13 July 2016, by Chris Arnott
This post explains the solutions to Question 1 of our speed coding 2016 competition. If you haven’t yet read the question, head back and have a go now.
6 July 2016, by Chris Arnott
Here’s the 4th and final question from our last speed coding competition. This is a long and tricky one, so make sure you’ve put some time aside if you’re planning to try and solve it.
29 June 2016, by Chris Arnott
In the programming world we like an interesting challenge, and one of the more challenging concepts in our profession is that of functional languages. With more functional languages gaining lots of traction (Softwire have done several projects in python and Scala, as well as other functional oriented languages) there are some interesting projects going on.
20 April 2016, by Chris Arnott
Here’s the third of our speed coding questions.
13 April 2016, by Chris Arnott
Here’s question 2 from our recent speed coding competition. See how quickly you can solve it.
6 April 2016, by Chris Arnott
Here’s the first question from our speed coding competition 2016. We’ve already held the event, so there are no prizes, but if you want to play along at home, see how quickly you can solve the challenge.
30 March 2016, by Chris Arnott
In case you didn’t hear through our twitter or facebook accounts, we recently held our 2016 speed coding competition. Questions were devised by the last competition’s runner-up Rupert Wood, with help from John Ginger.
The format of the evening was:
Question 1 – 20 minutes
Question 2 – 30 minutes
Question 3 – 40 minutes
Pizza – 30 minutes
Question 4 – 1 hour
In the upcoming series of posts, we’ll be releasing the questions, quickest answers as well as some hints and tips on interesting techniques that people took in their solutions.
30 March 2016, by Chris Arnott
So you want to move your application to the cloud? Well is that really the right thing to be doing? There are lots of pros and cons for using cloud services rather than physical servers. In this blog post we’ll discuss some of the different aspects to consider before taking the leap.
10 February 2016, by Chris Arnott
It is very common to write ToDos in code. This makes sense. You’re working on a piece of functionality and suddenly remember something relevant, but slightly off topic, which needs to be done. So you add a ToDo. Brilliant, you’ve successfully not shaved any yaks.
But when will you actually get around to finishing off the ToDo? How urgent is it? Will you remember that the ToDo is there when you do get around to implementing that extra functionality?
11 November 2015, by Chris Arnott
How do they work?
Hopefully you are already familiar with the fundamentals of a classical computer. You take a load of 1’s and 0’s and combine them using logic gates to do calculations, represent data, etc. Quantum computers take quantum states and use quantum gates to act upon the data. The result can then be read to generate a classical value.
The difference between a normal bit (1 or 0) and a quantum bit, is that the quantum bit is a superposition of both 1 and 0 at the same time. When reading the value of a quantum bit there’s a possibility of getting either 1 or 0, with certain probabilities. It follows from this that classical states are also quantum states, where the probabilities are 1 and 0 of each of the two states.
Why is this useful? Well, if you consider a simple function
f(x), in a classical system, if you want to find out if
f(0) = f(1), you will need to put both 1 and 0 into the function, measure the output and see if they are the same. However, in a quantum system, x can be a superposition of both 0 and 1. This means that the output of the gate can indicate whether the
f(0) = f(1) from only one application of the function. The proof of this is Deutsh’s Algorithm, which is well worth reading about further if you would like to learn more about this.
What can they do?
The above is great, but what practical applications does this have? Well, it turns out there are certain classes of problems that quantum computers are able to solve more quickly than classical problems.
- Deutsh’s Algorithm (above)
- Period finding. Which is the ability to to find the period,
a, of a periodic function – one that satisfies
f(x) = f(x+a)
- Shor’s Algorithm. Which is the ability to find factors of a non-prime integer.
Those of you who are up to date on your security algorithms will know that RSA encryption is based on how hard it is to find factors of large non-primes. This means that a quantum computer would be able to break many modern security systems. Fortunately, the dawn of any quantum age will result in new techniques of security, so all is not lost.
An interesting story of note is that recently security experts have been warning about “Capture now, decrypt later“. This is a method where hackers capture encrypted traffic today, and intend on decrypting it years later when decryption time will be much faster.
Where can I get one?
While technically available, you’ll need a great deal of money, as commercial quantum computers are expensive. In order to build a quantum computer, you need large entangled states (for your input), states that do not interact with the environment (to reduce noise in the computations) and the ability to manipulate and measure individual systems. Common methods for achieving this are:
- Ion traps, which use electron energy levels as the quantum bits. The downside of this method is that interaction between atoms is difficult to control and slow.
- Linear optics, which use polarization (or position) of photons. Unfortunately, it is difficult to generate single photons and detectors often struggle to measure such low levels of light (which can distort results).
- Atoms in an optical lattice, which uses sublevels of neutral atoms as quantum bits. The difficulty of this method is measuring individual quantum bits.
If you really do want to get a quantum computer without doing this yourself, D-Wave might be able to sell you one. The D-Wave Two has 512 qbits, but can only solve very specific quantum problems.
When discussing the abilities of quantum computers, I mentioned that they break many common security practices. Fortunately all is not lost; quantum computers are designed to solve very specific problems, and many brilliant security researchers have come up with alternative methods of keeping our data safe that they can’t break.
The core idea is to make a problem that’s difficult to solve for both classical and quantum computers, for example:
- Lattice based cryptography uses a sequence of points in a high dimensional space. A message is then represented by the distance to one of those points. This is difficult to calculate unless you have the required secret key.
- McEliece encryption uses vectors to encrypt messages with intentional errors. The decryption algorithm then uses the inverse of parts of the public key to correct the errors inserted and calculate the message that was encrypted.
Has this piqued your interest in post-quantum encryption? If you’re interested to learn more, a good place to start would be investigating the options listed on wikipedia.