Computational Physics
Propagation electrodynamics differential conduction of action potentials in geometrically branched squid giant axons
Xi Liu, Wenxi Fang and Ken Perlin
Classical cable theory neglects
magnetic induction, Lorentz forces, and transient electromagnetic (EM) currents, limiting its accuracy for action potential propagation in branched neuronal geometries. We develop a coupled Maxwell-cable framework that integrates finite-difference time-domain (FDTD) solutions of Maxwell's equations with extended Hodgkin-Huxley and Fitzhugh-Nagumo dynamics, including
magnetic gating, EM transmembrane currents $I_{\text{EM}}$, and
quantum corrections for thin segments. Controlled simulations in asymmetric and symmetric axonal bifurcations show that inductive effects lower the critical branch radius for conduction failure and break
symmetry in identical daughter branches under transverse
magnetic fields. We introduce an EM-corrected
geometric ratio $GR_{\text{EM}}$ that revises branch-point impedance matching and captures size-dependent axial current imbalances. Parent axon conduction velocity deviates significantly from the $\sqrt{d}$ scaling law when EM feedback and
quantum effects are included, leading to early blockage at large diameters. Overall, quasi-static models underestimate EM corrections to speed, waveform, and transmission fidelity; our framework offers a multi-physics tool for electrodynamic signaling in complex neuronal architectures.
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Computational Physics
Electromagnetic analysis of low dropout regulator circuit small-signal stability characterization for inductive LC filters and transformers
Xi Liu, Wenxi Fang and Ken Perlin
This work systematically evaluates the capability of generative large
language models (LLMs), specifically GPT-4o, to support the full design, simulation, and optimization workflow of low-dropout (LDO) linear voltage regulators. The study covers four core design phases: pre-design specification mapping, transistor-level
circuit topology generation, SPICE simulation guidance, and post-simulation performance fine-tuning, with an extended investigation into the integration of
magnetic inductive components within the LDO signal path. GPT-4o autonomously proposes a single-stage differential-pair error amplifier architecture with thin-
oxide MOS transistors, provides sizing guidance for the PMOS pass element, and recommends passive compensation networks to secure closed-loop stability. The LDO testbench adheres to low-voltage portable electronics specifications: an input range of 0.8-1.2 V, tunable 0.7-1.1 V output, maximum 250 mA load current, and integrable output capacitance below 10 nF. Transient and small-signal AC SPICE simulations validate LLM-assisted
circuit implementations, quantifying settling time reduction via compensation capacitors and verifying adequate phase margin across operating bandwidth. A key novel extension explores three distinct inductor placement schemes, input-side supply filtering, out-of-loop LC output filtering, and inductive loading embedded within the feedback divider, rooted in Maxwell's electrodynamic principles and MOSFET small-signal device physics. Comparative Bode and output impedance analysis reveals that inductors inserted inside the feedback path introduce resonant complex poles, severe gain peaking, and degraded phase margin, while inductors placed external to the feedback sensing tap preserve regulator stability while suppressing high-frequency electromagnetic interference.
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Computational Physics · Cross-listed from math.NA
Runge–Kutta-Aligned Oscillation Elimination: Restoring Superconvergence for Fully Discrete Shock-Capturing DG Schemes
Manting Peng, Zhuoyun Li and Kailiang Wu
Nonlinear stabilization is indispensable for discontinuous Galerkin (DG) discretizations of
hyperbolic conservation laws, yet it typically disrupts the delicate error structure required for superconvergence analysis. Consequently, existing theory has largely been restricted to linear or semi-discrete schemes lacking oscillation control. This paper bridges this gap by proposing a Runge–Kutta (RK) aligned oscillation-eliminating (OE) DG framework that restores the superconvergence properties. By synchronizing the pseudo-time step in the OE procedure with the cumulative RK stage coefficients, we unlock a cancellation mechanism for low-order interface errors that is inaccessible to standard OEDG formulations. We rigorously prove that this fully discrete scheme achieves $(k+2)$-th order superconvergence to a tailored projection of the exact solution for linear conservation laws in both one and two dimensions, while maintaining the non-oscillatory shock-capturing capabilities of the original method. Moreover, we establish a general guiding principle for designing a class of OE-type DG schemes that exhibit such superconvergence. Key theoretical innovations include the construction of stage-aligned correction functions to compensate for nonlinear OE sources and the discovery of a two-dimensional projection operator that preserves
outflow-edge averages, a property essential to close the discrete shift estimates. Numerical experiments confirm the predicted superconvergence rates and demonstrate that RK
alignment preserves the parameter-free robustness of OEDG for problems with strong discontinuities.
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Instrumentation and Detectors
Cusp-singularity-enhanced Coriolis effect for ultrasensitive chip-scale gyroscopes
Sen Zhang, Dingbang Xiao, Fei Wang et al. (+8 more)
Gyroscopes, as fundamental inertial sensors, are crucial for rotation measurements in consumer electronics, automotive, and aerospace industries, with the most widely used kind relying on the Coriolis effect. The chip-scale Coriolis vibratory gyroscopes (CVGs) show reduced size, weight, and cost, but remain far lower performance than traditional macroscale CVGs, as the weak intrinsic Coriolis factor sets a fundamental limit on scaling the sensitivity against the inherently louder Brownian noise in microchips compared to the macroscale ones. Here, to overcome this physical limit, for the first time, we propose and experimentally demonstrate the use of third-order singularities lying within cusp catastrophes in the phase-tracked oscillations of an on-chip CVG to facilitate a cubic-root scaling of the Coriolis-effect-induced frequency modulation. Employing this effect, we achieve a three-order-of-magnitude enhancement in the Coriolis factor, yielding a 253-fold improvement in signal-to-noise ratio and a 297-fold increase in precision. Moreover, the cusp singularity enables a previously unattainable ultrasensitive phase-modulated sublinear measurement, achieving a world-record signal-to-noise ratio performance for silicon-chip gyroscopes. These findings not only provide revolutionary advancements in gyroscope technologies, by filling the gap in observing and controlling the singularity-enhanced Coriolis effect, but also shed new light on other ultrasensitive sensing applications.
