Quantum Physics
Identifiability and Estimation Precision in Quantum Network Tomography with Imperfect Bell-State Measurements
Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley et al. (+3 more)
We study
Quantum Network
Tomography (QNT) for end-to-end link-error characterization under imperfect Bell-state measurements (BSMs), where multiplicative coupling between link and measurement parameters makes identifiability non-trivial. For an n-node
star network, we design probes that ensure unique identifiability and derive closed-form expressions for the Fisher Information
Matrix (FIM) and Maximum Likelihood
Estimators (MLEs), and characterize estimation precision through the Cramer-Rao Bound (CRB). The results show that BSM imperfections degrade estimation precision, while the proposed probes maintain nearly stable precision for individual link parameters as the network size increases. Monte Carlo simulations further confirm that the Mean Squared Error (MSE) approaches the CRB with increasing sample size.
Read the full abstract ▾
All authors Athira Kalavampara Raghunadhan, Matheus Guedes De Andrade, Don Towsley, Indrakshi Dey, Daniel Kilper, Nicola Marchetti
Quantum Physics
Programmable Doppler real-space pattern formation in cold atoms
Yijun Tang
Red-detuned Doppler cooling decelerates atomic motion toward zero velocity, whereas blue-detuned light produces acceleration that separates a cold cloud into finite-velocity packets. Here we combine these complementary dynamics in a programmable split-stop protocol for real-space pattern formation. During each stage, a blue-detuned pulse splits existing packets and drives them apart, while a subsequent red-detuned pulse returns their center-of-mass velocities close to zero, results in spatially resolved stationary packets. Repeating this process recursively multiplies the number of packets in real space. We model the dynamics using
stochastic photon-jump simulations that include absorption and spontaneous-emission
recoil in one and two dimensions. Using experimentally realistic parameters for the $689~\mathrm{nm}$ ${}^{1}S_{0}\rightarrow{}^{3}P_{1}$ transition of ${}^{88}\mathrm{Sr}$, we demonstrate an 8-packet one-dimensional array and a 64-packet two-dimensional square array.
Read the full abstract ▾
Cosmology and Nongalactic Astrophysics
Simulation Tests of PSF Modeling for Cosmic Shear with the Vera C. Rubin Observatory
Claire-Alice Hébert, Erin S. Sheldon, Tianqing Zhang et al. (+3 more)
Exceptional control of systematic effects is required in order to achieve unbiased
cosmic shear two-point correlation function measurements with the next generation of
galaxy imaging surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). One critical challenge is accurately modeling the point-spread function (PSF), as errors in PSF estimation can introduce spatially correlated biases in
galaxy shape measurements. The LSST Science Pipelines, which will be used to process Rubin data, include an implementation of the PIFF (PSFs in the Full Field of View) package originally developed for, and demonstrated to perform well on, DES-Y3 and Y6 data. In this work we use semi-realistic image simulations, mimicking LSST observing conditions in $i$-band over 100 square degrees, to perform an end-to-end test of the Rubin PSF modeling pipeline. PSF model residuals are quantified using both second- and fourth-order moment parameters and performance is evaluated, for both LSST year 1 and year 10 depth, with a series of diagnostic tests. We find that the additive bias contribution from PSF modeling errors to the non-tomographic
cosmic shear data vector is well below 30% of the
cosmic shear uncertainty estimated from our analytic covariance
matrix. Though our simulations exclude several known effects that may further challenge PSF modeling, these results demonstrate promising performance from PIFF on LSST-like data and provide an early
benchmark for ongoing PSF validation efforts for LSST weak
lensing analyses.
Read the full abstract ▾
All authors Claire-Alice Hébert, Erin S. Sheldon, Tianqing Zhang, Joachim Harnois-Déraps, Mike Jarvis, the LSST Dark Energy Science Collaboration
High Energy Astrophysical Phenomena
Galactic Electron-Positron Annihilation Emission from X-Ray Binaries with Transient and Persistent Jets
Argen Gian Detoito and Henric Krawczynski
The
Galactic Center exhibits a persistent 0.511 MeV emission characteristic of electron-positron annihilation. Various astrophysical sources may be responsible for supplying the positrons, yet their contributions with respect to the total annihilation rate is uncertain. X-ray binaries have historically been a primary candidate, possibly contributing a significant fraction of the
Galactic positrons. X-ray binaries can produce positrons through the Blandford-Znajek mechanism, two-
photon pair production in the corona, and/or one-
photon pair production for strongly-magnetized compact objects. These positrons may then be channeled into the Interstellar Medium through jets or winds. In this work, we argue that X-ray binaries cannot contribute to the electron-positron annihilation flux alone. We present 0.511 MeV line fluxes and all-sky maps produced by X-ray binaries and
stellar flares from the
Galactic stellar population, along with the gamma-ray continuum from positrons produced by X-ray binaries. To do so, we solve the particle transfer equation using Green's functions. The total morphology is slightly asymmetric towards negative longitudes and positive latitudes. We find five 0.511 MeV flux hotspots in the generated all sky maps and scrutinize the contribution of individual sources to these hotspots. Observations of these hotspots can reveal the contribution of X-ray binaries to the
Galactic positrons. The upcoming Compton Spectrometer and Imager (COSI) mission could image a hotspot near Cygnus X-1. The detection of the other hotspots requires a
telescope with improved arcminute angular resolution.
