Keeping the Axe Sharp

"To chop a tree quickly, spend twice the time sharpening your axe." --Chinese Proverb

I first heard the above proverb in the form of a fable.  In the fable, two boys were given axes and told to each chop down a tree.  The first boy sets right off to the tree and begins to work.  The second boy, spends the extra time to sharpen the axe and make sure his tool is in fine working order.  As the first boy continues to labour, the second boy quickly brings down the tree.  The morale of the story keep your tool in good working order.

I very rarely get to chop down trees, although I love to chop wood, but my axe is my mind.  The period before my PhD qualifying exams was probably when my mind was at its sharpest.  The razor edge of my mind could easily do complex Laplace and Fourier transforms, solve chemical equilibrium problems, calculate escape velocity and find the efficiency of a jet engine.  Sadly since then my mind's razor edge has started to dull.  It was a process that accelerated once I left grad school.  Although I have been working full time and solving really hard engineering problems, I haven't had to do the same kind of rigorous mental work required during an exam.  I fear the atrophy and would like to return my mind to its former glory.

I have started to challenge my self to learn new skills: financial analysis and forecasting, programming in other languages (I am a big fan of codecademy) and tinkering with my Arduino.  I have recently found a new forum for sharpening my mind: Project Euler.  From the Project Euler website:

"Project Euler is a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. Although mathematics will help you arrive at elegant and efficient methods, the use of a computer and programming skills will be required to solve most problems."

So far I am up to question 11 and have learned lots of new math (especially sieves like the sieve of Atkin and the sieve of Eratosthenes).  If you are looking for a math/programming challenge or a way to stay sharp I highly recommend it.  

Linear Trend

Often in my career I have been asked to mine data and find underlying trends.  The hope of the requester, usually a manager or Professor when in grad school, was to see a nice linear trend.  They would recommend I plot X versus Y and hopefully I would see the familiar linear relationship of y = mx + b.  When that failed to produce the trend they wanted, they would start having me non-dimensional the variables (even if the variables were not non-dimensionalized appropriately).  For example they would say "Divide X by Z and plot on a log scale."  Usually the dimensions for X divided by Z would make no sense.  I have created a nice little plot that summarizes these experiences (click on the image to enlarge).

 

I created the plot in Python using Matplotlib (see here for an example).

Advice to Startups

I just finished watching a talk by David Heineimeier Hansson, who is the creator of Ruby on Rails and a partner at 37signals.  The talk was part of Stanford's Entrepreneurship series and focused on Mr. Hansson's advice for starting a company and running a business

I was very impressed by Mr. Hansson's talk.  It has compelled me to download his book Rework to my Kindle.  Mr. Hansson and I share many sentiments about business: meetings can be helpful but are generally a waste of time; revenue doesn't matter as much as profit; quality of time working matters more than quantity; planning is guessing; and most importantly, you can do a lot with a small team.

Watching this video also got my entrepreneurship blood percolating -- both my parents were/are entrepreneurs.  I have often thought about starting my own venture, but so far I have not been able to get any traction. 

Was a PhD worth it?

I came across this article on The Economist that discusses the disadvantages of pursuing a PhD.  The last paragraph particularly resonated with me (emphasis mine):

Many of those who embark on a PhD are the smartest in their class and will have been the best at everything they have done. They will have amassed awards and prizes. As this year's new crop of graduate students bounce into their research, few will be willing to accept that the system they are entering could be designed for the benefit of others, that even hard work and brilliance may well not be enough to succeed, and that they would be better off doing something else. They might use their research skills to look harder at the lot of the disposable academic. Someone should write a thesis about that.

For me, I think the PhD was NOT worth it.  After my undergraduate degree, I started to work at Pratt & Whitney in the Combustion Department.  I was something of an anomaly in the Combustion Department: very few people "only" had their bachelor's.  The majority had either a Masters or a PhD.  It seemed to me that the way to advance and work on the most interesting projects was to get a PhD.  My boss at Pratt had a PhD.  My boss's boss had a PhD and an MBA.  Clearly, to advance I needed more education.