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All authors Sen Zhang, Dingbang Xiao, Fei Wang, Ran Huang, Lei Yu, Ning Zhou, Kaixuan He, Xuezhong Wu, Franco Nori, Hui Jing, Xin Zhou
General Physics
Constraints on the Modified Emergent Dark Energy Model Using DESI DR2 BAO
Himanshu Chaudhary, Dhruba Jyoti Gogoi, Salvatore Capozziello et al. (+1 more)
In this work, we investigate the modified emergent dark energy (MEDE) model using
baryon acoustic oscillation measurements from the Dark Energy Spectroscopic Instrument Data Release 2 (DESI DR2), together with CMB information from the LoLLiPoP (low-$\ell$) and HiLLiPoP (high-$\ell$) likelihoods based on the latest Planck NPIPE PR4 release, Planck PR4
lensing, ACT DR6
lensing, and three Type Ia
supernova samples (Pantheon$+$, DES-Dovekie, and Union3). We find that the MEDE model remains largely consistent with the standard $\Lambda$CDM cosmology. Although small departures from $\Lambda$CDM are allowed, the inclusion of SNe~Ia data drives the model parameters toward the standard cosmological scenario, with the parameter $\alpha$ remaining consistent with $\alpha=0$ at the $1\sigma$ level. The model does not significantly alleviate the $H_0$ or $S_8$ tensions: the inferred $H_0$ values remain below the SH0ES measurement, the sound horizon $r_d$ is nearly unchanged, and the predicted $S_8$ values remain close to those of $\Lambda$CDM. The reconstructed cosmological
evolution closely follows the $\Lambda$CDM prediction, with deviations generally below the $0.5\sigma$ level. While the CMB + DESI DR2
dataset favors a full phantom regime, the inclusion of SNe~Ia shifts the
evolution toward a full quintessence regime. Finally, although the $\Delta\chi^2_{\rm MAP}$ and $\Delta{\rm AIC}$ criteria indicate a marginally better fit than $\Lambda$CDM, the logarithmic Bayes factor provides only inconclusive evidence in favor of the MEDE model. Overall, the MEDE model remains compatible with current observations but does not exhibit the phantom-crossing behavior suggested by recent DESI DR2 analyses.
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All authors Himanshu Chaudhary, Dhruba Jyoti Gogoi, Salvatore Capozziello, G. Mustafa
General Physics
Emergent Space, Time, and Lorentz Symmetry from Binary Sequences
Sam Powers and Dejan Stojkovic
We construct an information theory framework in which the fundamental objects are binary sequences of length $n$, equipped with the bitwise XOR operation. The only physical observables are counts of XOR-generated symbol classes, while the exact locations of symbols are inaccessible. Averaging over those locations ultimately yields the Minkowski interval as an invariant object that maximizes (information)
entropy. Correlations between two binary sequences are base-4 sequences that we label as “events”, and events are connected with maps. The entire kinematic structure of Special Relativity is recovered under minimal assumptions, i.e. counts that represent space and time increments carry equal informational weight. The central claim is that Lorentz
symmetry is the typical large-n behaviour of XOR counting. At finite $n$ the framework yields a discrete rapidity spectrum, a bound $\gamma_{\max} = O(\sqrt{n})$, and interval fluctuations of relative size $O(n^{-1/2})$, with standard special relativity recovered as $n \to \infty$. However, the light cone and one null coordinate are exact for every microscopic configuration, so the
symmetry group is undeformed and dispersion relations are unmodified. Thus, the theory, though discrete, implies no Lorentz violation of the standard phenomenological kind. Ultra-high-energy
cosmic rays already require $n \gtrsim 10^{23}$; interferometry excludes the variant in which $n$ scales linearly with system size, leaving a
holographic area law. The most striking prediction of the framework concerns systems at the maximum of their information capacity, where $n$ is necessarily finite: black holes and de Sitter space. There the corrections are of order one within a Planck proper length of the horizon, regardless of the horizon's size, and the spacetime description fails altogether at the endpoint of black-hole evaporation, where $n$ itself is of order unity.
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General Physics
Observational constraints on Barrow holographic dark energy coupled with a non-cold dark matter component from DESI DR2
Abdulla Al Mamon, Genly Leon, Subhajit Saha et al. (+1 more)
We investigate the cosmological viability of Barrow
holographic dark energy in a spatially flat Friedmann–Lemaître–Robertson–Walker universe in which the dark matter component is allowed to have a non-zero pressure, characterized by a constant equation-of-state parameter $w_{m}$. By considering the future event horizon as the infrared cutoff, we derive the master equation, which describes the cosmological dynamics for the background space. We constrain the model against late-time data, combining the
baryon acoustic oscillation from DESI DR2 with three different catalogues for the Type Ia
Supernova measurements and the
Cosmic Chronometers. The dark matter equation of state is constrained to $w_{m}=0.033_{-0.030}^{+0.045}$, $0.009_{-0.041}^{+0.047}$, and $0.033_{-0.029}^{+0.042}$, for the PantheonPlus, the Union3.0 and the DES-Dovekie
supernova datasets respectively. Therefore, the pressureless limit is recovered within the $2\sigma$ regime. On the other hand, the Barrow exponent is weakly constrained, due to the $\Delta-w_{m}$ degeneracy. The dark energy equation of state remains above the phantom divide throughout the
redshift range probed. Finally, in the comparison of the statistical parameters with that of $\Lambda$CDM, it follows $\Delta\mathrm{AIC}=+2.23$, $+0.75$, and $+1.38$, $\ $while for the
Bayesian evidence we find $\Delta\ln Z=-0.63$, $+0.47$, and $-0.13$, which suggest that the
datasets considered in this analysis do not have a preferred model. Finally the relation with the corresponding Tsalis
holographic dark energy model is discussed.