Read the full abstract ▾
Computational Physics
Inverted model selection in physics-informed neural networks: when a lower residual selects a worse solution
Rabiu Musah
Physics-informed neural networks (PINNs) are commonly evaluated via a single aggregate residual, assuming a smaller residual indicates a better solution. Testing this directly across three constrained PDE systems, I find this assumption can systematically fail. In matched pairs of solvers differing only in whether a defining structural identity is hard-wired or penalized, the penalized variant frequently attains a lower equation residual while violating that identity by several orders of magnitude, causing the exact variant to be falsely ranked worse. Over 64 matched pairs spanning two systems, four network variants, and eight seeds, this inversion occurs in 83% of cases (95% Wilson CI: 72–90%), with rates from 72% to 94% across systems. Testing across six architectures–MLP, cPINN, XPINN, hp-VPINN, and physics-informed DeepONet and FNO–inverts the ranking in 46 of 48 pairs, indicating that this variability is problem-dependent rather than specific to the approximator. A third, larger vorticity–streamfunction problem shows the same ordering: the residual-optimal solver violates its structural identity by over six orders above tolerance, despite a residual margin of only 9.37%. Because a scalar loss cannot expose this, I introduce a lexicographic admissibility gate spanning the structural identity, boundary trace, and a solvability integral that must vanish independently of the equation residual. All three must pass before residuals can compete. This gate catches three artifact classes but misses a fourth: a prescribed-structure prior yields fields that pass every single-run check, yet deleting the source term reveals that 97% of the reported structure survives removal of the physics. Reference data and figures accompany the paper.
Read the full abstract ▾
Optics
Simultaneous Intensity and Frequency Control for Optical Waveform Generation using an Acousto Optic Modulator
Hariprasad Madathil, Shengzhi Wang and F. Elohim Becerra
We describe a method for calibrating the response of an acousto-optic modulator (AOM) to enable precise, arbitrary control of the intensity and frequency of optical fields. The method involves characterizing the nonlinear response of the AOM to its input RF drive voltage and applying an iterative calibration/correction
algorithm to accurately map input RF amplitude and frequency drive to output optical intensity and frequency shifts. After a few calibration/correction iterations, the calibration of the AOM maintains the optical power within 1$\%$ of a constant target value over relatively wide frequency tuning range ($\approx$100 MHz), with $\sigma=0.2\%$ relative deviation. We apply this calibration method to generate programmable waveforms and optical pulses with tailored intensity and frequency profiles that closely match their target specifications. This technique offers a simple and robust method for applications that require high-accuracy optical modulation.
Read the full abstract ▾
Applied Physics · Cross-listed from cs.LG
Read, Write, Relax: Why Neural PDE Surrogates Need Both Global and Local Processing
Anuj Kumar, Heiko Zimmermann, Josiah Bjorgaard et al. (+4 more)
Recent mesh-based simulation advances have, in no small part, relied on neural surrogates of two distinct families: global models that route information through a small set of latent
tokens, and local models that perform message passing across mesh edges. Consistent with both classes is the inability to perform beyond low-dimensional problems and small-scale or oversimplified meshes, the simulation regimes where industrial problems reside. Our work shows this explicitly and presents a unified formulation. In global approaches, latent-
token attention acts as a spatial low-pass filter, while local message passing lacks the global reach necessary to propagate information across large mesh spaces. Viewed through the error, the two operators are the halves of a multigrid cycle: one corrects errors at the lower end of the spectrum, the other at the higher end, and neither can do the other's job. We introduce Read-Write-Relax (RWR), which interleaves latent
attention with message-passing relaxation under a unified formulation. The interleaved processor lowers error across the entire spectrum, making RWR the most accurate model in nearly every comparison across our industrial and public
benchmarks. It is also markedly data-efficient in the scarce-data regimes, accurate on the engineering quantities of interest, and scales full-field predictions to challenging, large-scale problems.
Read the full abstract ▾
All authors Anuj Kumar, Heiko Zimmermann, Josiah Bjorgaard, Jacan Chaplais, Nikolaos Bouklas, Matteo Salvador, Alexander Lavin
General Relativity and Quantum Cosmology
Kerr-Newman and genuine Kerr black holes in the Bertotti-Robinson magnetic field
Hryhorii Ovcharenko and Jiri Podolsky
We present a spacetime that describes a rotating and charged black hole immersed in an external
magnetic field. This exact solution to the Einstein-Maxwell equations has a surprisingly simple form which reduces to standard Kerr-Newman metric, and to the uniform Bertotti-Robinson
magnetic universe. We show that the Kerr-BR solution presented in [Phys. Rev. Lett. 135, 181401 (2025)] has a special charge, and we identify a genuine Kerr black hole without any charge, in the
magnetic field. In the weak-field limit it gives the Wald solution. We analyze main physical properties of the new family, namely singularities, horizons, regularity of axes, charges,
entropy and temperature.
Read the full abstract ▾
Quantum Physics
Tasdiqul Islam, Rasman Mubtasim Swargo, Engin Arslan et al. (+1 more)
Conventional
Quantum Key Distribution (QKD) requires the transmission of
qubits proportional to or exceeding the length of the key, as protocols such as BB84 transmit more
qubits than the final key size due to basis sifting and
privacy amplification. Since
quantum networks are still in their infancy and have limited capacity, this overhead puts significant pressure on network resources. To address this issue, we propose a Multi-
Qubit Greenberger–Horne–Zeilinger (GHZ) State-based QKD scheme that reduces the number of
qubits transmitted over the
quantum channel. The proposed method transmits one GHZ
qubit between endpoints and reuses the resulting
entanglement to convey multiple classical key bits with the help of
Quantum Non-Demolition (QND) measurements. Under the stated assumptions on authenticated classical communication, local reset verification, and bounded-error QND discrimination, one can transfer $L$ classical bits by generating an (L+1)-
qubit GHZ state and transferring one
qubit to the remote party. We verify correctness using the NetSquid
quantum network simulator: the protocol achieves 100% raw-key fidelity for keys of length up to 12 bits under both ideal conditions and depolarizing noise up to p = 0.005 per round. We further show that the proposed QKD
algorithm can be extended to multi-party QKD and server-client deployment. The proposed scheme offers a transmitted-
qubit-efficient, noise-tolerant alternative for bandwidth-limited
quantum networks.
