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The advent of layered materials has unveiled new opportunities for tailoring electromagnetic waves at the subwavelength scale, particularly through the study of polaritons, a hybrid light–matter excitation. In this context, twist-optics, which investigates the optical properties of twisted stacks of van der Waals (vdW) layered specimens, has emerged as a powerful tool. Here, we explore the tunability of phonon polaritons in α-V₂O₅via interlayer twisting using scanning nano-infrared (IR) imaging. We show that the polaritonic response can be finely adjusted by varying their interlayer electromagnetic coupling, allowing for precise control over the propagation direction and phase transition from open unidirectional iso-frequency contours to closed elliptic geometries. Our experimental results, in conjugate with theoretical modeling, reveal the mechanisms underpinning this tunability, highlighting the role of twist-induced nano-light modifications for advanced nanophotonic control at the nanoscale. 

Microtubule-kinesin active fluids are distinguished from conventional passive fluids by their unique ability to consume local fuel, ATP, to generate internal active stress. This stress drives internal flow autonomously and promotes micromixing, without the need for external pumps. When confined within a looped boundary, these active fluids can spontaneously self-organize into river-like flows. However, the influence of a moving boundary on these flow behaviors has remained elusive. Here, we investigate the role of a moving boundary on the flow kinematics of active fluids. We confined the active fluid within a thin cuboidal boundary with one side serving as a mobile boundary. Our data reveals that when the boundary's moving speed does not exceed the intrinsic flow speed of the active fluid, the fluid is dominated by chaotic, turbulence-like flows. The velocity correlation length of the flow is close to the intrinsic vortex size induced by the internal active stress. Conversely, as the boundary's moving speed greatly exceeds that of the active fluid, the flow gradually transitions to a conventional cavity flow pattern. In this regime, the velocity correlation length increases and saturates to those of water. Our work elucidates the intricate interplay between a moving boundary and active fluid behavior. *We acknowledge support from the National Science Foundation (NSF-CBET-2045621). 

An investigation of high-transverse-momentum (high- $p_T$) photon-triggered jets in proton-proton ( $p\text{−}p$) and ion-ion ( $A\text{−}A$) collisions at $\sqrt{s_{NN}}=0.2$and $5.02\mathrm{TeV}$is carried out, using the multistage description of in-medium jet evolution. Monte Carlo simulations of hard scattering and energy loss in heavy-ion collisions are performed using parameters tuned in a previous study of the nuclear modification factor ( $R_{AA}$) for inclusive jets and high- $p_T$hadrons. We obtain a good reproduction of the experimental data for photon-triggered jet $R_{AA}$, as measured by the ATLAS detector, the distribution of the ratio of jet to photon $p_T$( $X_{J\gamma }$), measured by both CMS and ATLAS, and the photon-jet azimuthal correlation as measured by CMS. We obtain a moderate description of the photon-triggered jet $I_{AA}$, as measured by STAR. A noticeable improvement in the comparison is observed when one goes beyond prompt photons and includes bremsstrahlung and decay photons, revealing their significance in certain kinematic regions, particularly at $X_{J\gamma }>1$. Moreover, azimuthal angle correlations demonstrate a notable impact of bremsstrahlung photons on the distribution, emphasizing their role in accurately describing experimental results. This work highlights the success of the multistage model of jet modification to straightforwardly predict (this set of) photon-triggered jet observables. This comparison, along with the role played by bremsstrahlung photons, has important consequences on the inclusion of such observables in a future Bayesian analysis. Published by the American Physical Society2025 

The Collaboration reports a new determination of the jet transport parameter $\hat{q}$in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published Bayesian inference determination of $\hat{q}$, which was based solely on a selection of inclusive hadron suppression data. is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation. Published by the American Physical Society2025