microexcelanlyst

by George Taniwaki

While working toward my Microsoft Data Science Certificate (see Jul 2017 blog post), I also completed the Microsoft Excel for the Data Analyst XSeries Program sponsored by Microsoft and edX.

There are 3 classes in the program, two of which were also courses for the Microsoft Data Science Certificate.

DAT205x – Introduction to Data Analysis using Excel

This basic course on data analysis using Excel covers pivot tables, using SUMIF() and SUMIFS() functions to create dashboards and year-over-year comparison tables (something that is not possible using pivot tables alone), creating reports with hierarchal data, using Power Pivot, and creating multi-table reports using the data model and the More tables… feature.

Year-over-year comparison tables can also be created using the Excel data model and time intelligence functions. These are covered in the third course, DAT 206x.

Time: Since I am already an experienced Excel user, I skipped the videos and just did the homework. I covered the 8 modules in about 6 hours

Score:  I missed 1 quiz question and no lab questions for a combined score of 99%

image     image

DAT222x – Essential Statistics for Data Analysis using Excel

[I took DAT222x in order to earn the Microsoft Data Science Certificate. This section is copied from this  Jul 2017 blog post.]

This class is comprehensive and covers all the standard statistics and probability topics including descriptive statistics, Bayes rule, random variables, central limit theorem, sampling and confidence interval, and hypothesis testing. Most analysis is conducted using the Data analysis pack add-in for Excel.

Time: I used to work in market research, so I know my statistics. However, there are 36 homework assignments and it took me over 20 hours to complete the 5 modules.

Score: I missed 9 questions on the quizzes (88%) and six in the final exam (81%) for a combined score of 86%. (Despite the time it takes to complete, homework counts very little toward the final grade)

DAT222x-Score_thumb10     DAT222x-Certificate21

DAT206x – Analyzing and Visualizing Data with Excel

Topics include importing data and using queries with Excel, the Excel data model, using the M query language and DAX query language, creating dashboards and visualizations, and using Excel with Power BI.

Within the M language, topics include using the functions in the ribbon, including filtering rows, Table.Unpivot function.

Within the DAX language, topics include using the X functions like SUMX() and the CALCULATE() function, using Calendar table and time intelligence, and customize pivot tables and pivot charts using the CUBE functions from multidimensional expressions (MDX) language. The CUBE functions can also generate a table that can be used to create chart types that Excel does not support directly from a pivot table (for instance the new treemap, sunburst, and histogram charts).

Time: I am an experienced Excel user, but some of the advanced DAX functions were new to me. 6 hours for 8 modules

Score: I got a bit sloppy. I missed 2 lab questions and 1quiz question for a combined score of 95%

DAT206x Score     DAT206x Certificate

Final Certificate

Below is my certificate of completion for the Microsoft Excel for the Data Analyst XSeries Program.

ExcelXSeries Certificate

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MsftBigData

by George Taniwaki

Big data and machine learning are all the rage now. Articles in the popular press inform us that anyone who can master the skills needed to turn giant piles of previously unexplored data into golden nuggets of business insight can write their own ticket to a fun and remunerative career (efinancialcareers May 2017).

Conversely, the press also tells us that if we don’t learn these skills a computer will take our job (USA Today Mar 2014). I will have a lot more to say about changes in employment and income during the industrial revolution in future blog posts.

But how do you learn to become a data scientist. And which software stack should one specialize in? There are many tools to choose from. Since I live in the Seattle area and do a lot of work for Microsoft, I decided to do take an online class developed and sponsored by Microsoft and edX. Completion of the course leads to a Microsoft Data Science Certificate.

The program consists of 10 courses with some choices, like conducting analysis using either Excel or Power BI, and programming using either R or Python. Other parts of the Microsoft stack you will learn include SQL Server for queries and Microsoft Azure Machine Learning (MAML) for analysis and visualization of results. The courses are priced about $99 each. You can audit them for free if you don’t care about the certificates.

I started the program in February and am about half way done. In case any clients or potential employers are interested in my credentials, my progress is shown below.

DAT101x – Data Science Orientation

If you haven’t been in college in a while or have never taken an online class, this is a good introduction to online learning. The homework consists of some simple statistics and visualization problems.