Read the full abstract ▾
All authors Tasdiqul Islam, Rasman Mubtasim Swargo, Engin Arslan, Md Arifuzzaman
Statistical Mechanics
Emergent Second Law for Time-Dependent Nonequilibrium States
Nahuel Freitas, Timur Aslyamov and Massimiliano Esposito
For nonautonomous open systems described by macroscopic
stochastic thermodynamics, we derive an emergent second law that constrains time-dependent macroscopic fluctuations by the
entropy production along the most probable
evolution under the time-reversed driving protocol. We show that this bound can be understood as a macroscopic consequence of the fluctuation
theorem: the time reverse of this
evolution provides a possible fluctuation path under the forward dynamics. In the linear-response and slow-driving regime, the bound becomes an equality to first order and generalizes the McLennan-Zubarev formula to the time-dependent probability density of nonautonomous systems with weak nonconservative affinities. We illustrate our results in a bistable system under sudden quenches and periodic driving.
Read the full abstract ▾
Instrumentation and Detectors
Precise Modeling of a Complex Solenoidal Magnetic Field Using a Combination of Analytic Functions and a PINN
Cole Kampa, Susan Dittmer, Henry Glass et al. (+1 more)
We demonstrate an iterative approach to modeling a sparsely measured
magnetic field in a large-bore solenoid. This approach uses a hybrid of traditional and machine learning techniques. The traditional technique is a linear least-squares fit using a series solution to Laplace's equation, while the machine learning technique involves the training of a physics-informed neural network (PINN) on the least-squares fit residuals. We use a newly defined activation function "DELTAsnake," a modification to the snake activation function proposed by Ziyin et al. that allows for stronger
curvature and non-monotonicity. The combined model approximately obeys Maxwell's equations to a level sufficient for producing high quality physics simulations and analysis. Our approach is applied to a highly realistic calculation of the expected
magnetic field in the Mu2e experiment's Detector Solenoid which includes a simple model for the expected statistical measurement uncertainties. Using ten toy measurement simulations, we demonstrate the capabilities of our model in comparison to the least-squares method alone; the least-squares method alone results in a reduced chi-squared statistic of ${2.15 \pm 0.01}$, while our approach improves the reduced chi-square to ${1.034 \pm 0.005}$. Furthermore, for an average toy simulation, we show that the range of the RMS of the three field component residuals reduces from ${0.07-0.37}$ Gauss to ${0.05-0.07}$ Gauss. We find that this novel method is robust against a realistic systematic uncertainty deriving from
Hall probe calibration bias and can be used to significantly reduce the number of measurements required to achieve an accurate model.
Read the full abstract ▾
All authors Cole Kampa, Susan Dittmer, Henry Glass, Michael Schmitt
Materials Science
Attractor-Basin-Limited Fidelity in Reproducible Multistate Vortex Memory
M. Rabiu, S. S. Abukari and M. Amekpewu
Multilevel non-volatile
memory technologies face recurring trade-offs among information density, endurance, retention, and switching energy. We investigate an alternative state variable based on the discrete
vortex configuration of self-organized
vortices in a boundary-driven electron fluid. A dissipative point-
vortex model derived from magnetohydrodynamic dynamics yields six reproducible
vortex codewords, corresponding to 2.585 bits per
cell, whose write fidelity, noise sensitivity, 100-cycle endurance, and effective information capacity are quantified. The ordering of their finite-amplitude basin radii $r_{50}$ differs from that predicted by both fixed-circulation and fully coupled linear-stability spectra. A nonlinear saddle-point construction based on the reduced dynamics likewise does not recover the measured basin ordering. The discrepancy is associated with escape pathways involving coupled position–circulation dynamics that are absent from the fixed-circulation description. These results show that local stability alone does not determine the finite perturbation tolerance of the
vortex states considered here. The proposed
memory requires active hold power, and passive retention remains to be established experimentally.
Read the full abstract ▾
Quantum Physics
Measurement and reload costs in direct quantum simulation of nonlinear waves
Ziqing Guo, Viraj Dsouza, Alex Khan et al. (+3 more)
Quantum processors encode an N-point field in log_2(N)
qubits, which renders nonlinear wave equations an important application for
quantum simulation. Nonlinear
evolution, however, requires the field values themselves, and these are not directly accessible without
quantum measurement. Existing
algorithms circumvent this measurement through linear
embeddings and state copies, thereby obscuring its cost within the truncation order, the auxiliary dimensions, and the state preparation. In order to expose this cost, a hybrid split-step solver is proposed in which the field is measured, updated classically, and reloaded at every step, with all shots and gates accounted for in a single cost-and-error model. Since the entire field is available at every step, a property unavailable to linear approximations in strongly nonlinear regimes, the design of the solver reduces to a budgeting problem over the timestep, the
polynomial degree, and the shot count. The coherent kernels of the solver are validated on superconducting hardware. An identical structure and bottleneck govern the viscous Burgers' equation in one and two dimensions. Because every step reads the full field, the
quantum cost per step, measured as
circuit depth multiplied by measurement shots, exceeds the classical cost with increasing grid size. The framework consequently identifies a coherent, measurement-free nonlinear update as the quantitative target that any end-to-end advantage must meet.
