The Event Horizon Telescope (EHT) is an international collaboration aiming to capture the first image of a black hole by creating a virtual Earth-sized telescope. This short animated movie explains some of the nuts and bolts behind this ambitious endeavour.
Recording of a series of 4 presentations and a Question & Answer session from the panel named "EHT: A Planetary Effort to Photograph a Black Hole" at the 2019 SXSW festival that took place on March 8--17, 2019 in Austin, Texas, USA.
Speakers (https://schedule.sxsw.com/2019/events... 1) Sheperd Doeleman, EHT Project Director, Senior Astronomer, Center for Astrophysics | Harvard & Smithsonian 2) Dimitrios Psaltis, Professor of Astronomy and Physics, University of Arizona 3) Sera Markoff, Professor of Theoretical Astrophysics and Astroparticle Physics, University of Amsterdam 4) Peter Galison, Joseph Pellegrino University Professor, Harvard University
TESS, the Transiting Exoplanet Survey Satellite, is NASA's newest exoplanet mission. Led by MIT, TESS will find thousands of new planets orbiting nearby stars. During its two year survey, TESS will watch a wide variety of stars, looking for signs of planets ranging from Earth-size to larger than Jupiter.
Each of TESS's cameras has a 16.8-megapixel sensor covering a square 24 degrees wide — large enough to contain an entire constellation. TESS has four of these cameras arranged to view a long strip of the sky called an observation sector. TESS will watch each observation sector for about 27 days before rotating to the next. It will cover the southern sky in its first year, and then begin scanning the north.
TESS will study 85 percent of the sky — an area 350 times greater than what NASA's Kepler mission first observed — making TESS the first exoplanet mission to survey nearly the entire sky. Because TESS's observation sectors overlap, it will have an area near the pole under constant observation. This region is easily monitored by the James Webb Space Telescope, which allows the two missions to work together to first find, and then carefully study exoplanets.
All of the Kepler multi-planet systems (1815 planets/planet candidates in 726 systems) from Kepler's original mission as of the announcement of Kepler's end of life: October 30, 2018. The systems are shown together at the same scale as our own Solar System (dashed lines).
The size of the orbits are all to scale, but the size of the planets are not. For example, Jupiter is actually 11x larger than Earth, but that scale makes Earth-sized planets almost invisible (or Jupiters annoyingly large). The orbits are all synchronized such that Kepler observed a planet transit every time it hits an angle of 0 degrees (the 3 o'clock position on a clock). Planet colors are based on their approximate equilibrium temperatures, as shown in the legend.
Artificial intelligence will be the most consequential technology of the 21st century—augmenting human capabilities, transforming industries and economies
Artificial intelligence will be the most consequential technology of the 21st century—augmenting human capabilities, transforming industries and economies, and reshaping societies. The Stanford Institute for Human-Centered Artificial Intelligence (HAI) was established to advance AI technology and applications, and to provide leadership in understanding and influencing its impact on the world. Join Stanford HAI via livestream for their 2019 symposium on March 18.
U.S. space agency NASA announced the discovery of more than 200 new planets on Monday, 10 of which are believed to be about the right size and temperature to support life. Of the 219 new suspected planets to have been discovered by NASA's Kepler telescope, 10 were found to exist in the so-called 'Goldilocks zone' of their solar system. This refers to the distance between the planet and their star, which is neither too hot nor too cold to support complex life. The presence of liquid water on these "rocky" Earth-like planets is seen as a key ingredient required for the existence of life.
"Are we alone? Maybe Kepler today has told us indirectly, although we need confirmation, that we are probably not alone," Mario Perez, Kepler program scientist, said at a news conference. NASA launched the Kepler telescope in 2009 in a bid to discover whether other Earth-like planets are common or rare. The latest identification of suspected exoplanets – planets outside our own solar system – brings the tally discovered by the Kepler telescope to 4,034. The number of worlds thought to be approximately the same size and temperature as Earth is around 50.
Dr. Demis Hassabis is the Co-Founder and CEO of DeepMind, the world’s leading General Artificial Intelligence (AI) company, which was acquired by Google in 2014 in their largest ever European acquisition. Demis will draw on his eclectic experiences as an AI researcher, neuroscientist and video games designer to discuss what is happening at the cutting edge of AI research, including the recent historic AlphaGo match, and its future potential impact on fields such as science and healthcare, and how developing AI may help us better understand the human mind.
