Exoplanet Discovery By An Amateur Astronomer

To find new worlds around distant stars, you don’t have to be an expert astronomer. Andrew Grey, a Darwin mechanic and amateur Astronomer, helped to find a new exoplanet-system with at least four planets orbiting it. Andrew received professional support and help. This discovery was the highlight of ABC Stargazing Live’s three-evening special ABC Stargazing Live. It featured Brian Cox, a British physicist, and Julia Zemiro, as well as other presenters.

Exoplanet Explorers invited viewers to join the search for distant planets. Following a brief tutorial, they were ask to search through data from thousands of stars that had been recently view by NASA’s Kepler Space Telescope. Grey scanned more than 1000 stars before he discovered the distinctive dips in brightness that indicate an exoplanet.

Grey will be list with the other co-discoverers on a scientific paper that reports the significant discovery of a star with 4 planets. They orbit closer to the star then Mercury orbits to our Sun.

Grey Spoke To Stargazing Live Astronomer

This is incredible. This is my first scientific publication. I’m just glad I could contribute. It feels great. Cox was obviously impress by this new discovery. This is the most important scientific discovery I’ve made in the seven years Stargazing Live has been running.

Citizen Science Is A Breakthrough Astronomer

What does this discovery mean? Let’s be honest: This is not a publicity stunt or fake news. This is a scientific discovery that should be publish in scientific literature, just like other discoveries by astronomers. It will allow us to understand how our Earth formed. It will also help us determine if we are the only ones in the universe or if there are other planets populate with other civilisations.

However, this discovery adds to the more than 2,300 exoplanets that Kepler has discovered so far. There are many more potential planets that need to be explore. Grey and his co workers would not have discovered the new planetary system if they hadn’t. This can said for all discoveries. Grey and his fellow citizen scientists made this discovery.

Professionals And Amateurs Working Together

The greatest significance of this discovery, I believe, is the fact that it will change the way science is done. Grey was not the only one to make this discovery, as I mentioned earlier. Grey used data from Kepler’s spacecraft at a cost of US$600 millions. We can create stunning telescopes capable of producing large amounts of valuable data but we are still unable to develop an algorithm capable of analysing that data with the same precision and speed as the human brain.

The human brain is able to detect patterns in data much better than any machine-learning algorithm. Due to the huge amount of data generated through Kepler and other scientific instruments we require large teams of human brains, larger than any research laboratory.

The brains do not need to be trained in astrophysicists. They just need to possess the incredible cognitive abilities of the human mind. This partnership allows big science to produce data and citizen scientists to inspect it in order make discoveries. This allows anyone to participate in cutting-edge science and accelerates the growth of knowledge.

Gathering Brainpower Astronomer

This is happening in science and the arts as well, from butterfly hunting to transcribing Shakespeare’s handwriting. The largest known cluster of galaxies was discovered by citizen scientists last year as part of the Australian-led Radio Galaxy Zoo Project. Without widespread internet access and the readily-available tools for building citizen science projects such as Zoo universe, none of these projects could be realized.

Are machines going to make citizen scientists obsolete? I’ve argued that algorithms, called machine scientists, are need to discover new things from the huge amounts of data generated. These algorithms still require human training. Our machine scientists will be more successful if we have a larger human-generated training collection.

Instead of making citizen scientists redundant, machine scientists multiply citizen scientists power, so that a discovery made in the future Andrew Grey could lead to hundreds of discoveries by machines that are train with his discovery.

I can see citizen scientists’ power growing. This is just the beginning, I think. We can do much more. You can make citizen science more fun by including gaming elements in citizen science programs or using new technologies like immersive virtual reality and augmented reality. We might be able to tap into our human creativity and imagination to accomplish goals that frustrate machines.

I look forward every day that a Nobel prize will be won by someone from a developing nation without access to traditional university education but who uses their mind, the wealth information on the internet and citizen science tools to surpass the dreams of traditional science.

Data Driven Science More Than Just A Buzzword

Don’t look through a telescope data at stars. Today’s astronomer is more likely online. He or she can digitally schedule observations, run them remotely using a telescope in the desert and download the results for analysis. Many astronomers consider exploring the data computationally to be their first step in science. Although data-driven science may sound like a trendy term, it is a fundamental shift in fields such as astronomy.

The Australian Academy of Science’s 2015 report found that around 25% of the research efforts of professional astronomers in Australia were now computational. Many high schools and universities still view the required skills as second-class citizens, despite their technology and engineering courses.

Computing refers to both the modelling of the world using simulations and the exploration observational data. It is central to not only astronomy, but also to a variety of sciences including bioinformatics and computational linguistics. We must create new teaching methods that recognize data-driven, computational approaches as primary tools in contemporary research to prepare the next generation.

Big Data Is The Future Of Science

The 17th-century empiricists believed that understanding the world would be possible if we used all our senses to gather as much information as possible. While empirical science is a well-established tradition, there are key differences between the traditional approach to science and today’s data-driven science.

Computers can now store a lot of data, which has had perhaps the greatest impact. This has allow a shift in philosophy, data can now be gather to serve multiple projects instead of just one. The way we explore data and mine it allows us to plan for serendipity.