Read the full abstract ▾
All authors Ziqing Guo, Viraj Dsouza, Alex Khan, Abhishek Chopra, Rut Lineswala, Ziwen Pan
Materials Science
Charge Transport Framework for Crystalline pi-Conjugated Materials
Nisarg Trivedi, Maximilian F.X. Dorfner, Michel Panhans et al. (+1 more)
Quantitative charge-transport modelling in crystalline pi-conjugated
polymers requires an electronic representation that captures extended conjugation and material-specific electron-
phonon interactions on equal footing. We present a Wannier-orbital-based formulation of the transient-polaron-localization (TPL) framework for quantitative charge-transport simulations in crystalline pi-conjugated
polymers. By expressing all interactions directly in a Wannier representation derived from first-principles calculations, the approach avoids artificial fragmentation of
polymer backbones and enables a consistent, material-specific description of electronic couplings and electron-
phonon interactions. Low- and high-frequency vibrational modes are incorporated within a mode-resolved TPL formalism, yielding an effective electronic
Hamiltonian that captures both dynamic disorder and polaronic renormalization. The methodology is demonstrated for the ambipolar crystalline naphthalenediimide-bithiophene copolymer, enabling a direct comparison of electron and hole transport along the
polymer backbone and pi-stacking directions. The simulations reproduce key transport features, including pronounced anisotropy and higher electron than hole mobility. Additional studies on single- and bi-chain systems reveal the essential role of inter-chain coherence in supporting efficient transport along the
polymer backbone. Beyond this specific system, the Wannier-orbital-based TPL framework provides a transferable route to disentangle intrinsic charge-transport mechanisms in crystalline pi-conjugated materials and establishes a foundation for future work.
Read the full abstract ▾
All authors Nisarg Trivedi, Maximilian F.X. Dorfner, Michel Panhans, Frank Ortmann
Mathematical Physics
How Much Geometry Does Newtonian Dynamics Fix?
C S López-Monsalvo
Newtonian mechanics is usually written on a spacetime of fixed geometry. Here we build that geometry, introducing a propagator and a bilinear form only as the description demands. Within this reconstruction the Principle of Inertia emerges as a
theorem rather than an independent postulate. Inertial motion is blind to the scale of the form and to the torsion the propagator defines, and that blindness is a
geometric precursor of the universality of free fall, before
gravity enters. Newton's Second Law is a compatibility between two derivatives along a curve. The force exceeds the mass times the lowered acceleration by an exact term, and the law survives arbitrary torsion. Requiring force-free motion to be inertial along curves parametrised by arc length restricts the torsion to be totally antisymmetric. The remaining torsion is a three-form which we postulate the particle carries along its worldline. Its contraction with the velocity annihilates that velocity, so the supplementary condition of spinning-particle mechanics holds identically, and we propose that contraction as a classical
spin. The
algebra is familiar from relativistic
spin hydrodynamics; the assignment, to the best of our knowledge, has not been proposed elsewhere. Since inertial motion resolves neither the mass nor the
spin, the predictive content lies in the transport law we postulate, which turns the
spin against a parallel-transported frame at a rate fixed by the acceleration alone and by no coupling constant. That rate becomes a laboratory number only once the arc-length parameter is identified with a clock, which we leave open. The dynamics asks non-degeneracy of the form, so this spacetime is not Newton–Cartan's Galilean one, and gravitation lies outside the construction. We prove every mathematical result, make three constitutive postulates and one physical
conjecture.
Read the full abstract ▾
Instrumentation and Methods for Astrophysics
Image persistence flagging for SPHEREx
Candice Fazar, C. Darren Dowell, Brendan P. Crill et al. (+3 more)
Image persistence in HAWAII-2RG HgCdTe detectors has been observed by multiple parties. Also known as latent signal, this effect occurs when sensor images following an illumination show a decayed form of the illuminated image even though the source has been removed and the detector has been reset. Using data from an engineering grade detector array delivered for SPHEREx testing illuminated with a wide range of fluxes, we demonstrate an interpretation and a working model from which the decaying signal can be estimated, providing the ability to flag pixels subject to excess persistence current beyond a specified threshold. Simulated persistence images allow validation of the module and prediction of its effect in flight data.
Read the full abstract ▾
All authors Candice Fazar, C. Darren Dowell, Brendan P. Crill, Phil Korngut, Chi Nguyen, Howard Hui
Quantum Physics
Increased cyclicity of atomic transitions via coherent interference of decay paths
Eliza Cornell, Benjamin Pingault, Gergő Thiering et al. (+3 more)
Optical readout is a fundamental tool in atomic state measurement, yet the fidelity of optical readout is frequently limited by imperfect
photon collection. This can be mitigated when readout occurs on a cycling transition which continuously fluoresces under resonant excitation, thus increasing signal and enabling single-shot readout. We present a method to extend the cyclicity of atomic transitions via coherent destructive interference between spurious decay paths. We describe the characteristics of atomic systems in which this method can be implemented and model several examples in which the number of emitted
photons is increased by multiple orders of magnitude.
