Papers

Particle Dobble is an open-access, gamified learning tool designed to address persistent misconceptions in particle physics education by symbolically representing elements of the Standard Model. Aimed at upper secondary and introductory undergraduate students, the card game adapts the combinatorial structure of Dobble to create a deck in which each pair of cards shares exactly one particle symbol, fostering repeated retrieval practice and conceptual discussion. By deliberately replacing literal depictions of particles with abstract icons, the game challenges Newtonian "tiny billiard ball" mental models and promotes a relational, non-classical understanding of elementary particles. Grounded in research on student difficulties in quantum mechanics and gamification in science education, Particle Dobble serves as a low-threshold intervention to prepare learners for more formal engagement with quantum field concepts.

Photoacoustic tomography (PAT) and thermoacoustic tomography (TAT) both leverage acoustic signals generated by electromagnetic absorption to noninvasively image deep tissues. PAT operates by detecting optical absorption, whereas TAT targets radiofrequency (RF) absorption, providing complementary information on tissue composition and structure. Combining these modalities into a single system promises richer contrast but remains difficult due to the expense and complexity of the RF source. Here, we show that PAT can be integrated with a low-cost RF heater and used to image both optical and RF absorption in tissue phantoms. RF Heating-Enhanced Photoacoustic Tomography (HEPAT) maps RF absorption via temperature-dependent changes in thermomechanical properties, which enables the use of slow, inexpensive RF subsystems and provides an additional layer of contrast. HEPAT therefore provides distinct, complementary contrast relative to existing photoacoustic imaging systems, expanding specificity and diagnostic power while opening new avenues for studying temperature-related tissue phenomena.

Thin-film dewetting is classically governed by an adhesion-mediated spinodal instability in which curvature-driven diffusion controls post-rupture coarsening. We show that internal activity fundamentally restructures this instability. Using a minimal microscopic model of an active liquid film on a solid substrate, we identify a competition between active stresses and film-substrate adhesion that produces two independently regulated dynamical length scales: vertical liquid accumulation and lateral rupture propagation. While passive films exhibit universal diffusion-limited growth, $\ell_z(t)\sim t^{1/3}$, activity converts transport from curvature-controlled diffusion to persistence-driven motion, yielding a continuous increase of the coarsening exponent from $\approx 0.33$ to $\approx 0.6$. The growth law analysis shows that persistent self-propulsion introduces an advective flux that competes with curvature-induced chemical potential gradients, enhancing growth when the persistence length becomes comparable to the evolving domain size. Simultaneously, the rupture front transitions from dissipative spreading to strongly accelerated propagation approaching ballistic scaling. This decoupling shows that activity does not simply renormalize effective surface forces but generates a distinct nonequilibrium interfacial instability governed by the balance between persistence length and adhesion. The results provide a minimal physical mechanism linking classical thin-film dewetting to dewetting-like rupture observed in active and biological materials.

Atomically confined spins are emerging as active components in quantum optoelectronic devices such as quantum bits and sensors. However, interrogating single spins at atomic length-scales remains a sizeable challenge, limited by diffraction in conventional optics. Here we show that the highly-local excitation provided by injecting energetic charge carriers from the atomically sharp probe of a scanning tunneling microscope can trigger single-photon emission from individual atomic vacancy centers in a layered semiconductor. With an effective spatial resolution of <1 nm, we show that the captured light closely mirrors the orbital symmetry of the bound-state wavefunction of the vacancy center while photon correlation measurements confirm single-photon emission, as reflected in clear photon anti-bunching signatures. Our results constitute an important step toward the realization of an electrically addressable single-atom quantum light source and solid-state spinphoton interface, addressed at the atomic-scale.

Ultracold molecules provide opportunities for exploring quantum matter, chemical dynamics and information processing thanks to their rich interactions, which can be controlled by external fields. Magnetic fields tune interactions through Feshbach resonances, enabling the formation of ultracold dimers and triatomic molecules from atom-dimer collisions. Here we demonstrate electric-field control of atom-molecule Feshbach resonances. In mixtures of ground-state sodium-potassium molecules and potassium atoms, electric fields shift resonance positions systematically, revealing specific trimer bound states and their electric-field dependent energies. The response differs markedly from isolated dimers, showing hindered rotation of the molecular constituent near an atom. Electric fields therefore add an independent knob for atom-molecule resonances, open spectroscopic access to triatomic quantum states, and advance controlled polyatomic quantum matter.