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All authors Abdulla Al Mamon, Genly Leon, Subhajit Saha, Andronikos Paliathanasis
Instrumentation and Detectors
Compact nondestructive generator for microsecond-class ultrafast pulsed magnetic fields
Y. Ishii, A. Ikeda, H. Sun et al. (+2 more)
The sweep rate of pulsed
magnetic fields is a key factor in exploring of nonequilibrium phenomena in matter. However, the nondestructive generation of ultrafast pulsed
magnetic fields is challenging because of the large time constants associated with the large inductance and capacitance of conventional pulsed
magnetic field generators, as well as the residual inductance of the power devices and the system itself. We have developed a new compact pulsed
magnetic field generator using commercially available state-of-the-art ultrafast power devices, enabling the generation of ultrafast pulsed
magnetic fields up to approximately 1 T with a pulse duration of 3.8 $\mu$s. We present the performance of the newly developed system and compare the experimentally obtained
magnetic field waveforms with the results of a simple
circuit simulation. In addition, we demonstrate magnetization measurements on cobalt powder and Faraday rotation measurements on CdS single
crystal using the developed system.
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All authors Y. Ishii, A. Ikeda, H. Sun, H. Oike, Y. H. Matsuda
Computational Physics · Cross-listed from nlin.CD
Flux-form spatiotemporal neural operators for coarse-grained dynamics of multiscale PDEs
Junfeng Chen
We study data-driven prediction of coarse-grained dynamics in multiscale PDE systems. Adopting a closure-free operator-learning viewpoint, we apply a linear coarse-graining map and learn a surrogate
evolution operator for the resolved field directly from filtered high-fidelity trajectories. Motivated by the Mori-Zwanzig formalism, we propose a spatiotemporal neural operator mapping a resolved history slab on $\Omega\times[-T_{\mathrm{in}},0]$ to a resolved future slab on $\Omega\times[0,T_{\mathrm{out}}]$. Spatial mixing uses
Fourier convolution, while temporal mixing uses a causal kernel operator with position-
attention weights on time lags. This causal temporal operator encodes finite-
memory effects in the resolved dynamics while preserving the directionality of the history-to-future map. To improve rollout robustness and suppress nonconservative artifacts, we embed a flux-form inductive bias by parameterizing the windowed update in explicit divergence form. We also provide a data-driven guideline for selecting the
memory length $T_{\mathrm{in}}$ via the decorrelation time of a closure-injection diagnostic computed from filtered trajectories. We validate on the coarse-grained viscous Burgers' equation, the Kuramoto-Sivashinsky equation, and two-dimensional turbulent flows, obtaining stable autoregressive rollouts with improved long-horizon accuracy and statistical fidelity.
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Data Analysis and Statistics · Cross-listed from quant-ph
A formal correspondence between Bayesian inference problems and the Heisenberg representation
C. Abugattas Chacoff
The proposed formulation establishes a formal correspondence between the Heisenberg representation and the
Bayesian formulation of inverse problems. The likelihood function is first expressed in
Hilbert space through a quadratic norm of the difference between the noisy observations and the response of a forward model depending on the unknown parameters, weighted by the inverse of the observational noise covariance. Based on the common mathematical structure of this quadratic form and the observable operator in the Heisenberg representation, the inverse observational noise covariance operator is identified with the initial observable. To establish this correspondence, a
stochastic field with Matérn covariance is considered and represented through the Karhunen-Loève expansion. The
eigenvalues and eigenfunctions of this expansion are then used to define the state $|\Psi\rangle$ within the proposed formalism. The main results are summarized by four
theorems: the unitarity of the
evolution operator, the self-adjointness of the
Hamiltonian, the conservation of the trace of the observable, and the formal correspondence between the
Bayesian likelihood and the Heisenberg observable structure. Limiting cases of the Matérn covariance are analyzed. Finally, numerical examples illustrate the analytical results.
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Plasma Physics
Data-Driven Generation of Compact Quasi-Isodynamic Stellarators
Yang Han, Hanlin Chen. Shuai Cao, Zhiyuan Lu et al. (+3 more)
Stellarator design explores a vast space of three-dimensional
plasma boundaries, only a small fraction of which yields usable
equilibria. Data-driven models can narrow this search by learning from existing optimized configurations. Building on the ConStellaration database, we extend conditional boundary generation to four-field-period QI configurations, focusing on the sparsely sampled low-aspect-ratio regime. The approach learns the common
geometric structure of known QI
equilibria and then adapts it using a small high-fidelity compact
dataset, allowing target
magnetic properties to guide generation beyond the original data distribution. This adaptation reduces the compact-domain test loss by approximately 87% and yields converged ultra-compact candidates consistent with the prescribed conditions. Several candidates show favorable confinement indicators, and one provides a useful seed for further QI optimization and finite-beta assessment. The method therefore serves as a data-informed front end to high-fidelity physics and optimization.