Time: 3 hours for 3 modules

Score: 100% on 3 assignments

DAT101x Score    DAT101x Certificate

DAT201x – Querying with Transact-SQL

I took a t-SQL class online at Bellevue College two years ago. Taking a class with a real teacher, even one you never meet, was a significantly better experience than a self-paced mooc. This course starts with the basics like select, subqueries, and variables. It also covers intermediate topics like programming, expressions, stored procedures, and error handling. I did my homework using both a local instance of SQL Server and on an Azure SQL database.

Time: 20 hours for 11 modules

Score: I missed one question in the homework and two in the final exam for a combined score of 94%

DAT201x Score     DAT201x Certificate

DAT207x – Analyzing and Visualizing Data with Power BI

I already have experience creating reports using Power BI. I also use Power Query (now called get and transform data) and M language and Power Pivot and DAX language, so this was an easy class.

The course covers data transforms, modeling, visualization, Power BI web service, organization packs, security and groups. It also touches on the developer API and building mobile apps.

Time: 12 hours for 9 modules

Score: I missed one lab question for a combined score of 98%

DAT207x Score     DAT207x Certificate

DAT222x – Essential Statistics for Data Analysis using Excel

This class is comprehensive and covers all the standard statistics and probability topics including descriptive statistics, Bayes rule, random variables, central limit theorem, sampling and confidence interval, and hypothesis testing. Most analysis is conducted using the Data analysis pack add-in for Excel.

Time: I used to work in market research, so I know my statistics. However, there are 36 homework assignments and it took me over 20 hours to complete the 5 modules.

Score: I missed 9 questions on the quizzes (88%) and six in the final exam (81%) for a combined score of 86%. (Despite the time it takes to complete, homework counts very little toward the final grade)

DAT222x Score     DAT222x Certificate

DAT204x – Introduction to R for Data Science

Now we are getting into the meat of the program. R is a functional language. In many ways it is similar to the M language used in Power Query. I was able to quickly learn the syntax and grasp the core concepts.

The course covers vectors, matrices, factors, lists, data frames, and simple graphics.

The lab assignments use DataCamp which has a script window where you write code and a console window that displays results. That makes it easy to debug programs as you write them.

The final exam used an unexpected format. It was timed and consisted of about 50 questions, mostly fill-in-the-blank responses that include code snippets. You are given 4 minutes per question. If you don’t answer within the time limit, it goes to the next question. I completed the test in about 70 minutes, but I ran out of time on several questions, and was exhausted at the end. I’m not convinced that a timed test is the best way to measure subject mastery by a beginning programmer. But maybe that is just rationalization on my part.

Time: 15 hours for 7 modules

Score: I got all the exercises (ungraded) and labs right and missed two questions in the quizzes. I only got 74% on the final, for a combined score of 88%

DAT204x Score     DAT204x Certificate

DAT203.1x Data Science Essentials

The first three modules in this course covered statistics and was mostly a repeat of the material introduced in DAT222x. But the rest of the course provides an excellent introduction to machine learning. You learn how to create a MAML instance, import a SQL query, manipulate it using R or Python, create a model, score it, publish it as a web service, and use the web service to append predictions as a column in Excel. I really like MAML. I will post a review of my experience in a future blog post.

The course was a little too cookbook-like for my taste. It consisted mostly of following directions to drag-drop boxes onto the canvas UI and copy-paste code snippets into the panels. However, if you want a quick introduction to machine learning without having to dig into the details of SQL, R, or Python, this is a great course.

Time: 10 hours for 6 modules

Score: 100% on the 6 labs and the final

DAT203.1x Score     DAT203.1x Certificate

I have now completed six out of the ten courses required for a certificate. I expect to finish the remaining 4 needed for a certificate by the end of the year. I will also probably take some of the other elective courses simply to learn more about Microsoft’s other machine learning and cloud services.

