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We investigate how well the Large Interferometer for Exoplanets (LIFE) mission concept can detect habitable conditions on exoplanets through the presence of atmospheric water vapor as a proxy for surface oceans. We model the atmosphere of a pre-biotic Earth-like planet across a range of water concentrations, from water-poor to water-rich, with surface partial pressures from 10$^{-7}$ to 1 bar of H$_2$O. We simulate LIFE-like noise at spectral resolutions R = 50 and 100 using LIFEsim and perform Bayesian atmospheric retrievals to determine the technical requirements for LIFE to confirm habitability. We model three vertical water distributions: a vertically constant profile, a Manabe-Wetherald based Earth-like profile, and a diffusion and photochemistry profile to test how the assumed vertical structure influences the retrieved abundances. Clouds are not modeled. We find the ability for LIFE to detect water strongly depends on the vertical profile assumed. LIFE is unable to constrain the highest water cases and provides upper limits on low water planets. For the highest water abundances, absorption features saturate and reduce sensitivity to characterize precise H$_2$O levels. Water

The oxidation state of rocky exoplanets is expected to play a fundamental role in shaping the chemical composition of their secondary atmospheres by influencing the chemical composition of volcanically released gasses. Distinguishing planetary redox states through direct atmospheric characterization would offer insight into the formation and evolution of secondary atmospheres on exoplanets and inform the background chemistry of putative biosignatures. The Large Interferometer For Exoplanets (LIFE) mission concept aims to employ a space-based mid-infrared nulling interferometer to characterize exoplanetary atmospheres. In this work, we assess LIFE's performance in distinguishing the redox states of rocky exoplanets by direct spectroscopic measurements. We focus on the observability and spectral features of redox-sensitive molecules in secondary atmospheres of Earth-sized exoplanets. We develop and apply a retrieval framework based on the ARtful modeling Code for exoplanet Science (ARCiS) and the LIFE mission simulator (LIFEsim) to simulate observations of Earth-sized planets with atmospheres from a range of plausible mantle redox conditions. Our simulations show that LIFE in its bas

Detection claims surrounding life beyond Earth often attract intense attention because the question of whether we are alone in the cosmos carries unusually high scientific, social, philosophical, and theological stakes. This chapter compares two high uncertainty life-detection claims, the 2020 phosphine detection claim on Venus and the 1976 Viking life-detection experiments on Mars, to examine how evidence, interpretation, and public narratives interact when results are ambiguous. We trace how each case unfolded through critique, reanalysis, and shifting assessments, and how institutional choices shaped subsequent research pathways, from long term monitoring and renewed Venus exploration to a Mars strategy centred on habitability rather than direct life-detection. Drawing lessons across both cases, we propose best practices for scientists, institutions, the wider scientific community, and science communicators, with emphasis on open science, constructive follow-up, cognitive bias awareness, and careful framing so that initial detections are not framed as final conclusions. We argue that managing future life-detections is less about eliminating uncertainty than about building transp

Conway's Game of Life shows that simple rules can generate a rich diversity of emerging structures. This cellular automaton has been translated to continuous space by Rafler (2011) in a simulation called SmoothLife. The isotropic rule of this continuous Game of Life generates patterns whose beauty has attracted the attention of a growing community at the intersection of science and computer art. We study a minimal variant of this model, continuous in space and time, that generates cell-like patterns capable of self-replicating, gliding and disappearing. The phenomenology of these unit patterns is reported and related to homogeneous-state bifurcations, symmetry breaking, observed shape instabilities, finite-amplitude morphological changes, and a dilute-to-dense transition associated with cell proliferation. Its mapping onto a large reaction--diffusion system is interpreted in terms of homeostatic concentrations of morphogens, regulated by the nonlinear survival rule and generated through a cell-sourced cascade of auxiliary reactions. Introducing a global conservation law that limits resource availability causes the system to self-organize at this dilute-to-dense transition, which we