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All authors Yang Han, Hanlin Chen. Shuai Cao, Zhiyuan Lu, Dehong Chen, Guosheng Xu, Baonian Wan
Data Analysis and Statistics
Exploring new directions in enhancing the ACTS parameter optimization suite
Chance LaVoie, Qi Bin Lei, Rocky Bala Garg et al. (+1 more)
Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are commonly tuned through expert intuition and repeated trial and error. ACTS reduces this burden with an Optuna Tree-structured Parzen
Estimator auto-tuner, but expensive evaluations, a restricted search space, and a scalarized objective can limit evaluation efficiency, exclude promising configurations, and obscure performance trade-offs. We investigate whether
Bayesian optimization can address these limitations using ACTS with the Open Data Detector (ODD). Under identical search ranges and a common 100-trial budget, we compare Expected Improvement and Upper Confidence Bound with TPE and random search on the existing eight-parameter problem, extend the best-performing
Bayesian method to fifteen parameters, and apply Expected Hypervolume Improvement to optimize efficiency, fake rate, duplicate rate, and runtime without fixed scalar weights. Candidate configurations are evaluated through the full ACTS reconstruction chain and validated on disjoint held-out events. The
Bayesian acquisition methods identify strong configurations earlier than TPE, and their advantage persists in held-out validation. Expanding the search further improves performance, while multi-objective optimization reveals competitive non-dominated solutions spanning distinct trade-offs. These results indicate that
Bayesian optimization can strengthen ACTS auto-tuning through efficient evaluation, broader parameter searches, and post-hoc expert selection among non-dominated alternatives.
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All authors Chance LaVoie, Qi Bin Lei, Rocky Bala Garg, Lauren Tompkins
Fluid Dynamics
Influence of Flow on Discharge Behaviors and CO2 Conversion in Gliding Arc Discharges
Alexander Davis, Charles Burton, Stephanie Pecaut et al. (+4 more)
Plasma reactors present themselves as a unique means of electrified chemical production, particularly in the conversion of greenhouse gases (e.g., CO2) back into chemical feedstocks. Warm
plasmas, such as gliding arc discharges, represent a growing class of catalyst-free
plasma reactors that demonstrate high energy efficiency and scalability. Here, we introduce mean discharge time as a characteristic descriptor of gliding arc dynamics, extracted directly from voltage and current waveforms. Electrical signatures for distinct
plasma behaviors (modes) were established using high-speed photography, and discharge time distributions were evaluated as a function of Reynolds number. Mean discharge time is shown to decrease non-linearly with Reynolds number, providing a link between arc behavior and underlying fluid dynamics, which is otherwise neglected in traditional reactor characterization. Mean discharge time thereby provides a quantitative, operando descriptor of transient gliding arc dynamics and stability, offering insight into discharge behavior that traditional characterization approaches do not capture.
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All authors Alexander Davis, Charles Burton, Stephanie Pecaut, Matthew Hershey, Michelle M. Driscoll, Linsey C. Seitz, Dayne F. Swearer
Chemical Physics
A Perspective on Phase Space Electronic Structure Theory : From Its Surface Hopping Origins Through To Its Future Promise
Joseph E. Subotnik, Ethan Alguire, Nicole Bellonzi et al. (+20 more)
We trace the history of phase space electronic structure theory (PSEST), high- lighting how this powerful approach emerged from fundamental questions in semi- classical surface hopping dynamics and evolved into an alternative to standard Born- Oppenheimer based electronic structure theory (with moving instead of frozen
nuclei). Our goal herein is not to recapitulate the mathematical details of phase space electronic structure calculations, and few equations are presented so as to maximize readability. Instead, our goal is to provide intuition for those new to the field both (i) regarding the physics present when solving the Schrodinger equation in a non-inertial frame as well as (ii) regarding why PSEST is a necessary step forward towards understanding chemical problems involving
spin (with limited practical alternatives). We further high- light some of the many open questions in this fast developing area, which will hopefully inspire new practitioners in this field. This intuitive perspective lacks many equations and is meant to complement (rather than replace) the more technical review given in Bian et al, Chem. Phys. Rev. 7, 011303 (2026)
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All authors Joseph E. Subotnik, Ethan Alguire, Nicole Bellonzi, Xuezhi Bian, Mansi Bhati, Nadine Bradbury, D. Vale Cofer-Shabica, Ben Curlee, Titouan Duston, Shervin Fatehi, Gaohan Miao, Zheng Pei, Linqing Peng, Tian Qiu, Zhen Tao, Hung-Hsuan Teh, Xinchun Wu, Yanze Wu, Zain Zaidi, Yihan Shao, Jonathan Rawlinson, Neil Shenvi, Robert Littlejohn
Fluid Dynamics
Anisotropic Thermalization in Far-from-Equilibrium Flows
Arnab Debnath, Timothy Breitzman and Kaushik Dayal
We present a deterministic discontinuous Galerkin (DG) finite-element solution of the Boltzmann equation, without moment-closure approximations, under a class of far-from-
equilibrium deformations. Specifically, we consider affine flows which reduce the Boltzmann equation to a purely velocity-space problem for the reduced distribution function in a reduced velocity field. We solve the reduced equation using a tensor-product Lagrange DG discretization for four representative flows: simple shear, pressure shear, bi-directional shear, and a
vortex flow. Our principal finding is that the velocity distribution is well-approximated by an anisotropic Gaussian throughout the
evolution, despite the non-
equilibrium conditions. Further, we show the
evolution of the covariance tensor of the Gaussian distribution is equal to the inverse of the right Cauchy-Green tensor in the free-streaming limit without collisions. This prediction compares very well with the numerical solution at short times; at longer times, they grow apart, reflecting the influence of particle collisions.
