Instrumentation and Detectors
GPT-Based Fast Simulation of CLAS12 Detector Hits via Conditional Autoregressive Generation
Cole Granger, James Giroux, Richard Tyson et al. (+2 more)
Modern particles physics experiments have demonstrated an increasing need for fast, high-fidelity detector simulation as detector components have improved and subsequent computational requirements approach the limits of available resources. Recently, deep generative models have emerged as a promising alternative to traditional Monte-Carlo methods, with recent works drawing inspiration from large
language models (LLMs) and self-supervised next-
token prediction methods. In this work, we present an application of a GPT-style autoregressive
transformer as a fast surrogate model for the calorimeter inside the CLAS12 experiment at the Thomas Jefferson National Accelerator Facility. The model is conditioned on incident momentum and generates realistic detector hits autoregressively across all nine calorimeter layers as sequences of strip, ADC, and TDC
tokens. We demonstrate that the model faithfully reproduces hit multiplicity, spatial distributions, energy deposits, and the energy-momentum response of the electromagnetic calorimeter. The generator achieves inference rates exceeding 700 events per second on a single GPU, providing a substantial speedup over traditional Geant4-based simulations while maintaining physics fidelity essential for high-luminosity experimental programs.
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All authors Cole Granger, James Giroux, Richard Tyson, Maurizio Ungaro, Cristiano Fanelli
Other Condensed Matter
Machine learning enables roughness-driven inverse design of milling processes
Hadi Bakhshan, Sima Farshbaf, Fernando Rastellini et al. (+1 more)
Interest in applying data-driven approaches in manufacturing has grown significantly, particularly for mapping complex, high-dimensional relationships. The milling process is one area where predictive models can link influential parameters to surface roughness metrics prior to in situ operations. While this approach offers clear advantages, it faces challenges due to limited
datasets and robustness issues in inverse design paradigms. To address these challenges, this paper proposes a machine learning (ML)-based framework for the inverse design of the surface milling process, with a focus on surface roughness as the design objective. The framework employs forward training of two ML models, a deep neural network (DNN) and a random forest (RF) ensemble, both developed using a high-fidelity synthetic
dataset generated from a computational simulation framework. These trained models are integrated into a
Bayesian optimization (BO) procedure to overcome the multiplicity problem arising from the many-to-one mapping inherent in the
dataset. The approach identifies top-performing milling process configurations, considering both process and tool parameters, and presents them from the full solution space. The models achieve average relative errors below 5% when compared to reference results, thereby demonstrating the robustness and reliability of the proposed methodology.
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All authors Hadi Bakhshan, Sima Farshbaf, Fernando Rastellini, Josep Maria Carbonell
Mesoscale and Nanoscale Physics
Contacts to Low-Dimensional Semiconductors: Physical Theory and Analytical Model
Jimmy Qin and H.-S. Philip Wong
Metal contacts to low-dimensional
semiconductors are critical for nanoelectronics, yet a general physical description has remained elusive. We present an analytical model for metal-induced gap states (MIGS), revealing a universal scaling law governed by
semiconductor dimensionality. Linking MIGS to transport observables, we provide a unified formulation of Schottky barrier height, transfer length, and contact resistance. Our model explains recent experiments on carbon nanotubes and 2D materials, clarifying the fundamental criteria for achieving scalable, low-resistance contacts.
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Quantum Gases
Asymmetric binary Bose mixtures: a Functional Renormalisation Group study
Boris Krippa
Zero-temperature binary Bose mixtures with mass and intraspecies couplings imbalances are studied using the functional renormalisation group (FRG) framework. We find that this dual asymmetry induces a spontaneous redistribution of
quantum fluctuations between the components. This effect leads to a significant divergence in the quasiparticle residues of the two species, a phenomenon not captured in mean-field treatments. Critically, our FRG analysis predicts a systematic reduction of the density-channel sound velocity with increasing asymmetry – a result that qualitatively contradicts the behaviour predicted by standard Bogoliubov theory. The ratio of the renormalisation factors is proposed as a robust quantitative probe of many-body correlations and fluctuation transfer. These findings provide a consistent non-perturbative framework for interpreting future experiments on heterogeneous mixtures.
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Statistical Mechanics
Universality in the target arrival statistics of non-conservative search processes
José Giral-Barajas, Samantha Linn and Paul C. Bressloff
Stochastic search processes in which
agents are continuously inserted into and removed from a target search domain are fundamental to a wide class of physical and artificial systems. The theory of such non-conservative search processes is, however, much less developed than for search processes with a fixed number of
agents. Recent work on the non-conservative case has characterized the fastest first-passage time (FPT) to a target, after which the search process is terminated. Here we consider the complementary problem of continuous arrival statistics to a target. In particular, we derive the full time-dependent distribution of target arrivals, which we use to show that the inter-arrival time distribution is exactly exponential in steady-state regardless of the underlying search process. Thus, counterintuitively, the arrival statistics of non-conservative search are both universal and much simpler than sequential search-and-capture processes involving a fixed number of
agents. Our methods also yield an exact expression for the fastest FPT distribution with time-dependent insertion, thereby generalizing previous work on fixed-rate insertion for non-conservative search. Altogether these results have major implications for target resource accumulation, wherein the delivery of resources is counter-balanced by their downstream consumption.
