions to each g-tensor component. Because the method is based on atomic displacements sampled directly from molecular dynamics, it naturally incorporates anharmonic effects and does not require the harmonic approximation. This framework puts forward a regression-driven, mode-resolved, and coupling-order-separated spin-phonon analysis as a general strategy for predicting and engineering longer-lived molecular qubits.

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Mathematical Physics · Cross-listed from math.AP

The asymptotic structure of forward scattering

Nicholas Lohr, Izak Oltman, Ethan Sussman et al. (+1 more)

Perturbed plane waves are fundamental objects in scattering theory on Euclidean space and asymptotically Euclidean spaces. In this paper, we investigate the structure of perturbed plane waves in the $\textit{forward}$ direction, in which the outgoing spherical wave is typically singular and conjoined to the incoming plane wave. Melrose & Zworski provided a microlocal description (in the more general setting of asymptotically conic manifolds) using their notion of Lagrangian distributions associated to pairs of intersecting Legendrian submanifolds, on the way to proving that the S-matrix is an FIO. Here, we revisit the problem in the asymptotically Euclidean case, for which the oscillatory integrals used by Melrose–Zworski attain their most complicated form (relative to the more general asymptotically conic case). We seek a more elementary description in terms of physical-space asymptotics. These are specified using a two-faced compactification $X\hookleftarrow \mathbb{R}^d$, with one face for each asymptotic regime. We prove full polyhomogeneity. A transport equation arises as a model problem at the main face (`bf'). The quantum inverted harmonic oscillator arises as a model problem at the front face (`ff').

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All authors Nicholas Lohr, Izak Oltman, Ethan Sussman, Yuzhou Joey Zou

Instrumentation and Detectors

Migration of Belle II TOP Feature Extraction from the Zynq Processing System to PCIe40 Readout PCs

Harsh Purwar, Shahab Kohani, Vasily Shebalin et al. (+11 more)

The Belle II Time-of-Propagation (TOP) detector is a key system for charged-particle identification (PID). Although TOP operated successfully during initial Belle II data taking, increasing luminosity and beam-induced background led to more frequent single-event upsets (SEUs) in the radiation-exposed Zynq systems-on-chip (SoCs). Resulting lockups of the embedded processing systems (PSs) interrupted data acquisition. To mitigate this limitation, waveform feature extraction, a critical task of the on-detector Zynq PS, was migrated to the off-detector PCIe40 readout PCs (ROPCs). The new architecture bypasses the PS in the event data path and performs feature extraction outside the detector radiation environment. This change removed SEU-induced PS lockups from the event data path and enabled stable operation of the TOP front-end electronics and the Belle II data-acquisition system under increased luminosity and background conditions. The typical TOP deadtime decreased from about 1% to a level consistent with zero after the final firmware patch, and stable operation was demonstrated at a Level-1 (L1) trigger rate of 30 kHz with a microchannel-plate photomultiplier-tube (MCP-PMT) hit rate of approximately 5 MHz per PMT. This paper describes the migrated architecture, its deployment and validation, and its operational and PID performance.

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All authors Harsh Purwar, Shahab Kohani, Vasily Shebalin, Martin Bessner, Matt Andrew, Thomas Browder, Tommy Lam, Kurtis Nishimura, Sourav Patra, Vladimir Savinov, Marko Staric, Gary Varner, Satoru Yamada, Keisuke Yoshihara

Materials Science

Compositionally Complex Ceramics (CCCs): A New Paradigm in Ceramics

Jian Luo

The development of high-entropy ceramics (HECs) over the past decade has extended the exploration to a diverse range of oxides, borides, silicides, carbides, nitrides, fluorides, and other ceramic solid solutions, encompassing an increasingly broad range of crystal structures and bonding characteristics and exhibiting promising mechanical, thermal, and functional properties. Initial studies predominantly focused on five-component equimolar compositions. In 2020, we proposed extending the exploration beyond HECs to the broader class of "compositionally complex ceramics" (CCCs), in which rational non-equimolar compositional designs and long- and short-range order can reduce configurational entropy while providing additional opportunities to tailor and enhance materials properties, with the goal of outperforming their higher-entropy counterparts. Because CCCs have been defined somewhat vaguely in previous publications, this review seeks to establish more rigorous and explicit criteria for defining CCCs, despite the unavoidable degree of arbitrariness in the choice of thresholds. Meanwhile, 10-21-component ultrahigh-entropy ceramics have emerged as a subset of HECs, exhibiting intriguing abrupt phase transitions. Dual-phase CCCs have also been reported, with thermodynamic equilibria governing cation partitioning between the two phases. Recent studies have further revealed that grain-boundary complexion (phase-like) transitions can occur in CCCs, influencing microstructural evolution and materials properties. Overall, CCCs provide a versatile platform for tailoring materials properties through the interplay of diverse crystal structures and bonding characteristics, compositional complexity, rational non-equimolar designs, long- and short-range order, defects, and microstructural and interfacial engineering.