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Atomic Physics
Compact Actively-Shielded Magnetic Field Coil within Mu-Metal Shields for ACME Electric Dipole Moment Measurements
S. Liu, M. Watts, C. Diver et al. (+13 more)
A system of actively-shielded coils and mu-metal shields is devised, constructed and shown to provide the stable and spatially uniform
magnetic field needed for the ACME III electron electric dipole moment (eEDM) measurement. Two layers of current-carrying coils, enclosed within three layers of
ferromagnetic shields, produce a field that varies by less than 1 nT (10 $\uG$) within the 1 m $\times$ 4.2 cm $\times$ 4.2 cm interior volume in which a beam of ThO molecules are probed as they precess. The demountable shields are constructed from rectangular mu-metal plates. The largest, with a mass of 19 kg and an area of 2.18 m $\times$ 0.75 m, is easily carried by two people and just fits within a large available annealing oven. The assembly design facilitates low-stress mounting and handling to suppress changes in the
magnetic properties of the mu metal, and also provides modular access to apparatus within the coils for maintenance and upgrades. The nearly static external ambient field is reduced within the shielded precession volume by up to a factor of $10^5$. During the
magnetic field reversals that ACME uses to suppress systematic uncertainties, the “actively-shielded” coil largely cancels out its external fringing field to minimize the magnetization of the mu metal. Even though the shields are only 10 cm outside the coils, shield degaussing after every
magnetic field reversal is not required. The non-reversing residual field stays below 1 nT for up to 17 hours when the field is reversed every 30 seconds, for example. The measured performance, compared to the previous generation ACME II apparatus, suggests that the
magnetic-field-related systematic uncertainties for ACME III will be smaller by an estimated factor of 40 despite a five times longer precession volume and the use of three
magnetic shielding layers rather than five.
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All authors S. Liu, M. Watts, C. Diver, D. G. Ang, C. Meisenhelder, X. Fan, B. Hao, D. Lascar, A. Hiramoto, T. Masuda, P. Hu, Z. Han, X. Wu, D. DeMille, J. M. Doyle, G. Gabrielse
Space Physics · Cross-listed from astro-ph.SR
Solar-Cycle Modulation and Photospheric Magnetic Control of Turbulence in the Young Solar Wind
Yanwen Wang, Rohit Chhiber, Arcadi V. Usmanov et al. (+2 more)
The
solar wind is an
outflow of
solar plasma that expands from the corona to fill the heliosphere. Its
turbulence provides a pathway for non-adiabatic heating and acceleration, and is therefore central to understanding the thermodynamic and magnetohydrodynamic (MHD)
evolution of the young
solar wind. However, the variation of its
turbulence properties over the
solar activity cycle and the connection of these properties to
solar source regions remains incompletely understood. Here we analyze observations from 25
solar orbits of NASA's Parker
Solar Probe (PSP) mission, in combination with a global MHD model, photospheric magnetograms, and extreme ultraviolet maps of the low corona, to investigate the
solar-cycle dependence and the
solar sources of
turbulence in the very inner heliosphere. The observations reveal pronounced
solar-activity variation in fluctuation amplitude, cross helicity, and related
turbulence properties. By tracing PSP-connected
magnetic flux tubes to their
solar sources, we demonstrate that high turbulent-energy intervals are preferentially connected to coronal-hole sources with unipolar
magnetic topology, whereas low turbulent-energy intervals are associated with multipolar
topology and active-region environments. Our study combines in-situ measurements with numerical modeling and remote sensing observations to reveal how
solar-cycle-dependent source structure determines
turbulence variability and
plasma heating in the young
solar wind.
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All authors Yanwen Wang, Rohit Chhiber, Arcadi V. Usmanov, Marc Swisdak, William H. Matthaeus
Computational Physics · Cross-listed from cs.LG
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates
Qiyao Zhou, Xujia Zhu, Pierre Joli et al. (+2 more)
Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informative for parameter calibration. However, a systematic end-to-end differentiable formulation for coupling deep-learning-based reduced-order surrogates with variational parameter estimation remains underdeveloped. In this work, we introduce a physics-aware neural-network-based latent-space framework for reduced-order forward modeling and variational parameter estimation. The proposed autoencoder-based approach yields a differentiable surrogate that maps physical parameters to predicted flow fields through a latent representation. The observable supervision is used during offline training to encourage the latent variables to retain information correlated with system parameters, while the online inverse problem is solved in the parameter space through the surrogate-induced observation operator. The method is evaluated on two computational-fluid-dynamics
benchmarks. The results show that reconstruction accuracy alone is insufficient for inverse modeling, owing to the lack of end-to-end differentiability or physics awareness for variational parameter calibration. Quantitative latent-space analysis further shows that observable supervision improves case-level separability and temporal organization of latent representations. Experiments with realistic measurement settings, including noisy, low-resolution, randomly masked, and block-wise partial observations, demonstrate the robustness of the proposed framework and show that it generally reduces calibration error and variability compared with the standard surrogate models.