This Review is devoted to the presentation of the exact factorization as a framework employed to study a variety of quantum-mechanical many-body problems. Since its original formulation in the 70s, the main applications of the exact factorization were directed towards understanding the properties of multi-component systems, e.g. electron-nuclear systems. Especially in the electron-nuclear case, the exact factorization is viewed as an exactification of the Born-Oppenheimer approximation, thus it was, and still is, largely employed in nonadiabatic dynamics. Nonetheless, as early as the 80s, the formalism was employed to study many-electron interacting systems and, quite recently, i.e. less than a decade ago, it was extended to study the behavior of molecules in the context in cavity quantum electrodynamics. These formulations, perhaps less popular than the electron-nuclear formulation, have attracted a lot of attention over the years. Therefore, we review here the exact electron-only factorization and the exact photon-electron-nuclear factorization.

Electron attachment to DNA is strongly influenced by its molecular environment, yet the role of amino acids under physiologically relevant conditions remains poorly understood. Here, we investigate the effect of native and zwitterionic glycine on electron attachment to thymine using high-level electron-affinity calculations and QM/MM molecular dynamics simulations. Under micro-solvated conditions, electron attachment occurs through a dipole-bound doorway state that evolves into a valence-bound anion via nonadiabatic coupling. The zwitterionic form of glycine strengthens stabilization of the diffuse electron owing to its larger internal charge separation, whereas the stability of the valence-bound anion is determined by the hydrogen-bonding geometry. Barrier-free proton transfer is observed only for specific binding motifs and substantially stabilizes the thymine-centered anion. In bulk solution, the doorway mechanism persists, with a solvent-bound state replacing the dipole-bound state as the initial electron-trapping state. The larger electrostatic field of zwitterionic glycine delays electron localization on thymine, while permanent proton transfer is observed only in selected native glycine trajectories and is absent throughout the present simulations of zwitterionic glycine. Despite these differences in electron-transfer dynamics, both amino acid forms provide similar stabilization of the thymine-centered anion after solvent reorganization. Our results establish the solvent-bound state as the condensed-phase analogue of the dipole-bound doorway state and reveal how amino acid environments modulate electron attachment pathways in realistic DNA systems.

Personal care formulations often contain synthetic and non-biodegradable ingredients, such as silicone and mineral oils, which can offer a unique performance. However, due to regulations like the EU ban of Octamethylcyclotetrasiloxane (D4), Decamethyl-cyclopentasiloxane (D5), Dodecamethylcyclohexasiloxane (D6) already in effect for rinse off and for leave on cosmetics by June 2027 coupled with growing consumer awareness and expectations on sustainability, personal care brands face significant pressure to replace these synthetic ingredients with natural alternatives without compromising performance and cost. As a result, formulators are confronted with the challenge to find natural-based solutions within a short timeframe. In this study, we propose a pioneering approach that utilizes predicting modelling and simulation-based digital services to obtain natural-based ingredient combinations as recommendations to commonly used synthetic ingredients. We will demonstrate the effectiveness of our predictions through the application of these proposals in specific formulations. By offering a platform of digital services, it is aimed to empower formulators to explore good performing novel and environmentally friendly alternatives, ultimately driving a substantial and genuine transformation in the personal care industry.

Stroboscopic nanoscale imaging with free electron laser light is revolutionizing our understanding of fast dynamics in heterogeneous systems. The short wavelength of X-ray and extreme ultraviolet radiation makes it possible to achieve nanoscale resolution, while resonance with atomic transitions gives access to electronic and magnetic degrees of freedom. Here, we report on our implementation of a recently developed imaging method, randomized probe imaging, at a free electron laser. The advantage of randomized probe imaging over existing methods is its compatibility both with extended and strongly scattering samples. Our implementation delivers robust single-shot reconstructions at up to a full-pitch resolution of 400 nm over a field of view with a 40 {\mu}m diameter. We also demonstrate single-shot imaging of magnetic domain structures using circular dichroism at resonance, paving the way to future time-resolved studies of magnetic dynamics, shock physics, and the dynamics of collective electronic phases.