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High Energy Physics (Phenomenology)

Future of Artificial Intelligence for Science in Japan 2024 Community Report

Yoshitaka Itow, Jia Liu, Hirokazu Maesaka et al. (+16 more)

This white paper summarizes scientific challenges and AI/ML research opportunities identified through the FAIRS Japan 2024 unconference process. The discussion focuses on three major physics domains: accelerator physics, cosmology and astrophysics, and neutrino physics. Although each domain has distinct scientific goals and experimental constraints, several common technical themes emerge: high-dimensional reconstruction, fast and accurate simulation, uncertainty propagation, simulation-to-data mismatch, anomaly detection, real-time decision-making, and shared infrastructure.

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All authors Yoshitaka Itow, Jia Liu, Hirokazu Maesaka, Vinicius Mikuni, Nhat-Minh Nguyen, Hironao Miyatake, Atsushi J. Nishizawa, Patrick de Perio, Daniel Ratner, Kazuhiro Terao, Leander Thiele, Omar Alterkait, Francois Drielsma, Rocio Garcia, Masako Iwasaki, Ahsani Hafizhu Shali, Federica Tarsitano, Takahiro Terada, Junjie Xia

Chemical Physics

OrbGNN: A Wave function-based Machine Learning Interelectronic Representation

Brody Quebedeaux, Shahzad Akram, Markus Reiher et al. (+1 more)

Machine learning interatomic potentials (MLIPs) have become emerging tools in molecular modeling and computational chemistry. By learning high-dimensional potential energy surfaces from quantum chemical data, MLIPs enable accurate and efficient predictions of structural, thermodynamic, and dynamical properties. However, such models have limitations in predictions of electronic properties and the effects of static electron correlation due to their lack of electronic structure information. This work presents OrbGNN, an electronic structure graph architecture analogous to molecular graph and MLIP frameworks, where pair-orbital interactions constitute the graph representation, while orbital entanglement encodes the connectivity between them. By embedding information derived from orbital correlation metrics directly into the graph topology, OrbGNN provides a compact representation of a molecule s orbital landscape and electron correlation patterns. Analysis of the behavior of the feature space in an orbital graph are shown to demonstrate model robustness. The model is evaluated for the dissociation of nitrogen and for a larger dataset of diatomic molecules. Finally, the OrbGNN model is applied to a set of octahedral iron(II) complexes to predict spin-state energy gaps.

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All authors Brody Quebedeaux, Shahzad Akram, Markus Reiher, Konstantinos D. Vogiatzis

High Energy Physics (Theory)

Seiberg dualities for quiver gauge theories

Yuanyuan Fang, Jing Feng and Dan Xie

We study Seiberg duality for quiver gauge theories with fundamental, bifundamental, and rank-two tensor matter. The existence of a Seiberg dual description places strong constraints on the spectrum of undressed mesons, which is naturally encoded in a factorization equation for the matrix Hilbert series. We derive this factorization from a closed-form large-$N$ superconformal index for general quiver gauge theories with these matter contents. We apply the method to two-node quivers and recover known $SU$–$SU$ and $SO$–$USp$ product-group dualities. We also discuss finite-$N$ consistency conditions from anomaly and operator-spectrum matching.

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Solar and Stellar Astrophysics

Quiescent and Interacting Compact Remnant Binary Populations in the Space Telescope Era

Erin Eastep, Jan J. Eldridge and J. C. Bray

Since the discovery of Gaia BH1, interest in quiescent binary systems has grown. Two additional black-hole binaries have since been discovered alongside several candidate neutron-star binaries, yet the formation pathways of these systems remain poorly understood. Theoretical studies of these systems, together with the populations into which they evolve, such as X-ray binaries (XRBs), can help constrain their formation channels. We present predictions for the Galactic population of quiescent binary systems and their later evolutionary phases, including XRBs and post-interaction quiescent binaries. We combine stellar models from the Binary Population and Spectral Synthesis code (BPASS) with a synthetic Milky Way generated using Feedback In Realistic Environments (FIRE) simulations. We compare our results with existing observations to assess how well the synthetic population reproduces the observations. We find generally good agreement, with observed donor masses, compact-object masses, and orbital periods largely reproduced, except for the Gaia BH systems. Our results also suggest that some accreting compact remnants with low-mass donors and wide orbital periods may not be X-ray bright. Remaining discrepancies indicate that the BPASS initial parameter space should be expanded, the common-envelope evolution prescription revised, and magnetic braking included in low-mass donor models. We also predict the number of systems detectable in future Gaia data releases and by the Nancy Grace Roman Space Telescope (hereafter referred to as Roman). In particular, the Galactic Bulge Time Domain Survey is expected to yield a significant population of quiescent black-hole binaries. We predict that ~200-600 candidate quiescent binary systems will be detected in the Galactic Bulge Time Domain Survey, while ~2500-4000 candidate systems will be identified in Gaia DR5.