For my results in the remaining classes, see Microsoft Data Science Certificate-Part 2

Update: Modified the description of the final exam for DAT204x.

by George Taniwaki

SEIU_775_purple FFlogo Wa2016Yes1501

I’m a libertarian by nature. (That’s libertarian with a small L, meaning I believe in government transparency and clarity. Please don’t confuse it with Libertarian with a capital L, which I associate with mindless anarchy.) Every two year, I dutifully check for my ballot and voter pamphlet (Washington has voter by mail). The number of items seems to be getting longer, especially voter initiatives.

Here is my method of deciding how to cast my ballot on voter initiatives. First, I start skeptically. Most voter initiatives are funded by political extremists who do not consider the consequences of adopting their pet idea. But I do my online research, checking analysis produced by hopefully reputable and unbiased sources. Ultimately though, I usually vote against them.

This year in Washington, there a really bizarre ballot issue. It is Initiative Measure No. 1501. “Increased Penalties for Crimes Against Vulnerable Individuals”

This measure would increase the penalties for criminal identity theft and civil consumer fraud targeted at seniors or vulnerable individuals; and exempt certain information of vulnerable individuals and in-home caregivers from public disclosure.

Should this measure be enacted into law? Yes [ ] No [ ]

How could anyone be against this? We want to help seniors, right? Well, it’s not that simple.

A convoluted story

There is a very complex story about this initiative. It involves a union, an antiunion think tank, and the U.S. Supreme Court. Initiative 1501 is sponsored by the Service Employees International Union (SEIU) that represents healthcare workers that work in nursing homes or provide in-home care. Washington, like most states, requires certain workers, such as nurses, to have a license in order to provide services to the public. About one-third of all service workers in the U.S. require licenses. In many cases, these workers are also unionized.

Enter the Freedom Foundation. This antiunion policy group is headquartered in Olympia, Washington. It was founded by Bob Williams, who was formerly with the American Legislative Exchange Council (ALEC). You may have heard of ALEC; it is a corporate funded lobbying group that writes model legislation (which obviously is designed to further the goals of its corporate clients) which it then provides to state legislators to review. The legislators can then submit the bills for approval into law. The Freedom Foundation provides very similar services.

In 2014, the U.S. Supreme Court ruled 5-4 in Harris v. Quinn that an Illinois state law that allowed the SEIU to collect a representation fee (union dues) from in-home healthcare workers wages was unconstitutional. The reasoning was that the fee violated the First Amendment rights of the workers to not provide financial support for collective bargaining.

After the ruling, the Freedom Foundation complained that the SEIU was not doing enough to inform its members that they did not have to pay the representation fee in order to belong to the union. Though a public records act, it sued the union and the state, won, and started to send communications to members encouraging them to stop paying the fee.

Since a Supreme Court ruling covers the entire U.S., not just Illinois, the SEIU realized that it was very vulnerable to attack by the Freedom Foundation or other antiunion organizations.

Now the initiative makes sense

In Washington, the SEIU proactively sponsored Initiative 1501 as a direct attack against Freedom Foundation. The SEIU wants to avoid having to release the names, addresses, and phone numbers of its members (or having the state reveal these either). Initiative 1501 does this by saying that in-home caregivers are a protected class, like seniors or vulnerable individuals, that the state and the union cannot release personal information about.

After all that research, the story starts to make sense. This is a battle between two parties that a libertarian like me dislikes. But more transparency is better than less. So I will vote no. Sorry seniors and vulnerable individuals, you will have to rely on existing statutes to protect you.

by George Taniwaki

Did you watch the debate on Monday night? I did. But I am also very interested in the post-debate media coverage and analysis. This morning, two articles that combine big data and the debate caught my eye. Both are novel and much more interesting than the tired stories that simply show changes in polls after a debate.

First, the New York Time reports that during the presidential debate (between 9:00 and 10:30 PM EDT) there is high correlation between the Betfair prediction market for who will win the presidential election and afterhours S&P 500 futures prices (see chart 1).

PresidentSandP500

Chart 1. Betfair prediction market for Mrs. Clinton compared to S&P 500 futures. Courtesy of New York Times

Correlation between markets is not a new phenomena. For several decades financial analysts have measured the covariance between commodity prices, especially crude oil, and equity indices. But this is the first time I have seen an article illustrating the covariance between a “fun” market for guessing who will become president against a “real” market. Check out the two graphs above, the similarity in shape is striking, including the fact that both continue to rise for about an hour after the debate ended.