We propose a coupled system for the nonlinear interaction between high-frequency, circularly polarized, intense electromagnetic (EM) waves and low-frequency electron-density perturbations, driven by the EM-wave ponderomotive force, in an unmagnetized plasma composed of fully degenerate relativistic electrons and stationary positive ions, including a higher-order correction to the nonlocal nonlinearity. We show that the modulational instability (MI) growth rate associated with the generation of EM envelope solitons gets significantly reduced with a slight increase in either the nonlocal nonlinear correction or the degeneracy parameter. Furthermore, a three-wave temporal model predicts the existence of quasiperiodic and chaotic states of EM solitons while interacting with longitudinal electron density perturbations. We show that the greater the degeneracy (or the higher the contribution from the nonlocal correction), the smaller the instability domain of modulation wave numbers; thus, degeneracy favors the stability of EM soliton evolution. The existence of temporal chaos in a low-dimensional model could be a signature of the development of spatiotemporal chaos in the complete nonlinear model, in which many electromagnetic solitons can be excited and saturated as they interact with electron plasma waves.

We report on a comb-locked cavity ring-down spectrometer developed for high-precision, SI-traceable, molecular spectroscopy of air-broadened CO2 gas samples. The experimental setup relies on the use of a singly-resonant optical parametric oscillator that acts as an intermediate link between a 2 micron external-cavity diode laser and an optical frequency comb stabilized against a GPS-disciplined Rb-clock. Absorption spectra of the R(50) ro-vibrational component of the CO2 20012-00001 band have been recorded with high precision and fidelity. As a result of a refined spectral analysis, based on the implementation of the modified Hartmann-Tran profile, line center frequencies, pressure broadening and pressure shifting coefficients have been determined. Finally, we demonstrate the measurement of CO2 mole fractions with a subpromille statistical uncertainty

Optical-field sampling using second-harmonic generation (SHG) from strong-field ionization enables ultrabroadband terahertz detection, but the microscopic origin of the SHG signal and its ultrabroadband response have been unclear. Here we show that the target field lifts the half-cycle cancellation of photoelectron dipole emission, generating the SHG signal used for field sampling. Time-dependent Schrodinger-equation simulations, supported by classical-trajectory Monte Carlo analysis, demonstrate that the SHG yield directly encodes the instantaneous target electric field at the ionization time, enabling waveform retrieval by scanning the probe-target delay. Because the SHG response is gated by a subcycle ionization window rather than the probe envelope, the detection bandwidth can extend far beyond the probe duration. We further quantify practical constraints on retrieval, including intrinsic probe asymmetry and SHG back-action, providing a predictive framework to optimize sensitivity, temporal resolution, and fidelity through controlled electron dynamics.

Smoking behavior and awareness co-spread through social interactions, giving rise to coupled contagion processes on social contact networks. In addition to initiation and cessation, awareness of the harmful effects of smoking plays an important role in shaping individual behavior and population-level outcomes. In this work, we develop a mathematical model to study the coupled dynamics of smoking behavior, quitting, and awareness in a population. A deterministic framework based on ordinary differential equations is first formulated to capture the interplay between social influence and awareness-driven behavioral change. Analysis of the model reveals the existence of smoking-free and smoking-endemic steady states, and identifies conditions under which awareness can reduce or suppress the persistence of smoking. Since social interactions are often localized rather than well mixed, the mean-field description is then extended to a network-based model that incorporates structured contact patterns. Numerical simulations performed on empirical social networks indicate that contact heterogeneity and localized awareness spreading can influence the effectiveness of interventions. Our findings underscore the importance of population structure when devising awareness-based intervention strategies for smoking cessation.

In modern correlation imaging systems, also known as ghost imaging (GI), particularly under low-light or noisy conditions, preserving high image fidelity presents a significant challenge. This paper introduces an innovative approach by integrating Bose-Chaudhuri-Hocquenghem (BCH) error control coding (ECC) into CGI systems to assist imaging. By encoding target image with BCH codes and using order-statistic decoding (OSD) for error correction during reconstruction, this approach significantly improves image quality across various signal-to-noise ratio (SNR) conditions. Simulation and experiment results validate that BCH coding assisted imaging achieves significantly enhanced robustness against additive white Gaussian noise (AWGN) and improved image reconstruction quality. In addition, the imaging performance of different BCH codes varies, with each code exhibiting distinct advantages based on factors such as code length and coding efficiency.