What does it mean to be human? J. Wentzel van Huysteen, in his Gifford lectures, posed the question of whether or not we are “alone in the world?” With advances in artificial intelligence and increasing knowledge in the cognitive sciences, the lines that have traditionally defined human uniqueness are beginning to blur.
What constitutes our humanity—that intrinsic notion that separates us from other animals and machines, the essence that demonstrates we are more than the sum of our biological existence—is becoming less and less clear.
In a sense, we may be witnessing the collapse of Cartesian dualism, the idea of the human being having a spirit or soul that is separate from their physical body, or what philosopher Gibert Ryle has referred to the dogma of the “the ghost in the machine.” Is there more, however? Can religious notions of the soul, mind, and body navigate these new advances in science and technology and even provide meaning and value to them, or will religious notions become obsolete? Are there limits to what AI can achieve, and limits to how science can speak to our humanity?
David Bentley Hart has said that “rational thought—understanding, intention, will, consciousness—is not a species of computation.” Is there a line that, no matter the advances in technology or the passing of evolutionary time, no computer or animal will ever cross? Is it our ability to transcend our biology, to somehow rise above the fetters of our bodily existence and instincts that truly makes us human? Will machines one day rise above their programming?
What it means to be human is one of the most important and pressing questions of our day; as we learn more about our world and ourselves, the answer to this question is becoming ever more complex.
Many complex dynamical systems have critical thresholds—so-called tipping points—at which the system shifts abruptly from one state to another. In medicine, we have spontaneous systemic failures such as epileptic seizures or depressive disorders; in global finance, there is concern about systemic market crashes; in the Earth system, abrupt shifts in ocean circulation or climate may occur; and catastrophic shifts in rangelands, fish populations or wildlife populations may threaten ecosystem services. Such transitions are notoriously difficult to predict, because the state of a system may show little change before the tipping point is reached. Also, models of complex systems are usually not good enough to predict reliably where critical thresholds may occur.
Interestingly, though, it now appears that certain universal early-warning signals may occur in a wide class of systems as they approach a critical point. Professor Marten Scheffer, a Dutch mathematical biologist who has been studying critical transitions for years, explains that "If you recognize the early warning signals, you might be able to avoid the transition, or in some cases, promote it. Take for example a depression, or the poverty trap. You want to leave those behind as quickly as possible. But tipping into a much warmer climate without ice caps and with much higher sea levels is something you'd want to avoid."
At first sight, it may seem surprising that disparate phenomena such as the collapse of an over-harvested population and ancient climatic transitions could be indicated by similar signals. However, the dynamics of systems near a critical point share common characteristics, regardless of differences in the details of each system. Therefore, sharp transitions in a range of complex systems are in fact related. In models, critical thresholds for such transitions correspond to bifurcations. Particularly relevant are ‘catastrophic bifurcations’, where, once a threshold is exceeded, a positive feedback propels the system through a phase of directional change towards a contrasting state.
Another important class of bifurcations are those that mark the transition from a stable equilibrium to a cyclic or chaotic system. The most important clues that have been suggested as indicators of whether a system is getting close to a critical threshold are related to a phenomenon known as critical slowing down. The idea here is to directly measure the recovery time (or rate) of a system back to its initial equilibrium state following a perturbation. In case the system is close to a tipping point the recovery time increases (or the recovery rate decreases).
So is it possible to predict those changes? More and more so, according to Dr. Scheffers: "What we often find is that the resilience of a system decreases in the run-up to a tipping point. We see that in ecosystems, financial markets, health, etc." "The ecological systems that I study are in a certain state of equilibrium. A lake is clear, your mood is good. But there's always something happening. You get a speeding ticket, a volcano erupts, you name it. The system therefore fluctuates, but does have a tendency to return to its equilibrium. If it does so quickly, its resilience is high. But if the recovery is slow, it's a sign that the system is drifting. You might be close to a tipping point, and the system could turn into a different state just like that, without being able to easily return to its former state."
