This isn't your grandfather's stargazing: The amount of data we have on our universe is doubling every year thanks to big telescopes and better light detectors.
Think of all the data humans have collected over the long history of astronomy, from the cuneiform tablets of ancient Babylon to images---like the one above---taken by the Hubble Space Telescope. If we could express all of that data as a number of bits, our fundamental unit of information, that number would be, well, astronomical. But that's not all: in the next year that number is going to double, and the year after that it will double again, and so on and so on.
There are two reasons that astronomy is experiencing this accelerating explosion of data. First, we are getting very good at building telescopes that can image enormous portions of the sky. Second, the sensitivity of our detectors is subject to the exponential force of Moore's Law. That means that these enormous images are increasingly dense with pixels, and they're growing fast---the Large Synoptic Survey Telescope, scheduled to become operational in 2015, has a three-billion-pixel digital camera. So far, our data storage capabilities have kept pace with the massive output of these electronic stargazers. The real struggle has been figuring out how to search and synthesize that output.
Alberto Conti is the Innovation Scientist for the James Webb Space Telescope, the successor to the Hubble Space Telescope that is due to launch in 2018. Before transitioning to the Webb, Conti was the Archive Scientist at the Space Telescope Science Institute (STScI), the organization that operates the Hubble. For almost ten years, he has been trying to make telescope data accessible to astronomers and to the public at large. What follows is my conversation with Conti about the future of, and the relationship between, big telescopes and big data.
Last year I was researching the Hubble Deep Field (pictured below) and I interviewed
Bob Williams, the former head of STScI who originally conceived of and
executed the deep field image. He told me that the deep field, in
addition to its extraordinary scientific value, had changed the way that
data is distributed in astronomy. Can you explain how?
It's interesting, one of the very first papers I wrote as a graduate
student in astronomy was on the Hubble Deep Field. I was a graduate
student in 1995 when it came out, and of course there was this "wow"
factor---the fact that this was one of the deepest images ever taken,
the fact that you have thousands of galaxies in this tiny patch of
sky---you would take out your calculator and try to calculate how many
galaxies there are in the universe and you would come up with a hundred
billion, and it was mind-boggling. It still is.
it also changed the data regime. Before the Hubble Deep Field, data
(raw images) would be deposited in some archive and you would just tell
astronomers to "go get the images." Astronomers would then have to
download the images and run software on them in order to find all of the
objects using certain parameters, and then they'd have to assess the
quality of the data, for instance whether an object that was thought to
be a star was actually a star. So you had to do a lot of analysis before
you could really get into your research.
decided that this data was so overwhelmingly powerful, in terms of what
it was telling us about the universe, that it was worth it for the
community to be able to get their hands on the data immediately. And so
the original deep field team processed the data, found the objects in
it, and then catalogued each of them, so that every object in the deep
field had a description in terms of size, distance, color, brightness
and so forth. And that catalogue was available to researchers from the
very start---it started a whole new model, where the archive does all
I can tell you firsthand how
incredible it was at the time, because as a graduate student studying
quasars, I was able to identify all of the quasars within the data in
just a few minutes. What Bob did, which I thought was brilliant, was
enable us to do the science much quicker. If you take a look at what's
happening with these massive archives now, it's being done in the exact
same way; people realized that you aren't going to be able to download
and process a terabyte of images yourself. It's a huge waste of time.
The other thing Bob did was he released the data to the world almost
immediately; I remember it took forever to download, not because the
data set was especially large, but because there were so many people
accessing the archive at the same time. That was one of astronomy's
first open source exercises, in the sense that we use that term today.
Has data always been an issue for astronomy? Did Galileo ever run out of log books? I remember reading about William Herschel's sister Caroline, an accomplished astronomer in her own right, spending these long, cold nights underneath their wooden telescope, listening for her brother, who would scream these numbers for her to write down in a notebook. How have data challenges changed since then?
Conti: That's a good question. Astronomy has changed quite a bit since Galileo and Herschel. Galileo, for instance, had plenty of paper on which to record his observations, but he was limited in his capacity for observation and so was Herschel to some extent. Today we don't have those same observational limits.