Strong coupling between molecular excitations and quantized electromagnetic fields in optical cavities provides a powerful means to control the physical and chemical properties of molecular systems. Here, we study electron transfer (ET) dynamics in cavity-coupled molecules using the numerically exact hierarchical equations of motion (HEOM) method, which captures nonperturbative and non-Markovian effects beyond standard perturbative theories. We identify distinct resonance and collective effects associated with polariton formation and show that the ET rate saturates in the strong-coupling regime, a feature not captured by perturbative approaches. We further extend the cavity-modified ET model by incorporating the nuclear-coordinate dependence of molecular electric dipole moments, which gives rise to a three-body interaction involving molecular electronic and vibrational degrees of freedom and cavity photons. This vibronic polariton formation leads to non-monotonic, oscillatory dependencies of the ET rate on the light-matter coupling strength and cavity frequency, which we attribute to quantum interference among multiple transfer pathways. These findings establish cavity-modified electron transfer as a multichannel quantum process governed by the interplay of electronic, vibrational, and photonic degrees of freedom.

We experimentally investigate the Lagrangian dynamics of finite-sized, neutrally buoyant droplets in homogeneous isotropic turbulence. The droplet size follows a log-normal distribution whose average value decreases with increasing Reynolds number, reflecting enhanced turbulent breakup. While size-conditioned velocity and acceleration statistics show only weak finite-size dependence, temporal measures reveal clear size-dependent dynamics: larger droplets exhibit longer Lagrangian velocity integral times and an extended ballistic regime in their mean squared displacement. These findings indicate that though droplets exhibit mild deformation and internal circulation, they behave similarly to finite-size rigid particles in terms of Lagrangian dynamics. Our study opens the way to study droplet-laden turbulence and droplet-flow interactions.

The transport of the Antarctic Circumpolar Current (ACC) has been shown to increase with friction. Previous studies explained this counter-intuitive relationship called frictional control based on the eddy geometric parametrizations. They focused on the eddy momentum transfer and eddy energetics. To maintain the balance between wind stress and eddy interfacial form stress, eddy energy must remain unchanged as friction increases; this requires enhanced baroclinicity to compensate for stronger eddy energy dissipation. However, the independence of eddy energy has not been fully verified, and this interpretation assumes negligible barotropic energy conversion. To address this gap, we conduct sensitivity experiments in an idealized stratified reentrant channel with varying linear bottom drag. Numerical simulations show that eddy energy changes substantially with friction. Furthermore, in the high-drag regime, baroclinic energy conversion dominates eddy energy generation, whereas in the low-drag regime barotropic energy conversion contributes substantially. Despite these differences, baroclinicity increases with eddy energy dissipation across all regimes, although the relationship is somewhat weak in the low-drag regime owing to barotropic energy conversion. To explain this phenomenon, we extend the frictional control framework based on the Lorenz energy cycle. A simple scaling argument leads to a generalized frictional control, s~D(E)/{\tau}_w, where s is baroclinicity, D(E) is eddy energy dissipation, and {\tau}_w is wind stress. This framework provides a natural extension of the existing framework and successfully explains the numerical results. These results indicate that eddy dissipation controls the baroclinicity; therefore, properly parameterizing the eddy dissipation rate is essential for representing ACC dynamics in ocean models.

We investigated the impact of a coronal mass ejection (CME) on the transport and acceleration of relativistic protons in the solar wind using a coupled 3D magnetohydrodynamics (MHD) simulation and a test-particle approach. The CME is driven by a spheromak injected into a Parker solar wind at a heliocentric distance of 0.139 AU. We integrated the trajectories of 5 GeV protons, injected toward the CME from 3 AU, in the guiding-center approximation and scattered the particles in velocity space with a mean free path $\lambda_{\|}$. Our results show that the CME can increase the protons' energy by several gigaelectronvolts. The acceleration occurs while particles stream along the portion of a magnetic field line downstream of the quasi-perpendicular portion of the CME-driven shock. In our configuration, the maximum energy gain, which is on the order of a few percent per passage through the acceleration region, occurs when the shock approaches 0.3 AU. Large energy gains require multiple passes through the acceleration region, made possible by the combined action of the mirror force and pitch-angle scattering. The efficiency of the acceleration on timescales on the order of hours scales as $\lambda_{\|}^{-3/2}$. Energy spectra harden with decreasing parallel mean free path $\lambda_{\|}$.