"Tropical forests, for instance, can die from drought and heat and turn into a persistent savanna. Forests that are sensitive to such a change recover their canopy after heavy times slower than more resilient forests do. In depressive disorders we've shown something similar, along with psychologists and psychiatrists. If you get an unpleasant phone call, or a bird poops on your head, but soon after you are walking around whistling again, your mood is probably very stable. But if it still bothers you the next day, or maybe even a week later, then the recovery time is slower. That's a bad sign." There's been some criticism of the use of early warning signals, which may be too unreliable to accurately predict a tipping point.
"You can never predict exactly when a system goes haywire, because there's always an element of chance. Today we prefer to speak of indicators of resilience. If you have the right indicators, try to increase or decrease the resilience to affect the chances of a turnaround," Marten Scheffer clarifies. The question is: are we experiencing a big change now? In the Arctic, the signs of change are everywhere: Temperatures nearly 20°C above the seasonal average, summer sea-ice cover hitting new record lows. But only time can tell how those changes will unfold.
Sara Seager is a professor of planetary science and physics at MIT and a contributor to a recent collection of essays on the current state of the search for life beyond Earth.
Here she gives an in-depth presentation on the state of the art in detecting exoplanets, including what more we can learn about them now than we have been able to up to this point, and what the future holds for this field.
Climate scientists at Lawrence Livermore National Laboratory (LLNL) announced the release of new data sets that will provide fresh insights into past and future climate change. Some of these data sets come from model simulations performed at LLNL, one of the more than 40 climate research centers and consortia engaged in next-generation climate change simulations. These results have been produced as part of an international effort to determine the reliability of the models and to enhance understanding of climate change and the underlying processes.
The new data sets, hosted at LLNL and other sites around the world, provide open access to everyone and will enable a large international community of researchers to analyze and scrutinize the results.
Release of these new data sets represents a major milestone for the Coupled Model Intercomparison Project (CMIP), which was established more than 20 years ago by the World Climate Research Programme (WCRP). Its goal is to foster international cooperation among climate modeling centers and to define standard simulations that facilitate comparison of results and lead to new insights and a better understanding of the climate system. The project has grown substantially through five phases, from a single simulations in 1995 (CMIP1) to more than 200 simulations in the current phase (CMIP6). The volume of data produced also has ballooned -- from megabytes to billions of megabytes -- partly due to the expanded set of simulations, but also because model complexity and resolution have increased to address new science questions.
Scientists at LLNL have helped lead the CMIP activity from its inception: providing day-to-day coordination, helping to define the simulations and output requirements, and developing the software used to access the virtual cloud of CMIP6 results. In addition, LLNL scientists lead a consortium of Department of Energy (DOE) laboratories that has developed a new climate model, the "E3SM," which completed some of the CMIP6 core simulations as one of its early milestones. LLNL scientists also have led an international consortium of computer experts, known as the Earth System Grid Federation (ESGF), which has responsibility for the development of the software infrastructure supporting CMIP. Without this infrastructure, access to the new simulation results would not be streamlined so that few researchers would scrutinize them.
“The primary goals are to gauge the strengths and limitations of climate models and to use the spread in results from the collection of models to assess the robustness of conclusions,” said LLNL’s Chris Golaz, who managed the DOE E3SM model experiments, which will be part of the archive.
CMIP is coordinated by a panel appointed by the WCRP's Working Group on Coupled Modeling (WGCM), with governance and infrastructure provided by a number of core international centers. Participants are responsible for securing funds to support their activities, and by this means, CMIP thrives: modeling centers develop improved and more comprehensive climate models and perform the CMIP simulations; independent groups of scientists design targeted suites of simulations to address a diversity of scientific questions; and scientists and computer specialists develop the software "infrastructure" needed to deliver the results to researchers worldwide.
“The numerous phases of the CMIP multi-model archive have provided a wealth of coordinated information that has turbocharged climate research over the last two decades,” said LLNL climate scientist Paul Durack, a member of the WGCM Infrastructure Panel (WIP). “As one of the youngest members of the WIP, I am grateful to the work of the international modeling community that has led and contributed to the various CMIP phases. This considerable resource has hugely benefited my own research productivity, and I am glad to have personally contributed to the latest CMIP6 phase of the project."
At present, the CMIP6 archive includes results from DOE's new E3SM model along with results from nine other modeling groups. All the model output is available through an official CMIP6 portal located at LLNL.
