Aufbau, Optimierung und Charakterisierung der THz-Optik für GREAT auf SOFIA

Sternentstehung findet im dichten Teil der Molekülwolken des interstellaren Mediums statt. In diesen Gebieten werden die ablaufenden physikalischen und chemischen Prozesse maßgeblich von der Wechselwirkung zwischen der Materie und dem Strahlungsfeld eingebetteter junger Sterne bestimmt. Konsequenz der Bestrahlung mit FUV-Photonen (6eV10^6) ermöglicht. Dabei ist zu beachten, dass Frequenzen im Bereich von 1-10THz erdgebunden aufgrund der Absorption des atmosphärischen Wassersdampfs nicht beobachtbar sind. Daher müssen THz-Empfänger in großer Höhe nach Möglichkeit oberhalb der Troposphäre betrieben werden. GREAT wird am flugzeuggetragenen 2.5m-Teleskop des Stratospheric Observatory for Far Infrared Astronomy (SOFIA) in einer Höhe von ca. 13km operieren. Für die Planung und den Aufbau des Empfängers wurde ein Forschungskonsortium bestehend aus entsprechenden Arbeitsgruppen am MPIfR, dem MPIAe, dem DLR und KOSMA gegründet. Insgesamt befinden sich vier Frequenzkanäle im Bereich von 1.2-4.7THz im Aufbau, von denen in Abhängigkeit der wissenschaftlichen Fragestellung zwei ausgewählt, in das GREAT-Instrument eingesetzt und simultan betrieben werden können. Die hierfür erforderliche Modularität von GREAT stellt eine große Herausforderung für den Aufbau und die Justage des Empfängers dar. Zusätzlich waren die strengen Zertifizierungsregeln der amerikanischen Flugsicherheitsbehörde FAA zu erfüllen. Innerhalb des Konsortiums ist KOSMA für den Aufbau der 1.4 und 1.9THz-Kanäle, für die Entwicklung der kanalübergreifenden Optik und den Aufbau von Array acousto-optical Spektrometern zuständig. Wesentliche Teile der Aufgaben wurden im Rahmen von drei Dissertationen ausgeführt. Die Dissertation von P. Munoz umfasst die Entwicklung der supraleitenden Hot-Electron Bolometer (HEB) für 1.2-1.9THz. M. Philipp war für den Aufbau des 1.9THz-Lokaloszillator (LO) zuständig. Im Rahmen vorliegender Arbeit wurden sowohl die optomechanischen Komponenten der kanalübergreifenden Optik als auch die Optik der 1.4-1.9THz-Kanäle entwickelt. Ferner wurde die für die HEBs erforderliche kryogene Infrastruktur aufgebaut, und abschließend eine Charakterisierung des 1.9THz Kanals vorgenommen. Die wesentlichen technischen Entwicklungen und Ergebnisse aus vorliegender Arbeit sind nachfolgend kurz zusammengefasst. Kohärente Strahlungsquellen mit einer Ausgangsleistung von mehr Als 1000nW sind im Frequenzbereich von 1-10THz nur eingeschränkt verfügbar. Die Maximierung der nutzbaren 1.9THz-LO-Leistung machte die Entwicklung abbildender astigmatischer Spiegel für quasioptische Systeme erforderlich. Das Kryostatenfenster muss im Beobachtungsfrequenzband transparent sein. Materialien mit einem niedrigen Absorptionskoeffizienten im THz-Bereich (z.B. Silizium) besitzen im Allgemeinen hohe Dielektrizitätskonstanten und führen zu hohen Reflexionsverlusten. Im Rahmen dieser Arbeit gelang die Anwendung der Effective-Medium-Theorie, um entspiegelte ''Low loss THz-Windows'' herzustellen. Ein erstes Exemplar ist im Mikrostrukturlabor von KOSMA per Bosch-Prozess aus Silizium hergestellt worden. In Kooperation mit dem CSIRO, Australien, kam erstmalig eine neuartige smooth-walled spline-profile Hornantenne für 1.9THz zum Einsatz, deren Antennenkeule im Rahmen dieser Arbeit im Labor indirekt vermessen werden konnte. Die Bestimmung der spektralen Systemrauschtemperatur des 1.9THz-Kanals ergab über das Zwischenfrequenzband von 1.2-1.7GHz 2200-2500K. Die Allan-Minimumszeit als Maß der Systemstabilität beträgt 35s. Damit ist der 1.9THz-Kanal empfindlich und weist zugleich eine Stabilität auf, die ähnlich gut ist wie die von SIS-Empfängern. Logische Konsequenz der begrenzten Messzeit auf SOFIA ist die mittelfristige Steigerung der Effizienz des submm-Empfängers. Der Ausbau des 1.9THz-GREAT-Kanals zum 4-Pixel Array wurde im Rahmen der hier dokumentierten Arbeit vorbereitet. Mit der Fertigstellung des 1.9THz-Kanals steht der Wissenschaft der weltweit einzige, einsatzbereite Heterodynempfänger für 1.9THz zur Verfügung

