With the computer industry now struggling to adhere to Moore’s law, it is clear we are reaching the limits of microelectronics. Today’s silicon transistors are just 70 silicon atoms wide — the atomic composition of nature is imposing a limit on how small we can go. With the computational industry bound to reach a phase transition, only one question remains: what’s next?

Quantum.

But what is quantum? It’s the study of reality on an incomprehensibly tiny scale — working with single atoms, molecules, photons, and the things they are comprised of. As it turns out, the world works completely differently ‘down there’. “Quantum technologies” is the exploitation of these effects to design cool new ‘gadgets’ and rethink computer logic.

Most of us have heard of quantum computers, here and there, in the occasional news headline, but the promises of quantum technologies are abundant, interesting, and span way beyond quantum computing. In this article, we’ll go over a few flavors of quantum technologies that promise to perturb the blockchain industry, in particular– an enumeration of the main players, if you will. In Part 2 of the quantum article series, we’ll look at the caveats and take an overview of what the blockchain community’s stance is on embracing these changes.

So let’s start by addressing the elephant in the room:

Quantum computers

What? Computational architecture based on qubits (quantum bits) instead of bits. When? Expect fully working useful machines in anywhere between 5 to 25 years.

Quantum bits, or qubits, differ from bits mainly in that they can exist in a superposition of their two extremal values, 0 and 1. Once we measure the qubit, its state collapses to either 0 or 1. The same is true for groups of qubits: e.g. two qubits can exist anywhere between the 00, 01, 10 and 11 states. When measured, they also collapse to one of these four so-called basis states.

Using these two effects — superposition and wave function collapse (due to measurement) — to create useful quantum algorithms is all but trivial. It took almost 70 years from the formulation of quantum mechanics (cca. 1926) to conceptualizing the first useful quantum algorithm in 1994, Shor’s factoring algorithm. This breakthrough algorithm does just what it says: it factorizes numbers. For example, input 15 and the outputs are 3 and 5. Of course, it’s more impressive if it is tasked with figuring out the prime factors of 878,230,356,607 = 6,700,417 * 131,071.

The image is only illustrative: for the numbers presented here, classical computers also do the job. It’s only when we get to huge numbers (numbers with over 100 digits or so) that classical computers start struggling.

The astounding thing is that this problem is so hard for classical computers, that we’re currently betting all our money and national security on the assumption that no-one can factorize very large integers quickly. We make this ‘bet’ by using factorization as the basis of our cryptography — i.e. we encode our secret information (e.g. passwords), before sending it to another party (e.g. a bank) in such a way that the only way for a third party (e.g. a thief) to decode it is if they can factorize large numbers.

So, the first person to produce a working quantum computer could become the richest in the world, quickly gaining access to everyone’s online bank accounts and all kinds of government and corporate secrets?

Yes.

Unless we react in time by changing our approach to cryptography to something more quantum resistant, leading us to our next point:

Quantum cryptography

What? Cryptography, using qubits, which is so strong that not even quantum computers can break it. When? Now!

Classical cryptography: the public message “f5a23be012”, which everyone could see, is useless without the decrypting algorithm.

Cryptography is the art of transforming a secret message into a public message, such that only you and the person you want to send the message to can extract the secret from the public message. When you submit your password during a login process, before going to, for example, your bank, that information is directed through your telecom company, and possibly anyone exploiting one of a number of security issues present in today’s communication systems. So, basically, you should assume that the message you actually send is viewable by anyone/everyone. Ideally, this message carries your private message in an encrypted manner. As we saw before, quantum computers will, in future, be able to decrypt this encoding in no time using Shor’s factoring algorithm.

You see, classical cryptography typically relies on two parties encoding and decoding their messages with some function that is easy to compute, but hard to invert without some additional information; so-called ‘trapdoor’ functions.

Quantum cryptography, on the other hand, allows you to encode your information in such a way that no-one can decode it. This can be done by exploiting quantum entanglement, which comes about by having two distant qubits in a superposition of the basis states, e.g. a superposition of 00 and 11 states. At this point, it is undetermined which of these two states the system is in. Upon measuring one qubit, the superposition collapses, and you get either a 0 or a 1 on your side, each with a 50% probability. Let’s say you happen to get the result 0. Then you know that the other person’s qubit must also be 0, since your joint state could only be either 00 or 11. In the other 50% of cases, you both end up with 1. This is basically equivalent to having a pair of magic coins. When flipping a single coin you get a random outcome but when you and your friend both flip your coins, you will always get exactly the same results as each other.

