Let’s see how good of a programmer you are. What do you think will happen when these very simple Java methods are executed?

public static void main(String[] args) {

    int i = 1;

    System.out.println(1);

    while ( i > 0)

        i++;

System.out.println(i);

}

Apologies for the last few months of inactivity — as it turns out, getting to graduation was a long and arduous process. However, now that I have received that elusive B.S. of Computer Science, I suddenly find myself with much more time to update the blog!

Keep your eyes peeled, ladies and gents, as there will be much more to come. For all those who have started following already, thanks! I’ll be sure to pique your curiosity shortly (hopefully starting today, after a proof-reading!). If you like the blog, be sure to tell a friend or two, or just drop a comment telling me what you want to see more of.

Some things I’ve been thinking I’ll write on shortly:

1. The mind-bending aspects and implications of Relativity.
2. Quantum Mechanics and time-traveling quantons interfering with themselves.
3. Whatever happened to that faster-than-light neutrinos story?
4. The very latest in the future of gesture-based computing.
5. Nature’s most interesting paradoxes.
6. …and of course more on the current big stories in technology and computer science.

Let me know what you guys are interested in reading about first.

Hey everyone! Sorry for the pretty much dead interim. Now that finals are past, I can get back to regularly updating! Today, though, I thought I’d do a little piece on understanding the basics behind the future of computation, quantum computing. So maybe you’ve heard of it before, and maybe not. Either way, you’ll be fine to read this summarization.

Quantum Computing is the concept of combining computation as we know it now with the mysteries of quantum mechanics, a field well known for its mind-shattering ability to defy everything reasonable. Let’s start with the basics about how information has, is, and will be stored:

• In the old days, as I have written about before, computers utilized vacuum tubes to hold minute electronic charges (those being either 0 or 1). These charges were called bits. The vacuum tubes proved to be highly unreliable and rather unwieldy, so gradually developments were made until the invention of…
• Silicon chips. In today’s modern electronic silicon-chip based computing, we have shrunk the vacuum tubes down into small components of electronic logic, microscopic in size. Though they are no longer known as vacuum tubes, they retained the name of bits. Again, these bits held a charge of either 0 or 1. These will likely remain the modern standard until we research more about…
• Quantum bits (also known as qubits). A qubit is highly unusual compared to just a regular bit. You see, qubits possess some strange qualities — namely that instead of holding just a charge of 0 or 1, they hold both at the same time. Wait, what!?!

Yes, you heard right. Qubits are specially manufactured to harness the shall we say unpredictable nature of electrons. In case you didn’t know, electrons behave in weird ways, and when I say weird, I really mean it. An electron will behave differently based on whether or not it is being observed (i.e. the famed double-slit experiment showed that electrons behave like a particle when you observe them, and behave like a wave when you don’t!).

A qubit is thus a way to represent all possibilities instantly. So hypothetically speaking, if I had 10 bits vs. 10 qubits…

• 10 bits = 2^10 = 1024 possible values. However, as each bit must be either a 0 or a 1, these 10 bits can only represent one value at a time.
• 10 qubits = 2^10 = 1024 possible values. However, as each bit is both a 0 and a 1 at the same time, these 10 qubits represent all 1024 values at the same time.

It really blows my mind to think about it. Basically, what this means for the future of computation is that utilizing a quantum algorithm, we can solve problems (i.e. traveling salesman problem) that right now might take us more time than the universe has left to exist nearly instantaneously! It’s a show-stopper, really. Right now, from what I understand, scientists are still hard at work trying to develop better qubits, and have only chained together 8 qubits at max. Keep your eyes peeled on this subject, as I have little doubt that in 15-20 years, quantum computing will absolutely become the standard of computing.

You’ll be able to put computers smaller than the tip of a pencil that need nearly no power in anything, and they’ll be vastly more powerful than the largest and fastest super-computers of today. If that doesn’t blow your mind, I don’t know what will!

Did you ever wonder where the term ‘bug’ came from, in relation to computers? Why do we say when something goes wrong in a computer, it is a bug? Well, here’s your answer:

What you are looking at is the first documented case of a computer bug. See, back in 1947 scientists working on the Mark II computer noticed that the results they were getting weren’t quite right (for example, maybe they add 2+2 and get -4). These were the days before silicon-based chipsets. Computers were composed of tiny vacuum tubes which contained electrical charges (you can think of them as the old-school ‘bit’ unit, where 1 means charged and 0 means uncharged).

After a search through the computer room (yes, the computer was a room), they finally unearthed this specimen of moth that had evidently crawled into one of the tubes and short-circuited it, producing the given wonky results.

Pretty strange, but I find it fascinating!

- Source

So maybe you’ve heard people chattering online sometime about a famous and as of yet unsolved major computer science problem. I’m talking about P vs. NP of course! But have you ever wondered what it means, if only those techno geeks could turn it down a few notches for the average layman?

You don’t need to know this necessarily, but P stands for Polynomial Time and NP stands for Non-Deterministic Polynomial Time. Don’t worry about what those mean for now.

Here’s a simple example of the meaning of NP. I give you a stack of plates containing one million plates, and ask you the following: is there a plate, which, if you turn it over has a smiley face on it? Note that I do not tell you if such a plate exists. Currently, the only known way of solving this problem is the following: take a plate, turn it over, and see if there’s a smiley face. If there is, then your done, and if not, on to the next plate.

Now here’s a definition of the meaning of P: I give you a single plate, and ask you “does it have a smiley face on the bottom of it?” All you do is simply turn it over and examine. It’s a simple check, as all you have to do is that little flip, and you’re done with a definitive “yes there’s a smiley face” or “no, there’s no smiley face”.

The P vs. NP problem is basically asking that if we can check a solution to a problem quickly (i.e. flipping over the plate), is there also a quick solution to the million-plates problem? Mathematically speaking, if so then we would say that the set of functions P is a subset of NP, and if not, the set of functions P is a distinct set from NP.

As of yet, we don’t know. The best minds in mathematics and computer research still can’t quite come up with a formal proof either way (though there are often attempts which later become discredited).

What would the ramifications be?

Well, they’d be enormous. If we could find even just one algorithm to show that, yes, there is also a quick-solution to the million-plates problem, then for all NP problems (of which there are tons affecting your daily life), there is a quick solution.

Let me know if any of y’all out there would want some more clarification or for me to go in-depth on the subject.