Binary Black Hole Merger

Magnesium fluoride on xenon difluoride passivated aluminum (Al+XeMgF₂) mirrors have high reflectance encompassing the H Lyman-α at 121.6 nm. Al+XeMgF₂ is a key candidate for space telescopes and satellites that demand far-UV (FUV) measurements coupled with high reflectance at longer wavelengths. Contamination can significantly reduce FUV reflectance, so Al+XeMgF₂ mirrors must be as clean as possible. Protecting the surfaces while in storage is also desirable. We investigated the suitability of four different formulations of Photonic Cleaning Technologies' First Contact Polymer for cleaning and protecting Al+XeMgF₂ coatings by repeatedly cleaning test samples. These were cleaved from a silicon wafer coated with 300 nm of chemical vapor deposited (CVD) silicon nitride (Si₃N₄). All the formulations could clean samples at least once. Using Variable-Angle, Spectroscopic Ellipsometry (VASE), we determined that two (S2 and S3) of the four tested formulations were able to clean and protect the Al+XeMgF₂ surfaces multiple times (>20) over 5 months without detectable alumina growth on the Al in a low humidity environment. There were also no changes to the thickness of 'apparent' MgF₂. Apparent MgF₂ includes the deposited MgF₂, the 2–3 nm AlF₃ layer produced by the XeF₂ passivation step, and contributions from surface roughening. There was also no detectable alumina growth for the controls. The fact that the samples were stored between tests in a desiccator with their First Contact overcoat provides evidence that Al+XeMgF₂ samples can successfully be protected and stored under some First Contact formulations for at least five months in a dry environment. Far-ultraviolet reflectance is not reported here.

Passive radiators are notoriously difficult to characterize because one cannot effectively assess their mechanical parameters with loudspeaker electrical impedance techniques and no motors. This paper discusses the details of passive radiator and dynamic loudspeaker driver parameter measurements through practical experiments conducted with a plane wave tube, the two-microphone transfer function technique, and the two-load method to remove the need for an ideal anechoic termination. A previous theoretical paper demonstrated how normal-incidence transmission losses through these devices in an anechoically terminated tube could yield their mechanical and electrical parameters [Leishman and Anderson, J. Acoust. Soc. Am. 134(1), 223–236 (2013)]. The mechanical parameters follow from an open-circuit transmission loss condition, whereas a driver's electrical parameters follow from an additional closed-circuit condition. This paper presents several experimental results and compares extracted parameters to those derived from electrical impedance measurements and destructive methods. In addition to other parameters, the masses of diaphragm assemblies show favorable agreement. The presented techniques effectively assess passive radiator parameters without employing active driver configurations and then removing their motors, which changes the measured properties. PACS numbers: 43.38.Ja, 43.20.Ye, 43.20.Mv, 43.55.Rg

Volume 3 of the FCC Feasibility Report presents studies related to civil engineering, the development of a project implementation scenario, and environmental and sustainability aspects. The report details the iterative improvements made to the civil engineering concepts since 2018, taking into account subsurface conditions, accelerator and experiment requirements, and territorial considerations. It outlines a technically feasible and economically viable civil engineering configuration that serves as the baseline for detailed subsurface investigations, construction design, cost estimation, and project implementation planning. Additionally, the report highlights ongoing subsurface investigations in key areas to support the development of an improved 3D subsurface model of the region. The report describes the development of the project scenario based on the ‘avoid-reduce-compensate’ iterative optimisation approach. The reference scenario balances optimal physics performance with territorial compatibility, implementation risks, and costs. Environmental field investigations covering almost 600 hectares of terrain—including numerous urban, economic, social, and technical aspects—confirmed the project’s technical feasibility and contributed to the preparation of essential input documents for the formal project authorisation phase. The summary also highlights the initiation of public dialogue as part of the authorisation process. The results of a comprehensive socio-economic impact assessment, which included significant environmental effects, are presented. Even under the most conservative and stringent conditions, a positive benefit-cost ratio for the FCC-ee is obtained. Finally, the report provides a summary of the studies conducted to document the current state of the environment.

Protein function emerges from dynamic conformational changes, yet structure prediction methods provide only static snapshots. While AlphaFold3 (AF3) predicts protein structures, the potential for extracting dynamic information from its ensemble predictions has remained underexplored. Here, we demonstrate that AF3 structural ensembles contain substantial dynamic information that correlates remarkably well with molecular dynamics simulations (MD). We developed ChronoSort, a novel algorithm that organizes static structure predictions into temporally coherent trajectories by minimizing structural differences between neighboring frames. Through systematic analysis of four diverse protein targets, we show that root-mean-square fluctuations derived from AF3 ensembles can correlate strongly with those from MD (r = 0.53 to 0.84). Principal component analysis reveals that AF3 predictions capture the same collective motion patterns observed in molecular dynamics trajectories, with eigenvector similarities significantly exceeding random distributions. ChronoSort trajectories exhibit structural evolution profiles comparable to MD. These findings suggest that modern AI-based structure prediction tools encode conformational flexibility information that can be systematically extracted without expensive MD. We provide ChronoSort as open-source software to enable broad community adoption. This work offers a novel approach to extracting functional insights from structure prediction tools in minutes, with significant implications for synthetic biology, protein engineering, drug discovery, and structure–function studies.

We present ExoMiner++, an enhanced deep learning model that builds on the success of ExoMiner to improve transit signal classification in 2-minute TESS data. ExoMiner++ incorporates additional diagnostic inputs, including periodogram, flux trend, difference image, unfolded flux, and spacecraft attitude control data, all of which are crucial for effectively distinguishing transit signals from more challenging sources of false positives (FPs). To further enhance performance, we leverage multisource training by combining high-quality labeled data from the Kepler space telescope with TESS data. This approach mitigates the impact of TESS’s noisier and more ambiguous labels. ExoMiner++ achieves high accuracy across various classification and ranking metrics, significantly narrowing the search space for follow-up investigations to confirm new planets. To serve the exoplanet community, we introduce a new TESS catalog containing ExoMiner++ classifications and confidence scores for each transit signal. Among the 147,568 unlabeled TCEs, ExoMiner++ identifies 7330 as planet candidates (PCs), with the remainder classified as FPs. These 7330 PCs correspond to 1868 existing TESS Objects of Interest (TOIs), 69 Community TESS Objects of Interest (CTOIs), and 50 newly introduced CTOIs. 1797 out of the 2506 TOIs previously labeled as PCs in ExoFOP are classified as PCs by ExoMiner++. This reduction in plausible candidates, combined with the excellent ranking quality of ExoMiner++, allows the follow-up efforts to be focused on the most likely candidates, increasing the overall planet yield.

With the rapid growth and development of potential commercial fusion power plants, the urgency of building a skilled workforce is increasing. Therefore, it is necessary to train and educate early-career scientists and engineers to be able to work for current and future employment in fusion-related fields. In the Inertial Fusion Science and Technology (RISE) Hub, efforts are underway to address this urgency. Specifically in the RISE Hub, we train the next generation of “fusioneers” by involving them in every level of Hub activities. Here, we describe several training, outreach, and educational activities that are led by early-career scientists and engineers, graduate students, and postdoctoral researchers, under the supervision of Hub professionals. These activities educate and train students on key aspects of fusion systems, from the laser driver technologies to the target design, manufacturing, simulation, and validation. In addition, several of these initiatives are being supported by industry partners, national laboratories, and universities, facilitating the transition of knowledge between fusion experts and students. The goals of these outreach efforts led by the RISE Hub are not only to train and educate a skilled workforce but to grow young leaders and broaden their participation in developing commercial fusion power plants.