In real-time, while the debate was being broadcast, players on Betfair believed the chance Mrs. Clinton will win the election rose by 5 percent. Meanwhile, the price of S&P 500 futures rose by 0.6%, meaning investors (who may be the same speculators who play on Betfair) believed the stock market prices in November were likely to be higher than before the debates started. There was no other surprise economic news that evening, so the debate is the most likely explanation for the surge. Pretty cool.

If the two markets are perfectly correlated (they aren’t) and markets are perfectly efficient (they aren’t), then one can estimate the difference in equity futures market value between the two candidates. If a 5% decrease in likelihood of a Trump win translates to a 0.6% increase in equity futures values, then the difference between Mr. Trump or Mrs. Clinton being elected (a 100% change in probability) results in about a 12% or $1.2 trillion (the total market cap of the S&P 500 is about $10 trillion) change in market value. (Note that I assume perfect correlation between the S&P 500 futures market and the actual market for the stocks used to calculate the index.)

Further, nearly all capital assets (stocks, bonds, commodities, real estate) in the US are now highly correlated. So the total difference is about $24 trillion (assuming total assets in the US are $200 trillion). Ironically, this probably means Donald Trump would be financially better off if he were to lose the election.

****

The other article that caught my eye involves Google Trend data. According to the Washington Post, the phrase “registrarse para votar” was the third highest trending search term the day after the debate was broadcast. The number of searches is about four times higher than in the days prior to the debates (see chart 2). Notice the spike in searches matches a spike in Sep 2012 after the first Obama-Romney debate.

The article says that it is not clear if it was the debate itself that caused the increase or the fact that Google recently introduced Spanish-language voting guides to its automated Knowledge Box, which presumably led to more searches for “registrarse para votar”. (This is the problem with confounding events.)

After a bit of research, I discovered an even more interesting fact. The spike in searches did not stop on Sep 27. Today, on Sep 30, four days after the debates, the volume of searches is 10 times higher than on Sep 27, or a total of 40x higher than before the debate (see chart 3). The two charts are scaled to make the data comparable.

VotarWashPost

Chart 2. Searches for “registrarse para votar” past 5 years to Sep 27. Courtesy of Washington Post and Google Trends

VotarToday

Chart 3. Searches for “registrarse para votar” past 5 years to Sep 30. Courtesy of Google Trends

I wanted to see if the spike was due to the debate or due to the addition of Spanish voter information to the Knowledge Box. To do this, I compared “registrarse para votar” to “register to vote”. The red line in chart 4 shows Google Trend data for “register to vote” scaled so that the bump in Sept 2012 is the same height as in the charts above. I’d say the debate really had an unprecedented effect on interest in voting and the effect was probably bigger for Spanish speaking web users.

VoteToday

Chart 4. Searches for “register to vote” past 5 years to Sep 30. Courtesy of Google Trends

Finally, I wanted to see how the search requests were distributed geographically. The key here is that most Hispanic communities vote Democratic and many states with a large Hispanic population are already blue (such as California, Washington, New Mexico, New Jersey, and New York). The exception is Florida with a large population of Cuban immigrants who tend to vote Republican.

VotarRegionToday

Chart 5. Searches for “registrarse para votar” past 5 years to Sep 30 by county. Courtesy of Google Trends

If you are a supporter of Democrats like Mrs. Clinton, the good news is that a large number of queries are coming from Arizona, and Texas, two states where changes in demographics are slowly turning voting preferences from red to blue.

In Florida, it is not clear which candidate gains from increased number of Spanish-speaking voters. However, since the increase is a result of the debate (during which it was revealed that Mr. Trump had insulted and berated a beauty pageant winner from Venezuela, calling her “miss housekeeping”), I will speculate many newly registered voters are going to be Clinton supporters.

If the Google search trend continues, it may be driven by new reports that Mr. Trump may have violated the US sanctions forbidding business transactions in Cuba. Cuban-Americans searching for information on voter registration after hearing this story are more likely to favor Mrs. Clinton.

by George Taniwaki

LotteChocoPie

Moon pies for cheap. Photo by George Taniwaki

I love moon pies (apparently, I was a southerner in a past life). Surprisingly, they are big in South Korea too (who knew, for history see Wikipedia).