Read the full abstract ▾
All authors Eliza Cornell, Benjamin Pingault, Gergő Thiering, Neil Sinclair, Ádám Gali, Marko Lončar
Statistical Mechanics · Cross-listed from q-bio.MN
Motional Degrees of Freedom in Network Hamiltonian Models
Peng Huang, Elizabeth M. Diessner and Carter T. Butts
Network
Hamiltonian Models (NHMs) provide an efficient framework for modeling the aggregation of interacting particles (e.g., the condensation of
proteins into gel-like, oligomeric, or fibrillar states), representing the system as a network whose edges represent bound interactions. Terms within the network
Hamiltonian represent multi-body interactions governing aggregation behavior, and are specified via topological degrees of freedom. Because motional degrees of freedom are not explicitly represented within the NHM, their influence must be indirectly accounted for by introduction of corresponding terms to the
Hamiltonian. Here, we describe specifications for terms representing motional degrees of freedom of two, three, and four-body interactions. We also consider the impact of these terms on the aggregation states of a minimal system governed only by a pairwise edge potential, showing that three and four-body interactions favor condensation of the system into small droplet-like structures at low temperature.
Read the full abstract ▾
Materials Science
A high-entropy form of $R$Mn$_6$Sn$_6$ with distinct magnetotransport regimes correlated to different magnetic structures
Kyle W. Fruhling, Jonathan Gaudet, William D. Ratcliff et al. (+10 more)
The kagome $R$Mn$_6$Sn$_6$ material family has attracted significant
attention as high-temperature metallic magnets with a host of different
magnetic orderings and anisotropy. Theoretical studies point to the rare-earth ($R$) as the determining factor for both the direction of
magnetic anisotropy and the type of
magnetic ordering in a given compound. This motivates studying high-
entropy forms of $R$Mn$_6$Sn$_6$ to examine how the interplay of several rare-earth elements leads to different
magnetic states in a single
crystal. Here, we present a rare-earth mix of Tb, Dy, Ho, Er, Tm, and Lu that produces phase transitions from a paramagnet to an easy-plane ferrimagnet (FiM) below $T_{\text{C}}$ = 380 K, then to a FiM easy-axis state at $T_{\text{SR1}}$ = 207 K, to a canted FiM ground state below $T_{\text{SR2}}$ = 79 K. This behavior is consistent with previously reported high-
entropy $R$Mn$_6$Sn$_6$ compounds; however, uniquely, the rare-earth mix studied here exhibits a broad transition from easy-plane to easy-axis anisotropy from 270 K to 170 K, and reveals a nonmonotonic magnetoresistance. Using
neutron scattering data, we found that both observations correlate with an incommensurate modulated contribution to the
spin state due to competing rare-earth interactions. This magnetoresistive behavior and the correlated
spin structures underscore the potential for rare-earth engineering of magnetism.
Read the full abstract ▾
All authors Kyle W. Fruhling, Jonathan Gaudet, William D. Ratcliff, Jonathan S. White, Siddharth Nandanwar, Noah J. Fau, Gregory T. McCandless, Enrique O. González Delgado, Julia Y. Chan, Oksana Zaharko, Michael A. Susner, Michael J. Newburger, Fazel Tafti
Soft Condensed Matter
Electrostatic Persistence Length Revisited. II. Simulations and Comparison to Experiment
Alexey A. Gavrilov, Albert Johner and Artem M. Rumyantsev
For decades, debate has surrounded the electrostatic persistence length (EPL) controlling local polyelectrolyte stiffening, centered on two competing power laws: the linear BJ prediction, $\textbf{l}_\mathrm{e} \sim r_\mathrm{D}$, and the quadratic OSF/KK scaling, $\textbf{l}_\mathrm{e} \sim r_\mathrm{D}^{2}$, where $r_\mathrm{D}$ is the Debye screening length. Building on the asymptotic scaling theory developed in the accompanying paper, we validate a complete diagram of limiting regimes using large-scale coarse-grained Monte Carlo simulations of ideal chains with charged monomers interacting through a screened Coulomb potential. By simulating long chains of up to $N \simeq 10^{4} - 10^{5}$ Kuhn segments, we demonstrate that the electrostatic stiffening of both semiflexible and flexible polyelectrolytes obeys the same quadratic OSF/KK law. We track the exponent $\alpha$ which measures how the chain size $R$ grows with the Debye radius, $R \sim r_\mathrm{D}^{\alpha}$. For both cases, in agreement with the OSF/KK theory, $\alpha$ rises past 3/5 and slowly approaches 1 as the chain length increases, whereas within the BJ theory it can never exceed 2/5. We further find that three common size measures, the end-to-end distance $R_\mathrm{ee}$, radius of gyration $R_\mathrm{g}$, and hydrodynamic radius $R_\mathrm{h}$, reach this asymptotic behavior at progressively increasing chain lengths. Consequently, for any real polyelectrolyte, the apparent exponents obey $\alpha_\mathrm{ee} \geq \alpha_\mathrm{g} \geq \alpha_\mathrm{h}$, making $R_\mathrm{g}$ a sharper experimental probe than $R_\mathrm{h}$. Finally, we re-analyze the available experimental data and show that they rule out the linear BJ law and support the quadratic KK scaling, thereby resolving contradictions that stem from mistaking the apparent slopes measured for short chains for the true asymptotic exponent.
Read the full abstract ▾
Materials Science
Vibrational, structural, and chemical fingerprints of ion diffusion in crystalline solids
Gavin Winter, Juno Nam and Rafael Gómez-Bombarelli
Predicting mobile-ion self-diffusivity $D^*$ from molecular dynamics (MD) simulations is essential for identifying promising solid-state electrolytes, but directly simulating ion
diffusion is computationally expensive, particularly with high-accuracy machine learning interatomic potentials (MLIPs).