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All authors Qiyao Zhou, Xujia Zhu, Pierre Joli, Yu Cong, Sibo Cheng
Chemical Physics
Second-Derivative-Corrected FANPT for Robust Continuation of Nonlinear Wavefunction Equations
Rugwed Lokhande, Krisztina Zsigmond, Paul W. Ayers et al. (+1 more)
We present a second-derivative-corrected extension of the Flexible Ansatz for N-body Perturbation Theory (FANPT) for solving nonlinear Flexible Ansatz for N-body Configuration Interaction (FANCI) wavefunction equations. The original quasilinear FANPT approximation neglects second- and higher-order derivatives of the determinant overlap with respect to wavefunction parameters. In this work, we retain the overlap Hessian and neglect only third- and higher-order parameter derivatives, thereby including the leading nonlinear response of the wavefunction ansatz while preserving the same response-
matrix structure used in the original FANPT formulation. The resulting additional terms enter only through the constant vector of the response equations and are implemented for coupled-cluster wavefunctions in the FanPy/FANCI framework. The new approximation is tested on the Lithium Hydride molecule and the insertion of Beryllium into H$_2$ using seniority-restricted coupled-cluster wavefunctions in the STO-6G basis. The main advantage of the second-derivative correction is that it provides a better initial guess for solving the projected FANCI equations at the next point along the adiabatic connection. This improvement is diagnosed by comparing the FANPT-propagated parameters with the independently optimized FANCI parameters at the same value of $\lambda$. For nonlinear coupled-cluster ansatzes, especially when larger $\lambda$-steps are used, the corrected approximation reduces the same-$\lambda$ parameter deviations and suppresses large parameter-space excursions. These results show that the leading nonlinear overlap correction improves the reliability of FANPT as a continuation strategy for nonlinear wavefunction equations.
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All authors Rugwed Lokhande, Krisztina Zsigmond, Paul W. Ayers, Ramón Alain Miranda-Quintana
Physics and Society
Technology interactions reshape the economics of China's coal power decarbonization
Yun-Long Zhang, Jia-Ning Kang, Xiaoming Kan et al. (+5 more)
Decarbonizing existing coal-fired power plants can contribute to near-term
climate mitigation, but identifying cost-effective retrofit strategies is complicated by interactions among mitigation technologies. Here we develop an interaction-aware optimization framework that jointly evaluates energy conservation, biomass co-firing, and carbon capture across 1,885 coal-fired power plants in China while accounting for plant heterogeneity and shared biomass and CO2 storage resources. We find that technology interactions alter both mitigation costs and the emission reductions attributable to individual measures, thereby changing cost-optimal technology portfolios and marginal abatement cost curve at the fleet level. Approximately 1.2 Gt CO2 yr-1 can be mitigated at negative marginal cost, while reaching carbon neutrality requires a marginal abatement cost of US$56 t CO2-1. Progressively deeper mitigation shifts the cost-optimal portfolio from energy conservation toward biomass co-firing and ultimately carbon capture, with biomass combined with carbon capture enabling net-negative emissions. Explicitly accounting for interactions among mitigation technologies therefore provides a more consistent basis for evaluating coal-power decarbonization and coordinating retrofit investment, infrastructure development, and
climate policy.
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All authors Yun-Long Zhang, Jia-Ning Kang, Xiaoming Kan, Lan-Cui Liu, Zhimin Huang, Song Peng, Biying Yu, Yi-Ming Wei
Optics
Few-cycle electro-optic light on thin-film lithium niobate
Xinyi Ren, Chun-Ho Lee, Ian Christen et al. (+6 more)
The twin fields of ultrafast optics and nonlinear photonics enable applications ranging from attosecond science [1, 2] and ultrafast electronics [3] to molecular spectroscopy [4, 5], nonlinear optics [6-8],
quantum nanophotonics [9] and precision metrology [10]. However, bringing these capabilities-including ultrashort pulse generation, dispersion control, and strong nonlinear interactions-together within a scalable photonic integrated platform requires exceptional performance and cooperation between components while preserving sufficient optical power across the
circuit. Here we demonstrate an integrated multi-functional nonlinear photonic system that transforms continuous-wave (CW) light into high-peak-power femtosecond pulses and harnesses them for pulse-driven nonlinear optics on thin-film lithium niobate (TFLN). Microwave-driven electro-optic (EO) broadening followed by integrated dispersive compression generates 230-fs
Fourier-transform-limited pulses with energies up to 3.3 pJ at 30.7 GHz, representing orders of magnitude higher pulse energy than previous integrated pulse synthesis at comparable repetition rates [11]. In a 0.3-meter dispersion-engineered TFLN waveguide,
soliton dynamics compress the pulses to 35 fs (6.7 optical cycles), accompanied by coherent spectral broadening exceeding 330 nm. In a fully-monolithic architecture, EO synthesis, dispersive compression and a high-Q nonlinear resonator are integrated on a single TFLN chip, enabling resonantly-enhanced pulse pumping and coherent spectral broadening at pulse energies as low as 400 fJ. By unifying microwave-controlled pulse synthesis and pulse-driven nonlinear interactions, our work establishes a direct path from CW excitation to few-cycle nonlinear optics on chip, with opportunities spanning microwave photonics [12], optical frequency synthesis and metrology, and mid-infrared and terahertz generation [13, 14].
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All authors Xinyi Ren, Chun-Ho Lee, Ian Christen, Clayton Cheung, Reshma Kopparapu, Yue Yu, Lian Zhou, Zaijun Chen, Mengjie Yu
Physics and Society
Unlocking CCUS-Ready Coal Power Investments: A Spatial Real Options Approach
Yun-Long Zhang, Jia-Ning Kang, Lan-Cui Liu et al. (+3 more)
New coal-fired capacity may still be needed in some economies to support energy security, yet tightening carbon constraints increasingly threaten its long-term investment viability. Designing new plants to be Carbon Capture, Utilization and Storage (CCUS)-ready is therefore critical, but existing investment studies largely neglect the spatial factors that shape CCUS investment viability. In this study, we propose a Spatial Real Options (SRO) framework that couples national-scale siting screening with site-level real-options valuation. A national inventory of technically feasible sites across China (n = 194,027) is linked to a real-options model that incorporates temporal uncertainty together with province-specific conditions, CO2 transport distance, and alternative policy instruments. Results show that the nationwide investable window for conventional coal closes by the early-to-mid 2040s. CCUS integration materially reshapes project economics, but outcomes differ substantially across storage options and transport distances: oil-reservoir storage remains economically attractive at short distances, whereas saline-aquifer storage requires operational incentives to become competitive. Generation-hour compensation substantially outperforms investment-cost subsidies, indicating that operating costs, rather than upfront capital, constitute the binding constraint. The resulting spatiotemporal maps provide a practical decision-support tool for identifying where and when CCUS-ready coal investments are most attractive under progressive decarbonization.
