Quantum computing is no longer just a sci-fi trope. You can already access IBM’s open source computer from a web browser, and it won’t be long before quantum processors are in our homes.
Wise, future-thinking minds should stay apprised of this development. To that end, this article will answer the question: how do I learn about quantum computing?
First, we’ll start with a brief history of computing. Then, we’ll talk about where the current authorities on quantum computing find themselves positioned. Finally, we’ll offer you some tools to get started actually learning about how quantum programming is applied.
Feel free to scroll down to the section titled “Tools for Quantum Programmers” to access those immediately.
People often have some poor ideas of what computing will look like in the future. As proof, this quote from Howard H. Aiken, a contributing engineer in the Mark I computer, in 1947:
“Only six electronic digital computers would be required to satisfy the computing needs of the entire United States.”
Today, in a time where most households have six or more computational devices, Aiken’s quote is now little more than a cute sentiment.
However, to each time its own. What we mean is, our predictions for quantum computing might also fall well short.Learning #AI and #QuantumComputing is key to being relevant in future programming.Click To Tweet
Silicon Supercomputers are Not Enough
Built by IBM under the name ASCC, the Mark I was an electromechanical calculator that filled up an entire room (51 ft long and 8 ft high). With 500 miles of wires and thousands of dial switches, storage wheels, and other mechanical components, it was a true computational behemoth of its time.
Aiken’s 5-ton device, which could perform basic MDAS operations (multiplication, division, addition, and subtraction), was, at the time, “the world’s greatest calculating machine”, and dubbed the “superbrain”.
Today, the smallest and least powerful smartphone is thousands of times more powerful than the Mark I.
In fact, there are supercomputing systems capable of processing data with speeds in the petaFLOP range.
FLOP, or “floating-point operations per second”, is a measurement unit for supercomputing speed which indicates the number of operations a computer can perform in one second. One petaFLOP means the computer can process data at one quadrillion (one thousand trillion) calculations per a second.
The human brain, for example, is an organic super-calculating machine with a processing speed estimated to range between 38 petaFLOPS and 1 exaFLOPS, or, one-billion-trillion FLOPS.
There are many other behemoth supercomputers. Many belong to big corporations like Google, and universities like MIT, which serve a number of different research utilities.
Supercomputers are regular, silicone-based, binary computers scaled up in size so they can process larger amounts of data at faster speeds. Although computers are getting more and more powerful, not even room-sized super-calculating systems can solve some of the world’s most complex mathematical problems
The world’s need for computing power has inflated for many reasons. First, the digital revolution, and second, the proliferation of personal computers. Now, the emergence of the Internet of Things also raises the stakes.
But, what underlies all of this? The widespread collection of data, or Big Data, as some call it.
Using this mountain of data we’ve assembled over the digital age requires automatic systems and hardware with the ability to handing trillions of concurrent problems at once. This is where quantum processing shines.
The Quantum Frontier: Atom-Sized Transistors
In 1965, Intel’s Gordon Moore observed that the average number of transistors on a microchip was doubling every year. Then, in 1975, he adjusted the time to two years.
Moore’s law has stood the test of time so far. For over 50 years, thanks to the miniaturization of computer chips, the processing power of computers has grown exponentially. This has enabled a number of major technological advancements and is the driving factor behind the tech-centric society we live in today.
However, Moore’s law and miniaturization may be reaching their pinnacle. In the simplest of terms, we can’t keep shrinking electronic components forever.
In 2016, after nearly five decades of fulfilling Moore’s prophecy, Intel announced that it would slow down the pace at which it releases new microchips.
As Intel’s transistors get into the nanoscale (10 nanometers), it’s getting harder for the company to keep the miniaturization process going in a cost-effective way.
This may seem like it would spell the end of conventional microchip processes, and it will.
What looks like a limitation is actually a motive for computer companies to seek alternatives to keep their production momentum going.