There are two issues driving the current data challenges facing astronomy. First, we are in a vastly different data regime in astronomy than we were even ten or fifteen years ago. Over the past 25 to 30 years, we have been able to build telescopes that are 30 times larger than what we used to be able to build, and at the same time our detectors are 3,000 times more powerful in terms of pixels. The explosion in sensitivity you see in these detectors is a product of Moore's Law---they can collect up to a hundred times more data than was possible even just a few years ago. This exponential increase means that the collective data of astronomy doubles every year or so, and that can be very tough to capture and analyze.
You spent part of your career working with GALEX, the Galaxy Evolution Explorer. How did that experience change the way you saw data and astronomy?
Conti: GALEX was a big deal because it was one of the first whole sky ultraviolet missions. I want to stress "whole sky" here, because taking measurements of ultraviolet sources all over the sky is a lot more data-intensive than zooming in on a single source. Whole sky ultraviolet measurements had been done before, but never at the depth and resolution made possible by GALEX. This had tremendous implications for data archives at the time. When I started working on GALEX nine years ago, the amount of data it produced was gigantic compared with anything that we had in-house at the Space Telescope Science Institute, and that includes the Hubble Space Telescope, which of course doesn't take whole sky images.
What we were able to do was create a catalog of objects that were detected in these whole sky images, and the number was quite large---GALEX had detected something close to three hundred million ultraviolet sources in the sky. That forced the archive to completely revisit the way it allowed users to access these very large catalogs. There were large databases in astronomy ten years ago, but databases that would allow you to search large collections of objects were not common. GALEX helped to pave the way with this new searchable archive. I can remember when we first introduced the data, we had people all over the world trying to download all of the data, because they thought that was the only way they could access it. They were thinking that to use the data you had to have it locally, which was the old way of thinking. The big leap was that we created an interface that allowed you to get to your data, to a level where you're one step away from analysis, and we were able to do that without you having to download it. We did it by creating interfaces that allowed you to mine all three hundred million sources of ultraviolet light in just a few seconds. You could ask the interface to show you all of the objects that had a particular color, or all of the sources from a certain position in the sky, and then you could download only what you needed. That was a big shift in how astronomers do research.
How much data are we talking about?
Conti: Well, GALEX as a whole produced 20 terabytes of data, and that's actually not that large today---in fact it's tiny compared to the instruments that are coming, which are going to make these interfaces even more important. We have telescopes coming that are going to produce petabytes (a thousand terabytes) of data. Already, it's difficult to download a terabyte; a petabyte would be, not impossible, but certainly an enormous waste of bandwidth and time. It's like me telling you to download part of the Internet and search it yourself, instead of just using Google.
Would something like the exoplanet-hunting Kepler Space Telescope have been possible with the data mining and data storage capacities of twenty years ago?
Conti: Well, Kepler is an extraordinary mission for many reasons. Technologically, it would not have been possible even just a few years ago. Kepler measures the light of 170,000 stars very precisely at regular intervals looking for these dips in light that indicate a planet is present. The area that they sample is not very large---it's a small patch of sky---but they're sampling all of those stars every thirty minutes. So that's already a huge breakthrough, and it creates a lot of data, but it's still not as much as a whole sky mission like GALEX.
What's different about Kepler, from a data perspective, is that it's opening up the time domain. With a mission like GALEX, we collect data and store it in the database, but it's relatively static. It sits there and it doesn't really change, unless we get a new dump of data that helps us refine it, and that may only happen once a year. With Kepler you have these very short intervals for data collection, where you have new images every thirty minutes. That really opens up the time domain. We're working hard to figure out how to efficiently analyze time domain data. And of course the results are spectacular: a few years ago we had less than twenty exoplanets, and now we have thousands.
Is there a new generation of telescopes coming that will make use of these time domain techniques?
Conti: Oh yes. With Kepler we've developed this ability to make close observations of objects in the sky over time, but if you add millions or even billions of objects, then you get into the new regime of telescopes like the Large Synoptic Survey Telescope (LSST) which we expect to come online at the end of this decade. These telescopes are going to take images of the whole sky every three days or so; with that kind of data you can actually make movies of the whole sky. You can point to a place in the sky and say "there was nothing there the other day, but today there's a supernova." You couple that kind of big data, whole sky data, with the time domain and you're talking about collecting terabytes every night. And we don't have to wait that long; ALMA, the Atacama Large Millimeter Array is going to have its first data release very soon and its raw data is something like forty terabytes a day. Then in 2025, we're going to have the Square Kilometre Array (SKA), the most sensitive radio instrument ever built, and we expect it will produce more data than we have on the entire Internet now---and that's in a single year. This is all being driven by the effect that Moore's Law has on these detectors; these systematic advances let us keep packing in more and more pixels.
