Atmospheres of rocky exoplanets

The increasing number of known rocky exoplanets motivates investigations of the diversity of atmospheric and surface composition of these planets. We investigate the link between the composition of the surface, near-crust atmosphere and the lower atmosphere, including the presence of different cloud condensates. This allows working towards inferring the surface composition from clouds and gas species present in the atmosphere. Understanding the diversity of the atmospheric composition provides a further step towards the characterisation of rocky exoplanets. In this thesis, a fast and simple atmospheric model for the lower atmospheres of rocky exoplanets is presented. A range of different sets of total element abundances is used to investigate the surface composition in contact with the near-crust atmosphere in chemical and phase equilibrium. The atmosphere based on this crust-atmosphere interaction layer is build from bottom-to-top. At every point in the atmosphere, chemical equilibrium is solved and all thermally stable condensates are removed, depleting the atmospheric layers above in the affected elements. In order to characterise the general atmospheric composition, atmospheric types based on the chemical state of carbon, hydrogen, oxygen, and nitrogen are introduced. In order to further constrain the potential of an atmospheric environment for habitability, different habitability levels are introduced. These take the stability of liquid water as well as the chemical states of carbon, nitrogen, and sulphur into account. The investigation of the atmosphere-crust interaction layer shows, that the thermal stability of liquid water is only given, if all phyllosilicates (minerals which incorporate OH groups into their lattice structure) have completely formed. The composition of the resulting atmosphere can be categorised into three different atmospheric types. Of special interest is the possibility of the coexistence of CO₂ and CH₄ in chemical equilibrium. The atmospheric type is intrinsic to an atmosphere, as it does not change with the removal of thermally stable condensates in one given atmospheric model. The atmospheric models reveal a large diversity in thermally stable cloud condensates, which constrain the surface conditions of rocky exoplanets. The presence of water clouds is an integral part of many planetary atmospheres and is independent of the stability of water condensates at the surface. At the water cloud base, we show that reduced gaseous forms of carbon, nitrogen, and sulphur are present, while phosphorus is absent

The atmospheres of rocky exoplanets : I. Outgassing of common rock and the stability of liquid water

Funding: O.H. acknowledges the PhD stipend from the University of St Andrews’ Centre for Exoplanet Science.Context. Little is known about the interaction between atmospheres and crusts of exoplanets so far, but future space missions and ground-based instruments are expected to detect molecular features in the spectra of hot rocky exoplanets. Aims. We aim to understand the composition of the gas in an exoplanet atmosphere which is in equilibrium with a planetary crust. Methods. The molecular composition of the gas above a surface made of a mixture of solid and liquid materials was determined by assuming phase equilibrium for given pressure, temperature, and element abundances. We study total element abundances that represent different parts of the Earth’s crust (continental crust, bulk silicate Earth, mid oceanic ridge basalt), CI chondrites and abundances measured in polluted white dwarfs. Results. For temperatures between ~600 and ~3500 K, the near-crust atmospheres of all considered total element abundances are mainly composed of H2O, CO2, and SO2 and in some cases of O2 and H2. For temperatures ≲500 K, only N2-rich or CH4-rich atmospheres remain. For ≳3500 K, the atmospheric gas is mainly composed of atoms (O, Na, Mg, and Fe), metal oxides (SiO, NaO, MgO, CaO, AlO, and FeO), and some metal hydroxides (KOH and NaOH). The inclusion of phyllosilicates as potential condensed species is crucial for lower temperatures, as they can remove water from the gas phase below about 700 K and inhibit the presence of liquid water. Conclusions. Measurements of the atmospheric composition could, in principle, characterise the rock composition of exoplanet crusts. H2O, O2 and CH4 are natural products from the outgassing of different kinds of rocks that had time to equilibrate. These are discussed as biomarkers, but they do emerge naturally as a result of the thermodynamic interaction between the crust and atmosphere. Only the simultaneous detection of all three molecules might be a sufficient biosignature, as it is inconsistent with chemical equilibrium.Publisher PDFPeer reviewe

Influence of Motor Planning on Distance Perception within the Peripersonal Space

We examined whether movement costs as defined by movement magnitude have an impact on distance perception in near space. In Experiment 1, participants were given a numerical cue regarding the amplitude of a hand movement to be carried out. Before the movement execution, the length of a visual distance had to be judged. These visual distances were judged to be larger, the larger the amplitude of the concurrently prepared hand movement was. In Experiment 2, in which numerical cues were merely memorized without concurrent movement planning, this general increase of distance with cue size was not observed. The results of these experiments indicate that visual perception of near space is specifically affected by the costs of planned hand movements

Too good to be true? Ideomotor theory from a computational perspective

In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity.The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: (1) The range of potential actions and effects has to be restricted. (2) Effects have to follow actions within a short time window. (3) Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that IdeomotorTheory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations

Redundante Repräsentationen als Grundlage aufgabenbezogener optimaler Steuerung:Ein neuronales Netzwerk Modell menschlicher Zeigebewegungen