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Thursday 27 August

Instrumentation and Detectors

The efficiency of moderating neutron detector: Monte Carlo simulation, experimental validation, and angular dependence

Carl R. Brune

This paper describes the Monte Carlo simulation and experimental validation of the neutron detection efficiency in a 4pi polyethylene moderating detector. The experimental validation was performed using several sources providing neutron energies from 10s of keV up to 14 MeV. The Monte Carlo simulations employed the MCNP6 code are believed to be accurate within 3% for neutron energies below 6 MeV. A new method for parametrizing the dependence of the efficiency on the neutron angular distribution for in-beam experiments is also presented. This approach utilizes a Legendre decomposition of the efficiency and allows all of the needed information to be extracted from a single simulation.

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Medical Physics · Cross-listed from cs.AI

PEEL: Physics-Enabled Evidential Learning for Identifiable Uncertainty in CT Imaging

Ge Wang

Normal-inverse-gamma (NIG) regression is not uniquely identifiable from its marginal Student-t likelihood: the likelihood determines three combinations of four NIG parameters and is constant along a one-dimensional fiber. We identify that fiber using independent physical measurement. As an initial embodiment, a reconstruction network receives one noisy filtered-backprojection (FBP) image and is first trained only by Student-t negative log-likelihood to estimate the three identifiable coordinates (gamma, alpha, c). The network is then frozen; repeated physical-noise realizations propagated through its reconstruction output form a Monte Carlo (MC) teacher label for output-domain aleatoric variance. An aleatoric head attached to frozen features learns this label, after which (beta, nu) are recovered algebraically. On 30 held-out simulated objects at five photon levels, one-image predictions achieved pooled Spearman correlations of 0.832-0.951 against independent 400-repeat references, median within-image correlations were 0.834-0.947, and 98.81-99.55% of evaluated pixels satisfied the algebraic admissibility condition. The method needs no KL term, reference prior, evidence regularizer, or cross-loss weight.

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Materials Science

Building Atomic Structures from Natural Language

Pai Li

Large language models can write the input parameters of a materials simulation from a prompt, but they cannot build the atomic structure those parameters describe. A crystal, a surface slab or a mismatched interface must satisfy global constraints-periodicity along specific axes, a given vacuum thickness, a commensurate registry, sensible bond lengths. Generation one token at a time enforces none of them, and a violation is invisible in the output. We present ATLAS, a framework that makes structural construction scriptable. Seven components-analyzer, LLM skill, JSON format, build engine, validator, scorer and web interface-are organized around a component algebra of named structures and spaces. Every specification carries a check list, so a build is verified against the request rather than merely parsed from it, and builds are scored against the user's intent. Requests state physical sizes, and the engine computes the replication that reaches them. The translation is the one stochastic stage, and it is recorded, so a run replays with the model held fixed-which is what makes the framework's own behaviour measurable rather than merely observed. Fourteen structural classes are demonstrated, from bulk cells and nanoparticles through surfaces, defects and interfaces to amorphous networks and liquids. We outline how the same loop generates training sets for machine-learning force fields.

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High Energy Physics (Theory)

Unification of Einstein Gravity with Internal Interactions

S. Stefas and G. Zoupanos

The gauge-theoretic formulation of gravity, enriched with the observation that the tangent group of a curved manifold need not have the same dimension as the manifold itself, provides a natural framework for unifying gravity with internal interactions. In the present work we study the unification of Einstein gravity with the $SO(10)$ grand unified theory within an $SO(1,17)$ gauge theory. As a central result, we derive Einstein gravity with a cosmological constant from the spontaneous symmetry breaking (SSB) of an $SO(1,5)$ gauge theory to the Lorentz group via two independent routes: one using two scalar fields in the fundamental representation $\mathbf{6}$ of $SO(6)$, and one using a single scalar in the adjoint $\mathbf{15}$. Both yield a Gauss-Bonnet + Einstein-Hilbert + cosmological constant action. Embedding the $SO(1,5)$ gravitational sector in $SO(1,17)$ and breaking the full gauge group yields Einstein gravity coupled to $SO(10)$. The Weyl-Majorana condition reduces the fermion family degeneracy to two, in contrast to the four families obtained in the $SO(2,16)$ conformal gravity unification.