In my view, we've reached the point where storage is no longer the issue. You can buy disk, you can buy storage, and I think that at some point we may even have a cloud for astronomy that can host a lot of this data. The problem is how long it's going to take me to get a search answer out of these massive data sets. How long will I have to wait for it?
Has citizen science played a meaningful role in helping astronomy tackle all of this data?
Conti: I think so. I'm part of a group that has done a lot of work on citizen science, especially with the folks over at Galaxy Zoo and CosmoQuest on an in-house project called Hubble Zoo. The original Galaxy Zoo was a galaxy classification project, where volunteers could log on to the server and help to classify galaxies by shape. Galaxy shapes give you a lot of information about their formation history; for instance, round galaxies are much more likely to have cannibalized other galaxies in a merger, and on average they're a little older. Spiral galaxies are structures that need time to evolve; generally, they're a little younger than round galaxies. And so when you have thousands of ordinary, non-scientists classifying these galaxies you can get some great statistics in a short period of time. You can get the percentage of round galaxies, elliptical galaxies, spiral galaxies, irregular galaxies and so forth; you can get some really interesting information back. What's great about citizen science is that you can feed images to citizens that have only been fed through machines---no human eyes have ever looked at them.
There's another citizen science project that I'm trying to get started in order to to make use of all the old GALEX data. With GALEX we took these whole sky images in ultraviolet, and we did it at certain intervals, so there is a time domain at work, even if it's not as rapid as the Kepler. But as I said before, we have over three hundred million sources of UV light in these images. There was a professor who had a graduate student looking at this data at different intervals with the naked eye, and they were able to find four hundred stars that seemed to be pulsating over time. When I saw the data, I said "this is interesting, but it should be an algorithm." So we made an algorithm to detect these pulsating stars, and we ran it inside the entire database of 300 million sources, and we found 2.1 million pulsating star candidates. And of course, this is just the first pass at this; who knows how many of those candidates will convert. But it's an illustrative case---the idea is to feed these kinds of projects to the next generation of citizen scientists, and to have them to do what that graduate student did, and then in some cases they'll be able to find something remarkable, something that otherwise might never have been found.
Can we talk about image-processing? What percentage of Hubble images
are given the kind of treatment that you see with really iconic shots
like the Sombrero Galaxy or the Pillars of Creation?
It depends. There's an image coming out for the 22nd anniversary (of
the Hubble) here in a few days, and as you'll be able to see, it's a
very beautiful image. I'm a little biased in the sense that I tend to
think that every image from the Hubble is iconic, but they aren't all
treated equally. There's a group of people here in the office of public
outreach at STScI that think a lot about how images are released. But if
you go back to the Hubble Deep Field, or even earlier, you can see that
the imaging team really does put a lot of care into every Hubble image.
And that's not because each one of those images is iconic; rather it's
because we have this instrument that is so unbelievable and each piece
of data it produces is precious, and so a lot of work goes into
And now, with the Hubble
Legacy Archive, people can produce their own Hubble images, with new
colors, and they can do it on the fly.
Like Instagram filters?
Kind of, yeah. As you know, all data in astronomy is monochrome
data---it's black and white---and then the processing team combines it
into layers of red, green and blue, and so forth. Zolt Levay, the head
of the imaging team, takes these colored layers and combines them and
tries to make them as accurate as possible in terms of how they would
look to the human eye, or to a slightly more sensitive eye. This program
lets you take three monochrome images, which you can then make any
color you like, and it let's you make them into a single beautiful
image. There's actually a contest being held by the office of public outreach to see who can upload the most beautiful new image.
Footnotes. Numbers. Detailed proposals. The Donald’s economic address at an aluminum factory in Pennsylvania had it all.
Donald Trump must have hired some researchers.