The human motor system is adaptive in two senses. It adapts to the properties of the body to enable effective control. It also adapts to different situational requirements and constraints. This thesis proposes a new neural network model of both kinds of adaptivity for the motor cortical control of human reaching movements, called SURE_REACH (sensorimotor unsupervised learning redundancy resolving control architecture). In this neural network approach, the kinematic and sensorimotor redundancy of a three-joint planar arm is encoded in task-independent internal models by an unsupervised learning scheme. Before a movement is executed, the neural networks prepare a movement plan from the task-independent internal models, which flexibly incorporates external, task-specific constraints. The movement plan is then implemented by proprioceptive or visual closed-loop control. This structure enables SURE_REACH to reach hand targets while incorporating task-specific contraints, for example adhering to kinematic constraints, anticipating the demands of subsequent movements, avoiding obstacles, or reducing the motion of impaired joints. Besides this functionality, the model accounts for temporal aspects of human reaching movements or for data from priming experiments. Additionally, the neural network structure reflects properties of motor cortical networks like interdependent population encoded body space representations, recurrent connectivity, or associative learning schemes. This thesis introduces and describes the new model, relates it to current computational models, evaluates its functionality, relates it to human behavior and neurophysiology, and finally discusses potential extensions as well as the validity of the model. In conclusion, the proposed model grounds highly flexible task-dependent behavior in a neural network framework and unsupervised sensorimotor learning.Das motorische System des Menschen ist in zweierlei Hinsicht anpassungsfähig. Es passt sich den Eigenschaften des Körpers an, um diesen effektiv zu kontrollieren. Es passt sich aber auch unterschiedlichen situationsabhängigen Erfordernissen und Beschränkungen an. Diese Dissertation stellt ein neues neuronales Netzwerk Modell der motor-kortikalen Steuerung von menschlichen Zeigebewegungen vor, das beide Arten von Anpassungsfähigkeit integriert (SURE_REACH, Sensumotorische, unüberwacht lernende, redundanzauflösende Kontrollarchitektur). Das neuronale Netzwerk speichert kinematische und sensumotorische Redundanz eines planaren, dreigelenkigen Armes in aufgabenunabhängigen internen Modellen mittels unüberwachter Lernverfahrenen. Vor der Ausführung einer Bewegung bereitet das neuronale Netzwerk einen Bewegungsplan vor. Dieser basiert auf den aufgabenunabhängigen internen Modells und passt sich flexibel äu"seren, aufgabenabhängigen Erfordernissen an. Der Bewegungsplan wird dann durch propriozeptive oder visuelle Regelung umgesetzt. Auf diese Weise erklärt SURE_REACH Bewegungen zu Handzielen die aufgabenabhängige Erfordernisse berücksichtigen, zum Beispiel werden kinematische Beschränkungen miteinbezogen, Erfordernisse nachfolgender Aufgaben antizipiert, Hindernisse vermieden oder Bewegungen verletzter Gelenke reduziert. Desweiteren werden zeitliche Eigenschaften menschlicher Bewegungen oder die Ergebnisse von Primingexperimenten erklärt. Die neuronalen Netzwerke bilden zudem Eigenschaften motor-kortikaler Netzwerke ab, zum Beispiel wechselseitig abhängige Raumrepräsentationen, rekurrente Verbindungen oder assoziative Lernverfahren. Diese Dissertation beschreibt das neue Modell, vergleicht es mit anderen Modellen, untersucht seine Funktionalität, stellt Verbindungen zu menschlichem Verhalten und menschlicher Neurophysiologie her und erörtert schlie"slich mögliche Erweiterungen und die Validität des Models. Zusammenfassend stellt das vorgeschlagene Model eine Erklärung für flexibles aufgabenbezogenes Verhalten auf ein Fundament aus neuronalen Netzwerken und unüberwachten sensumotorischen Lernen

Where to Grasp a Tool? Task-Dependent Adjustments of Tool Transformations by Tool Users

Biomechanical and environmental constraints limit body movements and tool use actions. However, in the case of tool use, such constraints can often be overcome by adjusting a tool’s tool transformation to the requirements of the intended tool use action. The research presented here examined whether participants grasped a lever at different positions, thus modifying the lever’s tool transformation, to accommodate speed and accuracy requirements of different tasks. Participants were asked to quickly track a sequence of targets with the lever. If accuracy requirements were high, participants compensated for limits in the accuracy of hand movements by grasping the lever at a position that enabled precise control of the lever. If accuracy requirements were low, participants compensated for limits in hand speed by grasping the lever at a position that enabled fast lever movements with comparatively slow hand movements. This task-dependent grasp selection was only present after participants had practiced the tasks. The data show that in addition to adapting to fixed tool transformations, participants also actively controlled tool transformations to facilitate tool use actions. </jats:p

Modular neuron-based body estimation: maintaining consistency over different limbs, modalities, and frames of reference

This paper addresses the question of how the brain maintains a probabilistic body state estimate over time from a modeling perspective. The neural Modular Modality Frame (nMMF) model simulates such a body state estimation process by continuously integrating redundant, multimodal body state information sources. The body state estimate itself is distributed over separate, but bidirectionally interacting modules. nMMF compares the incoming sensory and present body state information across the interacting modules and fuses the information sources accordingly. At the same time, nMMF enforces body state estimation consistency across the modules. nMMF is able to detect conflicting sensory information and to consequently decrease the influence of implausible sensor sources on the fly. In contrast to the previously published Modular Modality Frame (MMF) model, nMMF offers a biologically plausible neural implementation based on distributed, probabilistic population codes. Besides its neural plausibility, the neural encoding has the advantage of enabling (a) additional probabilistic information flow across the separate body state estimation modules and (b) the representation of arbitrary probability distributions of a body state. The results show that the neural estimates can detect and decrease the impact of false sensory information, can propagate conflicting information across modules, and can improve overall estimation accuracy due to additional module interactions. Even bodily illusions, such as the rubber hand illusion, can be simulated with nMMF. We conclude with an outlook on the potential of modeling human data and of invoking goal-directed behavioral control