Diffusion is a slow, emergent process that requires long trajectories to converge. Thermodynamic properties, by contrast, converge much faster: the enthalpy $h$, vibrational
entropy $s_{vib}$, and 2-body, excess configurational
entropy $s^{ex}_{2,config}$ can be extracted from comparatively short MD trajectories, and they encode rich information about the free energy landscape from which transport properties like self-diffusivity ultimately arise. Intuitive correlations are discussed between these thermodynamic properties and ion
diffusion, motivating a data-driven approach to exploit this link. A simple neural network was trained to predict diffusivity from features computed over short MD trajectories: a vibrational fingerprint (the vibrational density of states, VDOS) and a structural fingerprint (the radial distribution function, RDF), conditioned on chemistry information encoded in the MLIP
embedding. This combination allows the model to predict the converged $\log_{10} D^*$ (cm$^2$/s) \textemdash\ normally obtained from significantly longer MD simulations \textemdash\ with a mean absolute error of 0.398 and a Spearman's rank correlation $\rho$ of 0.844.
Read the full abstract ▾
General Relativity and Quantum Cosmology
Beyond de Sitter: Longitudinal-Mode Instabilities and Spectral Evolution of Massive Vector Fields with Non-Minimal Curvature Coupling during Inflation
Ehsan Momeni and Fatimah Shojai
We investigate the inflationary dynamics of a spectator massive vector field with a non-minimal
curvature coupling in de Sitter (dS) and quasi-de Sitter (qdS) backgrounds, focusing on the transverse and longitudinal sectors. By solving the mode equations with Bunch-Davies initial conditions, we compute the spectral energy densities and quantify the deviations between the exact dS approximation and the slow-roll-corrected qdS
evolution. We find that the coupling parameter xi significantly affects the
evolution of the effective mass, the mass-crossing condition, and the behavior of the longitudinal mode. In particular, increasing xi suppresses the vector fluctuations and reduces transient tachyonic effects. We further follow the
evolution of the modes into the radiation-dominated era, showing how the inflationary initial conditions determine the subsequent spectral energy densities. Our results identify the parameter regime in which the dS approximation provides an accurate description and determine when slow-roll corrections become relevant.
Read the full abstract ▾
Physics Education
AI-Augmented Inquiry and Regulation in Hybrid Systems: A Control Allocation Architecture for Preserving Epistemic Agency in Hybrid Human-AI Cognition
Jochen Kuhn, Peter Gerjets, Ulrich Trautwein et al. (+4 more)
Generative artificial intelligence (genAI) systems are increasingly integral to epistemic processes such as hypothesis generation, explanation construction, and decision-making. Although they reliably enhance performance, emerging evidence reveals a metacognitive dilemma: as external generative capacity increases, internal monitoring, calibration, and cognitive engagement may decline. This reflects a redistribution of cognitive control within distributed human-AI systems that cannot be explained by automation bias or reliance on
algorithms alone. We propose the AIRIS (AI-Augmented Inquiry and Regulation in Hybrid Systems) framework to analyze this dilemma and specify where regulatory intervention can counteract it. AIRIS is a multi-level control allocation architecture specifying the conditions under which epistemic agency can be preserved in hybrid generative systems. Drawing on distributed cognition, cognitive load theory, multimedia learning, and self-regulated learning, it identifies seven interacting mechanisms through which hybrid cognition may become destabilized, from delegation and calibration drift to motivational-affective drift. Five regulatory operators (Anticipate, Interrogate, Reflect, Integrate, and Synthesize) target internal generative engagement at points of emerging instability. The architecture does not itself improve learning; it specifies what must remain in place for genAI-supported work to sustain understanding, whether through instructional design, teacher guidance, or learners' own regulation. We derive testable propositions concerning the seven mechanisms and the five operators, reframing AI augmentation as a problem of control allocation in distributed generative systems. Beyond theory, AIRIS offers a research agenda, a design framework for genAI-integrated learning environments, and a conceptual toolkit for the governance of hybrid human-AI cognition.
Read the full abstract ▾
All authors Jochen Kuhn, Peter Gerjets, Ulrich Trautwein, Jeffrey A. Greene, Sarah Malone, Patrik Vogt, Tim Fütterer
Soft Condensed Matter
Electrostatic Persistence Length Revisited. I. Theory
Artem M. Rumyantsev, Alexey A. Gavrilov and Albert Johner
The problem of single-chain conformations of polyelectrolytes in salt-added dilute solutions, and the associated concept of the electrostatic persistence length $\textbf{l}_\mathrm{e}$, has remained unresolved for decades. To address this challenge, we develop a comprehensive scaling theory and corroborate it with simulations. A unified scaling diagram is constructed that encompasses both flexible and intrinsically semiflexible/stiff polyelectrolytes. Nine distinct scaling regimes are identified, each characterized by different conformational statistics. The concept of the Gaussian electrostatic blob $\xi_\mathrm{e}$ used in the description of flexible polyelectrolytes is extended to the semiflexible case, and the new characteristic length $\xi_\mathrm{e}^{|}$ referred to as the rodlike electrostatic blob is introduced. This enables delineating the important crossovers and showcasing an analogy between semiflexible and flexible chains. The concept of electrostatic excluded volume is also reconsidered and generalized. Upon increasing the salt concentration, i.e., decreasing the Debye length $r_\mathrm{D}$, chain conformations evolve from (i) rodlike stretches to (ii) Gaussian and then (iii) swollen coils with local electrostatic stiffening characterized by $\textbf{l}_\mathrm{e}$, followed by (iv) swollen coils without stiffening but with electrostatic exclude volume, and finally to (v) quasi-neutral Gaussian coils. In regimes of type (ii) and (iii), the electrostatic persistence length scales quadratically with $r_\mathrm{D}$, in agreement with the OSF and KK predictions for semiflexible and flexible chains, respectively: $\textbf{l}_\mathrm{\mathrm{OSF}} \simeq r_\mathrm{D}^{2}/\xi_\mathrm{e}^{|}$ and $\textbf{l}_\mathrm{\mathrm{KK}} \simeq r_\mathrm{D}^{2}/\xi_\mathrm{e}$. These asymptotic scalings are confirmed by coarse-grained simulations presented in the accompanying article.