When measuring a pair of qubits in the (00 or 11) state, the two parties end up either both having 0, or both having 1, each with 50% chance. This process is repeated many times to produce a shared secret key.

These quantum correlations are much stronger than anything that can be achieved classically. We use these correlations to establish a secret key between the two parties who want to transmit a message. We just repeat the above procedure many times and both parties write down the bitstring they get. By the laws of nature, only the two parties will have access to these secret keys, and both will be the same. Using these keys, they can then encode and decode any message they wish, using one of the oldest and most secure techniques of cryptography, the one-time pad.

Quantum cryptography is as secure as it gets in terms of cryptography and the good news is that, unlike quantum computers, it’s already here and working. In fact, there are a handful of companies selling plug-and-play quantum cryptography systems working using the optical fibers that are anyway a part of today’s internet infrastructure. Yet, the conversion to quantum cryptography has some practical obstacles, such as the cost and achieved bitrate of communication. This motivates the research of non-quantum cryptography schemes which are resistant to quantum computers. Some of these so-called ‘post-quantum’ cryptography protocols seem to be promising candidates for protecting us from the power of quantum computers, but still there is some uncertainty shrouding the topic. More on this in the our next blogpost in this series. As for now, let’s move on to…

Other quantum technologies

What? Quantum optimization, quantum simulators, quantum measurement enhancing, … When? Now — 15 years

While the above-mentioned results of decades of quantum research — quantum computing and quantum cryptography — are perhaps the most relevant for the blockchain sector, it is interesting to take a look at a few other technologies that will have an impact on some of today’s leading industries.

Quantum optimization: Machine learning may be the first branch of algorithms to be propelled by advancements in quantum technologies. Though there is prominent research going on related to generic quantum machine learning algorithms, the most near-term application seems to be quantum optimization, more specifically quantum annealing. In machine learning and artificial intelligence, the machine has to scan a very bumpy parameter-landscape to find the ‘lowest point’ in that landscape, the optimum. This is similar to how, whilst skiing, you can keep sliding until you find the lowest point in the valley. This is difficult, however, due to the high-dimensional landscape of parameter space. Similar to skiing, even if you stop at a local minima, you’re not sure whether a neighboring valley has a lower one. With quantum optimization, we can use effects like quantum tunneling to find this optimum more quickly. The company D-Wave are actually already building these quantum annealers, though they still need a few years of development before they become more useful than our classical algorithms.

Quantum simulators: The pharmaceutical industry relies on developing dozens of new drugs each year. Quantum simulators can magnify the number and the quality of these new medications by helping to model their effects at a biochemical level. You see, molecules are notoriously hard to model computationally, since the laws of quantum mechanics govern their behavior. Quantum interactions grow exponentially more complex as you increase the size of the system, e.g. by adding extra atoms or molecules to a simulation. However, by using engineered quantum systems, we gain control over this insane complexity and can use it to our advantage, for example to model the quantum chemical reactions which are relevant for medication research. This means we can create special-purpose quantum simulators which simulate chemical reactions, which are needed for the pharma industry. If this technology is perfected, it’s hard to predict how large of an explosion pharma research will go through. Using the same principles, basic chemistry research as well as nanotechnologies will flourish, giving us better materials and smaller, more precise sensors.

Quantum measurement enhancing: All sorts of precision detectors can be developed using quantum technologies, which in turn affects nearly all engineering industries. However, here we’d like to mention one of the coolest, high-tech potential applications: using quantum interference to detect gravitational waves. Gravitational waves are extremely weak — when going through Earth they distort spacetime, but only ever so slightly, so researchers need to measure a distance contraction of 1/10 000th of the size of a proton over a length of 4 km. That’s equivalent to measuring the distance to the nearest star outside our solar system with an accuracy of about 100 micrometers, i.e. the width of a human hair. Sounds insane? It is. And getting a very weak measurement signal from a strong gravitational wave is barely achievable here on Earth, but scientists managed in 2015. However, to use this for graviational wave astronomy, we will need to boost the sensitivity of detectors, probably by using quantum measurement enhancing, where entanglement is used to overcome the statistical limits of classic measurement techniques.