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Quantum Physics

Localizable Bipartite Rank-One Ideal Measurements Have a Block-Replicated Nice-Bell Structure

Ahmed Younis

We prove a complete structural characterization of finite-dimensional bipartite rank-one ideal projective measurements that are localizable without communication in the sense of Akibue and Miyazaki. Up to local-unitary equivalence, every such measurement basis is obtained by replicating a single nice Bell basis across equal-dimensional local subspace blocks. The necessity proof combines the causal block structure of complete measurements established by Beckman, Gottesman, Nielsen, and Preskill with their eigenstate-composition theorem for localizable superoperators. A reference block is first forced to be a nice Bell basis; the same theorem then propagates that basis consistently along every row, column, and interior block. The converse follows from the explicit localization protocol of Akibue and Miyazaki. This establishes their Conjecture 1 and gives a protocol-independent classification of bipartite rank-one ideal measurements in this setting.

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Instrumentation and Detectors · Cross-listed from eess.SP

A Nonuniform-Sampling Theory for Static Multi-Threshold Sampling

Ao Qiu and Qingguo Xie

Multi-Threshold (MT) sampling fixes voltage levels and records when a waveform crosses them. The resulting signal-generated event stream is governed not by a prescribed clock but by the nonuniform geometry of the realized crossing set. Within classical nonuniform sampling, we develop a retained-event MT theory for static, uniformly spaced thresholds. For a realized retained MT time set, Beurling's weak-limit theorem gives the exact necessary-and-sufficient condition for stable sampling of $PW_\Omega$. For a fixed signal class, the same principle gives the a priori criterion: uniform stable MT sampling is equivalent to Bernstein uniqueness for every set in the class weak-limit hull. This criterion reduces to computable forms under structured priors. Periodic templates give finite fiber/rank tests, periodic-gap streams give a Shannon-type complete-interpolation boundary and a stable-sampling density rule, and finite-state gap priors reduce noncritical certification to a maximum-cycle-mean condition. Kadec-type local certificates, retained-density bounds, and finite-matrix tests provide practical sufficient conditions for finite active records, while conditional perturbation bounds quantify how jitter, front-end noise, and threshold error consume a clean sampling margin under event correspondence. The theory also identifies the unavoidable boundary of this model: unrestricted finite-energy retained MT records have zero full-line lower Beurling density and therefore cannot provide a universal prior-free sampling theorem for $PW_\Omega$. Within retained-event point sampling, the MT recovery question is resolved precisely: exact recovery is governed by event-set geometry, computable guarantees require structural priors or finite-dimensional/tail assumptions, and the unrestricted static finite-energy problem is impossible.

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Quantum Physics

Every architecture of six two-qubit gates is locally universal on three qubits

Hyunho Cha and Jungwoo Lee

We present the first analytical determination of the exact accessible dimension for every fixed architecture of arbitrary two-qubit gates on three qubits. A support word represents which pair of qubits each two-qubit gate acts on, and its reduced length is obtained by merging consecutive gates on the same pair. If the reduced length is $r$, then the set of implementable three-qubit unitaries has accessible dimension $d(w)=\min\{63,9r+9\}$. Consequently, six arbitrary two-qubit gates are necessary and sufficient for local universality: every fixed architecture reaches a nonempty open subset of $\mathrm{SU}(8)$ when its reduced length is at least six. The result is stronger than existence of one favorable architecture. Every reduced six-slot support word is locally universal, including the alternating nearest-neighbor line $AB,BC,AB,BC,AB,BC$. The upper bound follows from a standard parameter-counting argument. The matching lower bounds are proved by Jacobian certificates in the Pauli basis. Up to qubit relabeling and reversal, there are $22$ reduced architectures of lengths two through six. For each one, a product of rational Pauli rotations yields a nonzero maximal minor modulo the prime $1{,}000{,}003$. Thus, any obstruction to global universality with six two-qubit gates must go beyond parameter counting, connectivity, and differential rank.

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General Relativity and Quantum Cosmology · Cross-listed from math.DG

Spacetime closedness theorem for homogeneous Lorentzian foliations

Robert Monjo

Motivated by the geometric interpretation of spatially homogeneous cosmological models, we formulate a spacetime closedness theorem directly at the Lorentzian level. A classical space-form classification theorem organizes homogeneous and isotropic spatial geometries, but by itself it does not yield a Lorentzian statement about the ambient spacetime. The main technical step is to derive finite slice-volume from genuinely Lorentzian control hypotheses on the foliation. This is achieved in a strong version, for maximally regular globally hyperbolic $(n+1)$–spacetimes with a finite-time Big Bang and homogeneous complete spacelike slices, and in a weaker version in which maximal regularity is replaced by time-integrability of the accumulated expansion rate. In both cases, the argument separates an analytic step, deriving finite slice-volume from the Big Bang and temporal control, from a geometric step, upgrading finite volume to compactness by homogeneity and completeness. The theorem is stated in arbitrary spacetime dimension and is accompanied by a Lean~4 formalization of the strong and weak abstract statements.