As more modeling groups complete their simulations, the archive will become an increasingly rich resource for climate researchers. As in past phases, CMIP-based science should prove invaluable to the Intergovernmental Panel on Climate Change (IPCC) as it prepares the Sixth Assessment Report, due for release in 2021.
http://www.einstein.yu.edu - Dr. Michael Lipton's MRI course covers the basic technology of MRI, including signal intensity, contrast resolution and spatial resolution. Dr. Lipton is associate professor radiology at Albert Einstein College of Medicine and associate director of its Gruss Magnetic Resonance Research Center.
Have you heard the news of the detection of gravitational waves from a binary neutron star merger (GW170817) in the constellation of Hydra? This is a momentous event in physics and astronomy and will go down as one of the highlights of 21st century science. Several researchers in the School of Physics & Astronomy at Monash University were involved in this work, including Dr Paul Lasky and Dr Eric Thrane who gave this Public Lecture.
Evolution has selected wild organisms to be extremely well adapted to their environment. Because most genetic changes introduced by humans divert the resources of the organism to benefit humans, such mutations are typically eliminated by natural selection in the ancestral habitat. In his first talk, Dr. Kevin Esvelt explains how self-propagating CRISPR-based gene drives can be used to spread genetic alterations through wild populations, potentially impacting all organisms of the target species. Gene drives could be used to benefit public health, the environment, agriculture, and animal well-being. However, real-world use may incur ecological risks, and even research involving self-propagating gene drive systems may risk public trust in science and governance given the possibility of accidental spread. Esvelt explains how to minimize risk and discusses the importance of engaging communities in planning any projects which may affect them.
Esvelt’s second talk focuses on strategies to allow for the safe implementation of localized gene drive technologies that do not spread indefinitely. Daisy drive systems are made up of multiple elements connected like a daisy chain such that each causes the next to be preferentially inherited. They are designed to be self-exhausting by losing elements with each generation, thereby limiting spread. This technique has multiple applications such as removing an invasive species from one area without impacting the same species in its native habitat. Esvelt explains that daisy-drive stability might be tested in a species such as C. elegans where hundreds of generations can be grown in a short period of time. His lab is also developing technologies to reverse any unwanted genetic changes that might be introduced via gene drive. Once again, Esvelt emphasizes the importance of community input into any gene alteration projects. Although it does not currently involve gene drive, he uses the “Mice Against Ticks” project that seeks to prevent tick-borne diseases on the islands of Nantucket and Martha’s Vineyard as an example.
When a star passes close to a massive black hole (MBH), it is ripped apart by the strong tidal forces. As the resulting debris falls toward the MBH, it heats up, emitting light and x-rays in a tidal disruption event (TDE). Pasham et al. (Science, this issue p. 531) examined x-ray observations of a TDE that occurred in 2014. The x-ray emissions varied in a quasi-periodic oscillation every 131 seconds. The rapid rate of this oscillation could only have arisen from material orbiting close to the MBH's event horizon, which indicates that the MBH is spinning rapidly.
This talk discards hand-wavy pop-science metaphors and answers a simple question: from a computer science perspective, how can a quantum computer outperform a classical computer? Attendees will learn the following: - Representing computation with basic linear algebra (matrices and vectors)
The computational workings of qbits, superposition, and quantum logic gates - Solving the Deutsch oracle problem: the simplest problem where a quantum computer outperforms classical methods - Bonus topics: quantum entanglement and teleportation The talk concludes with a live demonstration of quantum entanglement on a real-world quantum computer, and a demo of the Deutsch oracle problem implemented in Q# with the Microsoft Quantum Development Kit.
This talk assumes no prerequisite knowledge, although comfort with basic linear algebra (matrices, vectors, matrix multiplication) will ease understanding.
We have left the Holocene and entered a new epoch, the Anthropocene, when the biosphere is rapidly changing due to human activities. Global warming is just part of this process.
About 1/4 of all chemical energy produced by plants is now used by humans. Humans now take more nitrogen from the atmosphere and convert it into nitrates than all other processes combined. About 8-9 times as much phosphorus is flowing into oceans than the natural background rate. The rate of species going extinct is 100-1000 times the usual background rate. Populations of large ocean fish have declined 90% since 1950.
This is a very informative talk about what humans are doing to their home planet...
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