759 papers
This paper demonstrates that applying Deep Neural Networks to a 2x2 array of linearly-graded Silicon Photomultipliers significantly improves position resolution and linearity while increasing the number of resolvable pixels by a factor of 5.7 to 12.1 compared to traditional reconstruction methods.
This study combines experimental measurements with linear modeling to reveal that low-frequency coherent structures in separated turbulent flow over a Gaussian bump are driven by a three-dimensional zero-frequency modal instability and finite-span standing-wave dynamics, offering a physical explanation for discrepancies between simulations and experiments while highlighting the critical need for adequate spanwise domain sizes in numerical studies.
This paper presents the first results of the CASSIA sensor, a novel monolithic active pixel sensor fabricated in 180 nm CMOS technology that utilizes fully integrated internal gain layers to achieve signal amplification, enabling operation in both low-gain proportional and high-gain single-photon avalanche modes for improved timing resolution and pile-up mitigation in high-luminosity particle physics experiments.
This paper proposes a Planck-scale "information-geometry ledger" that balances geometric entropy, reversible modular energy, and irreversible Landauer-Bennett costs on causal horizons to derive the nonlinear Einstein equations and motivate a specific two-component vacuum energy model in FLRW cosmology.
To support the ALICE Time Projection Chamber's continuous readout mode during LHC Run 3, the authors present a custom, large-scale FPGA-based pipeline that performs real-time signal processing—including common-mode correction, pedestal subtraction, and ion-tail filtering—to reduce raw data rates from over 3 TB/s to approximately 900 GB/s under extreme high-occupancy conditions.
This study utilizes an extended vertex model to demonstrate that cell-cell adhesion acts as a double-edged sword in tissue dynamics, where its energetic component promotes cell migration by lowering rearrangement barriers, while its dissipative component induces jamming and suppresses motion, thereby governing the balance between tissue fluidity and rigidity.
This paper introduces a novel early warning signal called DE-AC, which estimates the dominant eigenvalue from autocorrelation functions to reliably predict the onset of period-doubling bifurcations in cardiac systems with superior sensitivity and specificity compared to existing indicators.
This paper introduces Drifting Models for molecular conformation generation, leveraging a novel Drifting Force Identity to incorporate physical force labels into one-step sampling, thereby achieving million-fold acceleration over traditional molecular dynamics while maintaining perfect structural validity and Boltzmann distribution accuracy.
The paper introduces Programmable Acoustic Standing-wave Transfection (PAST), a non-invasive microfluidic platform that utilizes dynamically programmable ultrasonic fields to reversibly permeabilize cell membranes and enhance intracellular delivery of biomolecules in cell clusters with high viability and tunable transport rates.
This study develops and validates a combined analytical and numerical framework linking thermal spray nozzle operating conditions to far-field aeroacoustic signatures and in-flight particle transport, demonstrating that acoustic monitoring can serve as a non-intrusive method for controlling and optimizing the thermal spray process.
This study challenges the prevailing geometric paradigm of epithelial fluidization by demonstrating that reducing cell-cell adhesion can trigger a shape-independent transition to a fluid state, necessitating a revised theoretical model that accounts for adhesion's dual role in both interfacial energy and kinetic viscous drag.
This paper reviews the analogue gravity description of unidirectional water waves in two-dimensional flows with constant shear, demonstrating that such flows can be effectively modeled by a curved spacetime metric without requiring prior knowledge of general relativity.
This paper introduces a novel hybrid ensemble forecasting framework that uses spectral nudging to integrate machine-learned large-scale guidance with physics-based mesoscale dynamics, resulting in significant forecast skill improvements of up to two days in the tropics and enhanced tropical cyclone track predictions without compromising storm intensity or ensemble spread.
This paper proposes a constructive, physics-based approach to designing interatomic potentials by leveraging density functional theory theorems and analytic constraints to build interpretable latent space embeddings that formally couple electronic and atomic scales, thereby addressing the limitations of current machine learning models regarding combinatorial complexity and unseen bonding motifs.
This study develops and validates a computationally efficient ultra-high frequency ultrasound imaging pipeline using interframe subtraction with motion compensation to effectively quantify microvascular flow and assess treatment response in avian chorioallantoic membrane xenograft renal cell carcinoma models.
This paper establishes an operational criterion for the emergence of a well-defined global phase in time-dependent oscillator networks, demonstrating that phase robustness depends on the competition between coupling strength and ramp rates, with spectral properties governing synchronization in random networks while topological defects induce persistent partial ordering in spatial lattices.
This paper develops a reaction-coordinate-resolved information-theoretic framework using Partial Information Decomposition to analyze chemical reactivity, demonstrating how mutual information between electronic readouts and geometric progress variables reveals distinct redundant, unique, and synergistic signatures of bonding evolution in prototypical S2 reactions.
The paper introduces SAFT-P, a plaquette-level extension of Statistical Associating Fluid Theory that improves the modeling of self-assembly in patchy colloids by retaining topology-dependent information and accurately predicting critical points and coexistence curves for particles with identical valence but different patch layouts.
This study introduces a novel RT-TDDFTB+LQBE simulation framework to investigate real-time electron-electron scattering in plasmonic nanoclusters, revealing that quasiparticle lifetimes and relaxation dynamics are highly energy-dependent, exhibit quantum fluctuations in sub-2 nm clusters, and are significantly modulated by interband transitions and Auger scattering in gold.
This study evaluates activation foils and capsule materials for fusion neutron yield measurements, demonstrating that aluminum and copper foils are suitable for multi-foil configurations, 3D-printed thermoplastic capsules introduce negligible measurement bias despite slight count reductions, and lanthanum-based detectors offer a viable alternative to high-purity germanium spectrometers.