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High Energy Physics (Theory)
The O(4)-breaking bubble
Guy Avraham, Kfir Blum, Omri Rosner et al. (+1 more)
False
vacuum decay in scalar field theory is thought to be dominated by Coleman's O(4)-symmetric bounce, the minimum action nontrivial solution of the imaginary-time equations of motion. Beyond the bounce, non-constructive existence proofs of O(4)-breaking solutions are available in the mathematics literature, but the solutions themselves, and their physics, have remained unknown. Considering the simple, bounded-below, scalar field potential $V(\phi)=\frac{m^2}{2}\phi^2-\frac{\lambda}{4}\phi^4+\frac{g}{6}\phi^6$, we construct a nonradial solution explicitly: two bubble tubes of opposite sign wrapping orthogonal rings, invariant under ${\rm O}(2)\times{\rm O}(2)$ rotations combined with a $Z_2$
symmetry that exchanges the rings. The solution admits valid Cauchy data for real-time
evolution from a $t=0$ slice, and supports an odd $>1$ number of unstable deformation modes. Having found this first solution we proceed to discover additional examples, in 3d as well as other 4d theories including a $Z_2$-violating potential and scalar QED for which there were no previously known existence proofs or O(4)-dominance
theorems.
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All authors Guy Avraham, Kfir Blum, Omri Rosner, Isaac G. Smith
Quantum Physics
Quantum Algorithm for Open-System Battery Cathodes by Modeling Multiple Strongly Coupled Holstein Polarons with Chain-Mapped Caldeira-Leggett Dynamics
Joshua M. Courtney
Cathode lithiation occupies a chemical regime of tightly localized orbitals, narrow bandwidths, and strong electron-
lattice coupling. The defining electrochemical observables (open-
circuit voltage and differential capacity) are open-system, reservoir-equilibration quantities that closed-
Hamiltonian quantum simulation cannot produce, set by exchange with electron, Li$^+$, and
phonon baths. We present a fault-tolerant
quantum algorithm that recovers them through a
unitary chain-mapped Caldeira-Leggett
embedding, rendering the baths Trotterizable. The resulting fourth-order Trotter step has a T-gate count
polynomial in system size, validating its open-system dynamics against hierarchical equations of motion (HEOM) at strong coupling and the Lindblad limit at weak coupling. For single-carrier olivine LiFePO$_4$, a single voltage anchor on an otherwise DFT-fixed
Hamiltonian places the differential-capacity peak within the $\pm5$ mV reproducibility of the experimental plateau. For multi-carrier spinel LiMn$_2$O$_4$, whose $1{:}1$ Mn$^{3+}$/Mn$^{4+}$ filling makes the inter-site Coulomb repulsion dynamically active, the same kernel yields a two-plateau voltage curve with a $125$ mV split, within $17\%$ of the observed $150$ mV. We deliver an end-to-end fault-tolerant resource estimate for such a multi-carrier, three-reservoir observable: $368$ logical
qubits and $\sim3\times10^5$ T-gates per step, or $\sim1.7\times10^{12}$ T-gates for a full voltage curve (parallelizable over $\sim10^3$ trajectories), leaving the production-scale dynamical run as a milestone for future hardware. The same kernel reproduces macroscopic
quantum coherence, two-band superconductivity, and the Mikheyev-Smirnov-Wolfenstein resonance without modification, placing dynamical battery chemistry and similar
Hamiltonians within scope for fault-tolerant
quantum simulation.
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Disordered Systems and Neural Networks
The limits of interpretability in multiple linear regression
Anand Sharma, Chen Liu, Daniele Coslovich et al. (+1 more)
Interpreting machine-learning models has attracted increasing
attention, particularly in the physical sciences, where one often seeks to understand the underlying mechanisms rather than merely make predictions. Multiple linear regression is often regarded as an interpretable alternative to more complex models, such as deep neural networks, because its predictions are expressed as explicit weighted sums of input features. However, when input features are strongly correlated, namely in the presence of multicollinearity, the learned weights can exhibit large
dataset-to-
dataset fluctuations and oscillatory behavior across physically similar features, making their interpretation difficult or even impossible. Although the instability of the weights under multicollinearity is well known in statistics, its consequences for physical interpretation, in particular its connection to oscillatory weights across physically similar features, have not been systematically clarified. Here, we theoretically discuss the mechanism behind this loss of interpretability by analyzing the eigenmodes of the feature correlation
matrix. We show that small-
eigenvalue modes associated with multicollinearity amplify fluctuations in the weights and generate oscillatory patterns that do not necessarily reflect meaningful contributions. We test this theoretical picture numerically on physics
datasets and show that Ridge regularization suppresses these unstable modes, although the resulting weights must still be interpreted with caution. We further confirm the generality of our findings beyond physics by analyzing a diverse collection of publicly available
datasets. Our results clarify why, in the presence of multicollinearity, physical interpretation can remain difficult even for linear regression models.