My decision to pursue a PhD was not straightforward.  I was considering either a PhD or an MBA.  Both had merits.  In the end, I obviously chose the PhD.  Jack Welsh the famous CEO of GE had a PhD in Chemical Engineering.  I reasoned that a PhD would not preclude corporate advancement and it left the "door open" to an academic job. 

So I left Pratt and finished a Masters in Mechanical Engineering at the University of Toronto, followed by a PhD in Aerospace Engineering at Purdue University.  I won a couple fellowships along the way, published a handful of papers, all the while maintaining a 4.0.  I should also point out that my PhD work was sponsored by a Fortune 500 company.  Now I have graduated and I have the exact same job I had at Pratt but with a different company and for a little more money.

I knew the PhD was a poor return on investment, and that the post-PhD salaries were paltry compared to post-MBA salaries.  I reconciled this reduction in earning power with the fact that I would perform interesting work (hopefully an R&D based career).  This did not happen. 

A few of the guys at Pratt who had PhDs warned me not to pursue a PhD.  I thought they were unjustly bitter, but now at the end of the road I see clearly.  Corporations are run by MBAs and most PhDs are under-valued and under-utilized.  I also think the price of an MBA is over-inflated and most of the subject material can be learned through independent study (Michael Burry provides a good example).

For those young engineers looking to get a second degree, I would discourage them from pursuing a PhD (unless it is in Computer Science or Computer Engineering) and look to other degrees.  Despite its high price, the MBA still offers a substantial return on investment.  

The Generalist

I stumbled across this blog post by a fellow named Noah Lorang who works over at 37signals.  Noah works as a "data scientist" but was educated as a mechanical engineer (just like yours truly).  Noah contends that "...mechanical engineering programs are really about teaching you how to think about solving problems."  He gives as an example a process that he learnt for solving thermodynamic problems.  The process can be generalized to logically solve any problem. 

I fully agree with Noah and I think this blog post is excellent.  Mechanical engineering is a very general degree.  During my education, I took courses in the bedrocks of mechanical engineering like dynamics and statics, but also courses in computer programming, chemistry, digital logic and micro-processors, electric machinery, quantum mechanics, rocket propulsion, etc...  A very diverse list.  What my education taught me was how to solve problems.  Even if I have no background in the problem field, I can learn the necessary material and tackle the problem.  I also think that my broad education allows me to have a fast learning curve for any type of problem. 

Mechanical engineering might not have the sex appeal as computer or nano engineering, but I think mechanical engineering can provide any student with the background to be successful in any field. 

Raring Ringtail

Just installed Raring Ringtail (Ubuntu 13.04) on my laptop.  I have been using Ubuntu at home exclusively for a little over a year.  I started with Precise Pangolin (12.04 LTS) and then upgraded to Quantal Quetzal (12.10).  If you are comfortable with Mac OS X you can pretty easily make the transition to an GNU/Linux system especially Ubuntu.  It is pretty user friendly.  There is a small learning curve -- about the same as going from Windows to Mac.  You can download Ubuntu from: http://www.ubuntu.com/download

Once you install I would recommend immediately running this code from the terminal:
sudo apt-get update

I think there is enough Free and Open Source programs that everyone can now use a GNU/Linux distro.  I use LibreOffice as a replacement for MS Office.  I do have Matlab, but have been using Python with NumPy and SciPy more (just as good and free).  For word processor I like LaTeX with Texmaker editor.  Here is a quick desktop screen-shot.  I use Conky to display real time system info.  I also have a terminal open.