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Chemical Physics

Molecular Transferability of a Noble-Gas Coordinate for Electronegativity Equalization

Megan Simons, Jonathan Washburn and Elshad Allahyarov

Charge-equilibration models predict how electrons redistribute over a molecule more cheaply than quantum chemistry, and each begins from a table of atomic electronegativities and hardnesses. A recent table replaces ionization energies and electron affinities with one geometric quantity: each main-group atom's fractional distance to the noble gas closing its row. Holding geometries, electrostatic damping and the molecule list fixed, we compare it with spectroscopic values, with its own kernel refitted, and with a quadratic control, over a primary set of fifty-two molecules and ions at the B3LYP/def2-TZVP level. Two structural consequences follow from the table construction rather than the equalization solver. Atoms at equal fractional distance receive identical electronegativities, so the dipole moments of chlorine monofluoride, iodine monobromide and sulfur dioxide vanish exactly, and the measured $0.72$ debye $\mathrm{HF}/\mathrm{HCl}$ gap is lost. Because the first period is excluded, hydrogen retains its spectroscopic electronegativity above every geometric value, reversing $\mathrm{O{-}H}$, $\mathrm{N{-}H}$ and hydrogen-halide polarity. Fitted alike, geometric and quadratic kernels agree to $0.0022$ electron per atom, so predictions are set by the fitted energy scales, not the kernel shape. Resolving the electronegativity scale period by period restores correct polarity in all five polyatomic heavy-atom-hydrogen tests.

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Chemical Physics

Scaling Neural Network Quantum States for Ab Initio Quantum Chemistry

Chenxi Yu, Hanlin Kong, Jianan Wei et al. (+4 more)

Neural-network quantum states (NNQSs) can represent many-electron wave functions without explicitly enumerating the determinant space, but their accuracy depends jointly on model size and variational-optimization effort. Here we characterize this dependence for a physics-conditioned autoregressive NNQS trained separately on two six-molecule source benchmarks. Across eight model sizes and five optimization milestones, we find that model size and optimization steps jointly shape the energy error. The capacity advantage of larger models becomes more apparent with sufficient optimization, while the returns from additional optimization vary with model size. We capture this coupling using an interaction scaling law and quantify the cumulative compute of each evaluated configuration. The resulting error-compute Pareto frontiers provide a practical decision rule for jointly selecting model size and optimization steps under a given compute budget within the evaluated range. Furthermore, we find that this beneficial scaling trend persists during fine-tuning on held-out N$_2$. Pretrained models show decreasing error with increasing model size, with a steeper reduction following pretraining on the Hard benchmark. Together, these results place autoregressive neural quantum states within the broader landscape of empirical neural scaling and open a quantitative route toward the systematic scaling of neural quantum solvers for ab initio quantum chemistry.

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All authors Chenxi Yu, Hanlin Kong, Jianan Wei, Lizhong Fu, Honghui Shang, Wenguan Wang, Jinlong Yang

Quantum Physics

Anticoncentration and entanglement in Gaussian boson sampling

Laura Shou, Adam Ehrenberg, Yu-Xin Wang et al. (+2 more)

Anticoncentration and entanglement are two properties used to study classical hardness or easiness of Gaussian boson sampling in varying regimes. In this paper, we consider three directions concerning anticoncentration and entanglement in Gaussian boson sampling: (1) We derive closed-form expressions for the second moment of hafnians of symmetric Gaussian products, and use this to precisely locate the anticoncentration transition as a function of the number of squeezed input modes. (2) We derive closed-form expressions for the Rényi-$\alpha$ Page curves for Gaussian boson sampling. (3) We study unequal input squeezing parameters $(s_i)_i$, and prove estimates as well as monotonicity of the average-case Rényi-2 entropy Page curve in terms of the magnitudes $|s_i|$, which allow for extending equal squeezing results to unequal squeezing.