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All authors Anand Sharma, Chen Liu, Daniele Coslovich, Misaki Ozawa
Astrophysics of Galaxies
HYPERION. The cold ISM of rapidly growing $z>6$ quasars: diverse gas reservoirs, dust enrichment, and feedback signatures
Claudia Maria Pierro, Roberta Tripodi, Laura Pentericci et al. (+11 more)
Luminous QSOs at $z>6$ host some of the most rapidly assembled SMBHs in the early Universe. Characterizing their cold ISM is essential to determine their
evolution. We investigate the molecular gas, cold
dust,
star formation, gas-to-
dust ratio, and ionized ISM of ten HYPERION QSOs using new ALMA Band 3 observations targeting CO(6-5) and the underlying $\sim100$ GHz continuum, complemented by archival and literature ALMA/NOEMA data. We detect $\sim100$ GHz continuum emission in eight targets and CO(6-5) emission in four QSO hosts, J025-33, J083+11, J231-20, and J0252-0503, as well as in the companion of J231-20. The inferred molecular gas masses are of order $10^{10}~M_\odot$, while the non-detections imply upper limits of a few $10^9~M_\odot$, indicating a broad range of molecular reservoirs within the HYPERION population. For J025-33 and J083+11, the FIR SEDs are well sampled and yield low
dust temperatures, $T_{\rm dust}=36^{+13}_{-7}$ K and $32^{+4}_{-3}$ K, respectively, well below the average value for $z>6$ QSOs. Combining gas and
dust masses, we find a gas-to-
dust ratio for J083+11, ${\rm GDR}=16^{+5}_{-4}$, among the lowest measured in a high-
redshift QSO host. We also detect [NII]$\lambda 205\,\mu$m emission in J025-33 and tentatively in J083+11, suggesting dense or highly structured ionized gas. Finally, we identify a tentative connection among $T_{\rm dust}$, the X-ray
photon index $\Gamma$, and the C IV velocity shift. These trends may indicate that more powerful winds redistribute
dust away from the central AGN heating source, lowering its temperature and weakening the connection between the large-scale
dust reservoir and the X-ray corona. Overall, HYPERION QSOs emerge as a heterogeneous population in which SMBH growth,
star formation, gas consumption, enrichment, and feedback are not necessarily synchronized.
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All authors Claudia Maria Pierro, Roberta Tripodi, Laura Pentericci, Francesco Salvestrini, Luca Zappacosta, Alessia Tortosa, Blessing Musiimenta, Enrico Piconcelli, Livia Vallini, Fabio Di Mascia, Federico Esposito, Chiara Feruglio, Fabio Vito, Maria Vittoria Zanchettin
Medical Physics
Dosimetric characterization of a nanophotonic scintillator and applications to real-time in-vivo total body irradiation dosimetry
W. Jeffrey Zabel, Dixin Chen, Louis Martin-Monier et al. (+7 more)
Purpose: Recent advances in metasurface photonics and manufacturing have enabled a nanophotonic surface coating to be applied to conventional scintillators, which has been shown to significantly improve light yield. However, the dosimetric properties of such coatings has not been established. We performed the first dosimetric characterization of a nanophotonic scintillator and explored clinical application to real-time in-vivo total body irradiation (TBI) dosimetry. Methods: A 4.5x1.5 cm cerium-doped yttrium aluminum garnet (YAG:Ce) scintillator, half patterned with the nanophotonic structure, half left unpatterned, enabled direct comparison between conventional and nanophotonic surfaces. The scintillator was placed in a 3D-printed light-tight box with an off-axis CMOS camera and irradiated with a clinical linear accelerator. Absolute dosimetry was done with dose-calibrated radiochromic film. For TBI, the scintillator was positioned on an anthropomorphic phantom in a TBI booth, with signal measured by both CMOS and consumer-grade phone cameras under different room lighting conditions. Results: The nanophotonic scintillator showed a 4.1x increase in signal and a 3.7x increase in contrast-to-noise ratio versus the conventional scintillator. Both scintillators exhibited dose-rate independence and linear dose response, with modest energy dependence. For TBI, the nanophotonic scintillator produced a clearly detectable signal with both CMOS and phone cameras, whereas the conventional scintillator signal was undetectable. Conclusions: Nanophotonic structures significantly enhance light output of conventional scintillators without impacting their dosimetric properties. Nanophotonic scintillators may enable real-time in-vivo TBI dosimetry. Future work should investigate this technology for improved dosimetry equipment and X-ray imaging detectors.
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All authors W. Jeffrey Zabel, Dixin Chen, Louis Martin-Monier, Simo Pajovic, Shanhui Fan, Juejun Hu, Marin Soljačić, Lei Xing, Charles Roques-Carmes, M. Ramish Ashraf
Materials Science
Confined Oxygen-Vacancy Migration Drives Ferroelectric Switching
Hyeonhu Bae and Binghai Yan
Conventional ferroelectricity arises from intrinsic
lattice distortions, whereas oxygen vacancies are generally regarded as detrimental because their migration induces leakage currents and polarization degradation. However, the recently discovered ultrathin van der Waals ferroelectric Bi2SeO5 exhibits robust out-of-plane polarization switching despite its pristine
crystal symmetry forbidding the corresponding displacive ferroelectric instability. Here we show that this apparent contradiction originates from confined oxygen-vacancy migration. We find that oxygen vacancies preferentially form within SeO3 units and undergo reversible low-barrier rearrangements between nearly degenerate configurations. These localized vacancy dynamics generate a large switchable out-of-plane polarization, while long-range vacancy
diffusion is suppressed by substantially higher migration barriers. At a representative vacancy concentration of 2.5%, the resulting polarization reaches approximately 16 uC cm^-2, consistent with experiment. Our results identify confined oxygen-vacancy migration as the microscopic origin of ferroelectric switching in Bi2SeO5 and establish defect-enabled ferroelectricity as a general mechanism for layered van der Waals
oxides.