We propose that the symmetry-breaking bifurcation of coupled topological edge states (CTESs) can be used as a general principle for achieving spontaneous symmetry breaking (SSB) in a nonlinear topological lattice. Using an optical resonator array composed of two Su-Schrieffer-Heeger (SSH) chains as an example, we find that as the nonlinearity strength increases, the symmetric CTESs undergo a supercritical bifurcation. Beyond the critical threshold, the originally stable symmetric state becomes unstable, leading to the formation of a pair of stable asymmetric states. Both sides of the symmetric CTESs exhibit sublattice polarization, while the side of the asymmetric CTESs that is predominantly occupied demonstrates stronger sublattice polarization. We further find that as interchain coupling increases, the frequency range for stable CTESs expands, while the frequency range for stable asymmetric CTESs decreases. Our work provides a universal mechanism for realizing SSB in nonlinear topological lattices.

Imaging the full-field microvibration of extended targets remains a formidable challenge for conventional remote sensing. Traditional array-based sensors are often severely constrained by data throughput and sensitivity limits when scaling to high spatial resolutions, while point-scanning interferometric systems lack the instantaneous full-field capability required to capture transient, spatially coupled vibration modes. To overcome these limitations, we propose a Coherent Detection-Ghost Imaging (CD-GI) framework that synergizes the spatial multiplexing capability of single-pixel imaging with the high-dimensional sensitivity of coherent detection. We establish a comprehensive mathematical model that describes the coupling mechanism of the target's spatial distribution and temporal micro-dynamics within a 1D bucket detector signal. To resolve the resulting inverse problem, we develop a frequency-channel self-calibration scheme. This approach effectively decouples the micro-Doppler signatures from spatial speckle patterns without requiring prior knowledge of the vibration frequency. Experimental results demonstrate that our system successfully reconstructs the spatially resolved microvibration patterns of adjacent targets with a frequency difference as small as 1 Hz, achieving sub-wavelength vibration sensitivity. This work bridges the gap between computational imaging and coherent metrology, offering a robust solution for non-invasive, high-precision structural health monitoring.

Magnetic reconnection in partially ionized plasmas plays a crucial role in a wide range of solar, astrophysical, and laboratory environments. While reconnection in such plasmas is commonly characterized by the ion-neutral coupling strength and the ionization fraction $\chi=n_{i}/(n_{i}+n_{n})$, most previous studies have focused primarily on the former. A systematic exploration of the ionization fraction, particularly in combination with ion-neutral coupling, is still lacking. This study presents the first systematic scan of the two-dimensional parameter space defined by ion-neutral collisionality and ionization fraction, enabling investigation of the transition from strongly coupled reconnection to faster, decoupled reconnection. To achieve this, we employ a new three-fluid, five-moment numerical model that treats electrons, ions, and neutrals as separate species on an equal footing. We find that in the strongly coupled regime, the reconnection rate is consistent with a $\chi^{1/4}$ scaling. As collisionality decreases, the system transitions to a fast, ionization-independent regime. On the other hand, in the weakly coupled and fast-reconnection regimes, the current sheet approaches an ion-inertial-scale thickness rather than the expanded hybrid scale $d_{i}\chi^{-1/2}$ predicted by fully coupled analytic fluid theories. The identified critical thickness and the resulting onset of fast reconnection agree reasonably well with recent fully kinetic simulations and laboratory experiments. In addition, we show that, over a wide range of coupling strengths, the ion outflow velocities remain Alfvénic, scaling with the appropriate ion or hybrid Alfvén speed, while the hybrid outflow velocity scales as $\chi^{1/2}$ when normalized by ion Alfvén speed.

In this paper, we present development of a portable cosmic muon tracker tailored for both on-site measurements of cosmic muon flux as well as for outreach activities. The tracker comprises of two 70 mm x 70 mm plastic scintillators, wavelength shifting (WLS) fibers, and Hamamatsu made Silicon Photomultipliers (SiPM) S13360-2050VE. The detector uses plastic scintillator panels optically coupled to WLS fibers, which transmit scintillation light to the SiPMs. SiPM signals are routed to an electronics board equipped with op-amp amplifiers and a peak-hold circuit connected to an ESP32 microcontroller module. When muons traverse through both scintillators the light emitted is collected by the SiPMs, and thus generating signals proportional to the incident light intensity. These signals are then amplified and the pulse peak is held for 500 us. A high speed discriminator is used to generate trigger logic signals. The peak analog voltage is digitized using the onboard ADC of the ESP32 when a coincident trigger occurs. The SiPMs are powered by a High Voltage bias supply module while an onboard BMP180 module measures temperature and pressure. For real-time event tagging, a GPS module is interfaced with the ESP-32. Housed within an acrylic box measuring 100 mm x 100 mm x 100 mm the detector can be powered using a 5V 1A USB power bank. An open source mobile application was used for real-time monitoring. This versatile and cost-effective portable detector facilitates cosmic muon research in various experimental settings. Its portability and low power requirements enable on-site measurements in environments such as tunnels, caves as well as high altitudes.

