The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.

Much recent discussion in the aesthetics of nature has focused on Scientific cognitivism, the view that in order to engage in a deep and appropriate aesthetic appreciation of nature, one must possess certain kinds of scientific knowledge. The most pressing difficulty faced by this view is an apparent tension between the very notion of aesthetic appreciation and the nature of scientific knowledge. In this essay, I describe this difficulty, trace some of its roots and argue that attempts to dismiss it fail. I then develop a response to the problem, drawing on the notion of the theory-ladenness of observation. I conclude by considering the relationship between this response and one common approach to the problem, the appeal to expressive qualities in nature.

We applaud Bullot & Reber's (B&R's) attempt to encompass the function of artworks within their psycho-historical model of art appreciation. However, we suggest that in order to fully realize this aim, they require a clearer distinction between an artist's intentions toward an artwork and its proper functions. We also show how such a distinction improves the internal coherence of their model.

One of the most serious theoretical obstacles to contemporary spacetime substantivalism is Earman and Norton's hole argument. We argue that applying the bundle theory of substance to spacetime points allows spacetime substantivalists to escape the conclusion of this argument. Some philosophers have claimed that the bundle theory cannot be applied to substantival spacetime in this way due to problems in individuating spacetime points in symmetrical spacetimes. We demonstrate that it is possible to overcome these difficulties if spatiotemporal properties are viewed as tropes rather than universals.