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General Relativity and Quantum Cosmology
From information bounds to infrared gravity: implications of Sharma-Mittal entropy
Abdelhakim Benkrane, Giuseppe Gaetano Luciano and Ahmad Sheykhi
The Sharma–Mittal (SM)
entropy provides a two-parameter generalization encompassing both the Rényi and Tsallis statistical frameworks. In this work, we investigate its thermodynamic and gravitational implications in the context of black hole physics and emergent
gravity. Specifically, we examine the compatibility of the gravitational realization of the SM
entropy with the Bekenstein bound and show that the corresponding framework consistently interpolates between the Rényi and Bekenstein–Hawking
entropies in the appropriate limits. By incorporating Landauer's principle into black hole thermodynamics, we obtain a modified mass-loss relation associated with one-bit information erasure, exhibiting nontrivial parameter-dependent asymptotic behavior in both the small- and large-mass regimes. Furthermore, within Verlinde's entropic
gravity framework, we derive modified gravitational force and acceleration laws induced by the SM
entropy. We show that the resulting acceleration deviates from the Newtonian prediction at large distances and naturally reproduces a MOND-like regime for the specific parameter relation $R/\delta = 3/2$. This condition establishes a direct connection between the SM
entropy parameters and the MOND acceleration scale $a_0$. Our findings highlight the potential of the SM framework to provide a unified link between black hole thermodynamics, information theory, and infrared modifications of
gravity, while offering new insights into phenomena traditionally attributed to the dark matter paradigm.
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Quantum Physics
Influence of the Electron's Anomalous Magnetic Dipole Moment on High-Atomic-Number Atoms
C. A. S. Almeida and J. Auto-Neto
Super-heavy atoms ($Z > 100$) are usually studied in the context of the so-called “
Quantum Electrodynamics of Strong Fields”. In this theory the problem of the singularity in the electron energy whenever $Z > 137$ is overcome. This is done by considering the finite size of the
nucleus and leads to interesting phenomena, such as the spontaneous production of positrons. Here, we show that taking into account the contribution from the Anomalous
Magnetic Dipole Moment of the electron (by means of an effective theory), within a point-
nucleus model, is a sufficient condition to obtain regular wave functions and physically acceptable energy values for $Z > 137$.
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High Energy Physics (Theory)
Dressed Fock Spaces in Gauge Theory and Gravity
Sangmin Choi and Prahar Mitra
Four-dimensional gauge and gravitational theories exhibit long-range interactions that require asymptotic particles to be dressed by clouds of soft
photons and gravitons. Faddeev-Kulish dressings render scattering amplitudes infrared-finite, but the resulting multi-particle states do not factorise into tensor products of dressed one-particle states. We show that this loss of Fock-space factorisation is not fundamental, but reflects an inappropriate choice of infrared variables. The real soft divergence is reproduced by the Goldstone modes of asymptotic
symmetries, while the Coulomb phase is reproduced by new zero modes of the radiative fields that we introduce here. In these variables, infrared-finite dressed multi-particle states admit the usual Fock-space factorisation into single-particle dressed states.
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Lattice Field Theory
Learning the generating functional for variance reduction in lattice QCD
Ryan Abbott, Yang Fu, Daniel C. Hackett et al. (+3 more)
The generating functional in
quantum field theory provides the natural framework for constructing correlation functions as derivatives with respect to source operators. We present a methodology that leverages machine-learned normalizing flows to reduce the variance of arbitrary $N$-point correlation functions of bosonic operators in
lattice gauge field theory calculations by encoding a representation of the generating functional. We show that it is possible to systematically approach noiseless
estimators of correlation functions in this framework. We demonstrate this methodology with applications to calculations of glueball correlation functions and Wilson loops in
Quantum Chromodynamics and Yang-Mills theory. The results show up to three orders of magnitude variance reduction.
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All authors Ryan Abbott, Yang Fu, Daniel C. Hackett, Gurtej Kanwar, Fernando Romero-López, Phiala E. Shanahan
Fluid Dynamics
Quantum-enhanced Markov chain Monte Carlo sampling to model Lagrangian tracer dispersion in turbulent boundary layer
Fabian Schindler and Jörg Schumacher
We present a
quantum-enhanced Markov chain Monte Carlo (QE-MCMC) method to sample turbulent acceleration vectors from a joint target distribution that depends on all three components and height to model the transport and dispersion of massless Lagrangian tracer particles in two turbulent shear flows. A homogeneous shear flow, characterized by a uniform shear rate S, is considered as the starting point. Secondly, a turbulent boundary layer, which forms in both halves of a plane turbulent channel flow at friction Reynolds number Re_tau = 1000, is considered, where the mean shear rate S(y) varies with distance from the wall y. In this hybrid
quantum-classical method, the proposal distribution Q for the first of two Metropolis-Hastings sampling substeps is constructed by a parametric
quantum circuit. The
algorithm generates synthetic tracer particle tracks. The resulting scaling laws for tracer-particle pair dispersion, a central quantity to probe turbulent mixing from a Lagrangian perspective, agree with a
stochastic transport model consisting of coupled Langevin equations and with the classical MCMC counterpart. Differently from the classical sampling method, QE-MCMC uses a tempered target distribution. Due to the height dependence of the tracer dynamics in turbulent channel flow, an effective height-weighted spectral gap between the first and second
eigenvalue of the Markov-chain transition
matrix is introduced. The latter is found to significantly exceed the one of classical MCMC when sampling from a multivariate distribution with cross-correlations at the highest
qubit numbers and thus resolutions. Consequently, our results support the applicability of this one-shot
algorithm as a generative Lagrangian
quantum-computing module, possibly embedded in a complex fluid-flow problem. Our module is found to work reliably for a relatively small number of
qubits per spatial dimension of Nq <= 6.