Read the full abstract ▾
Quantum Physics
Prior-Informed Adaptive Shifts for Sequential Minimal Optimization in Variational Quantum Eigensolvers
Frederik Stalschus, Samuele Pedrielli, Stefan Kühn et al. (+3 more)
Sequential minimal optimization methods, such as the Rotosolve and the Nakanishi-Fujii-Todo
algorithm (NFT), are widely used for Variational
Quantum Eigensolvers (VQEs). These methods optimize one parameter direction at a time, requiring measurements at only a few locations along that direction. In the presence of measurement shot noise, however, their performance depends critically on the choice of measurement locations, and recent studies suggest that equidistant measurements are optimal. However, we often observe that equidistant measurements are not always optimal in practice. We argue that this discrepancy between theory and practice arises from the fact that two assumptions underlying previous analyses do not generally hold: (1) the absence of prior knowledge about the energy minimizer, and (2) the use of the uncertainty of the estimated energy as a proxy for optimization performance. In this paper, we develop a new theory for determining optimal measurement locations. First, we show that incorporating prior information about the minimizer is beneficial. Early in optimization, when little is known about the pivot, i.e., the current minimizer, equidistant measurements are indeed near-optimal, but as the prior belief sharpens the optimal locations move away from equidistant. Second, rather than analyzing the uncertainty of the estimated minimum energy, we study the uncertainty of the
estimator of the minimizer itself, which leads to substantially different strategies. Based on this analysis, we propose Prior-informed Adaptive Shifts (PAS), a method that automatically adjusts measurement locations during optimization. Numerical experiments across different shot counts and problems validate our theoretical findings and demonstrate that PAS adaptively recovers whichever fixed shift is best in each regime without it being specified in advance.
Read the full abstract ▾
All authors Frederik Stalschus, Samuele Pedrielli, Stefan Kühn, Karl Jansen, Kim A. Nicoli, Shinichi Nakajima
High Energy Physics (Theory)
One-Loop Quantum Correction to the Kink Mass in a Lorentz-Violating Scalar Field Theory
Reza Moazzemi
We study the radiative correction to the mass of the $(1+1)$-dimensional $\lambda\phi^4$ kink in the presence of an irreducible, spacelike Lorentz-violating interaction. The Lorentz-violating operator is chosen as $-\frac12 c\phi^2(u\!\cdot\!\partial\phi)^2$ with $u^\mu=(0,1)$, which is the lowest-order single-scalar operator considered in this class of models that produces effects that cannot be removed by a linear redefinition of coordinates or the field. We perform the one-loop renormalization of the underlying
quantum field theory. In contrast with Lorentz-invariant $\lambda\phi^4$ theory in two dimensions, the Lorentz-violating theory requires, at this order, both a modified mass counterterm and a nonzero field-strength counterterm. The corrected stability problem contains modified bound and continuum modes, while the continuum phase shift remains unchanged at $O(c)$ with the boundary-condition prescription adopted here. Finally, using the
vacuum-subtracted zero-point energy and the counterterm
Hamiltonian, we obtain the one-loop kink mass through first order in $c$. We give the finite coefficient in the subtraction prescription implemented in the accompanying thesis calculation, for which the Lorentz-violating contribution is numerically negative.
Read the full abstract ▾
Optics
Machine Learning to Foundation Models: Artificial Intelligence for Nanophotonic Modeling and Scientific Discovery
Chaobin Yang, Xueqing Liu, Yiqun Fu et al. (+4 more)
Artificial intelligence (AI) is increasingly used to model, design, and study nanophotonic systems. This review traces the development of the field from classical machine learning and deep learning to generative models, transfer learning,
transformers, and emerging foundation models. It first introduces major nanophotonic platforms, including nanoparticles, nanoholes, metasurfaces, photonic
crystals, multilayer thin films, and integrated photonic devices, together with their main forward and inverse problems. It then reviews data-driven methods for predicting optical spectra and fields, generating structures from target responses, improving designs through optimization, and accounting for fabrication constraints. Generative models are discussed as a way to produce multiple valid solutions to nonunique inverse problems, while transfer learning, few-shot learning, and physics-aware training help reduce data requirements and improve generalization. Recent domain-specific foundation models show that different optical structures and responses can be handled within shared representations, but current systems remain limited in scope and physical grounding. Future progress will depend on
multimodal models that connect geometry, materials, spectra, electromagnetic (EM) fields, fabrication data, experiments, and scientific literature with reliable simulation and validation tools. Current foundation models remain domain-specific, and their extension to broader nanophotonic tasks will require stronger physical grounding and validation.