Previous work has found a gap between the scale of neural networks that reliably learn Conway's Game of Life, and minimal networks capable of representing the classic cellular automaton with hard-coded parameter values. Viewing neural network learning as a search process suggests a dependence on networks large enough to contain sub-networks with lucky initializations (sometimes known as 'winning tickets') that actually learn the task. In this work, we reorient our perspective from discovering Life rules as a search problem back to a learning problem, and reason that with fitting inductive biases, the problem should be much more amenable to minimal networks. We find that network variants with several alternative activation functions meaningfully outperform the default choice of Rectified Linear Units, and in particular, that a 2nd degree polynomial activation function consistently learns Life dynamics with or without the benefit of learning neural weights. Our results provide an informative demonstration of the benefits of matching learning to the task at hand and challenge the easy default choice of scale for all problems. In particular, we advocate for the use of cellular automata

This chapter provides an overview of the different science cases covered by the "Cradle of Life" working group, which aims to leverage the capabilities of the Square Kilometre Array Observatory (SKAO) to trace the physical and chemical pathways toward stars and planets formation, how such stars impact their planets, and whether life could exist in such conditions. At its highest frequencies, the SKAO will probe the earliest stages of the raw material fuelling planet formation, while enabling deep, unprecedented searches for prebiotic molecules both in high-mass and solar-type protostars. Concurrently, the lowest frequencies will be deployed to detect and characterize exoplanetary magnetic fields via their auroral radio emission, and the type of space weather a planet experiences from its host star. Across the entire frequency range, the SKA telescopes will conduct systematic searches of technosignatures. Together, these high-impact research areas establish a comprehensive roadmap for the SKAO to uncover the origins of life in the universe.

The Mars Life Explorer (MLE) mission concept offers a critical opportunity to investigate whether extant life exists within the mid-latitude ice deposits of Mars. However, MLE's current science traceability matrix emphasizes habitability assessment and organic chemistry over direct life detection. As crewed missions to Mars may occur as early as 2040, the window for uncontaminated robotic exploration is rapidly closing. A high-confidence determination of Martian life must be achieved before irreversible anthropogenic contamination compromises scientific integrity. This paper evaluates the scientific, technical, and policy limitations of the current MLE architecture and recommends specific instrumentation upgrades and governance measures necessary to enable definitive and agnostic life detection while safeguarding planetary protection.

When is a material system a candidate for life at all? We argue that this question is prior to behavior, functional architecture, or computational capacity, and that at root it is one of physical admissibility. We develop a framework in which minimal autonomy, taken in the interactivist sense of normativity grounded in self-maintaining far-from-equilibrium organization, corresponds to a distinct non-equilibrium phase of matter, and we take complex plasmas, a physical and non-biological system, as its in-materio exemplar. We formalize a diagnostic phase-space whose criteria (sustained free-energy throughput, organizational closure, active information maintenance, and regulated noise sensitivity) constitute necessary conditions for life-attribution. We instantiate the diagnostics across contrasting systems and fix the boundaries of the phase space via Bénard convection as a driven baseline lacking closure, and a digital self-replicating soup that carries measured informational heredity while its physical closure remains a structural zero. We demonstrate that plasmas satisfy every admissibility condition for minimal physical autonomy while carrying none of the informational heredity t

Following the recommendations to NASA and ESA, the search for life on exoplanets will be a priority in the next decades. Two direct imaging space mission concepts are being developed: the Habitable Worlds Observatory (HWO) and the Large Interferometer for Exoplanets (LIFE). HWO focuses on reflected light spectra in the ultraviolet/visible/near-infrared (UV/VIS/NIR), while LIFE captures the mid-infrared (MIR) emission of temperate exoplanets. We assess the potential of HWO and LIFE in characterizing a cloud-free Earth twin orbiting a Sun-like star at 10 pc, both separately and synergistically, aiming to quantify the increase in information from joint atmospheric retrievals on a habitable planet. We perform Bayesian retrievals on simulated data from an HWO-like and a LIFE-like mission separately, then jointly, considering the baseline spectral resolutions currently assumed for these concepts and using two increasingly complex noise simulations. HWO would constrain H$_2$O, O$_2$, and O$_3$, in the atmosphere, with ~ 100 K uncertainty on the temperature profile. LIFE would constrain CO$_2$, H$_2$O, O$_3$ and provide constraints on the thermal atmospheric structure and surface temperatu