Theoretically, silicon transistors can get smaller and smaller until about the size of an atom. From there, we enter the realm of quantum physics with all its spooky effects that govern the microscopic world.
Engineers are beginning to investigate new types of processors that use atoms as transistors and leverage the power of quantum physics to process large amounts of data that not even classical silicon-based supercomputers can handle.
This is where we are heading: the era of quantum computers.
Seeking Supremacy in “Quantum Supremacy”
According to the rules of quantum mechanics, an atom-sized transistor is a superposition of states that can take the value 0, 1, or both at the same time.
Since the early 90s, quantum computing has been the subject of intense research with scientists being able to design basic quantum processors. However, this has only been for very specific and limited scientific research purposes.
Major tech companies headed by IBM, Google, Microsoft, and Nokia Bell Labs as well as other startups like D-Wave Systems all have quantum computers roadmaps with varying goals, timelines, and development.
D-Wave Systems, Inc. has been making waves recently with its quantum computers. Although, some experts argue that its systems might not be quite as “quantum” as the Canadian startup lead us to believe.
However, these D-Wave computers have been adopted by several organizations, like NASA, tech companies, and a number of research centers.
As it stands, we’re getting closer and closer to commercial desktop quantum computers. Until one of the above contenders announces the much-awaited “quantum supremacy” breakthrough, the technical and economical prospects seem huge.
In November of last year, Google, along with the University of California Santa Barbara, revealed its “Blueprint for Quantum Supremacy”, with the aim of demonstrating, for the first time, a 49-Qubit processor within the next few months.
If Google doesn’t get beaten at the post by a Russian startup, which claims to have built a quantum machine that runs on 51 “cold atoms”, this could be the breakthrough we’ve all been waiting for.
Regardless of who’s first past the post, everything seems to indicate that there are big things ahead for quantum computing in the next few years.
Tools for Quantum Programmers
Where the Opportunities in Quantum Computing Lie
If D-Wave, Google, IBM and others are covering the hardware aspect of quantum computers, the same can’t be said about software and applications.
If you already have a background in software development, this is where a serious opportunity has arisen.
Of course, if you have a solid knowledge of both computer science and quantum mechanics, you can consider a career in hardware development.
When it comes to the future world of quantum computing, it’s really in the software practical applications department that there will be the most positions to fill.
Luckily, D-Wave already thought of this. To help programmers with no background in quantum physics develop quantum applications for D-Wave systems, the startup has made a software tool opensource called Qbsolv.
Prerequisites for Quantum Programming
You don’t need to channel your inner Stephen Hawking and tap into the mathematical ether, but a good understanding of advanced mathematics and quantum physics will be necessary to follow this field.
Have a good understanding of these concepts, at the very least:
- Quantum mechanics (entanglement, multiple body systems, superposition, and more)
- Computational physics including knowledge of integer factorization and algorithms
- Fourier analysis
- Complex Numbers
- Quantum field theory
Quantum Computing Resources
The Quantum Macro Assembler (QMASM) is another tool from D-Wave that allows developers to work on quantum programs without having to worry about hardware.
With Qbsolv and QMASM, developers have just enough freedom to try their hands at quantum algorithms, which once built, must be tested. For this, ideally, you’d want access to one of the rare D-Wave quantum processors currently available.
If that seems unlikely, you still can test your quantum programs using a free D-Wave simulator that enables you to run the program on your own processor.
There are also some other free online tools that cater to quantum programmers.
IBM has also made an extensive library of learning resources openly available, called the IBM Q Experience.
The company also has an opensource platform, QISKit, which gives access to a “small” 5-qubit quantum chip, so developers can run and test their quantum algorithms.
If you’re not a fully-fledged programmer and can’t work on such tools yet, you may want to check one of the several massive open online courses from prestigious universities like MIT, Berkeley, and others.
Feel free to share any other public resources you know about that we didn’t mention. Good luck on your quantum computing journey!