Here is also my conky file (put into ~/.conkyrc)

# UBUNTU-CONKY # # Create own window instead of using desktop (required in nautilus) own_window yes own_window_type normal #own_window_transparent yes own_window_argb_visual yes own_window_argb_value 0 own_window_hints undecorated,below,sticky,skip_taskbar,skip_pager # Use double buffering (reduces flicker, may not work for everyone) double_buffer yes # fiddle with window use_spacer right use_xft yes # Update interval in seconds update_interval 3.0 # Minimum size of text area minimum_size 200 800 # Draw shades? draw_shades no # Text stuff draw_outline no # amplifies text if yes draw_borders no font arial uppercase no # set to yes if you want all text to be in uppercase # Stippled borders? stippled_borders 1 # border margins border_margin 1 # border width border_width 1 # Default colors and also border colors, grey90 == #e5e5e5 default_color grey own_window_colour brown own_window_transparent yes # Text alignment, other possible values are commented #alignment top_left alignment top_right #alignment bottom_left #alignment bottom_right # Gap between borders of screen and text gap_x 10 gap_y 10 # number of cpu samples to average # set to 1 to disable averaging cpu_avg_samples 1 text_buffer_size 1024 # stuff after ‘TEXT’ will be formatted on screen TEXT $color${font arial:size=9} $nodename@$sysname $kernel on $machine${font arial:size=8} Uptime: $alignr$uptime Battery ${battery_bar 6 BAT0} ${color orange}CPU $color #${freq}MHz${alignr}Load: ${loadavg} Load: ${loadavg} ${alignr}Proc: $processes ($running_processes run) ${alignr}${loadgraph 20,250 e5e5e5 F1AA0E} CPU Total:${color} ${cpu cpu0}% ${color}${alignr}Temp:${color} ${acpitemp} ${alignr}${cpugraph 0 20,250 e5e5e5 F1AA0E -l} Core one: ${color}${cpu cpu1}% ${alignr} Core two: ${color}${cpu cpu2}% ${cpugraph cpu1 10,120 e5e5e5 F1AA0E -l}${alignr}${cpugraph cpu2 10,120 e5e5e5 F1AA0E -l} Core three: ${color}${cpu cpu3}% ${alignr} Core four: ${color}${cpu cpu4}% ${cpugraph cpu3 10,120 e5e5e5 F1AA0E -l}${alignr}${cpugraph cpu4 10,120 e5e5e5 F1AA0E -l} NAME${alignr}PID CPU% MEM% ${top name 1}${alignr}${top pid 1} ${top cpu 1} ${top mem 1} ${top name 2}${alignr}${top pid 2} ${top cpu 2} ${top mem 2} ${top name 3}${alignr}${top pid 3} ${top cpu 3} ${top mem 3} ${top name 4}${alignr}${top pid 4} ${top cpu 4} ${top mem 4} ${color orange}MEMORY / DISK $color Total: ${color}${memmax} ${alignr} Free: ${color}${memfree} RAM: $memperc% #${alignr}Swap: $swapperc% ${memgraph 20,250 e5e5e5 F1AA0E} #${alignr} ${swapbar 20,120 } #root: ${fs_used_perc /}% ${fs_bar 6 /}$color home: ${fs_used_perc /home/wlamont}% ${fs_bar 6 /home/wlamont}$color ${color orange}WIFI (${addr wlan0}) $color ${wireless_essid wlan0} ${wireless_link_bar 6 wlan0} Down: $color${downspeed wlan0} k/s ${alignr}Up: ${upspeed wlan0} k/s ${downspeedgraph wlan0 20,120 e5e5e5 F1AA0E} ${alignr}${upspeedgraph wlan0 20,120 e5e5e5 F1AA0E}$color Total: ${totaldown wlan0} ${alignr}Total: ${totalup wlan0} Inbound: ${tcp_portmon 1 32767 count} Outbound: ${tcp_portmon 32768 61000 count}${alignr}Total: ${tcp_portmon 1 65535 count} #${color orange}LOGGING $color #${font arial:size=7}${execi 30 tail -n 10 /var/log/messages | fold -w45}

The Beginning

My old computer passion has re-ignited and I have become deeply interested in quantum computing.  This blog will mainly share my thoughts and work in this field.  However, I will occassionally post other material that I think is of interest or noteworthy. 

I have purchased a few books including Quantum Computing Since Democritus by Scott Aaronson (his blog is here) and Quantum Computing for Computer Scientists by Yanofsky and Mannucci.  I hope to post a review of these books soon.