The famously off-the-cuff orator delivered a surprisingly specific speech on trade, making seven detailed policy pledges while predicting that Hillary Clinton, if elected, would tweak and then sign the enormous Pacific trade pact she now opposes as a candidate for president.
Trump’s address to workers at a Pennsylvania aluminum factory continued his recent effort to lift both the tone and substance of his speeches. But it marked an even bigger departure in its sheer wonkiness.First, his campaign sent out the prepared remarks with 128 footnotes. And in delivering the speech from a teleprompter, Trump delved into such granular policy detail that he referenced specific sections of decades-old trade laws and vowed to invoke “Article 2205” of the North American Free Trade Agreement. Doing so, he said, would withdraw the U.S. from NAFTA if its trading partners don’t agree to renegotiate the Clinton-era accord.
It happened gradually—and until the U.S. figures out how to treat the problem, it will only get worse.
It’s 2020, four years from now. The campaign is under way to succeed the president, who is retiring after a single wretched term. Voters are angrier than ever—at politicians, at compromisers, at the establishment. Congress and the White House seem incapable of working together on anything, even when their interests align. With lawmaking at a standstill, the president’s use of executive orders and regulatory discretion has reached a level that Congress views as dictatorial—not that Congress can do anything about it, except file lawsuits that the divided Supreme Court, its three vacancies unfilled, has been unable to resolve.
On Capitol Hill, Speaker Paul Ryan resigned after proving unable to pass a budget, or much else. The House burned through two more speakers and one “acting” speaker, a job invented following four speakerless months. The Senate, meanwhile, is tied in knots by wannabe presidents and aspiring talk-show hosts, who use the chamber as a social-media platform to build their brands by obstructing—well, everything. The Defense Department is among hundreds of agencies that have not been reauthorized, the government has shut down three times, and, yes, it finally happened: The United States briefly defaulted on the national debt, precipitating a market collapse and an economic downturn. No one wanted that outcome, but no one was able to prevent it.
At least 36 people were killed in an attack Tuesday at Ataturk airport, one of the busiest in Europe.
Here’s what we know:
—Explosions and gunfire were reported Tuesday night at Istanbul’s Ataturk International Airport, one of the busiest in Europe. Turkey’s prime minister, Binali Yildirim, said in a news conference three attackers opened fire at the airport’s international terminal and detonated explosives, blowing themselves up.
—The prime minister said 36 people were killed and 147 wounded. Photos from the scene showed bloodied bodies and debris on the pavement outside the terminal. The airport was evacuated.
—We’re live-blogging what’s happening, and you can read how it unfolded below. All updates are in Eastern Standard Time (GMT -5). It’s after 3 a.m. Wednesday in Istanbul.
Turkish Prime Minister Binali Yildirim told reporters outside Ataturk airport that 36 people had been killed in the attack. The dead included five police officers. He said 147 people had been wounded, adding the three attackers blew themselves up.
Fears of civilization-wide idleness are based too much on the downsides of being unemployed in a society premised on the concept of employment.
People have speculated for centuries about a future without work, and today is no different, with academics, writers, and activists once again warning that technology is replacing human workers. Some imagine that the coming work-free world will be defined by inequality: A few wealthy people will own all the capital, and the masses will struggle in an impoverished wasteland.
A different, less paranoid, and not mutually exclusive prediction holds that the future will be a wasteland of a different sort, one characterized by purposelessness: Without jobs to give their lives meaning, people will simply become lazy and depressed. Indeed, today’s unemployed don’t seem to be having a great time. One Gallup poll found that 20 percent of Americans who have been unemployed for at least a year report having depression, double the rate for working Americans. Also, some research suggests that the explanation for rising rates of mortality, mental-health problems, and addiction among poorly-educated, middle-aged people is a shortage of well-paid jobs. Another study shows that people are often happier at work than in their free time. Perhaps this is why many worry about the agonizing dullness of a jobless future.
Their degrees may help them secure entry-level jobs, but to advance in their careers, they’ll need much more than technical skills.
American undergraduates are flocking to business programs, and finding plenty of entry-level opportunities. But when businesses go hunting for CEOs or managers, “they will say, a couple of decades out, that I’m looking for a liberal arts grad,” said Judy Samuelson, executive director of the Aspen Institute’s Business and Society Program.