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Quantum Physics
Learning ground state observables from quantum computing experiments
Ben Jaderberg, Freya Shah, Minjun Jeon et al. (+3 more)
Recent theoretical progress has established conditions under which machine learning models can efficiently predict ground-state properties of gapped local
Hamiltonians when trained on
quantum-generated data. Previous experimental demonstrations in this paradigm, however, have largely been limited to small systems or highly structured states, due to the difficulty of preparing many-body ground states on
quantum processors. In this work, we demonstrate learning from experimental
quantum data generated from approximate ground states of the two-dimensional Heisenberg XXZ model with system sizes up to 115
qubits. We construct a
dataset of single-site expectation values, two-point correlations, and 12-body loop correlations across the
antiferromagnetic phase. We then train neural networks on this data and show that they can accurately predict spatially resolved observables for previously unseen
Hamiltonian parameters, both within the training distribution and in an out-of-distribution regime approaching the phase boundary. Our results demonstrate the practical realization of learning from
quantum data for an interacting two-dimensional many-body system at scale, motivating a path toward regimes where
quantum processors could provide training data beyond the reach of classical approximation methods.
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All authors Ben Jaderberg, Freya Shah, Minjun Jeon, M. Emre Sahin, Christa Zoufal, Kunal Sharma
Chemical Physics
High-sensitivity hydrogen gas permeation: system development, sample preparation, and influence of testing variables
R. Li, A. Zafra, Z. D. Harris et al. (+1 more)
There is a need to develop quantitative, high-resolution hydrogen gas (H2) permeation techniques to provide a better understanding of hydrogen-material interactions. This study aims to develop and validate a high-sensitivity H2 permeation system, which is then leveraged to systematically quantify the influence of surface condition and key testing variables (surface
oxides, residual gas
impurities, pressure, and temperature) on hydrogen permeation. A gas permeation system capable of operating at pressures up to 50 bar and temperatures up to 250 C was developed, incorporating high-sensitivity mass spectrometric detection and controlled surface preparation protocols. Permeation transients were analysed in a model material (annealed pure Fe) to determine hydrogen diffusivity and permeability under systematically varied surface states, oxygen contents, pressures and temperatures. Surface
oxides are shown to play a dominant role in controlling hydrogen permeation at room temperature. The presence of
oxide layers can severely hinder or completely suppress hydrogen uptake, with measurable permeation requiring
oxide removal via pickling and Pd coating on both surfaces, or activation through hydrogen-assisted reduction at elevated temperature. Residual oxygen present prior to hydrogen exposure further reduces permeability by modifying surface boundary conditions, indicating strongly surface-controlled kinetics. Under optimised surface conditions, hydrogen transport follows bulk
diffusion-controlled behaviour, with steady-state flux obeying Sieverts' law at 25 C (1-5 bar) and diffusivity and permeability exhibiting Arrhenius behaviour between 25 and 150 C at 5 bar, indicating bulk
diffusion-controlled transport. The developed system resolves hydrogen fluxes as low as 1.98x10-9 mol(m2 s) and provides a robust platform for investigating surface, mechanical and environmental effects on H2 permeation.
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All authors R. Li, A. Zafra, Z. D. Harris, E. Martínez-Pañeda
Plasma Physics
Impact of energetic alpha particles on core turbulence in an ARC-class fusion power plant
J. Hall, N.T Howard, P. Rodriguez-Fernandez et al. (+7 more)
In this work, we investigate the impact of fusion-born alpha particles on core
turbulence and transport in the ARC tokamak fusion power plant using linear and nonlinear gyrokinetic CGYRO simulations. A significant reduction in ion-scale turbulent heat and particle fluxes is observed in the inner core (r/a $\leq$ 0.5), which is associated with multiscale interactions between fast ion-destabilized modes, zonal flows, and the background
turbulence. A nonlinear upshift in the ITG critical gradient is observed in the simulations with fast alphas compared to those with artificially thermalized alphas. The
turbulence reduction is found to scale beneficially with alpha particle density and
plasma $\beta_e$, and the radial extent of the
turbulence suppression is limited to the volume containing a significant density of fast particles. The suitability of local gyrokinetics and potential impacts of fast ion effects on fusion performance are discussed.