Incidentally, don’t confuse moon pies with moon cakes which are another Asian sweet (which I usually don’t like because of the salty egg flavor).

Anyway, today, I found a really cheap source of my favorite confection. Lotte brand is $3.50 for 335g or 29 cents a pie. Mysteriously, they are hidden next to weird spices in the international food aisle, not prominently displayed with the other cookies in the snack aisle. Perhaps it’s a form of American food protectionism by US cookie makers, Asian segregationist policy or redlining by the store, or the result of some other nativist conspiracy plot.

It’s crazy that a South Korean company can import all the ingredients, process them, ship them back to the U.S., and still be cheaper than US-made cookies. But I don’t care as long as I get my fix of graham cracker, marshmallow, and sugary goodness.

by George Taniwaki

I just returned from a short trip to New York. I have been to the city many times, but not recently. So I took time to go to places that are new since my last visit in 2009.

Cooper Hewitt Smithsonian Design Museum

CooperHewitt

Immersion room, courtesy Cooper Hewitt Smithsonian Design Museum

As a software program manager, the Cooper Hewitt is one of my favorite museums. It recently completed a major renovation (Press Release, Dec 2014). I was looking forward to seeing the redesigned design museum and was not disappointed.

Upon entering the museum, each visitor is given a stylus and a code number. The stylus is a bit bulky but is rugged. The pointed end can be used with large touchscreen monitors (probably Microsoft PixelSense devices since the newer Surface Hub wasn’t released until after the museum opened) scattered around some rooms. Visitors can select images, write text, and draw images on the touchscreens. Visitors can tap the other end of the stylus to the touchscreens to save their work. They can also tap on exhibit signs to save them and get more information for later.

On the second floor is a cubical Immersion Room that contains another large touchscreen monitor. On this one, visitors can select wallcovering patterns from the Cooper Hewitt collection or design their own using the pen. They can save their patterns and project them on the walls of the room. It is a very enjoyable experience to see your pattern fill the room (see photo above).

After your visit, you can go to the Cooper Hewitt website, create an account, enter your code, and review your visit and further explore exhibits that interested you. If you are a developer or tinkerer, check out the Toys section to use the API and to access anonymized visitor data.

Museum of Modern Art

moma_conner_crossroads197663

Crossroads (promotional still) 1976, Courtesy Connor Family Trust

The Museum of Modern Art is not new yet. However, since my last visit, MoMA has announced a major expansion. An increase of 4,600 sq. m (50,000 sq. ft) will add about 17%  of new space the the already large museum. Construction has started, though it hasn’t caused any closure of the current space for now.

The addition is expected to be well integrated with the existing museum. Construction will take over four years to complete (Curbed New York, Jan 2016).

I saw a special exhibit on Bruce Conner (1933-2008) an avant garde painter, sculptor, photographer, and film maker (see photo). The show was organized by the San Francisco Museum of Modern Art. In an ironic twist, I was unable to visit the newly remodeled SFMoMA while I was in SF in April since it was still closed for renovation (see SF Gate, May 2016).

The expansion of MoMA required the demolition of the American Folk Art Museum, which was a lovely bronze-clad building next door to it. (I saw a wonderful special exhibit on quilts during my last visit to New York.) The building is already gone and is now just a hole in the ground. The museum has moved to Columbus Avenue between 65th and 66th Streets.  I didn’t have time to visit it.

9/11 Memorial & Museum

911Memorial04

The north fountain with white rose. Photo by George Taniwaki

The National September 11 Memorial opened in 2014. It honors the victims killed in New York, Washington, DC, and Pennsylvania during of the awful attacks in September, 2001 as well as the people killed in the earlier attack on the World Trade Center in February, 1993.

The memorial consists of two square fountains, each encompassing the footprint of one of the towers. The fountains are surrounded by bronze panels with the names of each victim cut into them. A white rose is placed by each name on that person’s birthday (see photo). Water falls about 10 m (30 ft) into a reflecting pool. From there, it falls into a square hole so deep you cannot see the bottom. The sound of rushing water is emitted from the hole. The scale of the fountains is moving. Even on a busy summer weekend when thousands of tourists are viewing the memorial, there is plenty of space to stand and contemplate.