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All authors Yun-Long Zhang, Jia-Ning Kang, Lan-Cui Liu, Yi-Zhuo Ji, Song Peng, Yi-Ming Wei
Instrumentation and Detectors
Temperature-Dependent Performance of NaI(Tl) Crystal with Dual-Channel SiPM Readout for Low-Mass Dark Matter Searches
W. K. Kim, H. Y. Lee, K. W. Kim et al. (+1 more)
We report the first temperature-dependent characterization of a NaI(Tl)
crystal readout by two silicon photomultipliers (SiPMs) directly coupled to opposite ends of the
crystal for rare-event searches. A $6 \text{ mm} \times 6 \text{ mm} \times 13 \text{ mm}$ NaI(Tl)
crystal was directly coupled to two SiPMs and characterized in a
liquid nitrogen-cooled cryostat over a temperature range of 94$-$293 K. The light yield, energy resolution, and scintillation decay time were measured using $\gamma$-ray peak from a $^{241}$Am source. After correcting for optical crosstalk contributions, the light yield increased, reaching $17.7 \pm 1.1$ photoelectrons/keV at 238 K, corresponding to a 34.5% enhancement relative to room temperature (293 K). Furthermore, dual-channel configuration effectively suppresses random thermal noise via coincidence triggers, which together with the observed increase in light yield, provides a critical pathway toward lowering the energy threshold for dark matter and coherent elastic
neutrino$-$
nucleus scattering searches.
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All authors W. K. Kim, H. Y. Lee, K. W. Kim, H. S. Lee
Biological Physics · Cross-listed from cond-mat.stat-mech
Exact First-Passage Time Response Theory from Steady-State Response
Ruicheng Bao and Shiling Liang
The mean first-passage time (MFPT) provides a universal temporal measure of transport, reaction, search, and switching processes in physical, chemical, and biological systems. Understanding how MFPTs respond to perturbations is therefore crucial for prediction and control, yet a systematic theory has been lacking. We establish a compact theoretical framework for linear and nonlinear MFPT response in continuous-time Markov processes. The key tool is an exact correspondence that maps the intrinsically transient response of MFPTs onto the steady-state response of an auxiliary system. This correspondence yields exact and universal response relations for MFPTs between arbitrary state pairs, expressed entirely in terms of unperturbed MFPTs and steady-state probabilities. We then obtain a factorized physical decomposition of the MFPT response into linear upstream, linear downstream, and nonlinear contributions. Further corollaries include response-curve inference rules, fundamental bounds on MFPT responses, analytical expressions for higher-order responses of MFPTs and steady-state probabilities, and multi-rate response formulas. Additionally, our result offers computational advantages in calculating both MFPTs and steady-state distributions. Finally, a biologically motivated folding network is analyzed, and a recently reported paradox on MFPT is clarified.
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Optics · Cross-listed from cond-mat.str-el
Floquet Green's functions for lattice electrons driven by Gaussian quantum light
Atsushi Ono
We formulate Floquet Green's functions for noninteracting single-band
lattice electrons driven by a reservoir-stabilized single-mode Gaussian
quantum light source. The source is prescribed externally and is not updated by the many-electron polarization, while an active electronic probe still conditions the source
evolution through the Peierls coupling. The two time arguments of a Green's function share one source history: the lesser and greater components are obtained by convolving a shared-history four-endpoint kernel with the continuous bath kernels before the final source trace, while the bath canonical anticommutation relation yields an equal-time covariance that seeds the retarded and advanced one-leg propagations. The Peierls coupling is treated nonperturbatively within the prescribed-source model, and classical Floquet theory is recovered in the appropriate limit. Numerical calculations on a minimal one-dimensional model show finite-coupling
quantum-source corrections beyond a prescribed classical drive, together with spectral reconstruction and occupancy redistribution for squeezed
vacuum and squeezed coherent sources. The squeezing parameter and phase provide additional control knobs, beyond classical amplitude modulation, for both sideband structure and occupied weight. This work provides a theoretical framework for
quantum Floquet engineering of condensed matter with an externally prescribed
quantum light source.
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Optics · Cross-listed from quant-ph
Impact of strain and dark states on spectroscopic measurements of silicon-vacancy centers in diamond
Tommy Chin, Kesav V. Narayan, Imran Bashir et al. (+4 more)
Negatively charged silicon-vacancy (SiV$^-$) centers in diamond offer an attractive platform for the development of many forms of
quantum technology. However, questions remain in connection to how large ensembles of SiV$^-$ centers behave in concert. Here, we develop a computational model designed to simulate recent experiments where optical multidimensional coherent spectroscopy (MDCS) was used to examine a high-concentration sample of SiV$^-$ centers in diamond, revealing significant variations in spectral signature depending on the detection scheme. Simulation results reveal that strain effects are highly random in this system, with a characteristic axial strain of $2.8 \times 10^{-4}$ and a shear strain of $3.5 \times 10^{-5}$. They suggest in addition that highly strained centers (with values exceeding $1.5 \times 10^{-5}$) may become significantly decoupled from optical emission. The results have implications for the use of SiV$^-$ centers as
quantum sensors.