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All authors J. Hall, N.T Howard, P. Rodriguez-Fernandez, R.A. Tinguely, I. Sfiligoi, J. Ruiz-Ruiz, J.C. Hillesheim, A. Creely, E.A. Belli, J. Candy
Cosmology and Nongalactic Astrophysics
Axion-Sourced Gravitational Waves in $\mathrm{B\!-\!L}$ Hybrid Inflation
Ahmed Ayad and Shaaban Khalil
Minimal supersymmetric $\mathrm{B\!-\!L}$ hybrid inflation predicts a negligible
vacuum tensor-to-scalar ratio $r_{\rm vac}\sim 10^{-8}$ due to its extremely flat potential. In this letter, we show that adding a spectator pseudoscalar
axion-like field coupled to the $\rm {U}(1)_{\mathrm{B\!-\!L}}$ gauge sector via a Chern-Simons term circumvents this suppression. The rolling
axion triggers a tachyonic instability for one gauge field helicity, exponentially amplifying gauge fluctuations. These sourced modes generate a
stochastic gravitational-wave background with tensor power spectrum ${\cal P}_{T}^{\rm src}\propto e^{4\pi\xi}/\xi^{6}$, where $\xi = \alpha \dot{\phi} / (2 f_a H)$ is the gauge-field instability parameter. For $\xi\sim3.3$–$3.6$, the tensor-to-scalar ratio reaches $r\sim10^{-3}$, within the sensitivity of LiteBIRD. For $\xi\sim3.6$, the gravitational-wave spectrum develops a peaked shape that enters the LISA sensitivity band (peaking at frequencies around $10^{-3}$ Hz) with an amplitude $h^2\Omega_{\rm GW}\sim2.5\times10^{-13}$. The mechanism predicts
chiral gravitational waves, a broken consistency relation $r=16\epsilon$, and a distinctive $r$–$\Omega_{\rm GW}$ correlation that could be tested by future CMB and interferometer observations.
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Quantum Physics
Quantum Measurement and Continuous Markov Processes
Chris Jackson
These are the lecture notes for a course on diffusive
quantum measuring instruments. They were prepared and delivered at the Perimeter Institute on Mondays and Thursdays, from 2:30 to 4:00 PM, beginning October 27th, 2025 and ending December 11th, 2025. These lectures were recorded and can be found at https://pirsa.org/c25038.
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High Energy Physics (Phenomenology)
Axiverse Strings Resolved
Rudin Petrossian-Byrne and Giovanni Villadoro
Axiverse
cosmic strings are resolved by non-perturbative string states with large tension. We show how, in some regions of
moduli space, they dissolve into low-tension configurations that are fully captured by field-theoretic solitonic solutions, such as 't Hooft-Polyakov-like strings, allowing a post-inflationary cosmology within the original axiverse paradigm.
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Atmospheric and Oceanic Physics
Composite sub-micron solid particles engineered to enable safe, controllable, efficient, and practical SAI
A. Spector, T. Kislev, Y. Segev et al. (+2 more)
The properties of candidate particles for
solar radiation management (SRM) through stratospheric aerosol injection (SAI) should comply with safety, controllability, and functionality requirements. Following the proposal in arXiv:2604.02283 of safety and controllability requirements, we define here a set of functionality requirements on the particles' properties – optical properties, stratospheric residence time, scalable manufacturing compatibility, and aerial dispersion compatibility – that, if met, ensure the feasibility of practical implementation, providing reflection of $\sim1$% of the
solar flux. We then present design principles and fabrication methods for sub-micron solid particles that may enable satisfying the combined requirements. These requirements do not identify a unique solution, but favor sub-micron particles with tightly controlled size distributions and stable properties over their stratospheric lifetime, and motivate a composite design where the bulk core composition is selected primarily for optimal radiative properties and the outer shell surface is engineered to control atmospheric chemistry and aging, and enhance aerial dispersion compatibility. We present two specific particle designs that are viable for meeting the coupled requirements: amorphous silica spheres and calcium-carbonate cores surrounded by spherical silica shells (both with appropriate surface treatment). The former is at an advanced stage of experimental verification (described in detail in a companion paper) of meeting all requirements, provides a practical platform for surface engineering, and will enable reaching a substantial fraction of $\sim\!1$%
solar flux reflection. The latter is under development and will enable reaching $>1$% reflection.
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All authors A. Spector, T. Kislev, Y. Segev, Y. Yedvab, E. Waxman
Quantum Gases
Adiabatic preparation of a fractional quantum Hall fluid by coherently pumping atoms from a Bose-Einstein condensate
Alberto Tabarelli de Fatis, Christof Weitenberg, Alexander Schnell et al. (+2 more)
We propose a protocol to adiabatically prepare a many-particle fractional
quantum Hall fluid of bosonic ultracold atoms exploiting a time-dependent coherent coupling of a strongly interacting atomic state with a large dilute Bose-Einstein condensate. Starting from an empty cloud, atoms with well-defined angular momentum are coherently pumped into the fluid by Raman beams with a Laguerre-Gauss profile. Compared to number-conserving schemes which rely on finite-size-induced topological gaps, we identify an adiabatic path in the Fock space which avoids crossing topological phase transitions and thus maintains a sizable adiabatic gap open at all times. The efficiency of our preparation protocol is numerically assessed for typical experimental parameters up to particle numbers that largely exceed the experimental state-of-the-art. The crucial advantage of including an anharmonic confinement is finally highlighted.