911MuseumBalcony08P

View from the balcony entering the museum. Photo by George Taniwaki

911MuseumBlueSky04P

View of quote from stairs entering the museum. Photo by George Taniwaki

The 9/11 museum is also enormous and also within the footprint of the towers. The main floor is under the fountain about 18m (60ft) below ground. From the balcony you can see the slurry wall that holds back the Hudson River and a giant remnant of a column from the World Trade Center marked with spray paint (see photo).

An escalator takes you past a quote translated from Virgil’s Aeneid, “No day shall erase you from the memory of time” (see photo). The quote is surrounded by 2,983 watercolor paintings, one for each victim, by Spencer Finch recalling the shade of blue of the sky on the morning of 9/11.

Overall, the museum does a good job of explaining the events leading to the attack and the recovery effort afterwards. One can imagine the difficult task of presenting an evenhanded account in the face of enormous pressure from victim families, first responders, government agencies, donors, and politicians. Nearly every artifact and photo is heavily researched and annotated, which is somewhat chilling. One gets a sense of how invested the survivors are in preserving the memories of the loved ones lost in the attacks.

As a side note, when viewed in context, the use of the Virgil quote above is rather controversial. The “you” refers to the attackers, not the victims, giving it a very different meaning than what was intended (NY Times, Apr 2011). Yet the alternate interpretation is also true. Because of the horror they caused, we will not forget the attackers either.

The Cloisters

MetCloisters

A garden in the Cloisters. Courtesy of Metropolitan Museum of Art

Hudson04P

Panoramic view of the Hudson River and New Jersey. Photo by George Taniwaki

The Cloisters is part of the Metropolitan Museum of Art. It houses artwork and architectural fragments from twelfth to fifteenth century Europe. The building is shaped like a medieval cloister and is located at the top of a hill in Fort Tryon Park in northern Manhattan (see photos).

I’m not a big fan of art from this era, so have never bothered to go all the way up to the Cloisters. But after visiting Florence a few years ago I decided I should make the journey. It was well worth it. I took the subway and walked up the hill. The building is imposing.  The gardens are tranquil and beautiful. And seeing the historical transition in painting from flat to perspective is fascinating.

Dyckman Farmhouse Museum

Dyckman

Irises in bloom. Courtesy of Dyckman Farmhouse Museum

On my way to the Cloisters, I accidentally missed my stop. Rather than wait for a train the other direction, I decided to walk back. On a busy street filled with businesses I suddenly passed by a small garden and walked in. It turns out it was part of the Dyckman Farmhouse Museum. Opened in 1916, the museum is not very large, but is well maintained and reveals some of the history of Manhattan beginning with the Revolutionary War.

Final Notes

When visiting a city, I rarely buy City Pass tickets or their equivalents. The list of venues is fixed and limited. Instead, I just buy tickets in advance directly from each museum I visit. In fact, I just go to each museum first, checked out how long the line is, and if it is too long, then use my phone to buy tickets online. Museums with long lines and that lack online ticket sales don’t get my business.

To get around a strange town, I need more than a map. I need info on the best ways to get around by walking, biking, using public transit, or hailing Uber. Also, I want to compare estimated travel times and costs for each option. I have found two excellent apps to help. They are CityMapper and Transit, both available for iPhone and Android.

by George Taniwaki

NASA recently celebrated the fifteenth anniversary of the launching of the Chandra X-ray Observatory by releasing several new images. One of the images, shown below, is an amazing composite that reveals in exquisite detail the turbulence surrounding the remnants of the Tycho supernova. (Scroll down to Figure 2, then come back.)

Tycho supernova

The scientific name of the Tycho supernova remnant is SN 1572, where SN means supernova and 1572 refers to the year it was first observed. That’s right, over 400 years ago, in November 1572, many people noticed a new bright object in the sky near the constellation Cassiopeia. Reports at the time indicated that it was as bright as Venus (peak magnitude of –4) meaning it was visible during the day.