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All authors Laura Shou, Adam Ehrenberg, Yu-Xin Wang, Joseph T. Iosue, Alexey V. Gorshkov

General Physics

Exploring thermodynamic and photonic properties of new black hole solutions in F(R) gravity theory

Mohsen Dehghani

We investigate black hole solutions in F(R) gravity within a four-dimensional spacetime, separately treating the cases of vanishing and nonvanishing energy momentum tensors. We demonstrate that in the absence of an energy momentum tensor, the number of independent equations is sufficient to obtain the Ricci flat solutions without the need for a prescribed F(R) function. In the same case, also the solutions with variable Ricci scalar can obtained too. Furthermore, for a nonvanishing energy momentum tensor, we derive exact solutions for both constant and variable Ricci scalars, thereby introducing new charged black holes. Utilizing this new method, we not only recover the general relativistic and previously known F(R) gravity solutions but also introduce four new classes of F(R) black holes. We calculate their thermodynamic quantities and confirm the validity of the first law of black hole thermodynamics. The thermal stability of these new black holes is analyzed using both thermodynamic and geometrical approaches. Finally, the photon spheres and black hole shadows are studied within the F(R) gravity framework.

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Physics and Society

Save 2050: A Planetary-Scale Collective Prediction System for the Singularity Crisis

Jiang Zhang, Bing Yuan and Qian Zhang

The Anthropocene mode of development is driving civilization toward a "singularity crisis": artificial intelligence (AI) is rapidly approaching general intelligence (AGI) with escalating risks of losing control, while unrestrained economic growth generates super-exponential growth of entropy production that pushes the Earth system toward its tipping points. This paper proposes the "Save 2050" initiative: a distributed planetary-scale collective prediction system that aggregates judgments about the future from humans and AI through open registration, crowdsourcing, and incentive mechanisms, and integrates them via large-scale simulation into inspectable "predicted worlds," enabling humanity to systematically see the future for the first time. We argue for the initiative's feasibility along four dimensions—the maturation of AI forecasting, human collective intelligence and the institutional environment, supporting progress in related fields, and societal demand. We then identify three key enabling technologies: long-horizon automated resolution, simulation-based prediction aggregation, and reflexivity governance. We analyze potential risks—including reflexivity, cognitive monoculture, narrative capture, and regulatory and ethical concerns—together with mitigation strategies, and we outline a phased roadmap with open problems. The initiative's primary goal is not to intervene in the future, but to make the future visible, discussable, and co-writable.

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Lattice Field Theory

Machine Learning Unveils Finite-volume Energy Shifts in Three-body System

Wei-Jie Zhang, Zhenyu Zhang, Jifeng Hu et al. (+3 more)

Finite-volume extrapolation (FVE) is essential for extracting physical observables in the lattice calculation. While rigorous FVE formulations are well established for short-range potentials in both two- and three-body systems, long-range interactions with force ranges comparable to the lattice size $L$ remain challenging. Extending a previous data-driven scheme for two-body systems, we apply symbolic regression (PySR) to uncover universal three-body FVE formulae. For short-range potentials, we reproduce the two limiting cases, i.e. $\kappa_3\gg\kappa_2$ and $\kappa_3\sim\kappa_2$. For pure long-range potentials, we obtain a dedicated analytic expression, and after incorporating short-range contributions, we uncover a unified formula consistent with the original PySR solution, which performs excellently in the intermediate force range around 1 fm. This work demonstrates that combining machine learning with physical constraints can yield novel analytical results inaccessible to conventional theoretical tools, advancing data-driven methodologies in hadron physics.

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All authors Wei-Jie Zhang, Zhenyu Zhang, Jifeng Hu, Bing-Nan Lu, Jin-Yi Pang, Qian Wang

Quantum Physics

Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors

Xiqiao Wang, Mark Field, Teng Zhang et al. (+18 more)

Recent advances in the alternating-bias-assisted annealing (ABAA) technique have successfully mitigated intrinsic Josephson-junction (JJ) fabrication variations. This new technique enables precision qubit frequency tuning alongside simplicity. However, it is critical to enhance tuning throughput and yield while investigating the factors that drive targeting performance as the technology scales. Here, we characterize ABAA tuning performance within a 150-mm wafer process flow and extend this technique to simultaneous, multi-channel tuning, demonstrating that a wafer-scale JJ resistance tuning precision of $\sigma=0.50\pm0.05\%$ alongside a component-level yield of $\ge 98.8\%$ can be achieved. Furthermore, we demonstrate a strong correlation between yield, tuning speed, and junction breakdown voltage, establishing the latter as a vital process control parameter for meeting production goals. Finally, we demonstrate a successful implementation of ABAA tuning on a quad-module quantum processor (Rigetti Cepheus-1-36Q), where we achieve an empirical frequency targeting precision of $\sigma \sim 30\text{ MHz}$ in both qubit and qubit-qubit detuning frequencies, contributing to high median two-qubit gate fidelities. These results confirm the efficacy and scalability of ABAA for high-precision Hamiltonian targeting, a critical enabler for modular superconducting quantum processor technology.