The search for what differentiates inanimate matter from living things began in antiquity as a search for a "fundamental life force" embedded deep within living things - a special material unit owned only by life - later transforming to more circumspect search for unique gains in function that transform nonliving matter to that which can reproduce, adapt, and survive. Aristotelian thinking about the matter/life distinction and Vitalistic philosophy's "vital force" persisted well into the Scientific Revolution, only to be debunked by Pasteur and Brown in the 19th century. Acceptance of the atomic reality and understanding of the uniqueness of life's heredity, evolution, and reproduction led to formation of the Central Dogma. With startling speed, technological development then gave rise to structural biology, systems biology, and synthetic biology - and a search to replicate and synthesize that "gain in function" that transforms matter to life. Yet one still cannot build a living cell de novo from its atomic and molecular constituents, and "that which I cannot create, I do not understand". In the last two decades, new recognition of old ideas - spatial organization and compartmental

We present the database of potential targets for the Large Interferometer For Exoplanets (LIFE), a space-based mid-infrared nulling interferometer mission proposed for the Voyage 2050 science program of the European Space Agency (ESA). The database features stars, their planets and disks, main astrophysical parameters, and ancillary observations. It allows users to create target lists based on various criteria to predict, for instance, exoplanet detection yields for the LIFE mission. As such, it enables mission design trade-offs, provides context for the analysis of data obtained by LIFE, and flags critical missing data. Work on the database is in progress, but given its relevance to LIFE and other space missions, including the Habitable Worlds Observatory (HWO), we present its main features here. A preliminary version of the LIFE database is publicly available on the German Astrophysical Virtual Observatory (GAVO).

According to panspermia, life on Earth may have originated from life forms transported through space from elsewhere. These life forms could have passed through molecular clouds, where the process of methanogenesis could have provided enough energy to sustain living organisms. In this study, we have calculated the Gibbs free energy released from synthesizing hydrocarbons for methanogenic (acetogenic) life in a molecular cloud, with methane (acetic acid) as the final metabolic product. Our calculations demonstrate that the chemical reactions during methanogenesis can release enough free energy to support living organisms. The methanogenic life may have served as the predecessor of life on Earth, and there is some preliminary evidence from various molecular biology studies to support this idea. Furthermore, we propose a potential distinguishing signal to test our model.

The Large Interferometer For Exoplanets (LIFE) initiative aims to develop a space based mid-infrared (MIR) nulling interferometer to measure the thermal emission spectra of temperate terrestrial exoplanets. We investigate how well LIFE could characterize a cloudy Venus-twin exoplanet to: (1) test our retrieval routine on a realistic non-Earth-like MIR spectrum of a known planet, (2) investigate how clouds impact retrievals, (3) refine the LIFE requirements derived in previous Earth-centered studies. We run retrievals for simulated LIFE observations of a Venus-twin exoplanet orbiting a Sun-like star located 10 pc from the observer. By assuming different models (cloudy and cloud-free) we analyze the performance as a function of the quality of the LIFE observation. This allows us to determine how well atmosphere and clouds are characterizable depending on the quality of the spectrum. Our study shows that the current minimal resolution ($R=50$) and signal-to-noise ($S/N=10$ at $11.2μ$m) requirements for LIFE suffice to characterize the structure and composition of a Venus-like atmosphere above the cloud deck if an adequate model is chosen. However, we cannot infer cloud properties. The

The increased brightness temperature of young rocky protoplanets during their magma ocean epoch makes them potentially amenable to atmospheric characterization to distances from the solar system far greater than thermally equilibrated terrestrial exoplanets, offering observational opportunities for unique insights into the origin of secondary atmospheres and the near surface conditions of prebiotic environments. The Large Interferometer For Exoplanets (LIFE) mission will employ a space-based mid-infrared nulling interferometer to directly measure the thermal emission of terrestrial exoplanets. Here, we seek to assess the capabilities of various instrumental design choices of the LIFE mission concept for the detection of cooling protoplanets with transient high-temperature magma ocean atmospheres, in young stellar associations in particular. Using the LIFE mission instrument simulator (LIFEsim) we assess how specific instrumental parameters and design choices, such as wavelength coverage, aperture diameter, and photon throughput, facilitate or disadvantage the detection of protoplanets. We focus on the observational sensitivities of distance to the observed planetary system, protopl

