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The NOMAD (“Nadir and Occultation for MArs Discovery”) spectrometer suite on board the ExoMars Trace Gas Orbiter (TGO) has been designed to investigate the composition of Mars’ atmosphere, with a particular focus on trace gases, clouds and dust. The detection sensitivity for trace gases is considerably improved compared to previous Mars missions, compliant with the science objectives of the TGO mission. This will allow for a major leap in our knowledge and understanding of the Martian atmospheric composition and the related physical and chemical processes. The instrument is a combination of three spectrometers, covering a spectral range from the UV to the mid-IR, and can perform solar occultation, nadir and limb observations. In this paper, we present the science objectives of the instrument and explain the technical principles of the three spectrometers. We also discuss the expected performance of the instrument in terms of spatial and temporal coverage and detection sensitivity.

The MMX infrared spectrometer (MIRS) is an imaging spectrometer onboard MMX JAXA mission. MMX (Martian Moon eXploration) is scheduled to be launched in 2024 with sample return to Earth in 2029. MIRS is built at LESIA-Paris Observatory in collaboration with four other French laboratories, collaboration and financial support of CNES and close collaboration with JAXA and MELCO. The instrument is designed to fully accomplish MMX’s scientific and measurement objectives. MIRS will remotely provide near-infrared spectral maps of Phobos and Deimos containing compositional diagnostic spectral features that will be used to analyze the surface composition and to support the sampling site selection. MIRS will also study Mars atmosphere, in particular spatial and temporal changes such as clouds, dust and water vapor.

Very high-quality sapphire substrates are key elements of the cryogenic Japanese gravitational interferometer KAGRA, in which they are used to build the main mirrors, working as the test masses to sense the gravitational waves. To meet the extreme requirements of this system, the sapphire test masses must possess an extremely low optical absorption, which makes their study challenging using standard methods. In this paper, we illustrate the results obtained on two typical samples using a specialized absorption setup based on the technique of Photo-thermal Common-path Interferometry (PCI). Our system combines a very high sensitivity to small absorption features with the possibility to perform a full three-dimensional mapping of the sample volume. Our results elucidate how the ultra-low absorption variations inside the sample possess a structure that is probably inherited from the growth history of the sample. Some conclusions on the role of structural defects as preferential sites for the inclusion of absorbing centers are drawn.

Complex matters ‘Scale-free’ networks, such as linked web pages, people in social groups, or cellular interaction networks show uneven connectivity distributions: there is no typical number of links per node. Many of these networks also exhibit the ‘small-world’ effect, called ‘six degrees of separation’ when applied to sociology. A new analysis of such networks, in which nodes are partitioned into boxes of different sizes, reveals that they share the surprising feature of self-similarity. In other words, these networks are constructed of fractal-like self-repeating patterns or degrees of separation. This may help explain how the scale-free property of such networks arises. Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks 1 , 2 , 3 , 4 , 5 . A large number of real networks are referred to as ‘scale-free’ because they show a power-law distribution of the number of links per node 1 , 6 , 7 . However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the ‘small-world’ property of these networks, which implies that the number of nodes increases exponentially with the ‘diameter’ of the network 8 , 9 , 10 , 11 , rather than the power-law relation expected for a self-similar structure. Here we analyse a variety of real complex networks and find that, on the contrary, they consist of self-repeating patterns on all length scales. This result is achieved by the application of a renormalization procedure that coarse-grains the system into boxes containing nodes within a given ‘size’. We identify a power-law relation between the number of boxes needed to cover the network and the size of the box, defining a finite self-similar exponent. These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics.

This book opens with a self-contained introduction to path integrals in Euclidean quantum mechanics and statistical mechanics, and moves on to cover lattice field theory, spin systems, gauge theories and more. Each chapter ends with illustrative problems.

The Philae lander of the Rosetta space mission made a non‐nominal landing on comet 67P/Churyumov‐Gerasimenko on November 12, 2014. Shortly after, using the limited power available from Philae's batteries, the COSAC instrument performed a single 18‐minutes gas chromatogram, which has remained unpublished until now due to the lack of identifiable elution. This work shows that, despite the unsuccessful drilling of the comet and deposition of surface material in the SD2 ovens, the measurements from the COSAC instrument were executed nominally. We describe an automated search for extremely small deviations from noise and discuss the possibility of a signal from ethylene glycol at m/z 31. Arguments for and against this detection are listed, but the results remain inconclusive. Still, the successful operations of an analytical chemistry laboratory on a cometary nucleus gives great hope for the future of space exploration. ESA's comet rendezvous mission Rosetta investigated the nucleus of comet 67P/Churyumov‐Gerasimenko to reveal information about the most pristine material preserved in the Solar System. This work reports, for the first time, the only gas chromatogram taken on the comet by the COSAC instrument and puts forward the possibility of a trace detection of ethylene glycol in the data from this historic measurement. Image credit: ESA/AOES Medialab

Scientists have grappled with reconciling biological evolution 1 , 2 with the immutable laws of the Universe defined by physics. These laws underpin life’s origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Evolutionary theory explains why some things exist and others do not through the lens of selection. To comprehend how diverse, open-ended forms can emerge from physics without an inherent design blueprint, a new approach to understanding and quantifying selection is necessary 3 – 5 . We present assembly theory (AT) as a framework that does not alter the laws of physics, but redefines the concept of an ‘object’ on which these laws act. AT conceptualizes objects not as point particles, but as entities defined by their possible formation histories. This allows objects to show evidence of selection, within well-defined boundaries of individuals or selected units. We introduce a measure called assembly ( A ), capturing the degree of causation required to produce a given ensemble of objects. This approach enables us to incorporate novelty generation and selection into the physics of complex objects. It explains how these objects can be characterized through a forward dynamical process considering their assembly. By reimagining the concept of matter within assembly spaces, AT provides a powerful interface between physics and biology. It discloses a new aspect of physics emerging at the chemical scale, whereby history and causal contingency influence what exists. Assembly theory conceptualizes objects as entities defined by their possible formation histories, allowing a unified language for describing selection, evolution and the generation of novelty.

Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.

Massive stars play a major role not only in stellar evolution but also galactic evolution theory. This is because of their dynamical interaction with binary companions, but also because their strong winds and explosive deaths as supernovae provide chemical, radiative and kinematic feedback to their environments. Yet this feedback strongly depends on the physics of the supernova progenitor star. It is only in recent decades that asteroseismology – the study of stellar pulsations – has developed the necessary tools to a high level of sophistication to become a prime method at the forefront of astronomical research for constraining the physical processes at work within stellar interiors. For example, precise and accurate asteroseismic constraints on interior rotation, magnetic field strength and geometry, mixing and angular momentum transport processes of massive stars are becoming increasingly available across a wide range of masses. Moreover, ongoing large-scale time-series photometric surveys with space telescopes have revealed a large diversity in the variability of massive stars, including widespread coherent pulsations across a large range in mass and age, and the discovery of ubiquitous stochastic low-frequency (SLF) variability in their light curves. In this invited review, I discuss the progress made in understanding the physical processes at work within massive star interiors thanks to modern asteroseismic techniques, and conclude with a future outlook.

The past decades have seen density functional theory (DFT) evolve from a rising star in computational quantum chemistry to one of its major players. This Theme Issue, which comes half a century after the publication of the Hohenberg-Kohn theorems that laid the foundations of modern DFT, reviews progress and challenges in present-day DFT research. Rather than trying to be comprehensive, this Theme Issue attempts to give a flavour of selected aspects of DFT.