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In-Plane Cation Ordering and Sodium Displacements in Layered Honeycomb Oxides with Tetravalent Lanth
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Strategies to Reduce Promoter-Independent Transcription of DNA Nanostructures and Strand Displacement Complexes
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The Formation and Displacement of Ordered DNA Triplexes in Self-Assembled Three-Dimensional DNA Crystals
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Capture and displacement-based release of the bicarbonate anion by calix[4]pyrroles with small rigid straps
The inherent selectivity of anion receptors can be reversed by ion pairing occurring both inside and outside of the receptor cavity.
Bifurcation-driven vertical plasma displacement
This paper considers vertical plasma motion resulting from plasma current decay during the disruption event. The presented filament-based model describes the motion in the ideal wall limit as an adiabatically slow evolution of the plasma equilibrium. Here, the equilibrium exhibits a pitchfork bifurcation when the decaying plasma current passes a critical value determined by the external magnetic field. This bifurcation affects the disruption-induced mechanical loads on the first wall.
Relative permeability as a stationary process: Energy fluctuations in immiscible displacement
Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work, we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large length scales and relying on averaging in both space and time to homogenize the behavior. Explicit criteria are obtained to define stationary conditions: (1) there can be no net change for extensive measures of the system state over the time averaging interval; (2) the net energy inputs into the system are zero, meaning that the net rate of work done on the system must balance with the heat removed; and (3) there is no net work performed due to the contribution of internal energy fluctuations. Results are then evaluated based on direct numerical simulation. Dynamic connectivity is observed during steady-state flow, which is quantitatively assessed based the Euler characteristic. We show that even during steady-state flow at low capillary number ([Formula: see text]), typical flow processes will explore multiple connectivity states. The residence time for each connectivity state is captured based on the time-and-space average. The distribution for energy fluctuations is shown to be multi-modal and non-Gaussian when terms are considered independently. However, we demonstrate that their sum is zero. Given an appropriate choice of the thermodynamic driving force, we show that the conventional relative permeability relationship is sufficient to model the energy dissipation in systems with complex pore-scale dynamics that routinely alter the structure of fluid connected pathways.
Interframe-tunable ultrafast differential-displacement holography
Here we describe the details of a digital holographic microscopy diagnostic capable of quantifying both the topography and velocity of a km/s object with adjustable temporal sensitivity. This technique involves spatially multiplexing a double pulse reflected from a target with reference beams of precisely known temporal separation.
Trigger strategy for displaced muon pairs following the CMS phase II upgrades
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Search for long-lived, massive particles in events with a displaced vertex and a muon with large impact parameter in pp collisions at $\sqrt{s}$=13 TeV with the ATLAS detector
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Heavy QCD axion at Belle II: Displaced and prompt signals
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Search for events with a pair of displaced vertices from long-lived neutral particles decaying into hadronic jets in the ATLAS muon spectrometer in p p collisions at s = 13 TeV
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Sequential displaced vertices: Novel collider signature for long-lived particles
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Dark photons and displaced vertices at the MUonE experiment
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Displaced signals of hidden vectors at the Electron-Ion Collider
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Displacement field analysis via optimal transport: Multitracer approach to cosmological reconstruction
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Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information
We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025
Cornering Higgsinos Using Soft Displaced Tracks
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