Structured x-rays carrying an orbital angular momentum break spatial inversion symmetry and have been proposed as probes of chirality. We theoretically investigate twisted non-resonant x-ray diffraction from chiral molecules and demonstrate that no dichroic signal can arise from randomly oriented molecules, irrespective of the beam spatial profile. However, a dichroic response emerges for oriented molecules. Our results establish the beam and sample conditions for which a measurable dichroic scattering signal survives axial and focal averaging.

Resonant tunneling diodes (RTDs) support room-temperature terahertz (THz) oscillation and simultaneous THz-band detection, enabling compact monostatic THz sensors for practical and cost-effective sensing applications. In this paper, we present a highly integrated 280 GHz-band radar system based on a single RTD that exploits the self-mixing effect to generate a low-frequency interferometric signal. The resulting self-mixing signal is further analyzed from a radar perspective and processed to extract micrometer-scale displacement and thin-film thickness variations. Experimentally, the proposed system demonstrates a minimum detectable displacement of approximately 5 um and quantitatively resolves polymer film thicknesses of 12.5, 25, and 50 um.

Diffractive optical neural networks (DONNs) have demonstrated unparalleled energy efficiency and parallelism by processing information directly in the optical domain. However, their computational expressivity is constrained by static, passive diffractive phase masks that lack efficient nonlinear responses and reprogrammability. To address these limitations, we introduce the Recurrent Diffractive Optical Neural Processor (ReDON), a novel architecture featuring reconfigurable, recurrent self-modulated nonlinearity. This mechanism enables dynamic, input-dependent optical transmission through in-situ electro-optic self-modulation, providing a highly efficient and reprogrammable approach to optical computation. Inspired by the gated linear unit (GLU) used in large language models, ReDON senses a fraction of the propagating optical field and modulates its phase or intensity via a lightweight parametric function, enabling effective nonlinearity with minimal inference overhead. As a non-von Neumann architecture in which the primary weighting elements (metasurfaces) remain fixed, ReDON substantially extends the nonlinear representational capacity and task adaptability of conventional DONNs through recurrent optical hardware reuse and dynamically tunable nonlinearity. We systematically investigate various self-modulation configurations to characterize the trade-offs between hardware efficiency and computational expressivity. On image recognition and segmentation benchmarks, ReDON improves test accuracy and mean intersection-over-union (mIoU) by up to 20% compared with prior DONNs employing either optical or digital nonlinearities at comparable model complexity and negligible additional power consumption. This work establishes a new paradigm for reconfigurable nonlinear optical computing, uniting recurrence and self-modulation within non-von Neumann analog processors.

The impact of magnetic geometry on zonal-flow generation in ion temperature gradient driven turbulence is investigated by means of linear and nonlinear gyrokinetic simulations. The modulation of geodesic curvature on various configurations has revealed amplification of the zonal-flow intensity in relatively smaller geodesic curvature. Based on these findings, a nonlinear proxy model for explorations of a novel magnetic geometry to activate the zonal-flow dynamics is proposed.

We present a microscopic, parameter-free approach for computing the photoluminescence spectra of a single semiconductor nanocrystal. The method derives exciton-phonon coupling directly from the semi-empirical pseudopotential framework and systematically incorporates both diagonal and off-diagonal interactions, expanded to second-order in the phonon modes. The dipole-dipole correlation function was calculated using a Dyson expansion within the Kubo-Toyozawa formalism, enabling a consistent description of the role of pure dephasing and population-transfer on the photoluminescence spectral features. Applied to CdSe/CdS core-shell nanocrystals, the approach quantitatively reproduces experimental photoluminescence spectra over a wide temperature range, revealing that quadratic phonon couplings account for nearly half of the homogeneous linewidth above 100-150 K, while off-diagonal couplings leading to exciton thermalization play only a minor role and only as T approaches 300K.