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All authors Xiqiao Wang, Mark Field, Teng Zhang, Xian Wu, Ferhat Aydinoglu, Joel Howard, Angela Q. Chen, Sara Elzeiny, Robert Smith, Timothy McSorley, Nicholas Sharac, Eyob Sete, Alysson Gold, Hilal Cansizoglu, Greg Stiehl, Josh Mutus, Kameshwar Yadavalli, Andrew Bestwick, Stefano Poletto, Raja Katta, David P. Pappas

High Energy Astrophysical Phenomena

Low-energy antinuclei measurements for background-free indirect dark matter searches and PBH signatures

Tsuguo Aramaki, Ilias Cholis, Philip von Doetinchem et al. (+7 more)

Light low-energy cosmic ray antinuclei constitute powerful probes for detecting dark matter or other sources of new physics in our Galaxy. This ASTRA Initiative Mission Concept reviews the theoretical motivation, highlighting the transformative potential and current experimental status. Motivated by exciting tentative results, it makes a clear case for the need for the next flagship mission to confirm or refute claims of cosmic antinuclei as signs of new physics.

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All authors Tsuguo Aramaki, Ilias Cholis, Philip von Doetinchem, Fiorenza Donato, Priya Ghosh, Dan Hooper, Timothy Linden, Keith McBride, Stefano Profumo, Stephanie Wissel

Instrumentation and Methods for Astrophysics

JUG: JAX-based Unified pulsar timinG

Matthew T. Miles, Stephen R. Taylor, Matthew Bailes et al. (+14 more)

We present JUG (JAX-based Unified pulsar timinG), a JAX-based, fully independent pulsar timing package emphasising speed and ease of use, designed to confidently handle the increasingly large and complex pulsar timing array datasets that are being created in the pulsar timing field. JUG implements the entire pulsar timing pipeline itself, from data handling and clock corrections through to the timing model and fitting, without relying on other timing software. It enables Pythonic programming at the speed of compiled code, is GPU-capable, and can be operated via a Python API or an interactive GUI. A user of JUG can interactively explore data, fit timing models with complex stochastic noise, model deterministic signals such as continuous gravitational waves, and obtain accurate point estimates of the parameters of the stochastic processes present, thereby bridging frequentist timing and Bayesian noise analysis. JUG is faster than PINT by more than fifty times and is comparably fast to Tempo2, can handle millions of arrival times, agrees with PINT at the picosecond level, and can reliably recover known timing model and noise parameter values. In this paper we describe its design, performance, and validation, and demonstrate its advantages for pulsar timing data analysis.

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All authors Matthew T. Miles, Stephen R. Taylor, Matthew Bailes, Aurelien Chalumeau, H. Thankful Cromartie, Kyle A. Gersbach, Rutger van Haasteren, Michael J. Keith, Nima Laal, Michael T. Lam, Kuo Liu, Aditya Parthasarathy, Scott M. Ransom, Daniel J. Reardon, Ryan M. Shannon, David C. Wright, Andrew Zic

Nuclear Theory

Nuclear lattice effective field theory as a testing ground for $\alpha$-cluster structures in ${}^{24}\mathrm{Mg}$

Gianluca Stellin, Serdar Elhatisari, Timo A. Lähde et al. (+1 more)

The framework of nuclear lattice effective field theory (NLEFT) is applied to $^{24}\mathrm{Mg}$, with the perspective of obtaining a model-independent density map of the geometry of a sample of excited states of the nucleus. The Hamiltonian incorporates Wigner SU(4)-symmetric nuclear forces as well as the Coulomb interaction. The coupling constants of the spin-isospin symmetric nucleon-nucleon potentials have been adjusted in order to reproduce the experimental ground-state (g.s.) energy of $^{24}\mathrm{Mg}$ as well as the experimental Tjon ratio between the binding energies of $^3\mathrm{H}$ and $^4\mathrm{He}$. The ensuing parameter set turns out to be capable of capturing the experimental trend of the binding energy per nucleon, reproducing simultaneously within 1% deviation the measured values for $^{18}\mathrm{F}$, $^{22}\mathrm{Na}$, $^{26}\mathrm{Al}$, $^{28}\mathrm{Si}$, $^{30}\mathrm{P}$ and $^{32}\mathrm{S}$. Considerations based on the convergence rate of Euclidean-time extrapolations for the two lowest energy eigenvalues highlight the dual nature of the $0_1^+$ and $2_1^+$ states, of hybrid mean-field and $\alpha$-cluster type. For the latter, triaxial $\alpha$-cluster configurations seem to be favoured over the axially-symmetric ones, whereas oblate superdeformation might characterize a rotational band at $20$ MeV excitation energy.