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All authors Alberto Tabarelli de Fatis, Christof Weitenberg, Alexander Schnell, André Eckardt, Iacopo Carusotto
Chemical Physics
Local, mm-scale $^1$H magnetic resonance imaging using atomic vapors
Sven Bodenstedt, Morgan W. Mitchell and Michael C. D. Tayler
We demonstrate a practical and sensitive low-field approach to
magnetic resonance imaging (MRI) of $\mu$L-scale samples using an optically pumped magnetometer (OPM). Using a simple setup where a commercial OPM is placed directly adjacent to a sample, without intermediary signal-pickup coils, we perform one- and two-dimensional imaging with a >1 cm field of view and sub-mm
Fourier-limited resolution at 10 $\mu$T, near Earth's field. This enables (i) high-throughput, low-field MRI of fluidic and tissue samples, and (ii) a quantitative
benchmark of the sensitive volume surrounding the OPM.
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Quantum Physics
Experimental Observation of Dynamical Phase Transitions in a Dephased Photonic Quantum Walk
Xiaojian Huang, Lei Xiao, Bingzi Huo et al. (+3 more)
Dynamical phase transitions in open
quantum systems govern how non-
equilibrium states relax toward a stationary state. We study these transitions experimentally using a discrete-time photonic
quantum walk on a three-node graph. A tunable synthetic gauge flux and calibrated dephasing allow us to control time-reversal
symmetry and the detailed balance properties of the effective Markovian dynamics. With detailed balance, we observe a first-order dynamical phase transition marked by a crossing of real Liouvillian
eigenvalues. When detailed balance is broken, we observe a second-order dynamical phase transition at an exceptional point where
eigenvalues and eigenvectors coalesce. By progressively reducing the dephasing strength, we track the crossover toward the
quantum-coherent regime and determine that the transitions persist down to a finite threshold. Our results link Liouvillian spectral
topology to relaxation criticality and demonstrate a controllable platform for engineered dissipative dynamics.
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All authors Xiaojian Huang, Lei Xiao, Bingzi Huo, Xiaowei Wang, Stefano Longhi, Peng Xue
Earth and Planetary Astrophysics
The breaking of cold traps and onset of titanium in ultra-hot Jupiter atmospheres: WASP-189b in context
Stefan Pelletier, Romain Allart, Valentina Vaulato et al. (+56 more)
Condensates are ubiquitous to all
Solar System
planets with significant ($>$10mbar) atmospheres. The same is true for most
exoplanets with characterised atmospheres, with even ultra-hot
exoplanets being able to form clouds on their cooler nightsides. One high-interest condensate is titanium, a highly refractory element that as an
oxide (TiO) is a potent optical absorber long believed to be a driver of thermal inversions in highly irradiated
exoplanet atmospheres. Observations have shown that some ultra-hot Jupiters have strong thermal inversions despite being significantly Ti-depleted, likely due to cold trapping, raising doubts about whether TiO is the main cause of their inverted temperature structures. Our aim was to retrieve the titanium-to-iron ratio of the dayside atmosphere of the ultra-hot Jupiter WASP-189b to determine whether the full titanium budget is accounted for in the gas phase. We analysed thermal emission observations of WASP-189b taken with the HARPS and NIRPS spectrographs using different atmospheric
retrieval prescriptions to infer the
planet's atmospheric thermal structure and composition. We observed Fe and Ti signals in cross-correlation and measured a sub-
solar Ti/Fe ratio for WASP-189b using both free and chemical
equilibrium retrieval approaches. We find the Ti/Fe of the planetary atmosphere to be between 28% and 81% (1-$\sigma$ bounds) that of the
stellar value. The slight underabundance of Ti with respect to Fe on the dayside atmosphere of WASP-189b suggests that some titanium is missing from the gas phase, potentially due to a partial nightside cold trap. In the context of the ultra-hot Jupiter population, the onset of titanium in exoplanetary atmospheres appears to occur progressively, coinciding not with when thermal inversions begin but rather when the vapourisation threshold of titanium is reached on the nightside.