Seismic wavefields recorded on land are strongly distorted by near-surface heterogeneity, introducing trace-specific, frequency-dependent phase perturbations that persist even after advanced time processing. Conventional surface-consistent deconvolution targets long- to mid-wavelength phase variability through overdetermination, but cannot correct localized, non-surface-consistent distortions, and its effectiveness degrades when such effects dominate, as is often the case for point-receiver data. Additionally, conventional workflows provide no direct, quantitative measure of phase reliability; phase quality is assessed only indirectly through amplitude behavior or visual inspection, leaving residual phase disorder largely undiagnosed. We introduce phase variance as a seismic quality-control attribute by treating seismic phases as circular random variables and analyzing local trace ensembles using circular statistics. This data-driven measure quantifies localized phase dispersion without phase unwrapping, enabling analysis of local phase trends without global assumptions or wavelet models. Phase variance is computed automatically and provides frequency-by-frequency classification from coherent signal to fully randomized, noise-dominated phase. Synthetic tests confirm that phase variance reliably captures imposed phase perturbations and their frequency dependence. Application to field prestack land data shows that conventional processing reduces phase variability primarily in the low-to-intermediate frequency range and struggles within the noise cone, while the highest and lowest frequencies show little improvement. Phase variance operates automatically over the full prestack volume, frequency by frequency, providing a consistent, human-independent metric for defining effective bandwidth and supporting phase-sensitive workflows such as AVO, migration, and full-waveform inversion.

In this work, we develop a random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of charged systems in the isothermal-isobaric (NPT) ensemble. We introduce an SOG splitting of the pressure-related $1/r^3$ kernel, yielding a smooth short-/long-range decomposition for instantaneous pressure evaluation. The long-range part is treated in Fourier space by random-batch importance sampling. Because the radial and non-radial pressure components favor different proposals, direct sampling either increases structure-factor evaluations and communication or leads to substantial variance inflation. To address this tradeoff, we introduce a measure-recalibration strategy that reuses Fourier modes drawn from the radial proposal and corrects them for the non-radial target, producing an unbiased pressure estimator with significantly reduced variance and negligible extra cost. The resulting method mitigates pressure artifacts caused by cutoff discontinuities in traditional Ewald-based treatments while preserving near-optimal $O(N)$ complexity. We provide theoretical evidence on pressure decomposition error, consistency of stochastic approximation, and convergence of RBSOG-based MD. Numerical experiments on bulk water, LiTFSI ionic liquids, and DPPC membranes show that RBSOG accurately reproduces key structural and dynamical observables with small batch sizes ($P\sim 100$). In large-scale benchmarks up to $10^7$ atoms on $2048$ CPU cores, RBSOG achieves about an order-of-magnitude speedup over particle-particle particle-mesh in electrostatic calculations for NPT simulations, together with a consistent $4\times$ variance reduction relative to random batch Ewald and excellent weak/strong scalability. Overall, RBSOG provides a practical and scalable route to reduce time-to-solution and communication cost in large-scale NPT simulations.

Wavefunction-based quantum methods are some of the most accurate tools for predicting and analyzing the electronic structure of molecules, in particular for accounting for dynamical electron correlation. However, most methods of including dynamical correlation beyond the simple second-order Møller-Plesset perturbation theory (MP2) level are too computationally expensive to apply to large molecules. Approximations which reduce scaling with system size are a potential remedy, such as the tensor hyper-contraction (THC) technique of Hohenstein et al., but also result in additional sources of error. In this work, we correct errors in THC-approximated methods using machine learning. Specifically, we apply THC to third-order Møller-Plesset theory (MP3) as a simplified model for coupled cluster with single and double excitations (CCSD), and train several regression models on observed THC errors from the Main Group Chemistry Database (MGCDB84). We compare performance of multiple linear regression models and non-linear Kernel Ridge regression models. We also investigate correlation procedures using absolute and relative corrections and evaluate the corrections for both molecule and reaction energies. We discuss the potential for using regression techniques to correct THC-MP3 errors by comparing it to the "canonical" MP3 reference values and find the optimum technique based on accuracy. We find that non-linear regression models reduced root mean squared errors between THC- and canonical MP3 by a factor of 6-9$\times$ for total molecular energies and 2-3$\times$ for reaction energies.