GREAT: the SOFIA high-frequency heterodyne instrument

We describe the design and construction of GREAT, the German REceiver for Astronomy at Terahertz frequencies operated on the Stratospheric Observatory for Infrared Astronomy (SOFIA). GREAT is a modular dual-color heterodyne instrument for highresolution far-infrared (FIR) spectroscopy. Selected for SOFIA's Early Science demonstration, the instrument has successfully performed three Short and more than a dozen Basic Science flights since first light was recorded on its April 1, 2011 commissioning flight. We report on the in-flight performance and operation of the receiver that - in various flight configurations, with three different detector channels - observed in several science-defined frequency windows between 1.25 and 2.5 THz. The receiver optics was verified to be diffraction-limited as designed, with nominal efficiencies; receiver sensitivities are state-of-the-art, with excellent system stability. The modular design allows for the continuous integration of latest technologies; we briefly discuss additional channels under development and ongoing improvements for Cycle 1 observations. GREAT is a principal investigator instrument, developed by a consortium of four German research institutes, available to the SOFIA users on a collaborative basis

Neuroscientific insights into the development of analogical reasoning.

Analogical reasoning, or the ability to find correspondences between entities based on shared relationships, supports knowledge acquisition. As such, the development of this ability during childhood is thought to promote learning. Here, we sought to better understand the mechanisms by which analogical reasoning about semantic relations improves over childhood and adolescence (e.g. chalk is to chalkboard as pen is to…?). We hypothesized that age-related differences would manifest as differences in the brain regions associated with one or more of the following cognitive functions: (1) controlled semantic retrieval, or the ability to retrieve task-relevant semantic associations; (2) response control, or the ability to override the tendency to respond to a salient distractor; and/or (3) relational integration, or the ability to consider jointly two mental relations. In order to test these hypotheses, we analyzed patterns of fMRI activation during performance of a pictorial propositional analogy task across 95 typically developing children between the ages of 6 and 18 years old. Despite large age-related differences in task performance, particularly over ages 6-10 but through to around age 14, participants across the whole age range recruited a common network of frontal, parietal and temporal regions. However, activation in a brain region that has been implicated in controlled semantic retrieval - left anterior prefrontal cortex (BA 47/45) - was positively correlated with age, and also with performance after controlling for age. This finding indicates that improved performance over middle childhood and early adolescence on this analogical reasoning task is driven largely by improvements in the ability to selectively retrieve task-relevant semantic relationships.National Institute on Neurological Disorders and Stroke, Grant/Award Number: R01 NS057146; James S. McDonnell Foundation Scholar Awar

Case-Based Translation: First Steps from a Knowledge-Light Approach Based on Analogy to a Knowledge-Intensive One

International audienceThis paper deals with case-based machine translation. It is based on a previous work using a proportional analogy on strings, i.e., a quaternary relation expressing that "String A is to string B as string C is to string D". The first contribution of this paper is the rewording of this work in terms of case-based reasoning: a case is a problem-solution pair (A, A) where A is a sentence in an origin language and A , its translation in the destination language. First, three cases (A, A), (B, B), (C, C) such that "A is to B as C is to the target problem D" are retrieved. Then, the analogical equation in the destination language "A is to B as C is to x" is solved and D = x is a suggested translation of D. Although it does not involve any linguistic knowledge, this approach was effective and gave competitive results at the time it was proposed. The second contribution of this work aims at examining how this prior knowledge-light case-based machine translation approach could be improved by using additional pieces of knowledge associated with cases, domain knowledge, retrieval knowledge, and adaptation knowledge, and other principles or techniques from case-based reasoning and natural language processing