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All authors Stefan Pelletier, Romain Allart, Valentina Vaulato, David Ehrenreich, Eduardo Cristo, Laurie Dauplaise, Christophe Lovis, Leslie Moranta, Nicolas B. Cowan, Thierry Forveille, Étienne Artigau, Frédérique Baron, Susana C. C. Barros, Björn Benneke, Xavier Bonfils, François Bouchy, Marta Bryan, Bruno L. Canto Martins, Ryan Cloutier, Neil J. Cook, Jose Renan De Medeiros, Xavier Delfosse, René Doyon, Jonay I. González Hernández, David Lafrenière, Izan de Castro Leão, Lison Malo, Claudio Melo, Lucile Mignon, Christoph Mordasini, Francesco Pepe, Rafael Rebolo, Jason Rowe, Nuno C. Santos, Damien Ségransan, Alejandro Suárez Mascareño, Stéphane Udry, Diana Valencia, Gregg Wade, Charles Cadieux, Lisa Dang, Emily Deibert, Xavier Dumusque, Dasaev O. Fontinele, Yolanda G. C. Frensch, Frédéric Genest, Roseane de Lima Gomes, Nicole Gromek, Melissa J. Hobson, Vigneshwaran Krishnamurthy, Khaled Al Moulla, Ares Osborn, Caroline Piaulet-Ghorayeb, Bennett Neil Skinner, Avidaan Srivastava, Atanas K. Stefanov, Joost P. Wardenier, Drew Weisserman, Vincent Yariv
Statistical Mechanics
Wavelet Localisation and Local Modulation Freezing in MRW Unwrapping
Mateusz Polakowski and Zbigniew R. Struzik
We develop a localised wavelet formulation of multifractal random walk unwrapping based on the local multiplicative modulation freezing. The framework is motivated by the observation that finite-support wavelet localisation may induce approximate local factorisation of multiplicatively modulated
stochastic fields, allowing the modulation component to become effectively frozen within sufficiently localised probing domains. Within this regime, logarithmic wavelet amplitudes admit an approximate additive decomposition linking local wavelet statistics directly to the underlying modulation field. This viewpoint reformulates covariance-based MRW unwrapping as a localised multiscale operator problem in which wavelet coefficients act as finite-support probes of multiplicative organisation. The validity of the approximation depends explicitly on support geometry, scale-dependent overlap, and residual multiscale mixing generated by internal modulation variability. We show that these effects naturally produce finite-scale deviations from ideal logarithmic covariance scaling and lead to structured covariance distortions whose form depends on the interaction between the modulation field and the geometry of the wavelet representation. In the resulting framework, localisation itself becomes the operational mechanism enabling multiscale probing of local
stochastic organisation. Numerical investigations using orthonormal wavelet decompositions support the proposed interpretation and demonstrate the emergence of scale-dependent freezing regimes, residual covariance mixing, and finite-support breakdown effects consistent with the theory. The proposed framework suggests a broader connection between wavelet localisation, local regularity organisation, and finite-support multiscale
stochastic operators. Wavelet localisation becomes an operational mechanism for probing localised multiscale structure.
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Mesoscale and Nanoscale Physics
Quantum Information Geometry of Multicomponent Superconducting Fluctuation Transport
Zi-Ting Sun, Ying-Ming Xie and Naoto Nagaosa
Quantum geometry underlies many electronic responses, but its transport signatures have so far been established mainly for pure single-particle Bloch states. Whether collective many-body fluctuations possess a measurable
quantum geometry remains largely unexplored. Here we show that superconducting fluctuation transport provides a direct probe of
quantum information geometry in collective many-body matter. Starting from a multicomponent time-dependent Ginzburg-Landau theory in the Gaussian fluctuation regime, we identify the
equilibrium density
matrix of fluctuating Cooper pairs as the static pair propagator, which defines a positive mixed-state
manifold in momentum space. The geometry of this
manifold is directly measurable through paraconductivity: the longitudinal paraconductivity is governed by the
quantum Fisher information of superconducting fluctuation modes, while the fluctuational anomalous
Hall effect is governed by the mean Uhlmann
curvature, the mixed-state counterpart of Berry
curvature. This correspondence further yields
geometric bounds between these two transport components, with no direct analogue in normal electronic transport. Applied to
chiral superconducting fluctuations in quarter-metal systems motivated by rhombohedral multilayer
graphene, a
symmetry-allowed Lifshitz invariant generates finite mean Uhlmann
curvature and logarithmically enhances the anomalous
Hall conductivity above the critical temperature. Our results establish collective superconducting fluctuations as an experimentally accessible transport probe of mixed-state
quantum information geometry.
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Quantum Physics
A Gauge-Covariant Geometric Framework for Non-Hermitian Quantum Systems
Gargi Das, Sudhanshu Shekhar and Bhabani Prasad Mandal
We develop a comprehensive, gauge-covariant
geometric framework for non-Hermitian
quantum systems in the quasi-Hermitian regime, that is, the region of parameter space where the non-Hermitian
Hamiltonian admits a real spectrum and a positive-definite metric operator. We build this framework by elevating the Dyson map to a central
geometric object. This map is the transformation that converts a non-Hermitian
Hamiltonian into an equivalent Hermitian one. From it we construct the Dyson connection and decompose it into Hermitian and anti-Hermitian parts, identified respectively as stretching and rotation components. This decomposition cleanly separates the genuine physical metric deformations from the
unitary gauge redundancies. Working with manifestly gauge-covariant states, we then derive the complex non-Hermitian Berry phase and the
quantum geometric tensor (QGT), and show that the non-Hermitian
geometric curvature originates from the non-commutativity of the stretching components at the operator level. We further analyse the
geometric singularities near an exceptional point (EP) and uncover a distinct hierarchy of divergences. For a general two-level non-Hermitian model, the
quantum metric tensor (QMT) exhibits a leading-order divergence $\sim |\epsilon_\mu|^{-2}$, while the Berry
curvature shows a weaker, subleading divergence $\sim |\epsilon_\mu|^{-3/2}$, with $\epsilon_\mu$ denoting the parameter displacement from the EP along an individual parameter axis $\mu$. Finally, we examine physical realizations of this model, including the non-Hermitian Su–Schrieffer–Heeger (SSH) and Hatano–Nelson (HN) models, where exact analytical results confirm the predicted critical scaling laws and illustrate the metric-deformation-driven non-Hermitian geometries.
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