Life is a planetary feature that depends on its environment, but it has also strongly shaped the physical conditions on Earth, having created conditions highly suitable for a productive biosphere. Clearly, the second law of thermodynamics must apply to these dynamics as well, but how? What insights can we gain by placing life and its effects on planetary functioning in the context of the second law? In Kleidon (2010), I described a thermodynamic Earth system perspective by placing the functioning of the Earth system in terms of the second law. The Earth system is represented by a planetary hierarchy of energy transformations that are driven predominantly by incoming solar radiation, these transformations are constrained by the second law, but they are also modified by the feedbacks from various dissipative activities. It was then hypothesised that life evolves its dissipative activity to the limits imposed by this hierarchy and evolves feedbacks aimed at pushing these limits to higher levels of dissipative activity. Here I provide an update of this perspective. I first review applications to climate and global climate change to demonstrate its success in predicting magnitudes of ph

Even when concepts similar to emergence have been used since antiquity, we lack an agreed definition. However, emergence has been identified as one of the main features of complex systems. Most would agree on the statement ``life is complex''. Thus, understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules. But how useful is this to understand living systems? Artificial life (ALife) has been developed in recent decades to study life using a synthetic approach: build it to understand it. ALife systems are not so complex, be them soft (simulations), hard (robots), or wet (protocells). Then, we can aim at first understanding emergence in ALife, for then using this knowledge in biology. I argue that to understand emergence and life, it becomes useful to use information as a framework. In a general sense, I define emergence as information that is not present at one scale but is present at another scale. This perspective avoids problems of studying emergence from a materialist framework, and can be also useful in the study of self-organization and complexity.

Deep AndersoNN accelerates AI by exploiting the continuum limit as the number of explicit layers in a neural network approaches infinity and can be taken as a single implicit layer, known as a deep equilibrium model. Solving for deep equilibrium model parameters reduces to a nonlinear fixed point iteration problem, enabling the use of vector-to-vector iterative solvers and windowing techniques, such as Anderson extrapolation, for accelerating convergence to the fixed point deep equilibrium. Here we show that Deep AndersoNN achieves up to an order of magnitude of speed-up in training and inference. The method is demonstrated on density functional theory results for industrial applications by constructing artificial life and materials `scientists' capable of classifying drugs as strongly or weakly polar, metal-organic frameworks by pore size, and crystalline materials as metals, semiconductors, and insulators, using graph images of node-neighbor representations transformed from atom-bond networks. Results exhibit accuracy up to 98\% and showcase synergy between Deep AndersoNN and machine learning capabilities of modern computing architectures, such as GPUs, for accelerated computatio

Recently we introduced a model of symbiosis, Model-S, based on the evolution of seed patterns in Conway's Game of Life. In the model, the fitness of a seed pattern is measured by one-on-one competitions in the Immigration Game, a two-player variation of the Game of Life. Our previous article showed that Model-S can serve as a highly abstract, simplified model of biological life: (1) The initial seed pattern is analogous to a genome. (2) The changes as the game runs are analogous to the development of the phenome. (3) Tournament selection in Model-S is analogous to natural selection in biology. (4) The Immigration Game in Model-S is analogous to competition in biology. (5) The first three layers in Model-S are analogous to biological reproduction. (6) The fusion of seed patterns in Model-S is analogous to symbiosis. The current article takes this analogy two steps further: (7) Autopoietic structures in the Game of Life (still lifes, oscillators, and spaceships -- collectively known as ashes) are analogous to cells in biology. (8) The seed patterns in the Game of Life give rise to multiple, diverse, cooperating autopoietic structures, analogous to multicellular biological life. We us

The next generation of space-based observatories will characterize the atmospheres of low-mass, temperate exoplanets with the direct-imaging technique. This will be a major step forward in our understanding of exoplanet diversity and the prevalence of potentially habitable conditions beyond the Earth. We compute a list of currently known exoplanets detectable with the mid-infrared Large Interferometer For Exoplanets (LIFE) in thermal emission. We also compute the list of known exoplanets accessible to a notional design of the Habitable Worlds Observatory (HWO), observing in reflected starlight. With a pre-existing method, we processed the NASA Exoplanet Archive and computed orbital realizations for each known exoplanet. We derived their mass, radius, equilibrium temperature, and planet-star angular separation. We used the LIFEsim simulator to compute the integration time ($t_{int}$) required to detect each planet with LIFE. A planet is considered detectable if a broadband signal-to-noise ratio $S/N$=7 is achieved over the spectral range $4-18.5μ$m in $t_{int}\leq$100 hours. We tested whether the planet is accessible to HWO in reflected starlight based on its notional inner and oute