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All authors Tommy Chin, Kesav V. Narayan, Imran Bashir, Kelsey M. Bates, Liam G. Stanton, Ehsan Khatami, Christopher L. Smallwood
Physics Education
Work Done by Sliding Friction
J. David Brown
Friction does work when two objects in contact slide past one another. This process is studied using a simple numerical model consisting of two flexible asperites, one for each object. The force of friction is modeled as a conservative electric force that can be either attractive or repulsive. Because the asperites are flexible, not rigid, the conservative friction force generates thermal energy and can decrease or increase the objects' translational kinetic energies. The concept of pseudowork plays an important role throughout the analysis. The difference between work and pseudowork is equal to the change in internal energy. The numerical model is used to illuminate the reasons why work is typically greater than pseudowork. For a real physical system, this is the source of thermal energy. The processes discussed here fall into two categories: forced sliding and free sliding. With forced sliding, applied forces keep the objects moving with constant velocities. With free sliding, the only force on one of the objects (in the direction of motion) is friction.
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Medical Physics
T1, T2, and complex permittivities of hydrogels, paramagnetic salt solutions, and oils at 0.35, 1.5, and 3 Tesla
H Michael Gach, Kerri Prinos and Hannah Sechaga
Approach: The T1, T2, and complex permittivities of candidate MRI phantom constituents (hydrogels, paramagnetic electrolytes, and oils) were measured at different
magnetic field strengths and concentrations. Data: T1 decreased with increasing concentration except for PEG. The T1 and T2 relaxivities of polyethylene glycol (PEG), polyvinylpyrrolidone (PVP), sodium polyacrylate, and deionized water did not significantly vary with field strength. The T2 relaxivities of gelatin and sodium alginate did not significantly vary with field strength. All of the hydrogels and paramagnetic electrolyte solutions had high static dielectrics (e.g., {\epsilon}s~70) similar to water. The static electrical conductivities of Miller's LB agar, gelatin, PVA, sodium alginate, sodium polyacrylate, xanthan gum, CuSO4, NiCl2, and Mn(NO3)2 rose with concentration. However, the conductivities of PEG and PVP did not rise with concentration. Conclusions: Sodium polyacrylate, PVP, and PEG hydrogels are challenging for generating consistent phantoms. Sodium alginate, Miller's LB agar, and xanthan gum were good hydrogel candidates. Mn(NO3)2 had the highest relaxivities of the tested samples. All three oils (canola, castor, and grapeseed) are good candidates for low dielectric ({\epsilon}s<10) phantoms for high field applications) but with low conductivities.
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Chemical Physics · Cross-listed from cond-mat.stat-mech
Exact Expressions of Entropy for Classical Non-interacting Many-body Systems
Yuheng Wu, Henrik Heelweg and Rigel Galgana
In the thermodynamic limit, the
equilibrium state of a many-body system can be characterized by three pairs of conjugate thermodynamic variables: $E/T,V/P,N/\mu$. In this limit, the thermodynamic properties in all ensembles are equivalent up to the leading order of $E,V,N$. However, for systems of finite size, this ensemble equivalence is no longer exact, and the thermodynamic properties may differ substantially among ensembles. To quantify these finite-size effects rigorously, it is desirable to develop a universal ensemble theory applicable to systems of arbitrary size, providing exact expressions for
entropy and, thereby, giving rise to the precise value of all
equilibrium thermodynamic quantities. In this work, we propose a theory that determines the exact
entropy expressions for classical non-interacting many-body systems of arbitrary size across all statistical ensembles, based on only two postulates: stationarity, requiring that the physical laws be invariant under time translation, and unbiasedness, requiring that the
equilibrium mixed state maximize the
entropy subject to the prescribed constraints. Moreover, we show that the
entropy expressions obtained in different ensembles converge to the common asymptotic form $S \asymp \ln\!\left( \left( \frac{4\pi m e E}{3N} \right)^{3N/2} \cdot \left(\frac{V}{N}\right)^N \right)+N$, consistent with the predictions of the large deviation theory.
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Optics
High-dimensional Supermode Photonics Enabled by Hierarchical Supersymmetric Transformation
Yuan Zhong, Kaile Chen, Qi Lu et al. (+8 more)
Modes provide a fundamental degree of freedom for photonic information processing, yet conventional multimode waveguides exhibit non-equidistant effective-index distributions, making closely spaced modes vulnerable to intermodal crosstalk. Supermode photonics can overcome this limitation by geometrically engineering coupled waveguide arrays to realize large and equidistant effective-index spacing, but precise supermode excitation and detection remain challenging at the subwavelength scale. Here, we report a hierarchical second-order discrete supersymmetric (DSUSY) transformation method that enables high-purity excitation and extraction of arbitrary target supermodes in a compact and scalable architecture. We experimentally demonstrate six-supermode multiplexing systems on silicon-on-
insulator and silicon nitride platforms. Benefiting from the large supermode index spacing and the isospectrality of DSUSY transformations, the fabricated devices exhibit low insertion losses (<2.6 dB) and intermodal crosstalk (<-11.1 dB) for all channels over a 100-nm wavelength range. A high-speed transmission experiment on the silicon device achieves an aggregate data rate of 1.2 Tbit/s, with all channel bit error rates below the 7% hard-decision forward-error-correction threshold. The method can further support polarization-insensitive architectures, enabling compact polarization-supermode hybrid multiplexing. This work provides a scalable route toward high-dimensional supermode photonics for high-capacity optical interconnects, highly parallel AI optical computing, and high-dimensional
quantum information processing.
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All authors Yuan Zhong, Kaile Chen, Qi Lu, Chunxue Wang, Jingchi Li, Yuru Li, Zhaohui Li, Chao Lu, Xinchen Ji, Yikai Su, Lu Sun