SN 1572 is called the Tycho supernova because a Danish scientist named Tycho Brahe published a paper detailing his observations. His paper is considered one of the most important in the history of astronomy, and science in the Renaissance.

Tycho_Cas_SN1572

Figure 1. Star map drawn by Tycho Brahe showing position of SN 1572 (labelled I) within the constellation Cassiopeia. Image from Wikipedia

What people at the time didn’t know was that SN 1572 was about 9,000 light years away, meaning it was unimaginably far away. The explosion that caused it happened long ago but the light had just reached the earth.

(Actually, SN 1572 is fairly close to us relative to the size of the Milky Way which is 100,000 light years across, and extremely close relative to the size of the observable universe which is 29 billion light years across. Space is just really unimaginably large.)

What they also didn’t know was that SN 1572 was probably a Type 1a supernova. This type of supernova is common, and has a very specific cause. It starts with a binary star system. Two stars orbit one another very closely. Over time, one of the stars consumes all of its hydrogen and dies out, leaving a carbon-oxygen core. Its gravity causes it to accrete the gas surrounding it until its mass reaches what is called the Chandrasekhar limit and it collapses. The increased pressure causes carbon fusion to start. This results in a runaway reaction, causing the star to explode.

About a supernova remnant

In the 400 years since SN1572 exploded, the debris from it has been flying away at 5,000 km/s (3100 mi/s). It is hard to see this debris. Imagine a large explosion on the earth that occurs at night.

The debris itself doesn’t generate very much light, but it does produce some. Space is not a vacuum. It is a very thin gas. When electrons from the moving debris of the supernova remnant strike a stationary particle, it gives off a photon (which depending on the energy of the collision, is seen as radio waves, microwaves, visible light, UV, or x-rays). This energy also heats up the remaining particles, releasing additional photons, making them detectable with a very sensitive telescope.

About false color images

The Chandra X-ray Observatory was launched in 1999 from the space shuttle Columbia. As the name implies, it can take digital images of objects in the x-ray range of light. Since humans cannot see in this range, images taken in the x-ray range are often color coded in the range from green to blue to purple.

Often, composite images of space objects are created using telescopes designed to capture photons from different wavelengths. For instance, visible light telescopes like the Hubble Space Telescope often have the colors in their images compressed to black and white. Images from infrared telescopes, like the Spitzer Space Telescope, and ground-based radio telescopes are often given a false color range between red to orange.

Pictures please

All right, finally the results. Below is the most detailed image ever of the Tycho supernova remnant. It is a composite created by layering multiple, long-exposure, high-resolution images from the Chandra X-ray Observatory. The press release says, “The outer shock has produced a rapidly moving shell of extremely high-energy electrons (blue), and the reverse shock has heated the expanding debris to millions of degrees (red and green).

“This composite image of the Tycho supernova remnant combines X-ray and infrared observations obtained with NASA’s Chandra X-ray Observatory and Spitzer Space Telescope, respectively, and the Calar Alto observatory, Spain.

“The explosion has left a blazing hot cloud of expanding debris (green and yellow) visible in X-rays. The location of ultra-energetic electrons in the blast’s outer shock wave can also be seen in X-rays (the circular blue line). Newly synthesized dust in the ejected material and heated pre-existing dust from the area around the supernova radiate at infrared wavelengths of 24 microns (red).”

Tycho2014

Figure 2. Tycho supernova remnant composite image released in 2014. Image from NASA

Compare Figure 2 above to an image of the Tycho supernova remnant that NASA released in 2009 using data from observations made in 2003 shown below. Notice the lack of details. Also notice the large number of stars in the background, some even shining through the dust of the explosion. Apparently, the image above has been modified to eliminate most of these distractions.

These two images dated only a few years apart reveal what is likely remarkable advances in software for manipulating space images. I say that because the hardware in the telescopes themselves, such as optics, detectors, and transmitters probably have not changed much since launch. Thus, any improvements in resolution and contrast between the two images is a result of better capabilities of the software used to process images after the raw data is collected.

A New View of Tycho's Supernova Remnant

Figure 3. Tycho supernova remnant composite image release in 2009. Image from NASA