Cognitive predictors of shallow-orthography spelling speed and accuracy in 6th grade children

Spelling accuracy and time course was investigated in a sample of 100 Norwegian 6th grade students completing a standardized spelling-to-dictation task. Students responded by keyboard with accurate recordings of response-onset latency (RT) and inter-keypress interval (IKI). We determined effects of a number of child-level cognitive ability factors, and of word-level factors—particularly the location within the word of a spelling challenge (e.g., letter doubling), if present. Spelling accuracy was predicted by word reading (word split) performance, non-word spelling accuracy, keyboard key-finding speed and short-term memory span. Word reading performance predicted accuracy just for words with spelling challenges. For correctly spelled words, RT was predicted by non-word spelling response time and by speed on a key-finding task, and mean IKI by non-verbal cognitive ability, word reading, non-word spelling response time, and key-finding speed. Compared to words with no challenge, mean IKI was shorter for words with an initial challenge and longer for words with a mid-word challenge. These findings suggest that spelling is not fully planned when typing commences, a hypothesis that is confirmed by the fact that IKI immediately before within word challenges were reliably longer than elsewhere within the same word. Taken together our findings imply that routine classroom spelling tests better capture student competence if they focus not only on accuracy but also on production time course

All's well that begins Wells: Celebrating 60 years of Animal Behaviour and 36 years of research on anuran social behaviour

The scientific study of frogs and toads as important systems in behavioural ecology traces its roots to an influential review published in this journal 36 years ago (Wells 1977a, ‘The social behaviour of anuran amphibians’, Animal Behaviour, 25, 666–693). In just 28 pages, Wells summarized the state of knowledge on important behaviours associated with anuran breeding and introduced an evolutionary framework ‘for understanding the relationship between social behaviour and ecology’ (page 666) that was largely lacking in earlier treatments of this group. Not only is Wells's review one of the most cited papers ever published in Animal Behaviour, it is also responsible for setting broad research agendas and shaping much of our current thinking on social behaviour in an entire order of vertebrates. As such, it is entirely appropriate that we honour Wells's review and its contributions to the study of animal behaviour in this inaugural essay celebrating 12 papers selected by the community as the most influential papers published in the 60-year history of Animal Behaviour. In our essay, we place Wells's review in historical context at the dawn of behavioural ecology, highlight the field's progress in answering some major research questions outlined in the review, and provide our own prospectus for future research on the social behaviour of anuran amphibians. Highlights ► This essay celebrates Kent Wells's (1977, Animal Behaviour, 25, 666–693) paper, ‘The social behaviour of anuran amphibians’. ► We place the article in historical context and outline its major contributions. ► We discuss progress on anuran social behaviour since its publication in 1977. ► We provide our own prospectus on the future of anuran behavioural ecology

Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense

Recent progress in deep learning is essentially based on a "big data for small tasks" paradigm, under which massive amounts of data are used to train a classifier for a single narrow task. In this paper, we call for a shift that flips this paradigm upside down. Specifically, we propose a "small data for big tasks" paradigm, wherein a single artificial intelligence (AI) system is challenged to develop "common sense", enabling it to solve a wide range of tasks with little training data. We illustrate the potential power of this new paradigm by reviewing models of common sense that synthesize recent breakthroughs in both machine and human vision. We identify functionality, physics, intent, causality, and utility (FPICU) as the five core domains of cognitive AI with humanlike common sense. When taken as a unified concept, FPICU is concerned with the questions of "why" and "how", beyond the dominant "what" and "where" framework for understanding vision. They are invisible in terms of pixels but nevertheless drive the creation, maintenance, and development of visual scenes. We therefore coin them the "dark matter" of vision. Just as our universe cannot be understood by merely studying observable matter, we argue that vision cannot be understood without studying FPICU. We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks, including tool use, planning, utility inference, and social learning. In summary, we argue that the next generation of AI must embrace "dark" humanlike common sense for solving novel tasks.Comment: For high quality figures, please refer to http://wellyzhang.github.io/attach/dark.pd