Consider the search for new types astronomical phenomena. Unexpected results can be achieve with large data sets. Recent examples include the discovery by Duncan Lorimer of radio bursts and Cleo Loi, a former undergraduate student of my, of plasma tubes in Earth’s atmosphere. Both depended upon mining archival data sets that were design for a different purpose.

Scientists now collaborate to create experiments that can be use for multiple projects and test different hypotheses. One example is the 135-page book that outlines the science behind the Square Kilometre Array Telescope. It will built in South Africa, Australia.

It Is Time For Our Education System To Change

One of the most iconic images of science is Albert Einstein writing the equations for relativity or Marie Curie discovering radioactivity in her laboratory. High school is where science theory and experiment taught. This helps us understand how science works. These twin pillars are often picture together with experimental scientists testing theories and theorists creating new explanations for empirical results.

However, computation is not often mention and many important skills are still un develop. Scientists need to be able to use statistical skills to design and analysis data in order for them not only do they have to be objective but also select reliable samples. This part of maths is often neglect in university degrees. Scientists need to be more knowledgeable than high school statistics in order to ensure that data-driven explorations and experiments are accurate.

Scientists need to be able to use computational thinking to solve the problems of this age. Although coding is a great start, it’s not enough. They will need to think creatively about algorithms and how to manage data using advanced techniques like machine learning.

Algorithms For Large Data

Simple algorithms for large data sets are impossible to apply, even if you have 10,000 core supercomputers. Software can be speeded up by switching to more advanced computer science techniques, such as the KD-tree algorithm for matching Astrological objects.

There are some steps being taken in the right direction. Many universities offer degrees and courses in data science. These include computer science and statistics, as well as business and science. My online course Data-Driven Astronomy was launched recently. It teaches skills such as data management and machine learning within the context of astronomy.

The new Australian Curriculum in Digital Technologies is now part of schools’ curriculum. It makes coding and computational thinking a compulsory subject starting in Year 2. These skills will be vital, but the next step in science education is to incorporate modern approaches directly into science classrooms.

Since more than 50 years ago, computation has been an integral part of science. The data explosion is making computational thinking even more important. We can make sure that our students are ready to make the next great discovery by teaching computational thinking as part science.

Science Needs True Diversity To Succeed Astronomy Shows

The research it conducts and the facilities diversity it has to offer astronomy in Australia are exceptional. In the last year, we have made amazing discoveries. Recent discoveries by our scientists have shortened the timeframe for the first light in all of the universe. We now know that the massive explosion at the Milky Way’s black hole occurred 3.5 million years ago.

The world’s astronomical ecosystem is important because of our facilities. From the Murchison Widefield Array (West Australia) to the Anglo-Australian Telescope (New South Wales). To make the most out of the next wave in stargazing technology. However, we need to have true diversity within our astronomical community.

In a paper I published in Nature Astronomy this week, I argue that Australia’s astronomers. Made significant strides in increasing diversity in recent years. This is something that can be used as a model for other scientific communities.

Why Diversity Is Important

However, even more powerful stargazing hardware will soon be available. A new generation of mega telescopes will include the Australian. Section of the Square Kilometre Array and the Extremely Large Telescope from Chile. These super-tools can reveal the universe in unprecedented detail and gather data in unprecedented quantities. We must as a discipline be ready to get the most out of them.

It will take more than just astronomical hands to extract the maximum signal from this new collection of noise. This will require different types and ways of seeing. Diverseness within organizations at all levels is a benefit that has been proven by numerous other industries, including business. It leads to higher productivity, greater profits, and stronger outcomes.

It’s not only in education or social work. Even in science that crunches numbers, personal history and lived experiences can influence how questions are asked and how networks are constructed.

Gender Equity And The Australian Model Diversity

The Pleiades Awards, a program operated by the Astronomical Society of Australia, has been a major factor in the recent progress made by Australian astronomy towards gender equality. This country has approximately 500 astronomers. The Australian Academy of Science commissioned the 2016-25 Australian Astronomy Decadal Plan. It sets a goal of 33% of all positions to be fill within six years.

The Pleiades offer a structured approach for improving equity. This marker is certain to be accomplish because of the enthusiasm of nearly all 14 universities, the two Centres of Excellence, and the three organisations that host Australia’s astronomical community. We need to think outside of the binary gender question and expand our understanding of fairness and empathy in the workplace.

Astronomers From All Over The Spectrum

The next generation telescopes will require huge international collaborations and intense competition among partner countries. We need to think beyond traditional hiring practices in order to reap the full benefits of the telescopes’ extraordinary power.

Will need to bring together people with diverse backgrounds and experiences, as well as new ideas. We must draw on the academic talent, insight, and experience of LGBTIQA+ astronomers as well as Indigenous astronomers and disabled astronomers.

While there many highly skill scientists, the prospects of a long-term stable career with funding and support seem slim for those who do not fall within this category. Scientist research institutions and organizations are just as guilty of failing to build proper structures that promote understanding, inclusion, and empathy as any other field.

Female astronomers from many years ago will often testify that sometimes, the support and welcome inside Australian faculties and organizations could have been warmer.

The Pleiades scheme allows women in my field to expect recognition for their skills and promotion according to merits. This is not possible for people from other categories. It must change. It is fair, but equally important, it is what science demands.