Read the full abstract ▾
All authors Chaobin Yang, Xueqing Liu, Yiqun Fu, Fengbo Zhou, Krzysztof Kempa, Stefano Anzellotti, Michael J. Naughton
Plasma Physics
AXUV synthetic diagnostic for ASDEX Upgrade and its application for SPI simulations
Ferenc Lengyel, Weikang Tang, Matthias Hölzl et al. (+14 more)
We introduce an Absolute eXtended UltraViolet (AXUV) diode-based camera forward-modelling tool to support the validation of mitigated disruption simulations and the interpretation of experimental phenomena, with applications to the ASDEX Upgrade (AUG) tokamak. AXUV diodes measure electromagnetic radiation across a wide spectral range with a significantly higher time resolution (~microseconds) than foil bolometers (~milliseconds), albeit with a non-uniform spectral responsivity. AXUV is suitable for examining fast phenomena, such as shattered pellet injection (SPI), where the radiation localisation and radiated power provide information on the deposition of pellet material. Due to the characteristics and degradation of AXUV diodes, absolute power measurements are subject to large systematic uncertainties, especially when the spectra are time-varying, as in e.g. mixed Ne/D2 SPI experiments. These challenges motivated the development of a synthetic diagnostic within the Cherab-Raysect optical modelling framework, which is applied here to four AXUV cameras in two poloidal cross-sections of AUG. The synthetic diagnostic provides a means to understand how the diodes measure radiation under SPI conditions and to connect first-principles
plasma simulations with experimental measurements. The details of the synthetic diagnostic are presented, and the capabilities are illustrated with applications to AUG SPI simulations performed in JOREK. The synthetic signals generated from these simulations are compared with experimental measurements from the 2022 SPI campaign and show qualitatively similar features in many respects. Particularly good agreement was found in the time
evolution of the studied high Ne-content (10%) pellet, whereas a different, low Ne-content (0.17%) case exhibited more pronounced differences, likely due to the absence of background
impurities in the underlying SPI simulations.
Read the full abstract ▾
All authors Ferenc Lengyel, Weikang Tang, Matthias Hölzl, Matthias Bernert, Matěj Tomeš, Peter Halldestam, Paul Heinrich, Gergely Papp, Stefan Jachmich, Umar Sheikh, Mathias Dibon, Pascal de Marné, Jörg Hobirk, Thomas Eberl, Gergő I. Pokol, for the ASDEX Upgrade Team, the EUROfusion Tokamak Exploitation Team
High Energy Astrophysical Phenomena
When the stars don't align: Investigating inconsistencies in binary black hole formation across population synthesis codes
Alexandra G. Guerrero, Michael Zevin, Duncan B. Maclean et al. (+4 more)
Binary population synthesis (BPS) codes are valuable tools for investigating the end-to-end lives of binary
stars as well as a myriad of observed astrophysical phenomena. Many “rapid" BPS codes rely on semi-analytical single-
star evolutionary tracks and disjointed prescriptions for binary physics. Updated “hybrid" or “detailed" BPS codes incorporate improved methodologies, but at a steeper computational cost that may limit broad exploration of physical uncertainties. Given the widespread use of BPS in modern astrophysical research, it is imperative to systematically compare BPS codes across the spectrum of computational efficiency, flexibility, and physical realism to gauge their consistency and robustness. In this work, we perform BPS on three single-
metallicity populations of identical initial binaries using three modern codes — the rapid code $\texttt{COSMIC}$, the hybrid code $\texttt{METISSE}$ integrated into $\texttt{COSMIC}$, and the detailed code $\texttt{POSYDON}$ — ensuring consistent physical parameterizations where possible. We find stark differences in the properties, formation pathways, and progenitors of binary black hole (BBH) merger populations across the three codes. In a population of one million binaries at $0.01 Z_\odot$, each code results in $\sim 5,000\mbox{--}9,000$ BBHs that merge within a Hubble time. However, $\lesssim 14\%$ of progenitors overlap between two codes, and only $\textit{one}$ initial binary becomes a BBH merger across all three codes. Identical progenitors often follow different evolutionary pathways in each code and result in inconsistent BBH properties. Our results highlight the need for a deeper understanding of physical and computational differences between BPS codes and caution against over-interpreting results from any individual BPS code.
Read the full abstract ▾
All authors Alexandra G. Guerrero, Michael Zevin, Duncan B. Maclean, Katelyn Breivik, Carl L. Rodriguez, Max M. Briel, Daniel E. Holz
Materials Science
Optically Coupled Noise Spectroscopy Quantifies Defect Passivation in Monolayer MoS2 FETs
Shashwata Chattopadhyay, Soumyadip Hazra, Sraboni Dey et al. (+4 more)
Transition metal dichalcogenide monolayers are promising materials for electronic and photonic applications, yet the performance of chemical vapour deposition grown samples is severely limited by native sulphur vacancies that introduce mid-gap trap states, degrade carrier mobility, and elevate electrical noise. Here we investigate octanethiol passivation of sulphur vacancies in monolayer MoS2 field effect transistors, combining x-ray photoelectron spectroscopy, photoluminescence, and Raman scattering with electrical transport and optically coupled low-frequency noise spectroscopy. Thiol treatment reduces the sulphur vacancy concentration from 7% to 4%, reducing the free electron density. Electrically, it increases the device resistance 35-fold while restoring gate switching with an on/off ratio of 10^4 and improving field-effect mobility from 1 to 5 cm^2/Vs. Low frequency noise spectroscopy directly quantifies the defect suppression: the Hooge parameter alpha_H drops by more than two orders of magnitude after passivation. Gate-dependent noise confirms carrier mobility fluctuation as the dominant dark noise mechanism, while optical excitation drives a crossover to carrier number fluctuation dominated noise, reflecting preferential interaction of photogenerated carriers with residual vacancy states via generation-recombination trapping, a mechanistic distinction inaccessible to gate-bias measurements alone. Density functional theory calculations corroborate these findings, showing suppression of vacancy-induced mid-gap states by more than half and partial restoration of the intrinsic bandgap. These results establish optically coupled low-frequency noise spectroscopy as a sensitive, low-cost, and non-destructive tool for quantifying defect passivation in TMDC-based devices.
Read the full abstract ▾
All authors Shashwata Chattopadhyay, Soumyadip Hazra, Sraboni Dey, Kritika Sharu, Renjith Nadarajan, Arijit Kayal, Joy Mitra