That presents a growing challenge to colleges and universities. Students are clamoring for degrees that will help them secure jobs in a shifting economy, but to succeed in the long term, they’ll require an education that allows them to grow, adapt, and contribute as citizens—and to build successful careers. And it’s why many schools are shaking up their curricula to ensure that undergraduate business majors receive something they may not even know they need—a rigorous liberal-arts education.
There are two basic modes of judgment: criticism and praise. The former consists of identifying a subject’s flaws; the latter of noting its merits.
In most settings, criticism tends to dominate. For any idea or book or movie or what have you, the question that people discuss is what’s wrong with it, why it didn’t live up to expectations. Often, one gets the feeling that the criticism isn’t dispensed in an effort to engage with the work but as a demonstration of the critic’s smarts, the implicit argument being that he or she is sharper and more discerning than the work’s creator.
Often, the greater intellectual challenge—as a reader, as a viewer, and as a manager—is to recognize when something is truly great.
The way members of the ‘model minority’ are treated in elite-college admissions could affect race-based standards moving forward.
In his new book, Earning Admission: Real Strategies for Getting Into Highly Selective Colleges, the strategist Greg Kaplan urges Asians not to identify as such on their applications. “Your child should decline to state her background if she identifies with a group that is overrepresented on campus even if her name suggests affiliation,” he advises parents, also referencing Jews. Such tips are increasingly common in the college-advising world; it’s not unusual for consultants, according to The Boston Globe, to urge students to “deemphasize the Asianness” in their resumes or avoid writing application essays about their immigrant parents “coming from Vietnam with $2 in a rickety boat and swimming away from sharks.”
Chimamanda Ngozi Adichie has a new short story: a Virginia Woolf-inflected ode to Melania Trump.
“Melania decided she would order the flowers herself.”
So begins the new short story from Chimamanda Ngozi Adichie, the first such work commissioned by, and for, The New York Times Book Review. The paper gave the acclaimed writer—author of Americanah and Half of a Yellow Sun, and the recipient of a MacArthur Genius grant—a broad assignment: Write anything about this election season you like.
Adichie chose Trump. Specifically, she chose the Trumps. And the result of that is “The Arrangements,” which, as its opening line suggests, trains its gaze on Melania, the woman most Americans know as silent and stoic and, perhaps most of all, a cipher. “The Arrangements” is, in the manner of Curtis Sittenfeld’s Eligible, a tribute to an earlier work of literature—in this case, Virginia Woolf’s Mrs. Dalloway, one of the still-soaring examples of literary modernism, and an early-20th-century novel that’s especially notable for being told from the perspective of a woman. In that sense, “Melania decided she would order the flowers herself” is at once a call-out to Dalloway’s opening line, an ironization of that line—ordering instead of buying—and a declaration of Adichie’s intent: It is Melania who will do the deciding. It is Melania who will do the thinking. It is Melania who will deal with the flowers.
There’s more to life than can be measured in monetary returns.
What’s a good use of money?
For investors, that question comes down to a relatively straightforward calculation: Which of the available options has the greatest expected return on the investment?
But investors are far from the only people who are using the “return on investment” framework to weigh different options. “This has become a very, very powerful tool for decision making, not only in business, but in our culture as a whole,” said Moses Pava, an ethicist and a dean of the Sy Syms School of Business at Yeshiva University, at the Aspen Ideas Festival, co-hosted by the Aspen Institute and The Atlantic. In particular, Pava sees this kind of thinking dominating the world of education, both on the part of students in choosing schools and majors, and on the part of school in how they market themselves to potential enrollees. This, he says, will not end well for liberal arts schools.
House Republicans released a lengthy report on Tuesday detailing how events unfolded and criticizing the government’s response to them.
After a two-year investigation that cost $7 million, one of the most politically contentious chapters of Hillary Clinton’s career came to a close on Tuesday. House Republicans released their long-awaited reporton the 2012 Benghazi terror attacks that killed four Americans, including Ambassador Chris Stevens.
Clinton was the secretary of state at the time. As a result, the investigation into the attack has been politically charged: It coincided with an election year in which Clinton is now the presumptive Democratic nominee. House Republicans, however, have repeatedly denounced accusations that the investigation was a political ploy. On Tuesday, they continued to do so, highlighting their efforts to make sense of the government’s response to the attacks.