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All authors Gianluca Stellin, Serdar Elhatisari, Timo A. Lähde, Shihang Shen

Astrophysics of Galaxies

High Dispersion Measure Fast Radio Bursts from Young, Dust-Poor H II Regions

Eliza C. Diggins, Calvin Leung and Wenbin Lu

Several repeating fast radio burst (FRB) sources exhibit host-frame dispersion measure (DM) excesses far exceeding those expected from the interstellar medium in their host galaxies, implying a substantial contribution from the sub-kiloparsec-scale local environment. These excesses are often attributed to an expanding supernova remnant; however, this canonical interpretation does not explain their apparent preference for low-metallicity dwarf galaxy hosts, suggesting that the mechanism producing the local DM is coupled to the properties of the host galaxy. In this work, we investigate whether the H II regions generated by young, massive stellar associations can simultaneously explain these DM excesses and their preferential association with low-metallicity dwarf galaxies. We develop a semi-analytic model for FRB-emitting neutron stars in cluster-forming molecular clouds and perform idealized one-dimensional radiation-hydrodynamic simulations using time-dependent ionizing luminosities from pySTARBURST99. Our findings indicate that high-mass $(M_\star \sim 10^5-10^6\;M_\odot)$, young ($\lesssim 10\;{\rm Myr}$) stellar associations in low-metallicity environments (LMC-like or lower) can produce ${\rm DM}_{\rm HII} \gtrsim 10^3\;{\rm pc\;cm^{-3}}$ for FRBs that form early ($\lesssim 5$ Myr) and remain embedded in the ionized gas. The low-mass/metallicity preference arises from dust: absorption of the Lyman continuum suppresses the ionized column at higher metallicity, making extreme local DMs preferentially generated in dust-poor, low-metallicity environments. At cosmological distances, selection of a metal-rich, massive, and quiescent host galaxy sample where such extreme local contributions are likely to be suppressed may yield a cleaner FRB sample for using extragalactic DMs as tracers of the intervening intergalactic and circumgalactic media.

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Instrumentation and Methods for Astrophysics

PolPy: A universal tool for X-ray/gamma-ray polarimetry using common data format standards

Sujay Mate, Hancheng Li, Utkarsh Pathak et al. (+4 more)

X-ray/gamma-ray polarimetry has been a rapidly developing field in recent years. However, the lack of standardized analysis frameworks has hindered cross-instrument comparisons and joint multi-mission studies. To address this, we present PolPy, a universal tool designed for polarimetry of high-energy astrophysical transients. Built as a plugin for the Multi-Mission Maximum Likelihood (3ML) framework, PolPy introduces standardized data and response formats, common reference frames based on IAU conventions for defining polarization angles, and a robust likelihood-based template-matching algorithm. The article briefly describes these standards and presents tests and results performed to validate the software using simulated gamma-ray burst (GRB) injections across two different mission mass models: POLAR and Daksha. Our verification tests demonstrate that PolPy accurately recovers the injected polarization angles and fractions without systematic bias. Furthermore, we show that performing simultaneous joint fits across multiple detectors and instruments can significantly improve parameter constraints compared to single-instrument analyses. By unifying data formats and methodology, PolPy enables reliable joint polarimetric analysis for current and future high-energy polarimeters.

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All authors Sujay Mate, Hancheng Li, Utkarsh Pathak, Yashowardhan Rai, Nicolas De Angelis, Varun Bhalerao, Merlin Kole

Astrophysics of Galaxies

Near-Infrared Spectroscopy of Low-Redshift Palomar-Green Quasars and Composite Spectra

Amy Cavanaugh, Michael Brotherton, Jacob McLane et al. (+1 more)

The Palomar-Green (PG) Quasars have been used extensively to establish the spectral properties of luminous active galactic nuclei (AGNs) at low redshifts in many wavebands, but not the near-infrared (NIR). We present NIR spectra of all 87 PG quasars with z < 0.5 observed with the Apache Point Observatory 3.5-m telescope and the TripleSpec spectrograph in standard cross-dispersed mode. Here we employ our data set to construct a NIR composite quasar spectrum spanning rest-frame wavelengths from approximately 8800-22000 angstroms reaching a signal-to-noise ratio of several hundred in the H-band for 4 angstrom pixels. We characterize the continuum and emission-line properties of this composite. Additionally, we construct composite spectra as a function of luminosity and Eddington ratio, finding some differences, not entirely unexpected. In particular, more luminous composite NIR spectra grow increasingly red at long wavelengths, consistent with relatively stronger dust emission at higher temperatures.

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All authors Amy Cavanaugh, Michael Brotherton, Jacob McLane, Richard Green